1 MECHANICAL VENTILATION: EFFECTS ON HUMAN DIAPHRAGM GENE EXPRESSION FOLLOWING CARDIOTHORACIC SURGERY AND BREATHING VARIABILITY IN PROLONGED MECHANICAL VENTILATION PATIENTS DURING SPONTANEOUS BREATHING TRIALS By TSENG TIEN HUANG A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2009
2 2009 Tseng Tien Huang
3 To my pare nts, family members, and my dear Qiong for their love and support
4 ACKNOWLEDGMENTS This project would not have been completed without the support and assistance of many people. First, I thank my mentor, Dr. A.D. Martin, for his guidance a nd continuous support during my graduate edu cation. He is a great model to the researcher I aspire to be. Also, I praise my supervisory committee members: Dr. P.W. Davenport, Dr. J.C. Rosenbek and Dr. David Fuller, for their direction and support thr oughout my graduate studies. I also thank all laboratory members, who have played a role in my achievements. Finally and most importantly, I am thankful for the experiences shared with my parents and family members throughout my life and career.
5 TABLE OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................................... 4 LIST OF TABLES ................................................................................................................................ 8 LIST OF FIGURES ............................................................................................................................ 10 ABSTRACT ........................................................................................................................................ 11 CHAPTER 1 INTRODUCTION ....................................................................................................................... 14 Specific Aim ................................................................................................................................ 15 Hypothesis ................................................................................................................................... 15 Significance of the Study ............................................................................................................ 15 2 LITERATURE REVIEW ........................................................................................................... 16 Mechanical Ventilation Induced Diaphragmatic Dysfunction................................................. 16 Diaphragm Muscle Atrophy ................................................................................................ 16 Oxidative Stress ................................................................................................................... 17 Myofibril Injury ................................................................................................................... 17 MV Induced Diaphragm Dysfunction on mRNA Levels ................................................. 18 Evidence of VIDD in Humans ............................................................................................ 20 Signaling Mechanisms During Skeletal Muscle Atrophy ........................................................ 20 TNF ................................................................................................ 21 Nuclear Factor Kappa B (NF kB) Signal ........................................................................... 21 IGF 1/PI3K/Akt Pathway .................................................................................................... 23 PI3K/Akt/FOXO in Muscle Atrophy ................................................................................. 24 Caspase 3 in Muscle Atrophy ............................................................................................. 25 Proteolytic Pathways in Skelet al Muscle ........................................................................... 26 Role of lysosomal proteolysis in disuse atrophy ........................................................ 26 Role of calpains in disuse atrophy .............................................................................. 27 Proteasome -mediated proteolysis ................................................................................ 28 Oxidative Stress ................................................................................................................... 29 Oxidative stress activates NF kB si gnal ..................................................................... 30 Oxidative stress activates MAPK signaling ............................................................... 30 Other Candidates Involved in Muscle Atrophy ................................................................. 31 Complexity of Signaling Mechanisms During Skeletal Muscle Atrophy ............................... 32 Summary and Future Directions ................................................................................................ 32
6 3 METHODS AND MEASUREMENTS ..................................................................................... 34 Research Design .......................................................................................................................... 34 Subjects ........................................................................................................................................ 34 Anesthetic Management ............................................................................................................. 34 Surgical Management ................................................................................................................. 35 Diaphragm Biopsies .................................................................................................................... 35 Isolation of Total RNA ............................................................................................................... 36 Microarray Processing ................................................................................................................ 36 Complementary Ribonucleic Acid (cRNA) Synthesis and Microarray Hybridization ... 36 Data Acquisition (Scanning) ............................................................................................... 37 Microarray Data Analysis and Biostatistics .............................................................................. 37 High level Statistical Analysis ............................................................................................ 37 Unsupervised analysis of gene expression patterns ................................................... 38 Supervise d analysis of gene expression patterns ........................................................ 38 Path analysis ................................................................................................................. 39 4 RESULTS AND DISCUSSION ................................................................................................ 41 Patient Collective and Clinical Data .......................................................................................... 41 Microarray Data Analysis and Biostatistics .............................................................................. 41 Unsupervised Analys is of Gene Expression Patterns ........................................................ 41 Supervised Analysis of Gene Expression Patterns ............................................................ 42 Path Analysis ........................................................................................................................ 42 Discussion .................................................................................................................................... 43 Generalized Stress Responsive and Redox Regulation Genes ......................................... 43 Interleukin 6 .................................................................................................................. 43 Oxidative stress ............................................................................................................ 44 Protein Metabolism .............................................................................................................. 46 Proteasome -mediated p roteolysis ................................................................................ 47 Lysosomal proteolysis ................................................................................................. 48 Calcium activated proteasomes ................................................................................... 49 Protein synthesis ........................................................................................................... 49 Energy Metabolism .............................................................................................................. 50 Muscle -specific Regulatory Genes ..................................................................................... 52 Path Analysis ........................................................................................................................ 54 Summary and Conclusion ........................................................................................................... 55 5 BREATHING VARIABILITY DURING SPONTANEOUS BREATHING TRIALS IN PROLONGED MECHANICAL VENTILATION PATIETNS .............................................. 68 Background and Significance ..................................................................................................... 68 Literature Review ........................................................................................................................ 69 Weaning Trials in Weaning Protocols ................................................................................ 69 Breathing Pattern Analysis .................................................................................................. 70 Reproducibility of Breathing Parameters ........................................................................... 71 Physiological Grounds of Breathing Pattern Variability................................................... 72
7 Breathing Pattern during Weaning ..................................................................................... 73 Breathing Variability during Weaning ............................................................................... 75 Methods ....................................................................................................................................... 77 Subjects ................................................................................................................................ 77 Study Procedure ................................................................................................................... 79 Data Analysis and Statistical Analysis ............................................................................... 80 Results .......................................................................................................................................... 80 Discussion .................................................................................................................................... 80 Summary and Conclusion ........................................................................................................... 83 6 CONCLUSIONS AND FUTURE DIRECTION ...................................................................... 87 APPENDIX GENE FUNCTIONAL CATEGORIES ................................................................. 88 LIST OF REFERENCES ................................................................................................................. 123 BIOGRAPHICAL SKETCH ........................................................................................................... 138
8 LIST OF TABLES Table page 2 1 Signals involved in disuse induced muscle atrophy ............................................................ 33 4 1 Clinical baseline characteristics of five patients undergoing cardiothoracic surgery ........ 61 4 2 List of genes related to generalized stress response and redox reg ulation that are significantly different after surgery ....................................................................................... 62 4 3 Expression of protein metabolism genes that are significantly different in the diaphragm after surgery ......................................................................................................... 63 4 4 List of genes related to energy metabolism that are significantly different in the diaphragm after surgery ......................................................................................................... 65 4 5 List of muscle -specific genes rela ted to contractile functions that are significantly different in the diaphragm after surgery ............................................................................... 66 4 6 Significant signaling pathways that were identified by Path Analysis ............................... 67 5 1 Demographic characteristic of the prolonged mechanical ventilation patients .................. 85 5 2 Breathing pattern variables in the Successful vs. Failed spon taneous breathing trials ...... 86 A 1 Expression of transport genes that are significantly different in the diaphragm after surgery..................................................................................................................................... 89 A 2 Expression of signal transduction genes that are significantly different in the diaphragm after surgery ......................................................................................................... 91 A 3 Expression of nuclei acid metabolism genes that are significantly different in the diaphragm after surgery ......................................................................................................... 93 A 4 Expression of regulation of transcription genes that are significantly different in the diaphragm after surgery ......................................................................................................... 95 A 5 Expression of binding genes that are significantly different in the diaphragm after surgery..................................................................................................................................... 98 A 6 Expression of cell adhesion genes that are significantly differe nt in the diaphragm after surgery .......................................................................................................................... 109 A 7 Expression of cell differentiation, growth, and proliferation genes that are significantly different in the diaphragm after surgery ....................................................... 110 A 8 Expression of structural constituent or molecular activity genes that are significantly different in the diaphragm after surgery ............................................................................. 112
9 A 9 E xpression of extracellular region, cell junction, and membrane genes that are significantly different in the diaphragm after surgery ....................................................... 113 A 10 Expression of neuronal factor, blood coagulation, catalytic activity, and miscellaneous genes that are significantly different in the diaphragm after surgery ....... 116 A 11 Expression of unknown function genes that are significantly different in the diaphragm after surgery ....................................................................................................... 120
10 LIST OF FIGURES Figure page 4 1 Unsupervised cluster analysis. ............................................................................................... 57 4 2 Functional classification of 763 genes differentially expressed in earlyvs. late surgical conditions. ................................................................................................................ 58 4 3 JAK-STAT signaling pathway. ............................................................................................. 5 9 4 4 p53 signaling pathway. .......................................................................................................... 60
11 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy MECHANICAL VENTILATION: EFFECTS ON HUMAN DIAPHRAGM GENE EXPRESSION FOLLOWING CARDIOTHORACIC SURGERY AND BREATHING VARIABILITY IN PROLONGED MECHANICAL VENTILATION PATIENTS DURING SPONTANEOUS BREATHING TRIALS By Tseng Tien Huang May 2009 Chair: A.D. Martin Major: Re habilitation Science s Failure to wean from mechanical ventilation (MV) is a serious problem in acute medical care today. Approximately 5% of patients receiving MV experience difficult weaning, but these patients acco unt for approximately 40 50% of all MV days. Numerous animal studies have documented that MV use leads to diaphragm atrophy, oxidative stress, reduced muscle strength and altered gene expression in as little as 6 24 hours, and this phenomenon has been term ed ventilator induced diaphragm dysfunction (VIDD). Additionally, recent human work has documented severe VIDD (diaphragm muscle fibers atrophying ~55%) following approximately 39 hours of MV, and clinical human studies have shown that patients experiencin g difficulty weaning have impaired respiratory muscle performance, consistent with changes seen in VIDD models. However, it is unknown how soon the diaphragm begins to start the process of atrophy following the start of mechanical ventilation. We hypothesi zed that the genes responsible for maintaining diaphragmatic contractile function, stress response, energy transduction would be altered over the course of a 5 hour cardiothoracic surgery. Two diaphragm biopsies were obtained from 5 male patients (67 +/ 11years) undergoing cardiothoracic surgery. The first biopsy was obtained as soon as the diaphragm was exposed; the
12 second biopsy was obtained as late in the surgery as possible (4.9 +/ 1.8 hours). We profiled mRNA from the 5 pairs of muscle biopsies with a microarray (Affymetrix Hu U133 plus 2.0). Microarray analysis identified 763 differentially expressed (early vs late samples) unique gene products (p< 0.005) after cardiothoracic surgical procedures. Post -operatively, the genes related to the generaliz ed stress response and redox regulation wer e upregulated. We also found significantly upregulated expression of cathepsin C (2.7 -fold), cathepsin L1 (2.0-fold), and various ubiquitin -conjugating enzymes (E2) (~1.5 -fold). Myocyte enhancer factor 2C (MEF2C), a key transcriptional factor for skeletal muscle development and regeneration, was significantly do wn regulated (3.5 -fold). We conclude that cardiothoracic surgery results in rapid changes in diaphragm gene expression, including genes related to generaliz ed stress response, redox regulation, and proteolysis. This work provides the first data examining the changes of diaphragm gene expression following surgical procedures. These data will lead to future research examining intraoperative pharmacological inte rventions aimed at preventing VIDD in humans. Meanwhile, most PMV patients require participating in unsupported, progressively lengthening, spontaneous breathing trials (SBT). Thirty eight PMV (46+/ 23 days) patients (male/female ratio: 16/22, Age 64+/ 12yrs) were studied. Breathing pattern (BP) variables including exhaled minute ventilation (VE), breathing frequency (f) inspired tidal volume (VT), peak inspiratory flow (PIF) inspiration time (TI), expiration time (TE), and duty cycle were measured durin g the first 30 min of successful and failed SBT and the mean values and coefficients of variation (CV) of these BP variables were calulated. SBT failure was defined with standard criteria. Compared to successful SBT, the failed SBT displayed significantly high PIF and f (31.3+/ 9.2 vs. 28.8+/ 5.9 L/min and 29+/ 11 vs. 26+/ 7 breath/min, respectively) The CV of VE, f and PIF were higher during successful trials. We conclude that selected BP variables are
13 different within subjects during the first 30 minute interval of failed and successful SBT in PMV patients, reflecting a higher drive to breathe in failed trials. BP CVs variables revealed more significant differences than the mean values.
14 CHAPTER 1 INTRO DU CTION With the advance in anesthesia and surgical techniques over the past decade, most patients undergoing c ardiac surgery are easily weaned from mechanical ventilation within a few hours after surgery (1). However, approximately 5% of cardiac surgical patients require postoperative prolonged mechanical ventilation (PMV), for 7 or mor e days (2). Additionally, serious complications from PMV use are commonly seen. While receiving MV, the cumulative risk of pneumonia is about 1% per day (3). Other complications of MV include cardiac arrhythmias deep vein thrombosis, pneumothorax, ascites, aspirat ion pneumonia, sepsis, gastrointestinal hemorrhage, acute renal failure, and infections (4). These PMV patients repeatedly fail to wean and face a substantial risk of long term complications and even death (5). Thus, weaning these PMV patients from M V support is one of great challenges in intensive care. Emerging evidence demonstrates that weaning difficulty is linked to inspiratory muscle dysfunction which results in the inability of the respiratory muscles to maintain adequate ventilation. Specific ally animal studies have shown that respiratory muscle weakness produced by prolonged MV is due to diaphragmat ic atrophy and contractile dysfunction (6 11) This decrease in diaphragmatic contractility is time -depe ndent (8) and may occur with as little as 6 18 hours of MV use (12) Moreover, recent work published in the NEJM has shown that clinically significant diaphragm atrophy occur s in humans following as little as 18 69 hours of MV (13) At the cellular levels, evidence supporting this dysfunction is associated with atrophy (10, 14) oxidative stress (10, 12) myofibrillar disruption (9, 15) and various remodeling responses (6, 11, 14, 16) in the diaphragm. DeRuisseau (17) in 2005 examined gene expression after 6 18 hour of CMV in 5 mice and concluded, Mechanical ventilation resulted in rapid changes in diaphragmatic gene expression and genes in the cell growth/cell maintenance, stress resp onse,
15 and nucleic acid metabolism categories showed predominant upregulation, whereas genes in the structural protein and energy metabolism categories were predominantly downregulated. These data imply t hat gene expression changes start very early followi ng the initiation of MV use. However, no comparable data is available on the acute effects of MV use on the human diaphragm It is unknown how the mRNA gene expression in the human diaphragm is altered by surgical procedures (including the use of MV) and, more importantly, whether patients undergoing short term procedures ( eg. surgical anesthesia accompanied with MV use ) are at risk for developing VIDD. Specific Aim To examine the effects of prolonged surgical procedures, which include the use of MV in mR NA gene expression in human diaphragms. Hypothesis T he genes responsible for maintaining diaphragmatic contractile function, stress response, energy transduction are influenced over the course of cardiothoracic surgery in humans Significance of the S tud y This research will expand our knowledge of how the gene expression is influenced by cardiothoracic surgery. The changes of gene expression following surgical procedures may be particularly relevant to understanding the pathophysiological significance of VIDD in patients at risks of post -surgical weaning difficulties. The knowledge of underlying molecular mechanisms of diaphragm dysfunction will help direct efforts to develop rehabilitation and pharmacologic i nterventions in the pre -, intra and post -opera tive periods.
16 CHAPTER 2 LI TERATURE REVIEW Animal studies in rats have shown that as little as 6 to 18 hours of controlled mechanical ventilation (CMV) results in changes in diaphragmatic gene expression and atrophy (10, 17) Moreover, r ecent work by Levine et al. in humans has shown that CMV for ~36 hours led to 55% atrophy of diaphragm muscle fibers, increased markers of oxidative stress and upregulation of genes controlling pathways leading to muscle atrophy (13) Clearly, the emerging evidence indicates that short periods of CMV may lead to ventilator -induced diaphragm dysfunction Thus, the effect of MV -induced diaphragm atrophy and weakening in the ICU patients cannot be ignored. The objective of this review is twofo ld 1) outline our current understanding of M V induced diaphragm dysfunction, and 2) provide a brief overview of signal transduction of muscle unloading. Mechanical Ventilation -Induced Diaphragmatic Dysfunctio n Experimental evidence suggests that controlled mechanical ventilation (CMV), associated with muscle unloading and inactivity, can induce dysfunction of the diaphragm, resulting in an early onset and progressive decrease in diaphragmatic force generating capacity, called VIDD The mechanisms of VIDD are not fully elucidated, but include muscle atrophy, oxidative stress, myofibril injury, and various remodel ing response s Diaphragm Muscle A trophy Disuse atrophy following the use of MV develops very rapidly as early as 18 hours and to a significantly greater extent in the diaphragm during CMV than in peripheral skeletal muscles (10) For example, using the rat as an experimental model, Shanely et al. (10) in 2002 reported that the onset of disuse muscle atrophy occurred approximately eight times faster in the
17 diaphragm compared with locomotor skeletal muscle. Interestingly, they also found that type II fibers exhibited a greater d egree of atrophy than type I fibers in the diaphragm during MV. Because the force produced by type I fibers is less than that generated by ty pe II fibers, greater type II fiber atrophy could potentially contribute to the decline of maximal force production by the diaphragm after short term CMV (18) Moreover, animal MV models demonstrate that d iaphragm atrophy results from both decreased rates of protein synthesis, (14) and enhanced r ates of proteolysis, (10) which functionally impairs maximal force generation Oxidative S tress It has been shown that diaphragmatic unloading is associated with a rapid onset of oxidative stress following 6 hours of MV (12) Importantly, oxidative stress can contribute to both muscle atrophy and contractile dysfunction (12) Data shows that oxidative stress can modify several proteins a ssociated with excitation -contraction coupling, contributing to a decrease in muscle force production (19) Moreover, MV -induced oxidative stress evokes myofibri llar protein oxidation in the diaphragm (12) and oxidized myofibrillar proteins are sensitive to proteolytic attack by proteases (20) Hence, oxidative stress plays an important role in MV i nduced diaphragm contractile dysfunction and atrophy. Myofibril Injury Diaphragm muscle inactivity is associated with diaphragm muscle injury (9, 15) After 2 3 days of CMV in rabbits, significant myofibril damage w as present in the diaphragm, but not in the soleus (9). It has been shown that myofibril injury contributed to the reduced diaphragm force -generating capacity ( 49% in the 3 days of CMV) (9). Structural abnormalities of different subcellular components of diaphragm also could be observed after 2 3 days of CMV in rabbits. These changes consist of disrupted myofibrils, increased numbers of lipid vacuoles in the sarcoplasm, and a bnormally small mitochondria containing focal membrane disruptions (15) .The
18 precise mechanisms of injury have not been clearly identified, but mechanical ventilator induced myofibril injury may involve activation of calpains, which have the ability to degrade several sacromeric proteins and direct cell injury due to augmented oxidative stress (21, 22) MV -I nduced Diaphragm Dysfunction on mRNA L evels Despite studies in animals which have documented the effects of MV on diaphragm muscle structure and function, the unde rlying mechanisms regulating rapid diaphragm dysfunction are not fully understood. There are a number of genes encoding for proteins functioning in the initiation of the muscle atrophy process. In mammals, protein degradation involves an ATP -dependent ubiquitin -proteasome pathway (23 ) (UPP) and is regulated by the muscle -specific ubiquitin ligases (24) (such as E3 ligase), muscle atrophy factor box (25) (MAF box), and muscle specific RING fing er 1 (23) (MuRF 1). In vitro studies have identified a number of specific mRNAs in the diaphragm that change in response to the use of MV. The mRNA expression of MAF -box (26, 27) MuRF 1, (28) and an E3 ligase (28) in the ubiquitin proteasome pathway (UPP) are thought to play a role in MV -induced diaphragmatic atrophy and weakness. Zhu et al. (27) demonstrated that MV animals (after 1 day of CMV) increased diaphragmatic mRNA levels of MAF -box and an E3 ligase in the UPP. Moreover, the upregulation of MAF -box mRNA levels occurre d before the presence of structural myofibril disarray (injury). Consistent with the above findings, DeRuisseau (28) reported 12 hour of CMV produced an increase in MuRF 1 mRNA levels (19 fold), MAF -box (8.3 fold) in rat diaphragm muscle as compared with the controls. Collectively, CMV increases diaphragmatic levels of key components with the ubiquitin -proteasome pathway contributing to MV induced proteolysis/atrophy in the diaphragm and the upregu lation of atrophic factors in m RNA levels occurs prior to the presence of structural myofibril injury.
19 Further evidence showing the alterations of mR NA levels after short periods of CMV (6 18 hours) was provided by a gene expression microarray study, (17) demonstrating 354 unique genes with statistically altered expression of at least 1.5 fold in mechanically ven tilated rat diaphragms compared with the controls. For the detailed analysis, genes with altered expression were functionally grouped into 4 categories: stress response, protein metabolism, calcium regulation, and energy metabolism. The authors concluded, (17) Mechanical ventilation resulted in rapid changes in diaphragmatic gene expression and genes in the cell growth/cell maintenance, stress response, and nucleic acid metabolism categories showed predominant upregu lation, whereas genes in the structural protein and energy metabolism categories were predominantly downregulated. Specifically, stress response genes, including superoxide dismutase 3, slelnoprotein P, peroxiredoxin 3, thioredoxin reductase 1, carbonic a nhydrase III, heme oxygenase 1, and metalothionein, demonstrated the largest changes indicating that MV induced dysfunction involved in oxidative type of stress and some protective adaptations in response to increased oxidative production were also occurre d at the earliest time points after the use of MV. Secondly, many protein metabolism genes were altered following 6 and 18 hours of MV. Several members of the cathepsin family of proteases, matrix metalloproteinase 14, tissue inhibitor of metalloproteinase 1 (TIMP 1) were upregulated while calpain 3 (muscle -specific calpain) was downregulated. The upregulation of the cathepsin family in response to MV contributes to overall proteolysis and decreased calpain 3 mRNA level may impact diaphragm muscle apoptosis Increased TIMP 1 and matrix metalloproteinase 14 may indicate an extracellular matrix remodeling in response to MV. Collectively, changed expression of these protein metabolism genes in response to MV were consistent with previous observations that MV re sulted in enhanced protein proteolysis. Third, change s in the expression of genes related to
20 calcium regulation included calmodulin 1 and 2, calsequsetrin 2, and two calcium ion channel subunits, indicating that dysregulation of intracellular calcium might play a role in the progression of MV induced diaphragmatic atrophy leading to further diaphragm contractile dysfunction. Finally, altered expression was noted for a large number of genes involved in energy metabolism, indicating that MV alter m RNA expres sion patterns of many genes, involved in fat, carbohydrate, and mitochondrial metabolism. Evidence of VIDD in Humans Despite the growing evidence from animal models that demonstrates that MV leads to diaphragm dysfunction, very little data are available on the effects of mechanical ventilation on the human diaphragm. There are only two studies that have directly studied the impact of MV on human diaphragm function. Knisely et al. 1998 used a case control design and qualitatively showed massive diaphragm mus cle fiber atrophy in a young child ventilated for 47 days compared to a child for 3 days (29) Levine et al. examined biopsy samples obtained from 14 brain -dead organ donors, and showed that 18 to 69 hours of controlled mechanical ventilation was associated with atr ophy of both slow twitch and fast twitch fibers in the diaphragm (13) Consistent w ith the animal studies Levine also showed that diaphragmatic dysfunction accounted for increased cellular stress (+100% caspase3 m RNA expression) and muscle proteins proteolysis (+200% MAF box mRNA vs. MBD4 (housekeeping gene); +590% MuRF 1 m RNA vs. MBD4). Signaling Mechanisms During Skeletal Muscle Atrophy The loss of skeletal muscle mass secondary to inactivity or disuse is a comm on phenomenon known as muscle atrophy or wasting. A variety of conditions lead to muscle atrophy including muscle disuse, multiple disease states, fasting and age associated atrophy. Regardless of the inciting event, skeletal muscle atrophy is characterize d by decreased muscle
21 fiber cross -section area and protein content, increased insulin resistance, morphological changes (atrophy) of muscle fiber type, and reduced muscle tension. It is well -established that the decrease in protein synthesis and the increa se in protein degradation rates account for muscle protein loss due to disuse. However, we are just beginning to understand the molecular signaling mechanisms that lead to protein loss. There is an accumulating literature that is beginning to elucidate ups tream molecules and/or signaling mechanisms during skeletal muscle atrophy and several potential signaling molecules/mechanisms have been identified. TNF and Other Cytokines In general, muscle atrophy due to disuse is initiated by a reduction in muscle contractile activity and muscle tension while muscle atrophy due to disease is initiated by TNF cytokines. Although both factors contribute to cause to the protein loss, it is unlikely that TNF or other cytokines are involved in disuse atrophy. Previous data found no difference in TNF protein levels in unloaded muscle (30) Thus, disuse atrophy does not appear to involve the production of TNF Nuclear Factor K appa B (NF kB) Signal NF kB is a ubiquitous transcription factor that mediates a variety of processes depending on the cell type and upstream triggers. Incorrect regulation of NF kB may cause inflammatory and autoimmune diseases, viral infection, and cancer. In mammals, five NF -kB family members have been identified: [p65(Rel A), Rel B, c Rel, p52, and p50]. All family members are expressed in skelet al muscle, existing in unstimulated cells as heterodimers bound to inhibitory protein Ikappa B (IkB). Activation of NF kB is achieved by nuclear transport of heterodimers of NF kB family members and often occurs by the ubiquitination and degradation of the IkB. Also, p50 and p52 can form homodimers and undergo nuclear translocation. Accumulating evidence indicates that a specific NF kB pathway is required for disuse muscle atrophy (reviewed in Refs.
22 (31 33) ). With un loading, the nuclear levels of p50 and Bcl 3 (a nuclear IkB family member) were markedly increased (30) Meanwhile mice with a knockout of the p50 gene showed to be resistant to the soleus muscle atrophy that resul ts from 10 days of hindlimb unloading (34) The same result was found when Bcl 3 knockout mice were used (34) These data indicate that NF kB pathway may be operative during disuse atrophy. However, the target genes of NF kB in disuse are currently under investigation. Recent work using transgenic mice revealed some candidate NF kB targets during muscle atrophy (35) Mice with muscle -specific expression of an activated IkB kinase beta (MIKK) show a distinct skeletal muscle wasting. Specifically, muscle mass in MI KK mice was significantly reduced compared with its wild -type controls, demonstrating that the NF kB activation by IKKbeta is sufficient to induce muscle atrophy. Cai et al. showed that activation of NF kB in MIKK mice resulted in increased expression of t he E3 ubiquitin ligase MuRF 1, whereas other target genes of NF kB were not activated in muscle of MIKK mice (35) Previous data has shown that MAF box and MuRF 1 were upregulated by muscle unloading (36) Thus, it is possible that MuRF 1 transcription is driven by the activation of NF kB and MuRF 1 may be the target of NF kB signaling. When MIKK mice were crossed with MuRF 1 -/ mice to create MIKK x MuRF 1 -/ mice, mice with this genotype had a significant redu ction in muscle mass, though less than that (MISR) mice. This incomplete inhibition of muscle loss implies that MuRF -1 is not the only crucial mediator of muscle atrop hy to be activated by NF kB pathway. Another target genes of NF kB in muscle cell were the proteasome subunits. In the MIKK mice, several proteolytic genes such as C2 and C9 were upregulated and these mRNAs were also upregulated in unloaded and cachectic m uscle (36, 37) In addition, microarray data found that
23 Nedd4 and Mdm2 were upregulated during unloading (36) and these genes could be the targets of NF kB signaling. Overall, it is conceivable that NF kB is a key signaling pathway activated by muscle unloading and may be involved in the activation of proteolytic process. However, the downstream target gen es have not been elucidated and this will be an important area for further study. IGF -1/PI3K/Akt Pathway The IGF 1/PI3K/Akt pathway is an important signaling pathway for muscle hypertrophy (38) Activation of phosphatidylinositol 3 kinase (PI3K) by upstream ligands such as insulinlike growth factor (IGF 1) leads to activation of the serine/threonine kinase (Akt), which in turn phosphorylates and activates the mammalian target of rapamysin (mTOR) kinase. Activated m TOR can result in increased protein synthesis by phosphorylation and activation of p70S6 kinase, and phosphorylation of eukaryotic translation initiation factor 4E binding protein 1 (4E BP 1), key regulatory proteins involved in translation and protein syn thesis (39) Importantly, this pathway is also thought to be a potent suppressor of proteoly sis and the expression of atrophy related ubiquitin ligases. In addition to stimulate muscle protein synthesis through activation of PI3K and Akt, IGF 1 and insulin also reduced the expression of MAF box (40) Moreo ver, during the disuse induced muscle atrophy, Akt protein and phosphorylation levels markedly decreased, as did the activation state of P70S6 kinase (36, 41) In addition, the amount of 4E BP 1 bound to eukaryotic translation initiation factor 4E(eIF 4E) was increased at 14 days of unloading in rat gastrocnemius muscle, suggesting a role in decrease protein synthesis (36) Furthermore, mice with a knock out of Akt1 gene display severe skeletal muscle atrophy, bone develo pmental impairment, and severe growth deficiency when compared to wild type mice (42, 43) Collect ively, these results show that IGF 1/PI3K/Akt pathway not only increase overall
24 protein synthesis, but also suppresses proteolysis and the expression of atrophy-related ubiquitin ligases. PI3K/Akt/FOXO in Muscle A trophy Activation of the PI3K/Akt pathway r esults in the phosphorylation of the FOXO proteins, which is a subgroup of the forkhead family of transcription factors. In mammals, three members of this family, FOXO1, FOXO3, and FOXO4 have been identified. These have been implicated in regulation of tar get genes in metabolism, apoptosis, and cell cycle progression (44) When Akt is activated, FOXO is phosphorylated and bound by 14 3 3 protein that mediate s its movement from nucleus to cytoplasm. Once phosphorylated FOXO proteins are translocated from the nucleus to cytoplasm, their transcriptional functions will be inhibited (45) Dephosphorylation of FOXO factors leads to FOXO protein to nucleus entry, resulting in suppression of the muscle growth and induction of apoptosis (46) Evidence showing that IGF 1/PI3K/Akt pathway cr itically mediated FOXO transcription comes from experiments by Stitt et al. (47) First, they used a pharmacological inhibitor of PI3K and allowed FOXO1 protein to translocate the nucleus. Second, they used a mutant form of FOXO1, which can not be regulated by Akt and remains active in the nucleus, and demonstrated that in the presence of this active, nuclear -localized mutant form of FOXO1, IGF 1 can not inhibit muscle atrophy mediators, the MAF box or the MuRF1. This finding demonstrates that IGF 1/PI3K/Akt antiatrophy activity required the blockade of FOXO. The study of transgenic mice specifically over expressing FOXO1 supports this idea since these transgenic mice exhibited less skeletal muscle mass than the non -t ransgenic controls (48) Enhanced gene expression of Atrogin1, MuRF 1, and cathepsin L suggested the increase protein degradation contributed to the loss of muscle mass in FOXO1 mice.
25 FOXO3 was also reported to upr egulate the gene expression of Atrogin1, and IGF 1 was found to reverse the FOXO3 mediated activation of the Atrogin1 promoter (49) In addition, over -expression of an active form of FOXO3 decreased the skeletal muscle fiber size (49) When FOXO3 activation was blocked by RNAi in muscles, Atrogin1 induction during muscle atrophy were blunted (49) Collectively, FOXO transcription fac tors may play a role in muscle atrophy and IGF 1/PI3K/Akt pathway might control these proteins. Caspase -3 in Muscle Atrophy Caspase is a specific endoprotease and, in some case, it plays a role in apoptosis (programmed cell death) (50) To date, over twelve proteins belonging to this group have be en identified in mammals. In the cells, caspases are expressed as inactive precursors (ie. Procaspases), and activation of caspases can result in events contributing to protein breakdown and apoptosis (50) Capase3 activation during muscle atrophy is thought to be involved in the initial steps of myofibrillar degradation. Although the ubiquitin proteasome system, which is thought to be the main proteolytic system during muscle atrophy, can degrade monomeric actin or myosin, it does not break down actomyosin complexes or myofibrils (51) This idea is supported by the evidence that capase 3 activation promotes degradation of actomyosin complexes, and inhibition of caspase 3 activity suppresses the overall rate of proteolysis in diabetic muscle undergoing atrophy (52) In addition, the data shows that caspase 3 inhibition results in the attenuation of myofiber atrophy during diaphragm muscle unloading suggesting that caspase 3 pl ays a role in muscle protein degradation during muscle disuse (53) Control of caspase 3 activity is complicated and may involve several interconnected signaling pathway s Powers at al. (2007) proposed that caspase 3 could be activated by oxidative stress, increased cellular calcium, and increased calpain activity (54) Also, multiple lines of
26 cross talk between pathways were proposed (54) Increased calpain activity can lead to the activation of caspase 3 (55) Thus, cross talk between the calpain and caspase 3 proteolytic systems may involve in the muscle atrophy duri ng period of disuse; but, the mechanisms under this process are largely unknown. It is also worth noting that caspase independent mechanisms, such as the release of apoptosis inducing factor (AIF) and endonuclease G (EndoG), are involved in myofiber apopto sis in skeletal muscle undergoing atrophy. EndoG is a mitochondrial apoptotic protein and is capable of inducing DNA fragmentation when translocated from mitochondria to nuclei through a caspase independent pathway (56) Dupont -Versteegden et al. found that the amount of EndoG in nuclei was consistent with myofiber nuclear loss in muscles atrophied in response to hindlimb suspension (57) Moreover, End oG translocation was very specific for myofiber nuclear apoptosis while very weak activated caspase 3 was seen in myofibers (57) Another protein released from mitochondria upon pro apoptotic stimulation and capable of inducing apoptosis independent of caspas e is apoptosis inducing factor (AIF). Ferreira et al. showed that AIF release was elevated in soleus skeletal muscle during 48 hours of unloading (58) Collectively, these data suggest that mitochondria associated apoptosis may contribute to the loss of muscle mass in the early phase of muscle atrophy. Proteolytic Pathways in Skeletal Muscle N umerous proteolytic systems contribute to the degradation of muscle proteins. The principal proteases in skeletal muscle can be classified into three categories: 1) lysosomal protease; 2) Ca 2 activ ated proteases (i.e., calpain); and 3) the ubiquitin -proteasome dependent. Role of lysosomal proteolysis in disuse atrophy It is believed that lysosomal pathway (i.e. cathepsins) did not play a major role in muscle atrophy. These proteinases (except cathepsin L) were not systematically activat ed in various
27 instances of muscle atrophy (59) With the agents that directly inhibit cathespins, myofilbrillar protein degradation rates are not significantly affected in disuse atrophy (31) Cathespins are unlikely to degrade myofibrils, but rather they seem to play a role to degrade membrane proteins, including receptors, ligands, channels, and transporters (60) Moreover, literature shows that proteolysis during muscle atrophy is the interaction of lysosomal and ubiquitin-proteasomal mechanisms. A number of mammalian receptors and ion channel s are ubiquitinated and then are degraded by either lysosomal or proteasomal systems. The signal that determines which of these pathways is used is the type of ubiquitin modification that occurs. Intracellular proteins with polyubiquitin chains are easily recognized and degraded by proteasomal systems while the protein substrate with mono(or di ) ubiquitin modification, then it is degraded by internalization and transport to the lysosome; it is not recognized by the proteasomal systems because of the lack of the polyubiquitin chain (61, 62) Future research on how monoubiquitin affects the structure, location, and activity of modified membrane associated protein will help us understanding the role of the lysosomal systems during muscle atrophy. Role of calpains in disuse atrophy Calpains (calpains I and II) are Ca 2 activated proteases that are activated in skeletal muscle during periods of inactivity (63) Although calpains do not directly degrade the c ontractile proteins actin and myosin, proteins that are involved in the assembly and scaffolding of myofibrils such as titin, vinculin and, nebulin are known calpain substrates (reviewed in Ref. (64) ). Moreover, calpain is known to degrade several kinases and phosphatases, including calcium/calmodulin depende nt kinase (CaM kinase II), protein kinase C (PKC (54) In addition, calpai n activity may indirectly influence the rate of protein degradation Data shows that a ccumulation of myofibrillar protein fragments
28 generate s a positive feedback resulting in an increase in prote asome activity by the stabiliz ing association of E3 ubiquitin ligases with their substrates (65) Nonetheless, much work is still needed to unravel the exact roles of calp ains during muscle disuse. Proteasome -mediated proteolysis Compelling evidence demonstrates that activation of the ubiquitin-proteasome system plays a key role in muscle atrophy. The ubiquitin-proteasome system involves two successive steps. The target pro tein is first polyubiquitinated and then recognized by the 26S proteasome, which degrades the substrate into peptides (59) Polyubiquitination involves the sequence action of the ubiquitinactivating enzyme (E1), specific ubiquitinconjugating enzymes (E2), and in many cases specific ubiquitin protein ligase enzyme (E3). Numerous studies demonstrate that there are significant increases in the expression of various components of the ubiquitinporteasome pathway (UPP) during muscle atrophy (36, 66 68) In addition, inhibition of the components of UPP with agents has also shown significant interference of muscle proteolysis in disuse muscle atrophy (review in Ref (24) ). The E1 enzyme has lo w expression in skeletal muscle and its mRNA level is not regulated during muscle wasting (59) In mammals, as many as 40 known E2s have been identified but only a small number of E2s (such as E2 K 14 E2 K 20 and UBC4/UBC5 isoforms) are o ver expressed during muscle wasting (59) In mammals, as many as 1000 E3s are recognized but only a very limited number of E3s that upregulated in muscle wasting have been identified (59) Importantly, significant attention has been paid to the increased expression of two muscle -specific E3 enzymes (MAF box and MuRF 1) in disuse because one signature study demonstrates that mice knocked out for either enzyme were partially resistant to muscle atrophy (69) With the various models of disuse, MAF -
29 box mRN A levels were increased rapidly before muscle weight loss was detectable, and maintained high expression during the period when overall proteolysis was accelerated (33) This observation suggests that MAF box may play a role in the initiation and maintenance of accelerated proteolysis. MuRF 1 was also upregulated in several models of disuse atrophy and its mRNA upregulation occurred as earl y as 12 hours after muscle denervation suggesting tha t MuRF 1 may involve in the initiation of atrophy process (33) Collectively, both M uRF 1 and MAF -box could be used as early markers of disuse muscle atrophy. Oxidative S tress Another area that has received significant attention is the generation of reactive oxygen species (ROS) in muscle unloading. Abundant evidence implicates oxidative stress as a potential regulator of proteolytic pathways leading to muscle atrophy during periods of muscle disuse (review in Ref (54, 70) ). The first evidence showing oxidative stress played a key signaling role in the regulation of disuse muscle atrophy was provided by Kondo et al. (71). Their work revealed that immobilization of skeletal muscles was associated with increased free radical production, resulting in oxidative injury in inactive muscle fibers. Importantly, this work also showed that disuse muscle atrophy could be delayed by exogenous antioxidants. These early observations have subsequently been confirmed by others (72, 73) In order to respond to oxidative stress, cells display adaptive mechanisms involved in increasing their antioxidant defenses. Elevated levels of ROS appear to be detected by redox sensitiv e regulatory molecules in the cell that can trigger various signal transduction cascades (74) It is believed that oxidative stress contributes to disuse muscle atrop hy by influencing the following cell signaling pathw ays: 1) the activation of NF kB, and 2) control of the mitogen activated protein kinases (MAPKs) singaling (54)
30 Oxidative stress activates NF kB signal Accumulating evidence indicates that a specific NF kB pathway is required for disuse muscle atrophy (as previously discussed). Either exogenous ROS or H2O2 triggered ROS cou ld activate NF kB pathways directly in muscle cells (75) This obse rvation is consistent with the concept that ROS can promote NF kB activation, which perhaps leads to increased proteolysis through the ubiquitin-proteasome pathway. In contrast, the DNA binding activity of oxidized NF kB is diminished, suggesting that ROS may also inhibit NF kB transcriptional activity (54) Nonetheless, it appears that NF kB activation is under redox control but how ROS regulates NF kB transcriptional activity remains largely unknown. Clearly, future research is needed to unravel the uncertainties about the redox regulation of NF kB in skeletal muscle during periods of inactivity. Oxidative stress activates MAPK signaling Another potential link between oxidative stress and muscle disuse atrophy involves the redox regulation of the MAPK activation. It is well established that MAPK can regulate the function of cytoplasmic components and the expression of a vari ety of genes involved either in survival and proliferation or in the induction of cell death (76) The MAPKs include four subfamilies in skeletal muscle: 1 ) e xtracellular signal regulated kinases (ERK) 1 and 2 (ERK1/2); 2 ) p38 MAPK; 3 ) c Jun NH2-terminal kinases (JNK); and 4 ) ERK5 or big MAPK. These protein kinases contribute to the regulation of life and death decisions in response to various stress signals (i .e. cytokines, growth factors, and cellular stress) (77) Importantly, MAPKs have been shown to be activated by oxidative stress. Kefalolyianni and associates, for example, found tha t ERK1/2, JNK, and p38 were activated in skeletal myotubes exposed to H2O2 (78) Moreover, the increase of atrogin1/MAF -box was not altered significantly by the ERK inhibitor or the JNK inhibitor, but was blunted by the p38 inhibitor
31 (33) These data suggest that atrogin1/MAF -box gene is a down-stream target of p38 MAPK signaling. In addition, immobilization of skeletal muscles also resulted in elevated p38 activity during periods of muscle disuse (79) Collectively, these data suggest a potential role for oxidative stress -induced activation of p38 in disuse muscle atrophy. JNK can be activated in response to many of the same stimuli that activa te p38 such as oxidative stress. There is growing evidence that JNK plays an important role in oxidative stress mediated apoptosis. Because ROS themselves are unable to activate apoptotic cascade, it is hypothesized that a death -signal pathway such as JNK is a mediator between ROS and apoptosis. Similar to p38, JNK activity was significantly elevated in atrophic muscles following a period of immobilization (33) Suppression of JNK by either genetic or pharmacological approaches demonstrates some resistance to ROS induced apoptosis (80) These findings support a link between ROS, JNK, and apoptosis. However, it is still unknown if JNK activation is response for the myonuclear apoptosis that occurs during disuse muscle atrophy. Other Candidates Involved in Muscle Atrophy There are also additional molecular triggers or signaling pathways yet to be elucidated. Additional pathways that contain differentially expressed gene with unloading include those involved with myogenic signaling (MyoD, Mrg1), Notch signaling (transducin like enhancer of split 4) (Tle4), JAK/STAT signaling, amino acid metabolism, and serine proteases, as well as genes involved in synaptic vesicle remodeling, cell proliferation, and cytoskeletal function (see Ref. (36) for discussion of the full data set). In addition, another microarray study demonstrated that many genes required for ATP production and late s teps in glycolysis were downregulated in multiple types of skeletal muscle atrophy (37) Although there is no obvious relationship between reduced ATP utilization and muscle atrophy, these changes in gene expressio n would be expected to suppress muscles capacity to utilize glucose and reduced muscle energy turnover.
32 Nevertheless, microarray data on global mRNA expression are providing multiple avenues for further study of the regulation of disuse atrophy. Complexit y of Signaling M echan isms During Skeletal Muscle A trophy The more we learn about the disuse atrophy, the more we become aware of its complexity and highly regulated nature. Signals involved in disuse muscle atrophy are summarized in Table 1. Many signaling pathways involved in muscle disuse atrophy are interacted or interdependent with each other. Activation or inhibition of a single pathway may have cascade effects on muscle protein balance, but there is no evidence to prove that the pathway is the sole re gulator of the process (33) For example, in muscle cells, ROS may induce activation of both the MAPK and the NF kB signaling pathway, an d the latter promotes increased proteolysis through the ubiquitin -proteasome pathway. Thus, discussing the communications between two or more signaling pathways help us to get a comprehensive understanding of the complexity of muscle atrophy. Summary and F uture D irections Prolonged periods of skeletal muscle inactivity due to immobilization, hindlimb unloading, or the MV use can result in significant muscle atrophy. The muscle atrophy is characterized as decreased muscle fiber cross -section area and protein content, increased insulin resistance, morphological changes of muscle fiber type, and reduced muscle tension. The decrease in protein synthesis and the increase in protein degradation rates account for the majority of the rapid loss of protein content du e to disuse. However, we are just beginning to understand the upstream molecules and signaling mechanisms that lead to protein loss. Literature suggests that NF kB pathway, IGF 1/PIK3/Akt pathway, and caspase 3 pathway as well as Ubiquitin proteasome pathw ay seem to play major roles of protein loss. Factors such as ROS, p38, and JNK are also demonstrative to linking to disuse muscle atrophy, but our current understanding of
33 how these factors influence the process of muscle atrophy is limited. Furthermore, because of the interplay between signaling pathways, a change in one signal may have multiple effects. Future microarray studies are needed to identify the possible pathways by which proteolysis is modulated and to visualize all the signaling pathways simul taneously, coordinately acting to produce the physiology underlying muscle atrophy. As more research reveals the details of these signaling pathways that are required for atrophy, a much better understanding will be gained of how to treat the atrophic cond itions clinically. Table 2 1 Signals involved in disuse -induced muscle atrophy Signals Expression Function References P50, Bcl 3 Promotes protein degradation (30, 34) PI3K, Akt Promotes protein degradation In hibits protein synthesis (49) Nedd4, Mdm2 Promotes protein degradation (36) Caspase 3 Promotes p rotein degradation (52) EndoG, AIF Promotes protein degradation (57, 58) Calpains Promotes protein degradation (64) MAF box, MuRF 1 Promotes protein degradation (69) ROS Promotes protein degradation (71) P38 Promotes protein degradation (79) JNK Promotes protein degradation? (54) FOXO1, FOXO3 Promotes protein degradation (48, 49)
34 CHAPTER 3 METHODS AND MEASUREM ENTS Researc h Design A prospective, observational, repeated-measures design was conducted in this project. Subjects Seven male patients between 50 to 80 years of age undergoing scheduled cardiothoracic surgical operations at Shands Hospital at the University of Florid a were recruited to enroll in this prospective study. The investigative protocol was approved by the Institutional Review Broad at University of Florida. In addition, patients signed a separate clinical consent form for their cardiothoracic surgical proced ures. Exclusion criteria include d NYHA Class III or IV Cardiac Disease, history of stroke, cerebrovascular disease, spinal cord injury or progressiv e neuromuscular disease, cardiothoracic surgery within the previous 12 weeks, any prior history of pneumonec tomy or lung surgery, a skeletal path ology such as scoliosis FEV1 <60% of a ge predicted value, and malignancy. Anesthetic Management A preoperative dose of intravenous v ancomycin (1 4 mg) was given A standard anesthesia regimen was used in all patients. Subjects were administered general anesthesia and endotracheally intubated by the anesthesiologist. Controlled mechanical ventilation was maintained at 5 cycles per minute with a tidal volume of 5 7 mL/kg. An esthetic induction consisted of fentanyl, propof ol, versed, vancomycin, and vecuronium. Intra operative paralysis maintenance was with vecuronium (0.6 0.8 mg/kg) /or pancuronium (0.1 0.12 mg/kg) A nalgesia was maintained during cardiopulomnary b ypass (CPB) with fentanyl and versed infusion, which changed to propofol infusion after CPB. Intraoperatively, hypertension was treated with
35 labetolol, nipride and hydralazine. H ypotensive episodes were treated with intravenous mannitol. No patient received corticosteroids before, during, or after the operation. S urgical Management All patients underwent a median sternotomy and CPB Standard aortic, valve replacement surgery was performed by the same surgeon, Dr. Thomas M. Beaver. Hypothermic CPB (temperatures of 1824C) with a retro -grade blood cardioplegia was u sed in all patients. Hypothermic circulatory arrest was performed. Mean arterial pressure of 50 -80 mmHg and blood flows of 2.4 2.8 min1 m2 were maintained during CPB. The hematocrit was maintained at >20% during CPB. The use of vasoactive drugs was a t the discretion of the anesthesiologist managing the case. Patients were actively rewarmed to 36.5C before removal of the aortic crossclamp and weaning from CPB. After surgery, all patients were transferred to the cardiothoracic intensive care unit for t he recovery. Diaphragm Biopsies Two f ull thickness biopsy specimens (approximately 6 mm diameter ) were taken from the antero -lateral aspect of the right or left di aphragm near the costal margin during surgery. The first biopsy was obtained immediately aft er exposing the diaphragm during c ardiothoracic surgery; the second biopsy was obtained as late in surgery as possible. Each specimen was stabilized by using RNAlater solution (Ambion Inc. Austin, TX, USA) and then transferred to liquid nit rogen and store d at 80C for microarray ana lysis. The RNAlater solution stabilized and protect ed RNA in fresh spe cimens and then the specimen could be indefinit ely stored at 20C or below until further analysis. The safety and ethics of obtaining diaphragm samples fro m humans must be addressed. Numerous studies have been published in which nontherapeutic, experimental human diaphrag m tissue samples during cardiac surger ies (81 88) and no complication was reported.
36 Isolation of Total RNA Total RNA was isolated with a Rneasy TM Mini Kit (Qiagen Inc) and processed according to the manufacturers instructions. Briefly, a portion of the costal diaphragm (~20mg) was homogenized with Polytron homogenizer and centrifuged at full speed f or 3 min (4C) to remove insoluble material if necessary. The sample was added two volumes of 100% ethanol and centrifuged at 10,000g for 1 min until the lysate/ethanol was mixed. Then the sample was added one volume of Lysis solution. Following transfer of the aqueous phase to a new tube, RNA was precipitated and washed twice with 500L 700 L Wash solution (e.g. 75% ethanol). The concentration and purity of the extracted RNA was processed according to the standard protocol. In addition, the high quality o f total RNA was determined by capillary electrophoresis using an Agilent bioanlysis system (Bioanalyzer 2001; Agilent, Palo Alto, CA). Microarray Processing Complementary Ribonucleic Acid ( c RNA ) Synthesis and Microarray H ybridization The microarray process ing and the following analysis were performed in Dr. Henry Bakers laboratory at University of Florida. In brief, cRNA was synthesized based on the two step amplification protocol outlined by the manufacturer (Affymetrix, High Wycombe, UK), using 0.4 g of total RNA as starting material. Secondly, cRNA was transcribed in vitro with the incorporation of biotinylated nucleotides using an ENZO Bio Array High Yield RNA Transcript Labeling kit (T7; Enzo Life science, Farmingdale, NY), and the Biotin-labeled prod uct was hybridized onto an Affymetrix Hu U133 plus 2.0 GeneChip, in which contains 54,675 probe sets representing over 38,500 well -substantiated human genes Staining and washing followed the protocol (EukGEWSv4; Affymetrix) using a fluidics station (Affym etrix).
37 Data A cqu isition (S canning) The arrays were scanned with a scanner (Affymetrix) and the fluorescence intensity calculated using Affymetrix Gene Chip Operating Software (GCOS). Chip to chip normalization was accomplished using dChip (Wong laboratory, Department of Biostatistics, Harvard School of Public Health, Cambridge, MA) normalization protocols. An expression matrix was modeled using the perfect match -only model algorithms of dChip. The detail of this model is described elsewhere (89) Briefly, each probe set of Affymetrix GeneChip was represented by ~16 20 perfectly matched oligonucletides. Comparison of the hybridization pattern of the perfect matchonly pairs allowed for estimating the signal intensity of the true target transcript as well as eliminating non -specific hybridization signals. Microarray Data A nalysis and B iostatistics Affymet rix Microarray Suite, version 5.0 (MAS 5.0, Stanford, CA) was used to identify probe sets whose hybridization signal intensity was at or below background levels. These probe set s were referred to as absent. Probe sets whose signal intensity were absent o n all arrays under study were excluded in the following highlevel statistical analysis. A transcript was required to be present on all the chips in the earlyand late -surgical conditions in reporting differentially expressed genes. High -level Statistical A nalysis High level statistical analysis was performed using algorithms within the software package dChip and BRB Array Tools (for details, see http//linus.nci.nih.gov/BRB -ArrayTools.html). In Dr. Bakers laboratory, a 3 -step general approach to the high level statistical analysis of microarray datasets was developed and it consists of: 1) Unsupervised Analysis of Gene Expression Patterns, 2) Supervised Analysis of Gene Expression patterns, and 3) path analysis.
38 Unsupervised analysis of gene expression p a tterns Initially, an unsupervised analysis was applied to assess the similarity and differences in apparent gene expression profiles among the samples. For this purpose, the dataset was passed through a variation filter to remove probe sets whose hybridiza tion signal intensities did not vary much across the data set. By ranking on coefficient of variation, the top half of the dataset was identified and subjected to the next step. Secondly, p rincipal component analysis (PCA), a form of multidimensional scali ng, was used to identify similarities between specimens and to identify outliers (90) In PCA, the dimensionality of the dataset was reduced to the principal components. The first principal component accounts for most of the variance in the dataset, followed by the second principal component and so on. In add ition, the principal components could be used to identify similarities in expression patterns among arrays without imposing structure. We performed PCA on the datasets in conjunction with cluster analysis. The results were visualized as a dendrogram on top of the cluster image. Supervised analysis of gene expression p atterns The aim of supervised analysis was identify a list of genes that were differentially expressed between early -surgery and late -surgery samples (paired by patients). Probe sets whose hybridization signal intensities differed between early -surgery and late -surgery samples at the p<0.005 level of significance (using a modified Students t test) were identified. The reason for choosing p<0.005 level of significance is justified below. The ke y statistical issue in the supervised analysis involves controlling for the multiple comparisons. To appreciate this, consider an example in which there are 1,000 genes and 10 subjects in two groups. Using a two -sample t test with a significance level of 0 .05, we would expect 50 of the gene expressions to b e significant by chance alone. Several methods to alleviate this problem are possible 1) to adjust for multiple comparisons using a Bonferroni adjustment. U s ing a Bonferroni adjustment
39 would result in a p er comparison significance level of 0.05/1000=0.00005, which might be too conservative because of the difficulty in achievi ng statistical significance, and 2) to control the False Discovery Rate (FDR), which is widely considered to be a more appropriate cr iterion in this context. A landmark paper by Storey and Tibshirani (91) in 2003 described the basics of FDR. In this method, let F be the number of false positives and T be the number of true positives. The FDR for an experiment is the expected proportion of F/( F+ T), or the ratio of the false pos itives divided by all positives. There are a number of methods available for controlling FDR, including a selection of conservative p value. Typically, a p -value of 0.005 to identify significant probes sets at this level of significance one would expect on e false positive by chance alone out of 500 probe sets analyzed. Therefore, in this study, a p-value of <0.005 was used to identify significance probe sets between early -surgery and late -surgery samples. Path analysis Once probe sets were identified that w ere differentially expressed between early -surgery and late -surgery samples, NetAffx query ( http://www.affymetrix.com/analysis/index.affx) was undertaken for retrieving Gene Ontology (GO) annotati ons of the significant probe sets. This web available software was used for functional annotation clustering. By using t his GO -enriched gene list, the P athway -Express, one of a package of microarray tools, (http://vortex.cs.wayne.edu/projects.htm) was used to provide searchable pathways that related to the significant gene products in our study. The aim of this path analysis was to produce biological meaningful knowledge from the huge amount of data resulting from the microarray experiments. When a user submit a list of genes, which show significant differentially different in a given condition, the Pathway-Express searches the Onto Tools database and builds a list of all associated pathways. The Onto Too ls database currently containes signaling pathways from Kyoto Encyclopedia of Genes and Genomes ( KEGG ) (http://www.genome.jp/kegg/ ). The
40 Pathway Express performs a classical enrichment analysis based on a hypergeometric distribution in order to identify th ose pathways that contain a proportion of differentially expressed genes that is significant from what is expressed just by chance (92). This analysis produces a set of p -values that characterize the significance of the pathway from this statistical perspective (a lower p -value corresponds to a higher significance). Last ly a freeware program of Advanced Pathway Painter v 2.08 ( http://www.gsa online.de/eng/app.html ) was used to visualize the functional relationship among the significant gene products in these biological pathways.
41 CHAPTER 4 RESULTS AND DISCUSSI ON Patient Collective and Clinical D ata Seven male p atients fulfilled the entry criteria and were enrolled in the study. However, two subjects data were excluded due to a diaphragm scarring in one case and the other case whose biopsy sample s w ere possibly mislabeled (early -surgical and late -surgical condit ions). Therefore, only five patients data were reported and analyzed. Clinical baseline characteristics, such as age, height weight, name of surgery, and type of anesthesia were given in Table 4 1. The patients underwent to cardiothoracic surgical proce dures with a mean (+/ -SD) duration of 4.9+/ 1.8 hours. The patients age ranged from 54 to 78 years with a mean (+/ -SD) of 67+/ 11 years. Cardio pulmonary bypass (CPB) time ranged from 159 to 266 minutes with a mean (+/ SD) of 218+/ 51 minutes. One of the five subjects did not complete the planned hypothermic circulatory arrest because an isoelectric EEG was noted upon reaching the selective low temperature. Total cross clamp time ranged from 42 to 204 minutes with a mean (+/ SD) of 142+/ 6 6 minutes. A ll su bjects tolerated surgery without event and no studyrelated post operative complications were noted Microarray Data Analysis and B iostatistics Unsupervised Analysis of Gene Expression Patterns Ten diaphragm muscle biopsy samples were obtained: five early-surgery and five late surgery samples (paired by patients). Of these 10 arrays investigated, the expression of 2558 probe sets was not above background on any array and these probe sets were classified absent and excluded from further analysis. Of the re maining 52117 probe sets detected above background on at least one array, only 3318 probe sets were identified by the variation filter as having a CV of greater than 0.5 and were subjected to hierarchical cluster analysis. Figure 4 1
42 showed the hierarchica l cluster analysis of the 10 arrays based on the expression level of the 3318 probe sets whose expression level varied the most. Supervised Analysis of Gene Expression Patterns Supervised microarray analysis identified 1081 probe sets differentially expres sed (early vs. late) samples at p <0.005 confidence level. Am ong these 1081 probe sets, 763 unique known genes were identified. The majority of transcripts (601/763) were upregulated. To obtain initial information regarding the functionality of those gene s that differentially expressed between early -surgical and late surgical conditions, the NetAffx query was undertaken for retrieving Gene Ontology (GO) annotations of those genes. The list of annotated genes was grouped into18 functional categories (Figure 4 2). Because of the number of differentially expressed genes, we elected to narrow our di scussion to selected categories including generalized stress response and redox regulation (Table 4 2 ), protein m embolism (Table 4 3), energy metabolism (Table 4 4), and muscle specific regulatory genes (Table 4 5) Remaining functional categories not presented in the discussion together within the lis t of expressed sequence tags were summarized i n the tables of Appendix (A1 -A11 ). Path A nalysis Out of the 763 unique products, the Pathway-Express analysis considered 212 focus genes in its database. Scrutinizing the functional and biological linkage between these genes, the Janus kinase/signal transducers and activators of transcription (JAK/STAT) pathw ay (n=16, p value< 0.0001) (Figure 4 3) the p53 signaling pathway (n=10, p value<0.000 1) (Figure 4 4) the ErbB signaling pathway (n=7, p value=0.03), and the MAPK signaling pathway (n=15 p value=0.04) were identified (Table 4 6 ).
43 Discussion Genome -wide gene expression pro filing has created unique opportunities to investigate complex biological processes regulated at the transcriptio nal level. A previous study used the microarray technique to describe the molecular response associated with ventilator induc ed muscle atrophy (VIDD) in an animal model (17) To our knowledge, this is the first repeated measures genome -wide profiling study examining molecular responses associated with diaphragm inactivity/MV in humans. Using gene expression profiling, we identified 763 unique transcripts that were differentially expressed (p<0.005) between early -surgical and late-surgical conditions. The majority of transcripts (601/763) were up-regulated. The list of differentially expressed genes was grouped into 18 functional groups. The objective of this study was to assess some of the transcriptional factors that are responsible for maintaining contractile function, stress response, protein metabolism, and energy metabolism, and how they were affected i n the course of cardiothoracic surgery. Generalized Stress Responsive and Redox Regulation G enes Interleukin 6 D uring cardiothoracic surgica l procedure, we observed increased expression in a number of genes linked to inflammatory and/or immune response. For example, interleukin 6 (IL6), a known proinflammatory cytokine, was signi ficantly upregulated (15.6 -fold). It is noted that, with cachexia, IL6 are the key triggers of muscle wasting, but IL6 induced muscle atrophy also occurs in the healthy animals (93) Meanwhile, IL6 may interact with a JAK/STAT signaling pathway, leading to changes in the expression of the suppressors of cytokine signaling (SOCS) family, and that this process may play a role in muscle atrophy with disuse (36) The J AK -STAT signaling takes part in the regulation of cellular responses to cytokines and growth factors. The deletion of SOCS genes in mice leads to significant overgrowth (94) In the present investigation, we
44 observe d an increase of several SOCS mRNAs in the diaphragm including suppressor of cytokine signaling 1 (SOCS1) (4.7 -fold), suppressor of cytokine signaling 2 (SOCS2) (3.1-fold), and suppressor of cytokine signaling 3 (SOCS3) (9.4-fold) as well as signal transdu cer and activator of transcription 3 (STAT3) (1.6-fold). The Path analysis identified that during the surgical procedure, increased expression of IL6 was associated with the increased expression of those genes (Figure 4 2) More interesting, a previous stu dy found that there was a significant negative correlation between SOCS3 mRNA and myofibrillar protein content in the IL6 induced atrophied muscle (93) Collectively, this suggests that IL6 triggers an intracellular cascade including a JAK/STAT pathway during the cardiothoracic surgical procedure and this process possibly regulate s the cellular respo nse in the context of diaphragm unloading. Despite previous studies in the animals suggested that cytokines e.g. IL6 are unlikely to involve in disuse muscle atrophy, we detected a significant increase in the mRNA for cytokines, namely IL6 (15.6-fold) and IL8 (9.2 -fold). This is most likely due to the fact that our model is not a pure MV inactivity paradigm with the addition of surgery. Our surgery/MV model, however, is the actual clinical situation that often leads to VIDD and difficult weaning in hu mans, and thus, our results indicate that cytokines may affect diaphragm muscle and are relevant to the clinical management of these patients. Oxidative stress Oxidative stress has been implicated as a contributing factor to disuse muscle atrophy and a rapid onset of oxidative stress can occur following as early as 3 6 hours of MV (12) Consistent with a previous study (28) we found several genes upregulated in the diaphragm responsible for oxidative stress, including peroxiredoxin 6 (PRDX6) (2 -fold), superoxide dismutase 2, mitochondrial (SOD2) (2.9 -fold) and thioredoxin (TXN) (1.9-fold).
45 PRDX6 is an antioxidant enzyme that can reduce H2O2 and alkyl hydroperoxide to water and alcohol, respectively (95) PRDX6 is widely expressed in all the vital organs including the skeletal muscle (96) Additionally, Wang et al. (97) have shown that PRDX6 is a unique nonred undant antioxidant that functions independently of other antioxidant proteins such as catalase (CAT), glutathione (GPX), and superoxide dismutase (SOD). In the present investigation, we observed an increase in PRDX6 mRNA in the diaphragm during the surgica l procedure, suggesting that the PRDX6 antioxidant properties might play a role in the human diaphragm muscle unloading. It is well established that in quiescent cell s much of reactive oxygen species (ROS) are produced as byproduct of mitochondria l respir ation when electrons leak from the electron transfer chain (ETC). The mitochondrial production of ROS results in the oxidation of mitochondrial lipids, protein, and DNA (98) SOD2, one of the enzymes of superoxide dismutase, converts superoxide to oxygen plus hydrogen peroxide and serves as the primary defense against mitochondrial superoxide. Theref ore, it is not surprising that we detect ed an increase of SOD2 mRNA in our study. In mammals, three isoforms of superoxides are present. SOD1 is located in cytoplasm, SOD2 in the mitochondria, and SOD3 in the extracellular region. In the present investigat ion, we observed an increase of mRNA expression level in SOD2, but not in SOD1 and SOD3 in the diaphragm. This finding was consistent with previous observation that the diaphragm of 12 hour MV animals exhibited increased mRNA expression for SOD2 and no cha nge in the mRNA expression of SOD1 was detected (99) Additionally, Chen et al. (100) found that the antioxidant systems eg. glutathione (GSH) and thioredoxin (TXN) were functionally distinct in cells and they showed that mitochondrial TXN 2 was more sensitive to oxidation than cytoplasmic TXN 1 by exogenously added peroxides. Hence, oxidative stress in
46 mitochondria may present a n early signal of diaphragm unloading and play an important role in our surgery/MV model. Th is intriguing possibility await s further confirmation. TXN is a small (12 kD) globular, ubiqu itous enzyme whose function is involved in antioxidant defense mechanisms such as the elimination of peroxide and the reduction of oxidized proteins. In the present investigation, we observed an increase in TXN mRNA in the diaphragm during the surgical procedure This finding is co nsistent with the animal study reporting (101) that the expression of TXN is significantly increased by 2 and 4 -day hindlimb unloading, which precedes the muscle weight loss. More interest ing, TXN involves in various cellular process via redox signaling pathway, some of which are thought to be closely associated with muscle atrophy (101) Specifically, TXN can exert suppressive effects on the process of muscle atrophy as follows: (1) TXN suppresses the activation of NF kB via the inhibition of I kB breakdown, which then inhibits the NF kB -induced activation of ubiquitin pathways (102) and (2) TXN works with PRD X to eliminate ROS production, which in turn suppresses the ROS mediated activation of NF kB, FOXO, and the ubiquitin-proteasome system. Collectively, our data suggests that increased expression of a series of antioxidant genes, including PRDX6, SOD2 and T XN, participate in establishing an antioxidant firewall and their antioxidant properties are important in response to oxidative insult in the human diaphragm muscle unloading. Protein M etabolism Disuse atrophy can be detected following as little as 18 ho urs of MV use (10) In muscle atrophy, the balance between protein synthesis and degradation is shifted. The majority of muscle protein loss results from the acceleration of muscle protein degradation (103) At least three proteolytic systems are known to be involved in muscle protein degradation. These include lysosomal pro teolysis, calcium activated proteasomes, and ubiqutin -proeasome dependent
47 pathway. Several studies have shown members of each of these pathways are upregulated during disuse (17, 36, 37, 104, 105) Consistent with p revious studies, our data indicates that cardiothoracic surgical procedure s with MV support increase the proteolytic processes, which may cause significant atrophy of the human diaphragm. The parallel regulation of these proteolytic pathways under the surg ical procedure was discussed as follows: Proteasome -mediated proteolysis P roteasome -mediated proteolysis is thought to be responsible for the majority of protein breakdown that occurs during disuse atrophy (24) This proteolytic process is characterized by the concerted action of ubiqutin-conjugating enzymes that link chains of polyubiqutin onto target proteins for degradation by either the 26S proteasome or the 20S protease core (106) In the present investigation, we found that mRNAs for polyubiqutination were upregulated in the diaphragm including several ubiqutin -conjugating enzymes (UBE2) and u biquitin specific peptidases (USP). Although the USP itself does not involve in proteasome binding, the upregulation of the USP enzymes may assist to recycle free ubiquitin efficiently when the ubiquitin -proteasome systems is activated (59) More importantly, we found a 2. 6 -fold upregulation of the ubiquitin protein ligase enzyme (E3) in the diaphragm. Tripartite motif -containing 63 (TRIM63) (otherwise known as MuRF 1) is a muscle -specific E3 identified being important to the regulation of protein loss during atrophy. Thus, the modest upregulation of TRIM63 in the diaphragm indicates that patients undergoing a short term surgical procedure (4.9+/ 1.8 hours), including the use of MV, are at risk for developing VIDD Interestingly, our data demonstrated downregulation in anoth er muscle -specific E3 gene, namely F -box protein 32 (FBXO32) (otherwise known as MAF -box). FBXO32 is a component of an SCF type (Skp1/Cdc53/F -box complex) E3 ubiquitin ligase that determines substrate specificity for proteasome degradation. This protein is specifically
48 expression in cardiac and skeletal muscle and has previously been identified as a marker of muscle atrophy (25) In this study, we found a 3.5 -fold downregulation of FBXO32 in the muscle samples. Previ ous animal work showed that 12 hours of MV resulted in significant elevations in mRNA levels in both FBXO32 (MAFbx) (3.8 -fold) and MuRF 1 (19 -fold) (28) However, in contrast to the animal studies, a consistent elevation of MAFbx and MuRF 1 mRNA has not been observed in published human muscle disuse studies (review in Ref. (107) ). For example, de Boer et al. (108) showed 10 days of limb immobilization to result in elevated mRNA levels of MuRF 1, but not FBXO32, in the vastus lateralis of healthy human volunteers. These observations ques tion the role of MuRF 1 and FBXO32 consistently in human muscle disuse atrophy. Further work is required to explain these important observations. Lysosomal proteolysis As mentioned earlier cellular proteins can be tar geted by lysosomal enzymes, known as cathepsins. In the present investigation, we observed an increase in cathepsin C (CTSC) (2.7 fold) and cathepsin L1 (CTSL1) (2.0 -fold) mRNA in the diaphragm during the surgical procedure Although cathepsin are unlikely to degrade the bulk of myobrillar proteins, some repor ts have suggested that cathepsin may play a special role in turnover of membrane proteins, including receptors, ligands, channel s, and transporters (60) Meanwhile, literature suggests that proteolysis during muscle atrophy represents an interaction of lysosomal and ubiquitinproteasomal mechanisms (31) In support of this, we f ound that upregulation of cathe p s ins were coordinated with an increase of pr otein ubiquitination in the diaphragm suggesting that lysosomal proteolysis may play a role in human diaphragm muscle disuse during the cardiothoracic surgical procedure.
49 Calciumactivated proteasomes Calpains (such as calpains I and II) are Ca2+ activat ed proteases that are activated in skeletal muscle during periods of inactivity (63) Calpain substrates include proteins that are involved in the assembly and scaffolding of myofibrils. For example, nebulin and titin, two proteins that connect myofilament to the Z -disc, are known calpain substrates (64) However, calp ains cleave their protein substrate, rather than completely degrading them, thereby generating fragments (63) It has been hypothesized that these fragments resulting from calpain cleavage become substrates for the ubiqutin-proeasome dependent pathway (UPP). In support of this hypothesis, Menconi et al. (109) demonstrate that calpain activation in myotubes results in a dose and time -dependent increase in proteasome activity Additionally, Smith et al. (110) demonstrate d that the calpain proteases act upstream of the UPP and calpain activation ar e sufficient to activate the UPP However, in the present investigation, no change in mRNA levels for calpains was found, concomitantly with the UPP. We admit that, because of our study design, we may have missed early or transient increases in the express ion of calpains. In fact, the mRNA level of calpain does not necessarily reflect its in vivo activity because 1) calpains activity varies with cyto solic calcium concentration and 2) its activity is further regulated by its inhibitor, calpastatin, and membrane phospholipids (111) Protein s ynthesis Consistent with the idea that decreased protein synthesis is involved in the loss of protein during muscle disuse, two nuclear genes coding for mitochondrial ribosomal proteins were modestly downregulated, including mitochondr ial ribosomal protein S25 (MRPS25) (1.4 -fold decrease) and mit ochondrial ribosomal protein L47 (MRPL47) (1.8 -fold decrease). Several mRNAs encoding eukaryotic translation initial factors (EIFs), the elongation factor 2 (ELL2), and the termination factor 1 (ETF1) were upregulated in the diaphragm in response to the
50 cardiothoracic surgical procedure. In addition, the surgical procedure was associated with increased ribosomal protein S24 (PRS24) (2.4 -fold) and S6 (RPS6) (2.4 -fold) mRNA, a 40S ribosome subunit. Overall, this suggests that the diaphragm may upregulate the protein translation capacity after the cardiothoracic surgery; however, the rate of mitochondrial protein synthesis is decreased. Energy M etabo lism During cardiothoracic surgical procedures, us e of controlled MV ex poses the diaphragm to a unique mode of disuse. The diaphragm is simultaneously unloaded, electrically quiescent and phasically shortened by cyclical lung inflation In addition, neuromuscular junctions are blocked by neuromuscular bl o cking ag ents Under such conditions, the energy metabolic requirements of the diaphragm are decreased, which likely impacts the rate of cellular energy turnover Previous muscle disuse studies have demonstrated that many genes required for ATP production a nd the key regulatory steps of the glycolysis /gluconeogenesis were down regulated (17, 37) Consistent with this, we observed a decreased expression of malate dehydrogenase 1 (MDH1) (2.2 -fold decrease). MDH1 is impo rtant in transporting NADH equivalents across the mitochondrial membrane, controlling tricarboxylic acid (TCA) cycle pool size and providing contractile function (112) It plays a crucial role both in the malate aspartate shuttle and the TCA cycle in all aerobic tissues of mammals, including the skeletal muscles (113) A decreased expression of MDH1 suggests that during the surgical procedure the diaphragm tends to decreased reliance on carbohydrate oxidation because less metabolic requirements are needed. In addition, an increase in pyruvate dehydrogenase kinase, isoform 4 mRNA level (PDK4) (4.0 -fold), a mitochondrial enzyme responsible for regu lation of pyruvate dehydrogenase complex (PDC) was observed. PDC is able to catalyze the oxidation of pyruvate to acetyl -CoA in the mitochondria. Induction of PDK4 will inhibit the PDC activity and decrease carbohydrate
51 oxidation; thereby conserve glucose and the substrate for gluconeogenesis (114) More importantly, activation of PDK4 may enhance the oxidation of fatty acids by inactivation of PDC (115) Therefore, an increased expression of PDK4 suggests that the diaphragm during the surgical procedure tends to utilize fatty acid, rather than carbohydrate, as a fuel source. These observations seemingly conflict with prev ious studies showing that unloading muscle is associated with a fiber type switch (from slow to fast myosin fiber types) as well as metabolic changes including increased substrate level activation of glycolysis and inhibition of fatty acid oxidation. For e xample, Wittwer et al. reported a downregulation of the capacity to oxidize fatty acids and an increase in glycolytic capacity in prolonged unloading of rat soleus muscle (116) The cause of this discrepancy is unknown; however one explanation may be that an early adaptation to unloading induced metabolic deregulation occurs via increasing lipid utilization, while in the later phase of unloading metaboli c flexibility is lost, resulting in enhanced reliance on glucose utilization concomitant with lipid accumulation in tissue. In support of this hypothes is, Mazatti et al. found that 24 hours of muscle unloading rather than 12 days of muscle unloading result e d in significantly the upregulation of peroxisome proliferators activated unloading (117) F urther studies are needed to tes t this hypothesis. A downregulation of phosphoenolpyruvate carboxykinase 1 (PCK1) (2.3 -fold decrease) which plays a role in the regulation of gluconeogenesis was observed. This finding was not anticipated since the diaphragm is not considered to be a major site of glucose synthesis. Collectively, the surgical procedure alters mRNA expression patterns of the genes encoding key energy metabolism enzymes and results in an impairment of muscle carbohydrate metabolism as indicated by the upregulation of PDK4 mRN A.
52 Muscle -specific Regulatory G enes S everal muscle -specific regulatory genes were affected during the cardiothoracic surgery, including myogenic differentiation 1 (MYOD1) (2 -fold increase), myogenic factor 5 (MYF5) (1.6 -fold decrease), supervillin (SVIL) ( 2 -fold increase), and myocyte enhancer factor 2C (MEF2C) (3.5 -fold decrease) as well as mesenchyme homeobox 2 (MEOX2) (3.5-fold decrease). MYOD is one member of myogenic transcription factors, which can stimulate and modulate the transcription of muscle -sp ecific genes and thus are able to contribute to muscle plasticity (118) While its role in adult muscle is not f ully understood, it implicated in fiber ph enotype adaptation in limb muscles. Although it is still controversial, several studies have shown that an adaptation from slow to fast phenotype was associated with elevated MYOD1 mRNA expression. Consistent with previous finding (36) upregulation of MYOD1 was seen during the initial stage of atrophy. However, upregulation of MYOD1 also has been seen with increased muscle loading (119) Additionally, in MYOD1 knockout mice, MYOD1 deletion resulted in a decrease in diaphragm maximal titanic tension, along with decrements in peak power output (120) These conflicting findings raise a question as to whether MYOD1 gene expression is dependent on interaction of the co activators or inhibitors present in different activity paradigms. In support of this hypothesis, Stevenson et al. demonstrated that in a microarray study the expression pattern of MYOD1 and Mrg1, a transcriptional co activator, were tightly co regulated (r2 = 0.96) during muscle disuse atrophy (36) F urther studies are ne eded in progress to test this hypothesis. MYF5, another member of myogenic transcription factors, was downregulated (1.6 -fold). MYF5 plays an integral role in the initiation and control of skeletal muscle development (121) In adult muscle, MYF5 is expressed in satellite cells (122) and upregulation of MYF5 also has been reported after a single bout of exercise, indicating that upregulation of MYF5 is associated with load -mediated satellite activation (123) Additionally, MYF5 is also present in muscle
53 spindles in adult muscle (122) and therefore MYF5 expression could be also reflected to muscle spindle activity in the diaphragm. We observed a n upregulation of SVIL mRNA (2 -fold increase) SVIL is an actin -binding protein and it expresses in muscle -enriched tissue, especially skeletal muscle (124) The role of SVIL in muscle is still under investigation. It forms a high affinity link between the acti n cytoskeleton and the plasma membrane (sarcolemma) of striate d muscle cells. Although dystrophin is required for sarcolemmal integrity (125) SVIL may provide an additional anchor mai ntaining the integrity and organization of the sarcolemma of striated muscle cells during the mechanical stresses associated with load -induced stretching and muscle contraction (126) Additionally, SVIL may mediate the interaction between actin filaments and myosin II, functioning as membrane associated scaffold (127) The upregulation of SVIL in our st udy suggests that this protein might be involved in the atrophy process following the surgical procedure. However, the role of SVIL in muscle disuse remain s elusive. MEF2C, a transcriptional factor for skeletal muscle development and regeneration was dow nregulated (3.5 -fold decrease) in the study. MEF2 proteins, MEF2A, B, C, and D, usually cooperate with myogenic transcriptional factor family to drive skeletal muscle development during embryogenesis, but little is known about the role of MEF2C in the a dult muscle. Potthoff et al. recently shows that MEF2C is an essential regulator of the M -line -specific protein, myomesin, and M protein and that loss of MEF2C in skeletal muscle resulted in improper sacromere organization (128) Additionally, a 14 days spaceflight suppressed MEF2C protein production, and with 9 days recovery in a 1 G environment MEF2C protein content returnd to the normal level, suggesting that MEF2C could be a key transcriptional factor for skelet al muscle atrophy and reloading (129) Collectively, MEF2C is sensitive to muscle loading/unloading
54 conditions and the downregulated MEF2C might impair contractile function be cause MEF2C is essential for sarcomere a ssembly. Path Analysis Path analys is via PathwayExpress identified that during the cardiothoracic surgical procedure affected the JAK -STAT, p53, ErbB, and MAPK signaling pathways (Table 4 2) Among these pathways the JAK STAT pathway appears to be key be cause it not only modulates the cell cycle, the apoptosis process and the MAPK signaling, but also is the signaling pathway that is most significantly modulated as indicated by the p -value <0.0001. The JAK/STAT pathway is a intracellular signal transducing pathway that is activated by oxygen radicals, various cytokines, and growth factors in various disease states and is also recognized as an important membrane to nucleus signaling pathway for a variety of stress responses and oxidative stress [see review r ef (130) ]. A critical outcome of JAK/STAT activity is the translocation of STAT to the nucleus, leading to alterations in the transcription and expression of a number of specific target genes (131) In the context of the surgery/MV, we observed the upregulation of specific target genes involved in PIM1 (pim 1) (3.5 -fold increase) MYC (c -Myc) (8.0 -fold increase) and CISH (CIS) (6.8 -fold increase) thereby possibly modulating cel l proliferation, development, immunity, and cell cycle (Figure 4 2) Another key pathway identified in this study is the p53 signaling pathway (p<0.0001). P 53 is a sequence -specific transcriptional factor and it can activate its downstream target in a man ner to induce cell growth arrest (132) In this study, many downstream targets of p53 revealed altered mRNA levels ( Figure 4 3).GADD45A, B, and G are genes that promote cell growth arrest are upregulated durin g the surgical procedure (3.0 -fold increase, 10.2-fold increase, and 4.3 -fold increase, respectively) A c yclin -dependent kinase inhibitor 1 (p21) ( otherwise known as CDKN1A ) (4.9 -fold increase) is also upregualted. P 21 plays a cooperative role with GADD45
55 prote ins in inducing cell growth arrest (133) Also, it is wellknown that p53 can mediate apoptotic cell death by elevating the transcriptional expression of several proapoptotic genes (e.g., Bax, PUMA, Noxa, and DR4/5) (134, 135) However, whether p53 induced apoptosis plays a role in skeletal muscle remains unknown. Siu and his college (136) found that p53 and its target genes were related to the unloading induced apoptosis in the animal models. Consistent with this finding two p5 3 -induced proapoptotic genes were upregu lated in this study, including N oxa (otherwise known as PMAIP1) (2.8 -fold increase) and DR5 (otherwise known as TNFRSF10B) (2.5 -fold increase) T hese data indicate that Noxa and DR5 may involve i n the apoptotic responses during the unloading induced muscle atrophy. However, it is noted that p53 induces either cell cycle arrest or apoptosis depending on specific cellular contexts. For example, previous data demonstrates that the activation of apopt otic targets (eg. noxa or/and DR5) alone is not sufficient to induce apoptosis in some cells and the induction of GADD45 mediated by p21 may inhibit cell apoptosis (135) Nevertheless, our data suggests that the p53 signal pathway controlling in apoptosis/cell cycle arrest through it targets may play an additional role in muscl e atrophy process during the surgical procedure. Summary and C onclusion In summary, we found that cardiothoracic surgery results in rapid changes in diaphragm gene expression. We identified 763 transcripts that were differentially expressed (p<0.005) betw een early -surgical and late -surgical samples. Genes could be categorized into 18 functional groups, of which we chose to focus on four categories for discussion The major findings includes: 1) surgical stress related genes demonstrated the largest changes which likely trigger an intracellular cascade including a JAK/STAT pathway during the cardiothoracic surgical procedure and this process possibly regulate s the cellular response in the c ontext of diaphragm unloading; 2 ) an increased expression of antioxi dant genes occurred, which may be related to
56 protective adaptations in response to stress including increased oxida nt production in mitochondria; 3 ) several proteolytic related genes, including ubiqutin -c onjugating enzymes (E2) and MuRF 1 (E3), were upreg ulated, indicating that the cardiothoracic surgical procedure increased the proteo lytic processes, which may lead to significant a trophy of the human diaphragm; 4 ) the diaphragm during the surgi cal procedure tends to decrease activity of the glycolytic enz ymes, concomitant with an decrease in gluconeogenic c apacity in the muscle; 5 ) several muscle -specific regulatory genes were affected by the cardiothoracic surgical procedure; however, their physiological role in muscle disuse remains elusive; and 6 ) th e p 53 signal pathway involved in negative growth control through it targets may play an additional role in the muscle atrophy process during the surgical procedure. O ur microarray data illuminate how the mRNA expression in the human diaphragm is affected by a surgical procedure (including the use of CMV). The changes in gene expression following surgical procedures may be particularly relevant to understanding the pathogenesis of VIDD in patients at risk of post -surgical weaning difficulties. The knowledge of underlying molecular mechanis ms of diaphragm dysfunction may help direct efforts to develop rehabilitation and pharmacologic interventions in the preoperative and postoperative periods. Further studies are anticipated to confirm and to clarify the biologi c al relevance of our study.
57 Figure 4 1. Unsupervised cluster analysis. This figure shows the hierarchal cluster pattern of the hybridization signal intensities of 33 18 probe sets that display a CV >0.5. In the heat map, the in tensity of the color indicates relative expression for each individual gene. The intensity of the color red indicates relative greater than the mean for that individual gene, blue indicates expression less than the mean, and the white indicates mean expres sion. The dendrogram of the clustering is displayed above and is used to identify similarities in expression patterns among the arrays. Dendrogram Patient ID Heat maps
58 Figure 4 2 Functional classification of 763 genes differentially expressed in early vs. late surgical conditions.
59 Figure 4 3 JAK-STAT signaling pathway. Yellow and blue indicate overexpressed a nd underexpressed genes in the chips respectively. Light green indicates that the gene was not present in the chip s or its expression did not change significantly after surgery White indicates that the gene has no reference in the KEGG database and the function of this gene is unknown p, phosphorylation; u, ubiquitination.A large oval represents a link to another pathway map. Solid line indicates a direct effect w hile dash line indicates an indirect effect.
60 Figure 4 4 p53 signaling pathway Yellow and blue indicate overexpressed and underexpressed genes in the chips, respectively. Light green indicates that the gene was not present in the chips or its expressi on did not change significantly after surgery White indicates that the gene has no reference in the KEGG database and the function of this gene is unknown. p, phosphorylation; u, ubiquitination.A large oval represents a link to another pathway map. Solid line indicates a direct effect while dash line indicates an indirect effect.
61 Table 4-1. Clinical baseline char acteristics of five patients u ndergoing cardiothoracic surgery Patient ID Age Height (cm) Weight (Kg) Type of Surgery Type of anesthesia CPB time (mins) HCA time (mins) CP time (mins) 1 56 183 155 Aortic, valve replacement (AVR) ascending general endotracheal 243 15 202 3 76 174 87 Resection and replacement of the ascending aorta and proximal arch; replacement of the aortic valve general endotracheal 159 10 135 4 71 182 100 Replacement of the ascending and arch aorta general endotracheal 166 24 42 5 54 183 110 Ascending and aortic arch replacement general endotracheal 266 5 204 6 78 180 100 Aortic root remodeling w/ preservation of the aortic valve and sinuses general endotracheal 255 N/A 130 Characteristics of patients undergoing cardiothoracic surgery. CPB time, cardiopu lmonary bypass time; HCA time, hypothermic circulatory arrest time; CP time, cross clamp time.
62 Table 4 2 List of g enes related to generalized stress response and redox regulation that are significantly different after surgery Probe set Symbol Fold change Description Function 200989_at HIF1A 2.6 hypoxia inducible factor 1, alpha subunit (basic helix loop -helix transcr iption factor) response to hypoxia 209189_at FOS 6.8 v fos FBJ murine osteosarcoma viral oncogene homolog inflammatory response 202376_at SERPINA 3 5.8 serpin peptidase inhibitor, clade A (alpha 1 antiproteinase, antitrypsin), member 3 inflammatory respon se 213146_at JMJD3 4.3 jumonji domain containing 3 inflammatory response 206157_at PTX3 20.5 pentraxin related gene, rapidly induced by IL 1 beta inflammatory response 211506_s_at IL8 9.2 interleukin 8 inflammatory response 204470_at CXCL1 7.4 chemokin e (C X C motif) ligand 1 (melanoma growth stimulating activity, alpha) inflammatory response 207850_at CXCL3 5.1 chemokine (C X C motif) ligand 3 inflammatory response 209774_x_at CXCL2 8.3 chemokine (C X C motif) ligand 2 inflammatory response 205207_a t IL6 15.6 interleukin 6 (interferon, beta 2) inflammatory response 203372_s_at SOCS2 3.1 suppressor of cytokine signaling 2 JAK STAT cascade 210001_s_at SOCS1 4.7 suppressor of cytokine signaling 1 JAK STAT cascade 208992_s_at STAT3 1.6 signal transduc er and activator of transcription 3 (acute phase response factor) JAK STAT cascade 227697_at SOCS3 9.4 suppressor of cytokine signaling 3 JAK STAT cascade 220088_at C5AR1 5.1 complement component 5a receptor 1 immune response 205403_at IL1R2 6.8 interle ukin 1 receptor, type II immune response 206637_at P2RY14 2.1 purinergic receptor P2Y, G protein coupled, 14 immune response 212196_at IL6ST 2.0 interleukin 6 signal transducer (gp130, oncostatin M receptor) immune response 206087_x_at HFE 1.7 hemochr omatosis immune response 236947_at SEMA3C 1.7 sema domain, immunoglobulin domain (Ig), short basic domain, secreted, (semaphorin) 3C immune response 203574_at NFIL3 4.2 nuclear factor, interleukin 3 regulated immune response 242751_at PRDX6 1.9 peroxir edoxin 6 response to oxidative stress 215223_s_at SOD2 2.9 superoxide dismutase 2, mitochondrial response to oxidative stress 208864_s_at TXN 1.9 thioredoxin cell redox homeostasis
63 Table 4 3 Expression of protein metabolism genes that are significant ly different in the diaphragm after surgery Probe set Symbol Fold change Description Function 201195_s_at SLC7A5 2.2 solute carrier family 7 (cationic amino acid transporter, y+ system), member 5 amino acid metabolism 225647_s_at CTSC 2.7 cathepsin C lys osome 202087_s_at CTSL1 2.0 cathepsin L1 lysosome 200881_s_at DNAJA1 1.9 DnaJ (Hsp40) homolog, subfamily A, member 1 protein folding 200664_s_at DNAJB1 2.8 DnaJ (Hsp40) homolog, subfamily B, member 1 protein folding 208810_at DNAJB6 1.7 DnaJ (Hsp40) ho molog, subfamily B, member 6 protein folding 210187_at FKBP1A 2.3 FK506 binding protein 1A, 12kDa protein folding 225827_at EIF2C2 1.7 eukaryotic translation initiation factor 2C, 2 protein synthesis 208624_s_at EIF4G1 1.6 eukaryotic translation initiat ion factor 4 gamma, 1 protein synthesis 1554309_at EIF4G3 1.9 eukaryotic translation initiation factor 4 gamma, 3 protein synthesis 211787_s_at EIF4A1 2.6 eukaryotic translation initiation factor 4A, isoform 1 protein synthesis 208707_at EIF5 1.9 eukary otic translation initiation factor 5 protein synthesis 201574_at ETF1 1.8 eukaryotic translation termination factor 1 protein synthesis 223481_s_at MRPL47 1.8 mitochondrial ribosomal protein L47 protein synthesis 224873_s_at MRPS25 1.4 mitochondrial r ibosomal protein S25 protein synthesis 1555878_at RPS24 2.4 ribosomal protein S24 protein synthesis 238156_at RPS6 2.4 ribosomal protein S6 protein synthesis 225954_s_at MIDN 4.3 midnolin protein modification 236975_at USP12 1.8 ubiquitin specific pept idase 12 ubiquitin thiolesterase activity 231990_at USP15 2.2 ubiquitin specific peptidase 15 ubiquitin thiolesterase activity 220370_s_at USP36 1.9 ubiquitin specific peptidase 36 ubiquitin thiolesterase activity 241762_at FBXO32 3.5 F box protein 32 ubiquitin protein ligase activity 236972_at TRIM63 2.6 tripartite motif containing 63 (MuRF 1) ubiquitin protein ligase activity
64 Table 4 3 Continued. Probe set Symbol Fold change Description Function 222435_s_at UBE2J1 1.7 ubiquitin conjugating enzym e E2, J1 (UBC6 homolog, yeast) ubiquitin protein ligase activity 243046_at UBE2D3 1.8 ubiquitin conjugating enzyme E2D 3 (UBC4/5 homolog, yeast) ubiquitin protein ligase activity 65521_at UBE2D4 1.5 ubiquitin conjugating enzyme E2D 4 (putative) ubiquitin protein ligase activity 202779_s_at UBE2S 1.6 ubiquitin conjugating enzyme E2S ubiquitin protein ligase activity 202779_s_at UBE2S 1.6 ubiquitin conjugating enzyme E2S ubiquitin protein ligase activity
65 Table 4 4 List of genes related to energy meta bolism that are significantly different in the diaphragm after surgery Probe set Symbol Fold change Description Function 240187_at PPP1R3C 2.8 protein phosphatase 1, regulatory (inhibitor) subunit 3C carbohydrate metabolism 204748_at PTGS2 5.2 prostagla ndin endoperoxide synthase 2 (prostaglandin G/H synthase and cyclooxygenase) fatty acid metabolism 209184_s_at IRS2 2.0 insulin receptor substrate 2 glucose metabolism 205960_at PDK4 4.0 pyruvate dehydrogenase kinase, isozyme 4 glucose metabolism 235374 _at MDH1 2.2 malate dehydrogenase 1, NAD (soluble) glycosis 206932_at CH25H 8.6 cholesterol 25 hydroxylase lipid metabolism 243296_at PBEF1 5.1 pre B cell colony enhancing factor 1 NAD biosynthesis 208383_s_at PCK1 2.3 phosphoenolpyruvate carboxykina se 1 (soluble) regulation of gluconeogenesis
66 Table 4 5 L ist of muscle -specific genes related to contractile functions that are significantly different in the diaphragm after surgery Probe set Symbol Fold change Description Function 215795_at MYH7B 2.4 myosin, heavy chain 7B, cardiac muscle, beta actin binding 222976_s_at TPM3 1.6 tropomyosin 3 actin binding 1567107_s_at TPM4 2.1 tropomyosin 4 actin binding 1569512_at SVIL 1.9 supervillin actin filament binding 236395_at MEF2C 3.5 myocyte enhanc er factor 2C muscle development 206201_s_at MEOX2 3.5 mesenchyme homeobox 2 muscle development 242795_at MYOT 2.8 myotilin muslce contraction 207424_at MYF5 1.6 myogenic factor 5 myogenic differentiation 206657_s_at MYOD1 2.0 myogenic differentiatio n 1 myogenic differentiation 211926_s_at MYH9 1.7 myosin, heavy chain 9, non muscle unknown
67 Table 4 6 Significant signaling pathways that were identified by Path Analysis Signaling pathway Up regulated transcripts Down regulated transcripts P value J AK STAT CBLB, CISH, CSF3, IFNGR1, IL6, IL6ST, JAK1,MYC, PIK3R3, PIM1, SOCS1, SOCS2, SOCS3, SPRED1, SPRY1,STAT3 ---<0.0001 p53 CCNB2, CDK2, CDKN1A, GADD45A, GADD45B, GADD45G, PMAIP1, SERPINE1, THBS1, TNFRSF10B ---<0.0001 ErbB ABL2, CBLB, CDKN1A, MYC, PAK6, PIK3R3 CDKN1B 0.03 MAPK ACVR1B, DUSP1, DUSP4, DUSP5, DUSP6, FOS, GADD45A, GADD45B, GADD45G, IL1R1, IL1R2, MAPKAPK2, MYC, NLK, NRA41 ---0.04
68 CHAPTER 5 BREATHING VARIABILIT Y DURING SPONTANEOUS BREATHING TRIALS IN PROLONGED MECHANICAL VENTILATIO N PATIETNS Background and Significance Mechanical ventilation is one of the cornerstone treatments for patients in intensive care units (ICUs). However, prolonged mechanical ventilation (PMV) is associated with increased risk of significant long term compl ications including mortality and high health care cost (137, 138) One common method for weaning patients is progressively lengthening spontaneous breathing trials (SBT) without ventilation support, until weaning is accomplished (139) Evaluation of the breathing pattern during SBT may impro ve clinical assessment of how patients are tolerating SBT and may predict ultimate weaning outcome (140) Therefore, any significant alteration in the breathing pattern of patients during the SBT requires investigation. Previous studies of breathing pattern during weaning trials have been largely confined to mean values of the breathing pa rameters (141145) Littl e attention has been focused on the variability in breathing pattern during weaning trials. Recently, evidence of the importance of the breathing variability in ICU patients was provided by Wysocki et al. 2006, who showed that reduced breathing variability, quantified by using coefficient of variation (CV), during a 60 min SBT was associated with a high incidence of acute weaning failure in the ICU patients (146) They also suggest that breathing variability indices, e.g. CV, are sufficient to distinguish successful case s from those who f ail and may serve as a w eaning predictor. Bien et al. reported that breathing pattern variability (measured by CV and the parameters of standard deviations) in patients who failed to weaning trials was significantly lower than those who passed weaning trials (147) In contrast, EI -Khatib el al. and Engoren found that the patients who failed to be separated from the ventilator had a lower breathing variability than the patients who succeeded (148, 149)
69 Therefore, we designed a prospective study in the ICU patients to inves tigate the b reathing variability during weaning trials. To eliminate any differences arising from different patient samples each patien t served as his or her own control. We hypothesized that comp ared with successful SBT bouts, the failed SBT bouts would demonstrate a significant lower breathing pattern variability. Literature Review Respiratory failure, requiring MV support, is characterized by impairment of respiratory mechanics and gas exchange. The severity of this impairment changes according to the p athophysiologic development of the disease. A fter resolution of respiratory failure, most patients are easily weaned, but as many as 20% of mechanically ventilated patients experience difficulty weaning (150, 151) According to the European Respiratory S ocietys classi fication in 2007, prolonged mechanical ventilatory (PMV) support is defined by a patient who fail s at least three weaning attempts or require s > 7 days of weaning after the first weaning attempt (137) T hese patients repeatedly fail to wean and face a substantial risk of longterm complications and even death (5, 138) It is esti mated that ICU mortality of PMV patients is about 25% (150, 152) Thus, weaning these patients from MV support is one of the great challenges in intensive care. Weaning Trials in Weaning P rotocols Weaning trials ar e recommended for MV patients who are considered to be ready to wean. In general, a weaning trial involves reducing the support provided by the ventilator while monitoring for evidence of respiratory distress or altered gas exchange. There are several dif ferent ways to perform a weaning trial. One common method for weaning patients is having the patient perform progressively lengthening spontaneous breathing trials (SBT) without mechanical ventilation support, until weaning is accomplished (139) During a SBT, a patient with a tracheostomy is removed from the ventilator to breathe spontaneously with supplemental
70 oxygen via a T -piece tube for a predetermined amount of time. During a SBT, the patient is carefully observed, vital signs and the adequacy of ventilation and/or gas exchange are measured Additionally, evidence suggests tha t breathing pattern represents the response of the respiratory system to physiologic distres s. For instance, during the SBT, patients adopt a breathing pattern that differs substantially from the pattern used when receiving MV support (145) The alteration of breathing patterns reflects global re spiratory system performance. Thus, breathing pattern analysis may be a helpful means of monitoring respiratory performance in PMV patients during SBT (140, 145) Breathing Pattern A nalysis The traditional strategy of breathing pattern analysis is to divide the breathing parameters into two parts: 1) mean value of the parameters (obtained by averaging over many breathing cycles) and 2) variability of the parameters (e.g. measured by the standard deviation and/or coe fficients of variation). More often, the mean values have been regarded as the true output of the respiratory control system and the measure of variability considered as an uncorrelated random (white) noise superimposed on the output of the respiratory con troller. However, emerging evidence shows that breath -to -breath variability of respiratory parameters is not rando m (153155) and may be explained either by a central neural mechanism or by instability of feedback l oops (156159) For example, in healthy humans, stimulation of the central /peripheral chemoreceptors with isocapnic hypoxia increased the gross breathing variability whereas external resistive loadings or elastic lo adings dec r eased the breathing variability (159161) These findings indicate that changes in the variability of respiratory parameters are specific and unique Analysis of variability may reflect different physiological influences on the control of breathing.
71 Reproducibility of Breathing P arameters A potential argument against studying the use of breathing pattern as weaning measurements could be made by citing the fact that breathing pattern in humans has shown its diversity and individuality: the breath to breath and day to -day variability in breathing pattern. In order to properly use the breathing pattern as an evaluative tool it is essential to know whether the breathing pattern parameters are reproducible. In 1988, Tobin MJ et al. designed a series of experiments that separately examined the breath -to -breath and day -to -day variability in breathing pat tern in healthy volunteers. T hey reported that breath to -breath variability in breathing pattern over a 15-min p eriod in 65 healthy subjects revealed large coefficient of variation s suggesting inter individual breath to -breath reproducibility of tests of respiratory control was limited (162) However, by examining day to -day data, the constancy of the average breathing pattern (mean of a 15-min recording) was acceptable when measured repeatedly (162) The following studie s further examined the reproducibility of breathing pattern parameters in critically ill, intubated patients. Krieger et al. investigated the variability of the breathing pattern before and after extubation in 50 clinically ready -to wean patients and they found that the CV for frequency and inspired tidal volume measured during a weaning trial over a 15-min recording were nearly identical pre -extubation and post -extubation, highlighting intra -individual breath -to -breath reproducibility was relatively stable (163) Yang KL also found a similar result (164) He examined the reproducibility of bre athing pattern parameters obtained on three weaning trials over a period of 15 minutes in 30 ICU patients whose primary diagnoses consisted of pneumonia, ARDS, neuromuscular diseases, chronic heart failure, and COPD. He found that the CV for frequency, ins pired tidal volume, and minute ventilation did not show any significant difference over three weanig trials indicating that breathing pattern parameters, measured with the CV, were reliable from one trial to the next with bedside instruments.
72 From the lit erature, we have learned that breathing pattern recording over a period of time exhibits inherent dynamics and fluctuations. This variability of breathing pattern is not random and demonstrates its diversity and individuality. This breath to -breath variabi lity is quite diverse among the healthy humans, but this irregular breathing pattern is reproducible for the same subjects under the same conditions, even in the critically-ill patients. Physiological Grounds of Breathing Pattern Variability Research int o breathing behavior of mammals demonstrates that the control of breathing is a n integrative process that result s from the interactions between several central neuronal networks (including the cerebral cortex that allow s behavioral and volitional modulatio n of respiration during wakefulness) and/or feedback modulations by mechanical and chemical afferents (159, 165167) The confluence of these complex interactions should result in some degrees of variability in brea thing pattern. However, this inherently dynamical behavior may become static (having reduced variability over a period of time) under high stress (168) or under some pathological conditions (169, 170) For instance, it has shown that loading respiration, in healthy humans mechanically (elastic and resistive) tends to reduce breathing variability (160, 161) Another striking case is people with compensated chronic heart failure (CHF). These patients usually demonstrate an oscillatory breathing pattern characterized by cyclical respiration (periodic breathing) during the daytime (171) This periodic breathing would enhance peripheral chemosensitivity in CHF, which in turn would result in instability of cardio -respiratory control (170) If peripheral chemoreceptor ove r activity couples with impaired baroreflex sensitivity, it would lead to slow the oscillations in blood pressure and respiration, representing a reduced variability in breathing pattern (172, 173) Additionally, e xperimental animal studies in acute lung injury demonstrated that application of variations in frequency and tidal volume during mechanical ventilation could
73 improve lung function and gas exchange, compared with a conventional volume -cycled MV mode (174, 175) This observation suggests that breathing variability added to mechanical ventilation provides an optimal level of physiological improvement. I t is speculative that breathing variability in physiological rhythms is invariabile and of the reserves to response challenges (176) A resp iratory controller with some degrees of variability may allow flexible responses to environmental/physiological changes by modulating the control parameters (177) As pointed out by Dejours et al. (1961), an infinite number of possible combinations of the ventilatory components exists capable of achieving the same minute ventilation. The number of combinations decreases when the demand for ventilation increases and at maximal ventilatory values all individuals tend to exhibit more similar patterns (178) Breathing Pattern during Weaning A number of breathing pattern parameters have been reported to be associated with the success or fail ure of ventilator discontinuation (139, 179181) Reported weaning predictors including vital capacity, tidal volume, respiratory rate, minute ventilation, rapid shallow breathing index (RSBI), and maximal inspirato ry pressure (PImax) have been developed and applied in clinical settings. Moreover, integrated factors also have been employed (139) for example, CROP index (CROP = dynamic compliance multiplies by maximal inspiratory pressure by PaO2/PAO2 and divides this product by the res piratory rate). However, analysi s of receiver operating c haracteristics curves (ROC) has shown none of these indices are sufficiently sensitive and specific to be useful in predicting the success of ventilation discontinuation, especially in the elderly and/or in the PMV patients (139) Studies of examining the breathing pattern, maximal inspiratory pressure, and lung mechanics in patie nts being weaned from MV displayed inconsistent findings (143, 144) Del Rosario et al. reported that patients who failed to wean had a higher respiratory rate and RSBI by
74 comparing with successfully wean ed groups. PImax and dynamic intrinsic p ositive airway pressure (PEEPi), measured from the oesophageal pressure were similar to both groups (143) On the contrary, J ubran and collegues found that at the early phase of a weaning trial, the fai lure group developed rapid shallow breathing and a higher value of PEEPi than the success ful group. Over the weaning course, the respiratory resistance increased in the failure group whereas it remains unchanged in the success group (144) At the end of weaning trials, they found that 13 of 17 failure to -wean patients increased in PaCO2 whereas 4 showed a decrease in PaCO2. They concluded that the patients who fail to wean developed rapid shallow breathing at the onset of the weaning trial and progressively increased in respiratory resistance and PEEPi, representing an excessive load to the respiratory muscles. This combination of increased mechanical load with rapid shallow breathing led to inefficient CO2 clearance, which was the dominant determinant of weaning failure in the overall group. However, that rapid shallow breathing developed at the onset of weaning trials in the failure group is not a universal phenomenon. Capdevia et al. investigate d 17 patients receiving PMV (average length of MV support > 20 days) and found that at the onset of weaning trials, high respiratory ra te and low tidal volume values were observed in both success and failure groups, without significant inter -group differences (142) But, they agreed that PEEPi increased in response to the increased respiratory rate in the failure group throughout the weaning period (142) It seems that an excessive inspiratory load imposed on the respiratory muscles is an essential determinant of weaning failure. This excessive load lead s to increase in the required breathing energy expenditure with a concomitant of breathing pattern alterations (144) Additionally, it is accepted that a high neural drive persisted over the weaning period in failure to -wean patients (145) The presence of a high neural drive indicates that the respiratory muscles
75 continue to generate large inspiratory pressure to cop e with this excessive load rather than a decrease in respiratory motor output. If the mechanical loads excessive to the capacity that respiratory muscle can generate, this imbalance will lead to respiratory distress and eventually, the weaning failure will ensue. The importance of the load-capacity balance on the weaning outcome of PMV patients has been highlighted by a recent study. Purro et al. have shown that in the presence of a high neural drive to breathe, the patients with a high load/capacity index (such as Pdi/Pdimax > 0.4) were unweanable (where Pdi is the pressure required for tidal breathing and Pdimax is maximal pressure that the respiratory muscles can generate) (182) They also found that a positive linear relationship between the load/capacity index and the effective inspiratory impedance (P0.1/tidal volume/inspiratory time and P0.1 is the v alue of airway pressure 100ms after the beginning of the occluded inspiration) (r = 0.61). Thus, they suggested that noninvasive methods such as breathing pattern and P0.1 might help to identify the patients who fail to wean. However, it was shown that the value of P0.1 would be underestimated in the presence of hypercapnia or in the patients with abnormal lung mechanics (183) Additionally, i t is reported that a progressiv e deterioration in respiratory mechanics during SBT in the patients who fail to wean and Pdimax probably decreased by the end of the weaning trials (184) Moreover, in clinica l settings, it is impractical to measure the ratio of Pdi/Pdimax on a breathby-breath basis during the weaning trials. Thus, an accessible and alternate index to represent the relationship of th e load -capacity balance is needed. Breathing Variability during Weaning F ew investigators have attempted to examine the breathing variability during weaning (146149) Bien et al. reported that breathing pattern variability (measured by CV and the parameters of standard deviations) in patients who failed weaning trials was significantly lower
76 than those who passed their weaning trials (147) Accordingly, they also reported that the area under t he ROC curves of these breathing variability indices was within the range of 0.73 0.80. Wysocki et al. showed that reduced breathing variability, quantified by using CV, during a 60 min SBT was associated with a high incidence of acute weaning failure in t he ICU patients (146) In contrast, El -Khatib et al. and Engoren found that breathing variability measured by entropy indices was more irregular (higher) in patients who failed extubation compared to patients who passed extubation trials (148, 149) It is hard to explain the inconsistency of these findings because of the nature of the corresponding populations and different experimental c onditions. Nevertheless, all authors agree that breathing variability may potentially serve as a weaning predictor for the ICU patients. It is speculative that breathing variability is likely to be a reflection of a load -capacity balance of respiratory sy stem. Previous studies have shown that external resistive loadings or elastic loadings decreased breathing variability during loaded respiration in healthy humans (160, 161) Additionally, it was reported that respi ratory variability was reduced in patients with restrictive lung disease, compared with that of healthy subjects (169) Caminal et al. examined breat hing variability in the respiratory volume signals based on non linear prediction methods in a group of 20 patients on weaning trials from MV and each patient placed under two different levels of pressure support ventilation (PSV), classified as low PSV (5 +/ 2 cm H2O) and high PSV (12+/ 2 cm H2O). They found an inverse relationship between the levels of PSV and the breathing variability in tidal volume and inspiratory time (185) These results suggest that breathing variability might parallel to the load capacity balance of the respiratory system and a high breathing variability indicates a large respiratory reserve. However, this supposition needs further studies to approve it.
77 In summary, patients requiring long term MV support face a high risk of mortality/mobility during their hospitalization. SBT are recommended f or patients who are ready to -wean. Evaluation of breathing pattern during SBT may be helpful to assess the effectiveness of weaning protocols. Many b reathing parameters represented by the mean values have been reported to be associated with the success or failure of SBT However none of these predictors are universally accepted and they lose their discriminatory power in the PMV population On the other hand, analysis of breathing variability reflecting different physiological influences on the control of breathing, may provide an alternate method to predict weaning outcome Recently, Wysocki et al demonstrated that reduced breathing variability, quantified by using CV during a 60 min SBT was associated with a high incidence of acute weaning failure in the ICU patients (146) It was suggest ed that breathing variability indices, e.g. CV, are sufficient to distinguish successful and fail ed cases and may potentially serve as a w eaning predictor. In contrast, El -Khatib el al. and Engoren found that the patients who failed to be separated from the ventilator had a lower breathing variability than the patients who succeeded (148, 149) There fore, we des igned a prospective study in ICU patients with prolonged MV support to investigate the breathing variability during the weaning trials. To eliminate any differences arising from a different patient population, each patient served as his or her own control. We hypothesized that compared with successful SBT bouts, the failed SBT bouts would show lower breathing pattern variability. Methods Subjects Thirty -eight tracheostomized PMV patients who were clinical ly stable (no fever, pain, o r anxiety, e tc.), with normal he modynamic conditions, without any evident signs of respiratory
78 distress (total breathing frequency < 35 breaths/min), and whose primary physician considered them ready to undergo a trial of weaning were enrolled in the study. Th e invest igative protocol was approved by the Institutional Review Broad at University of Florida and informed consent was obtained from the subjects or next of kin. The patien ts had received an average of 4623 days of MV support before study entry. The pertinent characteristics of patients in th is study are listed in Table 5 1. That the patients were included in this study should have 1): demonstrate an improvement or resolution of the underlying causes of respiratory failure and adequate gas exchange (eg. PaO2 ab ove 60 mmhg while breathing with a FiO2 of 0.5 or less); 2): be medically stable and ready to be weaned from the ventilator as determined by the attending physician; 3): demonstrate an intact phrenic nerve ; 4): have a hemoglobin level above 10 g/dl and bod y temperature of > 36.5 and < 38.5 C; and 5): be stable cardiovascular system (eg. HR < 140 beats/min; stable blood pressure) and stable metabolic status (eg. Acceptable electrolytes). P atients with spinal cord injury, progressive neuromuscular disease s primary cardiomyopathy, hepatic failure or requiring continuous analgesic agents that would depress respiratory drive were excluded. In addition to the above listed criteria, to qualify for inclusion, patients baseline ventilator setting had to meet the following specifications: SIMV 2O, PEEP H2O, and FiO2 All patients participated in progressively lengthening SBT daily. The daily test of SBT was conducted by disconnecting the patient s from mechanical v entilation without any form of ventilatory support and each patient spontaneously breathed through a T tube circuit, with the FiO2 set at the same level as that used during mechanical ventilation On the first day of SBT, the subject was asked to breathe o ff the ventilator as tolerated The SBT durations were progressed
79 per protocol. For example, the duration of the SBT was increased daily in the following progression: 1, 2, 3, 4, 6, 9, and 12 hours. On the day of SBT, the patient s were maintained a semirec umbent position (head of bed at 30 degrees) and receive d oxygen supplementation to maintain percutaneous oxygen saturation (SpO2) at > 90%. Between t wo daily SBTs, the subjects would rest on MV support. In addition, before performing a SBT, t he subjects wo uld be suctioned, if necessary, to minimize secretions. Study P rocedure Durin g the SBT, the subject was allowed to breathe off the ventilator per predetermined duration. A SBT was conducted by disconnecting the patient from the ventilator with any form of ventilatory support and the FiO2 was provided during MV was maintained with a T -piece adapter. The SBT was started at approximately 09:00 am each morning. P atient s were maintained in a semirecumbent position (head of bed at 30) and they received suppleme ntal oxygen between FiO2 of 0.3 to 0.5 to keep oxygen saturation (SpO2) at least 90 % The patients were continuously monitored during SBT by the ICU clinical staff. A computerized pulmonary monitoring system (CO2SMO Plus Novametrix Medical System I n c. Wal lingford, Connecticut, USA), incorporating an adult flow sensor placed between the tracheal canula and the T -piece of the breathing circuit, was used to measure the breathing pattern variables. Exhaled minute ventilation (VE), breathing frequency (f), insp ired tidal volume (VT), peak inspiratory flow (PIF), inspiration time (TI), expiration time (TE), and the duty cycle (TI/Ttot) were recorded electronically with Analysis Plus software ( Novametrix Medical System In c. Wallingford, Connecticut, USA ) The crit eria for terminating a SBT were hypertension (systolic blood pressure > 180 mm Hg), tachycardia (heart rate > 120 beats/minute or 30 beats/min over pretrial values), SpO2 < 90% lasting for more than 5 minutes, breathing frequency > 40 breaths/min lasting m ore than 5 minutes, diaphoresis, paradoxical breathing pattern,
80 significant accessory muscle use, persistent dysrhythmias, anxiety, or the patient requesting to be returned to MV support. Failure in a SBT (denoted as failed ) was defined as inability to s ustain spontaneous breathing efforts for the predetermined duration of SBT followed by reconnection of mechanical ventilation whereas when a subject successfully completes a scheduled SBT, this bout w ould be denoted as successful. Data Analysis and S tati stical A nalysis VE, f, VT, TI, TE, PIF, and TI/Ttot were acquired on a breath to -breath basis for a period of the the SBT tolerated duration and the reported data were their average values over the first 30 minutes of a fail/successful SBT for each subjec t Breathing variability was also calculated and express ed as the coefficient of variation (CV). Results were reported as meanSD. Paired t tests were used to compare the spontaneous breathing pattern between the failed and successful bouts. Statistical s ignificance was set at p<0.05. The analyses were carried out using SPSS 14.0 software (version 14, SPSS Institute Inc). Results Table 5 2 showed mean value and CV of seven breathing variables during a failed/successful SBT bout for each subject. Compared t o the successful bout s the failed bout s had higher mean value s for PIF and f (31.3+/ 9.2 vs. 28.8+/ 5.9 L/min and 29+/ 11 vs. 26+/ 7 breaths/min, respectively) (Table 5 2) The CV for VE, f, and PIF were significant ly lower during the failed SBT bout, whe reas the CV for VT, TI, TE, and TI/Ttot in the failed bout did not reach a significant difference (Table 5 2) Discussion The main finding of this study is that the mean values of PIF and f were higher during the first 30 minute interval of failed SBT in PMV patients, reflecting a higher drive to breathe in failed SBT trials. Secondly, among selected breathing variables, breathing variability, quantified
81 by the CVs, reveal ed more significant differences than the mean values. This finding suggests that ana lysis of the CVs provides additional information, which is ignored by the mean data. Previous studies (142, 145) have demonstrated that changes in breathing pattern, including increased respiratory drive and decrea sed TI were associated with weaning failure; however little is known about the breathing pattern during off the ventilator SBT in patients receiving PMV support. During the first 30 minute interval of failed SBT we found that the mean value of PIF was hi gher, compared with the successful bout ; whereas the mean value of TI did not reach significan ce This finding agrees with the previous data that there is a higher drive to breathe in failed SBT bout The presence of a high neural drive indicates that the respiratory muscles continue to generate large inspiratory pressure s to cope with this excessive load rather than a decreas e in respiratory motor output. However,i f an imbalance between the load faced by the respiratory muscles and the ir neuromuscular comp etence occurs which can cause the inability to sustain spontaneous breathing and/or hypercapnia, and thus, this imbalance will lead to respiratory distress and sooner or later the weaning failure will ensue. We also found that reduced breathing variabilit y, quantified by the CV for VE, PIF, and f during the first 30 minute interval of failed SBT, compared with the successful SBT bout. These findings are consistent with the literature. Bien et al. reported that CVs of PIF was lower in the post operative SIR S patients who failed to weaning trials than th ose who passed their weaning trials (147) Consistently, Wysocki et al. showed that reduced breathing variability, quantified by using CV, during a 60 min SBT was associated with a high inc idence of acute weaning failure in the ICU patient s (146) Alteration of breathing variability may reflect different physiological influences on the control of breathing (186) In this study, we observed reduced variability of VE, PIF, and f suggesting that breathing variability may provide additional information to how the
82 PMV patients adapts to an increased ventilation workload such as an off ventilator SBT and the breathing variability data, measured on CVPIF, is more sensitive to reflect this adaptation during a SBT than the mean value of PIF. It is speculative that breathing variability is likely to be a reflection of a load -capacity balance of respiratory system. Earlier studies (160, 161) have shown that loading respiration, in healthy humans mechanically (elastic and resistive) tends to reduce breathing variability in CVVE and CVTE. Moreover Caminal et al. (185) examined breathing variability in the res piratory volume signals based on non linear prediction methods in a group of 20 patients on weaning trials from MV and each patient placed under two different levels of pressure support ventilation (PSV), classified as low PSV (5 2 cm H2O) and high PSV (12 2 cm H2O). They found an inverse relationship between the levels of PSV and the breathing variability in tidal volume and inspiratory time. These results suggest that breathing variability might parallel to the load -capacity balance of the respiratory sys tem and a high breathing variability indicates a large respiratory reserve. In contrast, El khatib et al found that breathing patterns during CPAP trials (5 7.5 cm H2O) were more irregular in patients who failed extubation compared to patients who weaned (148) They repor ted that the CV of peak flow and tidal volume in passed and failed group were 11.6+/ 4.1% vs. 29.9 +/ 12% and 9.1+/ 4.1% vs. 26.1+/ 6.9%. These inconsistencies might be due to differences in study designs First, in El khatib et al.s study, 60 min of pe ak flow and tidal volume was recorded under SIMV conditions but not on spontaneous respiration through a T piece circuit B reathing variability was then measured on spontaneous breaths occurring between SIMV breaths. Of note, under SIMV conditions, no inf ormation on spontaneous breathing pattern in time can be obtained due to the presence of mechanical breaths. In addition,
83 s pontaneous breaths with CPAP (5 7.5 cm H2O) tended to be slower and deeper compared with spontaneous breaths without CPAP and this sl ower and deeper breathing behavior may increase the gross breathing variability because of greater elimination of carbon dioxide (187, 188) Our patients were disconnected from mechanical ventilators and did not rec eive any ventilatory support during SBT Thus, the present work and the study by El khatib et al are not fully comparable. Engoren found that weaning failure patients had a lower breathing variability, measured as Approximate Entropy (AppEn), than the pat ients who succeeded (149) AppEn is a mathematical approach to quantify the regularity of a system and a high AppEn value often indicates unpredictability and random variation in a system (189) They suggested a more complex tidal volume pattern corresponded to a failed SBT However, a high e ntropy value d oes not always occur in parallel to increase d variations if the variability is not random (190) For example, in animal stud ies, increased inspired CO2 (from 2.5% to 5% CO2) resulted in a decreased CV in VE but increased AppEn (190) In addition, d ata has shown that an increase in the e ntropy (such as AppEn) does not always indicate an increase in dynamical complexity. A typical example is that a randomized time series has higher entropy than the original time series although the process of randomization destroys inhere nt correlation and degrades the information content of the original signal (191) Summary and C onclusion We found that among the selected breathing pattern variables including VE, f, VT, TI, TE, PIF, and TI/Ttot, the mean value of PIF and f were significant ly different within subjects during the fi rst 30 minutes interval of failed and successful SBT in PMV patients, reflecting a higher drive to breathe in failed trials. Secondly, among selected breathing variables including VE, f and PIF breathing variability, quantified by the CVs, reveal more si gnificant differences than the
84 mean values. This finding suggests that analysis of the CVs provides additional information, which is ignored by the mean data.
85 Table 5 1. Demographic characteristic of the prolonged mechanical ventilation patients Patient No Age/ Gender Cause of ICU admission Days of MV support NIF* (cm H2O) SAPS II 1 39/F Hepatobiliary surgery for neoplasm 43 45.2 19 2 66/M ARDS 23 37.0 32 3 47/M Chronic Heart Failure 35 39.9 24 4 65/M Myocardiac Infarct with CPR/code event 29 43.1 4 0 5 59/F GI surgery, not for neoplasm 38 47.0 27 6 61/M Hepatobiliary surgery for neoplasm 19 42.0 28 7 75/F Craniotomy, not for neoplasm 81 31.9 36 8 72/F ARDS 107 36.5 53 9 62/F Post surgical acute respiratory failure 38 24.6 32 10 60/F COPD exacer bation 29 32.2 21 11 75/M Sepsis with shock 44 38.7 28 12 55/M Liver Transplant 15 64.5 37 13 59/F Sepsis with shock 43 70.9 40 14 68/F Hypercapnic respiratory failure 32 52.0 37 15 67/F Esophageal surgery 63 59.3 23 16 57/F Pneumonia (non aspiration ) 46 79.7 39 17 78/M other:burn 51 75.5 40 18 67/F Abdominal aortic aneurysm (AAA) repair 26 45.2 35 19 66/F Esophageal surgery 27 28.9 43 20 39/M Portal vein thrombosis 13 50.8 13 21 41/M Multiple trauma 40 20.4 38 22 77/F GI surgery, not for neopla sm 89 12.3 22 23 77/M GI surgery, not for neoplasm 21 52.4 36 24 81/M Multiple trauma 53 36.4 44 25 64/M Multiple trauma 48 87.0 34 26 55/F Post surgical acute respiratory failure 54 41.4 26 27 55/F MVR/aortic root replacement/ R pulmonary artery repa ir 63 42.1 19 28 69/F New CVA or intracranial hemorrhage (ICH) 44 64.3 32 29 64/M Dissecting abdominal aortic aneurysm 15 27.5 40 30 61/F ARDS 43 81.4 32 31 57/F Liver Transplant 47 42.3 29 32 63/M Abdominal aortic aneurysm (AAA) repair 57 57.2 35 33 87/F Cardiac valve replacement 106 40.3 35 34 68/F New CVA or intracranial hemorrhage (ICH) 60 34.2 36 35 40/F Multiple trauma 31 91.5 21 36 72/F GI surgery, not for neoplasm 47 63.7 18 37 69/M Myocardiac Infarct with CPR/code event 41 45.6 28 38 77/ M Post surgical acute respiratory failure 67 72.8 40 Mean 64 46 48.9 32 SD 12 23 19 9 *NIF, negative inspiratory force; SAPS II, simplified acute physiology score II.
86 Table 5 2. Breathing pattern variables in the Successful vs. Failed spontaneous br eathing trials Mean CV, % Successful Failed P Value Successful Failed P Value Ve (L/min) 7.872.03 8.202.94 0.36 18.119.4 14.497.35 0.03 RR (breath/min) 25.67.2 28.9811.2 0.02 17.411.03 13.386.04 0.02 Vt (ml) 306. 268.4 296.982.2 0.4 2 15.9812.7 14.7814.52 0.35 PIF (L/min) 28.85.88 31.349.2 0.04 19.119.25 14.8819.11 0.01 Ti (sec) 0.96 0 .21 0.900.24 0.07 20.98 1 8.47 18.1511.11 0.21 Te (sec) 1.580.42 1.540.8 0.72 27.7114.31 24.6812.9 0.42 Ti/Ttot 0.380.06 0.390. 07 0.75 19.0310.9 18.5910.1 0.42 CV, coefficient of variation; Ve minute ventilation; RR, respiratory rate; Vt, inspired tidal volume; PIF, peak inspiratory flow; Ti, inspiration time; Te, expiration time; Ti/Ttot, duty cycle; Data provides as MeanSD
87 CHAPTER 6 CONCLUSIONS AND FUTU RE DIRECTION In our first preliminary microarray study, we conclude that cardiothoracic surgery results in rapid changes in diaphragm gene expression, including genes related to generalized stress response, redox regulat ion, proteolysis, and energy metabolism. Further studies are needed to confirm and to clarify the biologic al relevance of our data. In our second study, we conclude that the mean value of PIF and f were significant ly different within subjects during the fi rst 30 minutes interval of failed and successful SBT in PMV patients, reflecting a higher drive to breathe in failed trials. Secondly, among selected breathing variables including VE, f, and PIF breathing variability, quantified by the CVs, reveal ed more significant differences than the mean values. This finding suggests that analysis of the CVs provides additional information, which is ignored by the mean data. This study enhances our understanding of the breathing variability changes that occur in weaning failure patients. Information gained from this study may provide insights for improved weaning strategies. We believe that a better understanding of mechanisms, which contributed to the weaning failure, could help to improve the care of prolonged mechani cal ventilation patients. Further work is needed to clarify the mechanisms of reduced breathing pattern variability in the failure of the spontaneous breathing trials.
88 APPENDIX GENE FUNCTIONAL CATEGORIES Gene functional categories and description were obtained from several public databases including gene ontology (Amigo; http://www.godatabase.org/cgi bin/amigo/go.cgi ), PubMed (http://w ww.ncbi.nlm.nih.gov/entrez/query.fcgi ), OMIM (http://www.ncbi.nih.gov/entrez/query.fcgi?db=OMIM ), and NetAffx (http://www.affymetix.com/analysis/netaffx/index.affx).
89 Table A 1. Expression of transport genes that are significantly different in the diaphragm after surgery Probe set Symbol Fold change Description Function 200787_s_at PEA15 1.8 phosphoprotein enriched in astrocytes 15 carbohydrate transport 202497_x_at SLC2A3 5.0 solute carrier family 2 (facilitated glucose transporter), member 3 carbohydrate transport 209681_at SLC19A2 3.3 solute carrier family 19 (thiamine transporter), member 2 folic acid transport 221020_s_at SLC25A32 1.8 solute carrier family 25, member 32 folic acid tran sport 201088_at KPNA2 2.1 karyopherin alpha 2 (RAG cohort 1, importin alpha 1) intracelluar protein transport 1565875_at NUP153 1.6 nucleoporin 153kDa intracelluar protein transport 241425_at NUPL1 1.4 nucleoporin like 1 intracelluar protein transport 200750_s_at RAN 1.5 RAN, member RAS oncogene family intracelluar protein transport 207624_s_at RPGR 1.7 retinitis pigmentosa GTPase regulator intracelluar protein transport 212902_at SEC24A 1.8 SEC24 related gene family, member A (S. cerevisiae) intracel luar protein transport 223225_s_at SEH1L 2.6 SEH1 like (S. cerevisiae) intracelluar protein transport 223209_s_at SELS 1.5 selenoprotein S intracelluar protein transport 235670_at STX11 2.5 syntaxin 11 intracelluar protein transport 212112_s_at STX12 1.7 syntaxin 12 intracelluar protein transport 221662_s_at SLC22A7 1.7 solute carrier family 22 (organic anion transporter), member 7 ion transport 212110_at SLC39A14 4.1 solute carrier family 39 (zinc transporter), member 14 ion transport 223044_at SLC4 0A1 1.7 solute carrier family 40 (iron regulated transporter), member 1 ion transport 219911_s_at SLCO4A1 3.0 solute carrier organic anion transporter family, member 4A1 ion transport 202068_s_at LDLR 5.3 low density lipoprotein receptor (familial hyper cholesterolemia) lipid transport 230494_at SLC20A1 2.6 solute carrier family 20 (phosphate transporter), member 1 phosphate transport 220948_s_at ATP1A1 2.0 ATPase, Na+/K+ transporting, alpha 1 polypeptide potassium ion transport 242836_at ATP1B3 2.6 AT Pase, Na+/K+ transporting, beta 3 polypeptide potassium ion transport 209112_at CDKN1B 1.6 cyclin dependent kinase inhibitor 1B (p27, Kip1) potassium ion transport 237007_at KCNB2 1.6 potassium voltage gated channel, Shab related subfamily, member 2 pot assium ion transport 206765_at KCNJ2 2.1 potassium inwardlyrectifying channel, subfamily J, member 2 potassium ion transport 229953_x_at LCA5 1.9 Leber congenital amaurosis 5 protein transport
90 Table A 1 Continued. Probe set Symbol Fold change Desc ription Function 227247_at PLEKHA8 1.5 pleckstrin homology domain containing, family A (phosphoinositide binding specific) member 8 protein transport 221704_s_at VPS37B 1.5 vacuolar protein sorting 37 homolog B (S. cerevisiae) protein transport 224953_at YIPF5 1.6 Yip1 domain family, member 5 protein transport 206170_at ADRB2 1.8 adrenergic, beta 2, receptor, surface regulation of sodium ion transport 218708_at NXT1 2.6 NTF2 like export factor 1 RNA export from nucleus 237648_x_at NHEDC2 1.6 Na+/H+ exchanger domain containing 2 sodium ion transport 229199_at SCN9A 1.8 sodium channel, voltage gated, type IX, alpha subunit sodium ion transport 205896_at SLC22A4 3.6 solute carrier family 22 (organic cation transporter), member 4 sodium ion transport 242836_at ATP1B3 2.6 ATPase, Na+/K+ transporting, beta 3 polypeptide sodium:potassium exchaning ATPase activity 205856_at SLC14A1 2.4 solute carrier family 14 (urea transporter), member 1 (Kidd blood group) water transport 243166_at SLC30A5 1.5 solut e carrier family 30 (zinc transporter), member 5 zinc ion transport 243524_at SLC30A7 2.0 solute carrier family 30 (zinc transporter), member 7 zinc ion transport 1561886_a_at SLC39A14 3.4 solute carrier family 39 (zinc transporter), member 14 zinc ion t ransport
91 Table A 2 Expression of signal transduction genes that are significantly different in the diaphragm after surgery Probe set Symbol Fold change Description Function 210517_s_at AKAP12 2.4 A kinase (PRKA) anchor protein (gravin) 12 signal tr ansduction 215483_at AKAP9 1.5 A kinase (PRKA) anchor protein (yotiao) 9 signal transduction 210390_s_at CCL15 1.7 chemokine (C C motif) ligand 15 signal transduction 209287_s_at CDC42EP3 1.5 CDC42 effector protein (Rho GTPase binding) 3 signal transduction 218157_x_at CDC42SE1 2.2 CDC42 small effector 1 signal transduction 1555730_a_at CFL1 1.6 cofilin 1 (non muscle) signal transduction 227481_at CNKSR3 2.2 CNKSR family member 3 signal transduction 205898_at CX3CR1 2.6 chemokine (C X3 C motif) rec eptor 1 signal transduction 208335_s_at DARC 2.7 Duffy blood group, chemokine receptor signal transduction 205419_at EBI2 3.7 Epstein Barr virus induced gene 2 (lymphocyte specific G protein coupled receptor) signal transduction 212951_at GPR116 1.5 G p rotein coupled receptor 116 signal transduction 223620_at GPR34 2.3 G proteincoupled receptor 34 signal transduction 233953_at GUCA1C 2.1 guanylate cyclase activator 1C signal transduction 211676_s_at IFNGR1 1.9 interferon gamma receptor 1 signal tran sduction 216944_s_at ITPR1 1.6 inositol 1,4,5 triphosphate receptor, type 1 signal transduction 212723_at JMJD6 2.1 jumonji domain containing 6 signal transduction 212935_at MCF2L 2.0 MCF.2 cell line derived transforming sequence like signal transductio n 225478_at MFHAS1 1.9 malignant fibrous histiocytoma amplified sequence 1 signal transduction 230550_at MS4A6A 1.7 membrane spanning 4 domains, subfamily A, member 6A signal transduction 217302_at OR2F2 1.5 olfactory receptor, family 2, subfamily F, m ember 2 signal transduction 219155_at PITPNC1 2.2 phosphatidylinositol transfer protein, cytoplasmic 1 signal transduction
92 Table A 2. Continued. Probe set Symbol Fold change Description Function 226122_at PLEKHG1 2.7 pleckstrin homology domain containi ng, family G (with RhoGef domain) member 1 signal transduction 215894_at PTGDR 1.6 prostaglandin D2 receptor (DP) signal transduction 209050_s_at RALGDS 2.0 ral guanine nucleotide dissociation stimulator signal transduction 208370_s_at RCAN1 1.7 regula tor of calcineurin 1 signal transduction 209324_s_at RGS16 4.5 regulator of G protein signaling 16 signal transduction 202388_at RGS2 5.4 regulator of G protein signaling 2, 24kDa signal transduction 224390_s_at RGS8 1.9 regulator of G protein signaling 8 signal transduction 209941_at RIPK1 1.9 receptor (TNFRSF) interacting serine threonine kinase 1 signal transduction 236606_at SAV1 1.5 salvador homolog 1 (Drosophila) signal transduction 209723_at SERPINB9 2.0 serpin peptidase inhibitor, clade B (ova lbumin), member 9 signal transduction 226837_at SPRED1 2.2 sprouty related, EVH1 domain containing 1 signal transduction 230212_at SPRY1 1.7 sprouty homolog 1, antagonist of FGF signaling (Drosophila) signal transduction 202286_s_at TACSTD2 2.6 tumor as sociated calcium signal transducer 2 signal transduction 209295_at TNFRSF10B 2.5 tumor necrosis factor receptor superfamily, member 10b signal transduction 227345_at TNFRSF10D 2.9 tumor necrosis factor receptor superfamily, member 10d, decoy with truncat ed death domain signal transduction 203120_at TP53BP2 1.8 tumor protein p53 binding protein, 2 signal transduction 215411_s_at TRAF3IP2 1.7 TRAF3 interacting protein 2 signal transduction 230192_at TRIM13 1.5 tripartite motif containing 13 signal trans duction 200641_s_at YWHAZ 1.5 tyrosine 3 monooxygenase/tryptophan 5 monooxygenase activation protein, zeta polypeptide signal transduction
93 Table A 3 Expression of nuclei acid metabolism genes that are significantly different in the diaphragm after surg ery Probe set Symbol Fold change Description Function 204510_at CDC7 1.9 cell division cycle 7 homolog (S. cerevisiae) DNA replication 209101_at CTGF 2.8 connective tissue growth factor DNA replication 201970_s_at NASP 1.7 nuclear autoantigenic sperm pr otein (histone binding) DNA replication 241797_at NFIX 1.5 nuclear factor I/X (CCAAT binding transcription factor) DNA replication 238992_at POLI 2.1 polymerase (DNA directed) iota DNA replication 209868_s_at RBMS1 1.5 RNA binding motif, single strand ed interacting protein 1 DNA replication 226153_s_at CNOT6L 1.5 CCR4 NOT transcription complex, subunit 6 like mRNA processing 200033_at DDX5 1.8 DEAD (Asp Glu Ala Asp) box polypeptide 5 mRNA processing 201386_s_at DHX15 1.6 DEAH (Asp Glu Ala His) box p olypeptide 15 mRNA processing 201303_at EIF4A3 2.1 eukaryotic translation initiation factor 4A, isoform 3 mRNA processing 229007_at LOC283788 1.7 hypothetical protein LOC283788 mRNA processing 236907_at PABPC1 2.2 poly(A) binding protein, cytoplasmic 1 mRNA processing 212015_x_at PTBP1 2.0 polypyrimidine tract binding protein 1 mRNA processing 201586_s_at SFPQ 2.5 splicing factor proline/glutamine rich (polypyrimidine tract binding protein associated) mRNA processing 209024_s_at SYNCRIP 1.8 synaptota gmin binding, cytoplasmic RNA interacting protein mRNA processing 202750_s_at TFIP11 2.3 tuftelin interacting protein 11 mRNA processing 222748_s_at TXNL4B 1.9 thioredoxin like 4B mRNA processing 229630_s_at WTAP 2.5 Wilms tumor 1 associated protein mRN A processing 204252_at CDK2 1.6 cyclin dependent kinase 2 regulation of DNA replication
94 Table A 3. Continued. Probe set Symbol Fold change Description Function 223397_s_at NIP7 2.7 nuclear import 7 homolog (S. cerevisiae) ribosome assembly 218156_s_a t TSR1 1.6 TSR1, 20S rRNA accumulation, homolog (S. cerevisiae) ribosome assembly 234295_at DBR1 1.7 debranching enzyme homolog 1 (S. cerevisiae) RNA splicing 201055_s_at HNRNPA0 1.7 heterogeneous nuclear ribonucleoprotein A0 RNA splicing 227110_at HNR NPC 1.5 heterogeneous nuclear ribonucleoprotein C (C1/C2) RNA splicing 212028_at RBM25 1.6 RNA binding motif protein 25 RNA splicing 222443_s_at RBM8A 1.8 RNA binding motif protein 8A RNA splicing 201070_x_at SF3B1 1.5 splicing factor 3b, subunit 1, 155 kDa RNA splicing 200892_s_at SFRS10 1.8 splicing factor, arginine/serine rich 10 (transformer 2 homolog, Drosophila) RNA splicing 214882_s_at SFRS2 1.6 splicing factor, arginine/serine rich 2 RNA splicing 206108_s_at SFRS6 1.6 splicing factor, arginine/ serine rich 6 RNA splicing 213649_at SFRS7 1.6 splicing factor, arginine/serine rich 7, 35kDa RNA splicing 213175_s_at SNRPB 1.6 small nuclear ribonucleoprotein polypeptides B and B1 RNA splicing 201478_s_at DKC1 1.8 dyskeratosis congenita 1, dyskerin r RNA processing 211951_at NOLC1 2.0 nucleolar and coiled body phosphoprotein 1 rRNA processing 212422_at PDCD11 1.6 programmed cell death 11 rRNA processing
9 5 Table A 4. Expression of regulation of transcription genes that are significantly different in t he diaphragm after surgery Probe set Symbol Fold change Description Function 1560765_a_at ARHGAP22 1.9 Rho GTPase activating protein 22 regulation of transcription 213138_at ARID5A 2.2 AT rich interactive domain 5A (MRF1 like) regulation of transcription 1558000_at ARID5B 3.1 AT rich interactive domain 5B (MRF1 like) regulation of transcription 225557_at AXUD1 6.4 AXIN1 up regulated 1 regulation of transcription 204194_at BACH1 1.9 BTB and CNC homology 1, basic leucine zipper transcription factor 1 reg ulation of transcription 201101_s_at BCLAF1 1.5 BCL2 associated transcription factor 1 regulation of transcription 201170_s_at BHLHB2 2.7 basic helix loop helix domain containing, class B, 2 regulation of transcription 200777_s_at BZW1 1.6 basic leucine zipper and W2 domains 1 regulation of transcription 204093_at CCNH 1.7 cyclin H regulation of transcription 1555411_a_at CCNL1 4.2 cyclin L1 regulation of transcription 212501_at CEBPB 2.2 CCAAT/enhancer binding protein (C/EBP), beta regulation of tran scription 207630_s_at CREM 3.3 cAMP responsive element modulator regulation of transcription 202776_at DNTTIP2 1.8 deoxynucleotidyltransferase, terminal, interacting protein 2 regulation of transcription 226952_at EAF1 1.5 ELL associated factor 1 regula tion of transcription 212418_at ELF1 1.8 E74 like factor 1 (ets domain transcription factor) regulation of transcription 226099_at ELL2 7.3 elongation factor, RNA polymerase II, 2 regulation of transcription 242868_at EPAS1 2.2 endothelial PAS domain pr otein 1 regulation of transcription 1561167_at ETV6 2.1 ets variant gene 6 (TEL oncogene) regulation of transcription 202768_at FOSB 5.2 FBJ murine osteosarcoma viral oncogene homolog B regulation of transcription 218880_at FOSL2 3.3 FOS like antigen 2 regulation of transcription 1569477_at FOXO3 2.0 forkhead box O3 regulation of transcription 218458_at GMCL1 1.6 germ cell less homolog 1 (Drosophila) regulation of transcription 222830_at GRHL1 2.3 grainyhead like 1 (Drosophila) regulation of transcri ption 213844_at HOXA5 2.0 homeobox A5 regulation of transcription 205453_at HOXB2 1.6 homeobox B2 regulation of transcription 228904_at HOXB3 1.7 homeobox B3 regulation of transcription
96 Table A 4. Continued. Probe set Symbol Fold change Description Function 208930_s_at ILF3 1.4 interleukin enhancer binding factor 3, 90kDa regulation of transcription 1557174_a_at IRAK1BP1 2.0 interleukin 1 receptor associated kinase 1 binding protein 1 regulation of transcription 202531_at IRF1 4.5 interferon reg ulatory factor 1 regulation of transcription 203297_s_at JARID2 1.6 jumonji, AT rich interactive domain 2 regulation of transcription 201473_at JUNB 4.1 jun B proto oncogene regulation of transcription 200704_at LITAF 3.2 lipopolysaccharide induced TNF factor regulation of transcription 201862_s_at LRRFIP1 2.1 leucine rich repeat (in FLII) interacting protein 1 regulation of transcription 209348_s_at MAF 1.7 v maf musculoaponeurotic fibrosarcoma oncogene homolog (avian) regulation of transcription 21 8559_s_at MAFB 2.6 v maf musculoaponeurotic fibrosarcoma oncogene homolog B (avian) regulation of transcription 36711_at MAFF 8.7 v maf musculoaponeurotic fibrosarcoma oncogene homolog F (avian) regulation of transcription 226206_at MAFK 1.5 v maf muscul oaponeurotic fibrosarcoma oncogene homolog K (avian) regulation of transcription 227538_at MED26 1.6 mediator complex subunit 26 regulation of transcription 1552330_at MGC16385 1.6 hypothetical protein MGC16385 regulation of transcription 205932_s_at M SX1 1.9 msh homeobox 1 regulation of transcription 225344_at NCOA7 1.9 nuclear receptor coactivator 7 regulation of transcription 210162_s_at NFATC1 1.5 nuclear factor of activated T cells, cytoplasmic, calcineurin dependent 1 regulation of transcription 1567013_at NFE2L2 1.9 nuclear factor (erythroid derived 2) like 2 regulation of transcription 223217_s_at NFKBIZ 3.9 nuclear factor of kappa light polypeptide gene enhancer in B cells inhibitor, zeta regulation of transcription 209706_at NKX3 1 1.7 NK3 homeobox 1 regulation of transcription
97 Table A 4. Continued. Probe set Symbol Fold change Description Function 202600_s_at NRIP1 2.1 nuclear receptor interacting protein 1 regulation of transcription 202861_at PER1 2.5 period homolog 1 (Drosophila) re gulation of transcription 205251_at PER2 1.9 period homolog 2 (Drosophila) regulation of transcription 209034_at PNRC1 1.8 proline rich nuclear receptor coactivator 1 regulation of transcription 206036_s_at REL 1.8 v rel reticuloendotheliosis viral onco gene homolog (avian) regulation of transcription 222815_at RNF12 2.1 ring finger protein 12 regulation of transcription 204900_x_at SAP30 1.6 Sin3A associated protein, 30kDa regulation of transcription 219993_at SOX17 4.1 SRY (sex determining region Y) box 17 regulation of transcription 213654_at TAF5L 1.9 TAF5 like RNA polymerase II, p300/CBP associated factor (PCAF) associated factor, 65kDa regulation of transcription 203313_s_at TGIF1 4.1 TGFB induced factor homeobox 1 regulation of transcription 2 29983_at TIGD2 1.6 tigger transposable element derived 2 regulation of transcription 215111_s_at TSC22D1 1.6 TSC22 domain family, member 1 regulation of transcription 204094_s_at TSC22D2 2.2 TSC22 domain family, member 2 regulation of transcription 235 170_at ZNF92 1.5 zinc finger protein 92 regulation of transcription
98 Table A 5 Expression of binding genes that are significantly different in the diaphragm after surgery Probe set Symbol Fold change Description Function 205304_s_at KCNJ8 1.6 potassiu m inwardly rectifying channel, subfamily J, member 8 ATP binding 236114_at RUNX1 2.7 runt related transcription factor 1 (acute myeloid leukemia 1; aml1 oncogene) ATP binding 213918_s_at NIPBL 1.7 Nipped B homolog (Drosophila) binding 227467_at RDH10 1. 8 retinol dehydrogenase 10 (all trans) binding 202083_s_at SEC14L1 2.4 SEC14 like 1 (S. cerevisiae) binding 225212_at SLC25A25 3.8 solute carrier family 25 (mitochondrial carrier; phosphate carrier), member 25 binding 32091_at SLC25A44 1.7 solute carrie r family 25, member 44 binding 229169_at TTC18 1.5 tetratricopeptide repeat domain 18 binding 1554588_a_at TTC30B 2.0 tetratricopeptide repeat domain 30B binding 212859_x_at MT1E 3.5 metallothionein 1E cadmium ion binding 217165_x_at MT1F 3.5 metallo thionein 1F cadmium ion binding 204745_x_at MT1G 3.5 metallothionein 1G cadmium ion binding 206461_x_at MT1H 3.4 metallothionein 1H cadmium ion binding 217546_at MT1M 11.4 metallothionein 1M cadmium ion binding 208581_x_at MT1X 3.3 metallothionein 1X c admium ion binding 216513_at DCT 3.0 dopachrome tautomerase (dopachrome delta isomerase, tyrosine related protein 2) copper ion binding 225987_at STEAP4 1.9 STEAP family member 4 copper ion binding 220936_s_at H2AFJ 1.7 H2A histone family, member J DNA binding 211997_x_at H3F3B 1.9 H3 histone, family 3B (H3.3B) DNA binding 214509_at HIST1H3I 1.6 histone cluster 1, H3i DNA binding 209317_at POLR1C 1.9 polymerase (RNA) I polypeptide C, 30kDa DNA binding 1554770_x_at ZNF785 1.8 zinc finger protein 785 DNA binding
99 Table A 5. Continued. Probe set Symbol Fold change Description Function 1552316_a_at GIMAP1 1.9 GTPase, IMAP family member 1 GTP binding 226402_at CYP2U1 1.6 cytochrome P450, family 2, subfamily U, polypeptide 1 heme binding 235985_at P ITPNB 1.9 phosphatidylinositol transfer protein, beta lipid binding 213629_x_at MT1JP 3.6 metallothionein 1J (pseudogene) metal ion binding 233085_s_at OBFC2A 2.7 oligonucleotide/oligosaccharide binding fold containing 2A nucleic acid binding 212027_at RBM25 1.5 RNA binding motif protein 25 nucleic acid binding 221213_s_at SUHW4 2.1 suppressor of hairy wing homolog 4 (Drosophila) nucleic acid binding 201873_s_at ABCE1 1.5 ATP binding cassette, sub family E (OABP), member 1 nucleotide binding 213198_a t ACVR1B 1.7 activin A receptor, type IB nucleotide binding 228201_at ARL13B 1.7 ADP ribosylation factor like 13B nucleotide binding 203586_s_at ARL4D 1.6 ADP ribosylation factor like 4D nucleotide binding 242727_at ARL5B 1.5 ADP ribosylation factor lik e 5B nucleotide binding 209186_at ATP2A2 1.9 ATPase, Ca++ transporting, cardiac muscle, slow twitch 2 nucleotide binding 230387_at ATP2C1 1.6 ATPase, Ca++ transporting, type 2C, member 1 nucleotide binding 219487_at BBS10 1.9 Bardet Biedl syndrome 10 nucleotide binding 204258_at CHD1 2.8 chromodomain helicase DNA binding protein 1 nucleotide binding 203104_at CSF1R 1.8 colony stimulating factor 1 receptor, formerly McDonough feline sarcoma viral (v fms) oncogene homolog nucleotide binding 240221_at CSNK1A1 1.6 casein kinase 1, alpha 1 nucleotide binding 207945_s_at CSNK1D 2.4 casein kinase 1, delta nucleotide binding 203302_at DCK 1.7 deoxycytidine kinase nucleotide binding 232541_at EGFR 2.3 epidermal growth factor receptor (erythroblastic leuk emia viral (v erb b) oncogene homolog, avian) nucleotide binding
100 Table A 5. Continued. Probe set Symbol Fold change Description Function 210287_s_at FLT1 3.5 fms related tyrosine kinase 1 (vascular endothelial growth factor/vascular permeability factor receptor) nucleotide binding 210005_at GART 1.7 phosphoribosylglycinamide formyltransferase, phosphoribosylglycinamide synthetase, phosphoribosylaminoimidazole synthetase nucleotide binding 232024_at GIMAP2 2.7 GTPase, IMAP family member 2 nucleotide bi nding 219243_at GIMAP4 1.7 GTPase, IMAP family member 4 nucleotide binding 236583_at GIMAP5 1.7 GTPase, IMAP family member 5 nucleotide binding 228071_at GIMAP7 2.0 GTPase, IMAP family member 7 nucleotide binding 227692_at GNAI1 1.7 guanine nucleot ide binding protein (G protein), alpha inhibiting activity polypeptide 1 nucleotide binding 240452_at GSPT1 2.1 G1 to S phase transition 1 nucleotide binding 201277_s_at HNRPAB 1.9 heterogeneous nuclear ribonucleoprotein A/B nucleotide binding 213076_at ITPKC 3.7 inositol 1,4,5 trisphosphate 3 kinase C nucleotide binding 223380_s_at LATS2 1.6 LATS, large tumor suppressor, homolog 2 (Drosophila) nucleotide binding 201461_s_at MAPKAPK2 1.6 mitogen activated protein kinase activated protein kinase 2 nucle otide binding 225613_at MAST4 1.9 microtubule associated serine/threonine kinase family member 4 nucleotide binding 200768_s_at MAT2A 2.5 methionine adenosyltransferase II, alpha nucleotide binding 238624_at NLK 1.4 nemo like kinase nucleotide binding 207075_at NLRP3 2.4 NLR family, pyrin domain containing 3 nucleotide binding 211949_s_at NOLC1 1.7 nucleolar and coiled body phosphoprotein 1 nucleotide binding 1555310_a_at PAK6 1.7 p21(CDKN1A) activated kinase 6 nucleotide binding 221918_at PCTK2 1.9 PCTAIRE protein kinase 2 nucleotide binding 227255_at PDIK1L 1.6 PDLIM1 interacting kinase 1 like nucleotide binding 202464_s_at PFKFB3 3.8 6 phosphofructo 2 kinase/fructose 2,6 biphosphatase 3 nucleotide binding 209193_at PIM1 3.5 pim 1 oncogene nucle otide binding
101 Table A 5. Continued. Probe set Symbol Fold change Description Function 219622_at RAB20 1.9 RAB20, member RAS oncogene family nucleotide binding 221014_s_at RAB33B 1.6 RAB33B, member RAS oncogene family nucleotide binding 223467_at RASD 1 5.7 RAS, dexamethasone induced 1 nucleotide binding 212168_at RBM12 1.6 RNA binding motif protein 12 nucleotide binding 212099_at RHOB 3.0 ras homolog gene family, member B nucleotide binding 223169_s_at RHOU 2.8 ras homolog gene family, member U nucl eotide binding 209941_at RIPK1 1.9 receptor (TNFRSF) interacting serine threonine kinase 1 nucleotide binding 218088_s_at RRAGC 1.6 Ras related GTP binding C nucleotide binding 200754_x_at SFRS2 1.6 splicing factor, arginine/serine rich 2 nucleotide bin ding 1562948_at SMC5 1.5 structural maintenance of chromosomes 5 nucleotide binding 202693_s_at STK17A 2.0 serine/threonine kinase 17a nucleotide binding 205214_at STK17B 3.3 serine/threonine kinase 17b nucleotide binding 202307_s_at TAP1 2.3 transport er 1, ATP binding cassette, sub family B (MDR/TAP) nucleotide binding 218459_at TOR3A 2.0 torsin family 3, member A nucleotide binding 213726_x_at TUBB2C 1.6 tubulin, beta 2C nucleotide binding 202932_at YES1 1.7 v yes 1 Yamaguchi sarcoma viral oncogene homolog 1 nucleotide binding 1553696_s_at ZNF569 1.8 zinc finger protein 569 nucleotide binding 224632_at GPATCH4 1.6 G patch domain containing 4 nuleic acid binding 220330_s_at SAMSN1 6.7 SAM domain, SH3 domain and nuclear localization signals 1 phos photyrosine binding
102 Table A 5. Continued. Probe set Symbol Fold change Description Function 205681_at BCL2A1 11.3 BCL2 related protein A1 protein binding 208536_s_at BCL2L11 1.5 BCL2 like 11 (apoptosis facilitator) protein binding 202710_at BET1 1.8 BET1 homolog (S. cerevisiae) protein binding 218723_s_at C13orf15 2.6 chromosome 13 open reading frame 15 protein binding 230424_at C5orf13 1.7 chromosome 5 open reading frame 13 protein binding 212923_s_at C6orf145 3.1 chromosome 6 open reading frame 145 protein binding 221003_s_at CAB39L 2.0 calcium binding protein 39 like protein binding 205899_at CCNA1 1.5 cyclin A1 protein binding 232768_at CCNB2 1.5 cyclin B2 protein binding 229900_at CD109 2.0 CD109 molecule protein binding 218351_at COMMD8 1.6 COMM domain containing 8 protein binding 202437_s_at CYP1B1 1.9 cytochrome P450, family 1, subfamily B, polypeptide 1 protein binding 230568_x_at DLL3 1.6 delta like 3 (Drosophila) protein binding 201041_s_at DUSP1 3.7 dual specificity phosphatase 1 protein binding 225656_at EFHC1 1.9 EF hand domain (C terminal) containing 1 protein binding 212418_at ELF1 1.8 E74 like factor 1 (ets domain transcription factor) protein binding 220386_s_at EML4 1.7 echinoderm microtubule associated protein like 4 p rotein binding 224657_at ERRFI1 4.0 ERBB receptor feedback inhibitor 1 protein binding 222853_at FLRT3 2.6 fibronectin leucine rich transmembrane protein 3 protein binding 205436_s_at H2AFX 1.8 H2A histone family, member X protein binding 201631_s_at IER3 3.6 immediate early response 3 protein binding 206245_s_at IVNS1ABP 1.7 influenza virus NS1A binding protein protein binding 222728_s_at JOSD3 1.8 Josephin domain containing 3 protein binding
103 Table A 5. Continued. Probe set Symbol Fold change Desc ription Function 226479_at KBTBD6 1.8 kelch repeat and BTB (POZ) domain containing 6 protein binding 223412_at KBTBD7 2.0 kelch repeat and BTB (POZ) domain containing 7 protein binding 205150_s_at KIAA0644 1.7 KIAA0644 gene product protein binding 2 43589_at KIAA1267 1.6 KIAA1267 protein binding 226370_at KLHL15 1.7 kelch like 15 (Drosophila) protein binding 203068_at KLHL21 1.6 kelch like 21 (Drosophila) protein binding 203835_at LRRC32 2.0 leucine rich repeat containing 32 protein binding 15595 80_at LRRC39 3.1 leucine rich repeat containing 39 protein binding 222231_s_at LRRC59 2.0 leucine rich repeat containing 59 protein binding 233487_s_at LRRC8A 1.6 leucine rich repeat containing 8 family, member A protein binding 200797_s_at MCL1 2.0 my eloid cell leukemia sequence 1 (BCL2 related) protein binding 202431_s_at MYC 8.0 v myc myelocytomatosis viral oncogene homolog (avian) protein binding 208093_s_at NDEL1 1.9 nudE nuclear distribution gene E homolog (A. nidulans) like 1 protein binding 2 24958_at NUFIP2 1.7 nuclear fragile X mental retardation protein interacting protein 2 protein binding 225842_at PHLDA1 3.0 pleckstrin homology like domain, family A, member 1 protein binding 211580_s_at PIK3R3 2.8 phosphoinositide 3 kinase, regulatory s ubunit 3 (p55, gamma) protein binding 202327_s_at PKD1 2.0 polycystic kidney disease 1 (autosomal dominant) protein binding 202446_s_at PLSCR1 3.3 phospholipid scramblase 1 protein binding 204286_s_at PMAIP1 2.8 phorbol 12 myristate 13 acetate induced p rotein 1 protein binding 37028_at PPP1R15A 2.2 protein phosphatase 1, regulatory (inhibitor) subunit 15A protein binding 202886_s_at PPP2R1B 1.7 protein phosphatase 2 (formerly 2A), regulatory subunit A, beta isoform protein binding 208965_s_at PYHIN1 3 .0 pyrin and HIN domain family, member 1 protein binding
104 Table A 5. Continued. Probe set Symbol Fold change Description Function 225039_at RPE 1.5 ribulose 5 phosphate 3 epimerase protein binding 201070_x_at SF3B1 1.5 splicing factor 3b, subunit 1, 15 5kDa protein binding 212470_at SPAG9 1.5 sperm associated antigen 9 protein binding 201060_x_at STOM 2.3 stomatin protein binding 218335_x_at TNIP2 1.6 TNFAIP3 interacting protein 2 protein binding 208900_s_at TOP1 2.3 topoisomerase (DNA) I protein bin ding 233970_s_at TRMT6 1.6 tRNA methyltransferase 6 homolog (S. cerevisiae) protein binding 242116_x_at ANKRD17 1.6 ankyrin repeat domain 17 RNA binding 201376_s_at HNRPF 1.6 heterogeneous nuclear ribonucleoprotein F RNA binding 236699_at MBNL2 1.4 mus cleblind like 2 (Drosophila) RNA binding 205135_s_at NUFIP1 1.9 nuclear fragile X mental retardation protein interacting protein 1 RNA binding 224956_at NUFIP2 1.8 nuclear fragile X mental retardation protein interacting protein 2 RNA binding 203737_s_a t PPRC1 3.3 peroxisome proliferator activated receptor gamma, coactivator related 1 RNA binding 238122_at RBM12B 1.8 RNA binding motif protein 12B RNA binding 212028_at RBM25 1.6 RNA binding motif protein 25 RNA binding 208804_s_at SFRS6 1.6 splicing f actor, arginine/serine rich 6 RNA binding 213175_s_at SNRPB 1.6 small nuclear ribonucleoprotein polypeptides B and B1 RNA binding 220104_at ZC3HAV1 2.1 zinc finger CCCH type, antiviral 1 RNA binding 201531_at ZFP36 4.5 zinc finger protein 36, C3H type, homolog (mouse) RNA binding 211965_at ZFP36L1 3.0 zinc finger protein 36, C3H type like 1 RNA binding 201369_s_at ZFP36L2 2.2 zinc finger protein 36, C3H type like 2 RNA binding 227188_at C21orf63 2.5 chromosome 21 open reading frame 63 sugar binding 2 10732_s_at LGALS8 1.8 lectin, galactoside binding, soluble, 8 (galectin 8) sugar binding
105 Table A 5. Continued. Probe set Symbol Fold change Description Function 222162_s_at ADAMTS1 4.1 ADAM metallopeptidase with thrombospondin type 1 motif, 1 zinc ion b inding 1562275_at ADAMTS9 8.4 ADAM metallopeptidase with thrombospondin type 1 motif, 9 zinc ion binding 203322_at ADNP2 1.6 ADNP homeobox 2 zinc ion binding 244519_at ASXL1 1.7 additional sex combs like 1 (Drosophila) zinc ion binding 231270_at CA13 1 .7 carbonic anhydrase XIII zinc ion binding 202284_s_at CDKN1A 4.9 cyclin dependent kinase inhibitor 1A (p21, Cip1) zinc ion binding 239648_at DCUN1D3 2.4 DCN1, defective in cullin neddylation 1, domain containing 3 (S. cerevisiae) zinc ion binding 2016 93_s_at EGR1 6.7 early growth response 1 zinc ion binding 205249_at EGR2 6.1 early growth response 2 (Krox 20 homolog, Drosophila) zinc ion binding 206115_at EGR3 4.1 early growth response 3 zinc ion binding 208989_s_at FBXL11 1.5 F box and leucine rich repeat protein 11 zinc ion binding 204224_s_at GCH1 4.6 GTP cyclohydrolase 1 (dopa responsive dystonia) zinc ion binding 208066_s_at GTF2B 1.6 general transcription factor IIB zinc ion binding 224569_s_at IRF2BP2 1.5 interferon regulatory factor 2 bind ing protein 2 zinc ion binding 225142_at JHDM1D 1.6 jumonji C domain containing histone demethylase 1 homolog D (S. cerevisiae) zinc ion binding 224933_s_at JMJD1C 2.1 jumonji domain containing 1C zinc ion binding 1556060_a_at KIAA1702 1.8 KIAA1702 prot ein zinc ion binding 202393_s_at KLF10 2.8 Kruppel like factor 10 zinc ion binding 221841_s_at KLF4 3.1 Kruppel like factor 4 (gut) zinc ion binding 224606_at KLF6 2.8 Kruppel like factor 6 zinc ion binding 203542_s_at KLF9 2.6 Kruppel like factor 9 zi nc ion binding 215322_at LONRF1 1.8 LON peptidase N terminal domain and ring finger 1 zinc ion binding 204575_s_at MMP19 3.2 matrix metallopeptidase 19 zinc ion binding 212185_x_at MT2A 2.4 metallothionein 2A zinc ion binding
106 Table A 5. Continued. Pro be set Symbol Fold change Description Function 221715_at MYST3 1.7 MYST histone acetyltransferase (monocytic leukemia) 3 zinc ion binding 215073_s_at NR2F2 1.9 nuclear receptor subfamily 2, group F, member 2 zinc ion binding 202340_x_at NR4A1 3.7 nucle ar receptor subfamily 4, group A, member 1 zinc ion binding 209959_at NR4A3 4.6 nuclear receptor subfamily 4, group A, member 3 zinc ion binding 210391_at NR6A1 1.4 nuclear receptor subfamily 6, group A, member 1 zinc ion binding 211564_s_at PDLIM4 1.8 PDZ and LIM domain 4 zinc ion binding 1557852_at PHC2 2.2 polyhomeotic homolog 2 (Drosophila) zinc ion binding 215281_x_at POGZ 1.5 pogo transposable element with ZNF domain zinc ion binding 228964_at PRDM1 2.7 PR domain containing 1, with ZNF domain z inc ion binding 203749_s_at RARA 1.9 retinoic acid receptor, alpha zinc ion binding 205178_s_at RBBP6 1.8 retinoblastoma binding protein 6 zinc ion binding 219897_at RNF122 1.6 ring finger protein 122 zinc ion binding 218738_s_at RNF138 1.8 ring finger protein 138 zinc ion binding 226104_at RNF170 1.7 ring finger protein 170 zinc ion binding 213038_at RNF19B 1.8 ring finger protein 19B zinc ion binding 201846_s_at RYBP 2.4 RING1 and YY1 binding protein zinc ion binding 243166_at SLC30A5 1.5 solute carrier family 30 (zinc transporter), member 5 zinc ion binding 219480_at SNAI1 1.6 snail homolog 1 (Drosophila) zinc ion binding 230380_at THAP2 3.4 THAP domain containing, apoptosis associated protein 2 zinc ion binding 212665_at TIPARP 6.2 TCDD indu cible poly(ADP ribose) polymerase zinc ion binding 202643_s_at TNFAIP3 3.2 tumor necrosis factor, alpha induced protein 3 zinc ion binding 202871_at TRAF4 1.5 TNF receptor associated factor 4 zinc ion binding 235081_x_at TRIM65 1.7 tripartite motif con taining 65 zinc ion binding
107 Table A 5. Continued. Probe set Symbol Fold change Description Function 241755_at UQCRC2 1.7 ubiquinol cytochrome c reductase core protein II zinc ion binding 1554036_at ZBTB24 2.3 zinc finger and BTB domain containing 24 z inc ion binding 227162_at ZBTB26 1.6 zinc finger and BTB domain containing 26 zinc ion binding 236557_at ZBTB38 1.6 zinc finger and BTB domain containing 38 zinc ion binding 206098_at ZBTB6 1.5 zinc finger and BTB domain containing 6 zinc ion binding 218810_at ZC3H12A 2.1 zinc finger CCCH type containing 12A zinc ion binding 222451_s_at ZDHHC9 2.2 zinc finger, DHHC type containing 9 zinc ion binding 208078_s_at ZEB1 6.0 zinc finger E box binding homeobox 1 zinc ion binding 217741_s_at ZFAND5 3.9 zi nc finger, AN1 type domain 5 zinc ion binding 207090_x_at ZFP30 1.5 zinc finger protein 30 homolog (mouse) zinc ion binding 201531_at ZFP36 4.5 zinc finger protein 36, C3H type, homolog (mouse) zinc ion binding 201369_s_at ZFP36L2 2.2 zinc finger prote in 36, C3H type like 2 zinc ion binding 216960_s_at ZNF133 1.4 zinc finger protein 133 zinc ion binding 219854_at ZNF14 1.5 zinc finger protein 14 zinc ion binding 206314_at ZNF167 1.9 zinc finger protein 167 zinc ion binding 219495_s_at ZNF180 1.6 zinc finger protein 180 zinc ion binding 213218_at ZNF187 1.6 zinc finger protein 187 zinc ion binding 200828_s_at ZNF207 1.5 zinc finger protein 207 zinc ion binding 233461_x_at ZNF226 1.6 zinc finger protein 226 zinc ion binding 242919_at ZNF253 1.8 zinc finger protein 253 zinc ion binding 1558700_s_at ZNF260 1.9 zinc finger protein 260 zinc ion binding
108 Table A 5. Continued. Probe set Symbol Fold change Description Function 1562991_at ZNF292 1.9 zinc finger protein 292 zinc ion binding 23395 2_s_at ZNF295 2.5 zinc finger protein 295 zinc ion binding 227613_at ZNF331 3.6 zinc finger protein 331 zinc ion binding 228927_at ZNF397 1.6 zinc finger protein 397 zinc ion binding 209944_at ZNF410 1.6 zinc finger protein 410 zinc ion binding 205514 _at ZNF415 1.6 zinc finger protein 415 zinc ion binding 1554007_at ZNF483 2.4 zinc finger protein 483 zinc ion binding 1562211_a_at ZNF491 1.7 zinc finger protein 491 zinc ion binding 1553957_at ZNF564 1.8 zinc finger protein 564 zinc ion binding 15 53696_s_at ZNF569 1.8 zinc finger protein 569 zinc ion binding 217627_at ZNF573 1.6 zinc finger protein 573 zinc ion binding 235690_at ZNF594 1.7 zinc finger protein 594 zinc ion binding 239007_at ZNF616 1.6 zinc finger protein 616 zinc ion binding 206188_at ZNF623 1.8 zinc finger protein 623 zinc ion binding 232272_at ZNF624 1.9 zinc finger protein 624 zinc ion binding 224492_s_at ZNF627 1.7 zinc finger protein 627 zinc ion binding 231950_at ZNF658 2.1 zinc finger protein 658 zinc ion bindin g 232563_at ZNF684 1.5 zinc finger protein 684 zinc ion binding
109 Table A 6 Expression of cell adhesion genes that are significantly different in the diaphragm after surgery Probe set Symbol Fold change Description Function 231907_at ABL2 2.0 v abl Abe lson murine leukemia viral oncogene homolog 2 (arg, Abelsonrelated gene) cell adhesion 201883_s_at B4GALT1 1.9 UDP Gal:betaGlcNAc beta 1,4 galactosyltransferase, polypeptide 1 cell adhesion 216598_s_at CCL2 8.2 chemokine (C C motif) ligand 2 cell adhes ion 217523_at CD44 2.9 CD44 molecule (Indian blood group) cell adhesion 203687_at CX3CL1 2.6 chemokine (C X3 C motif) ligand 1 cell adhesion 205898_at CX3CR1 2.6 chemokine (C X3 C motif) receptor 1 cell adhesion 204359_at FLRT2 2.1 fibronectin leucin e rich transmembrane protein 2 cell adhesion 222853_at FLRT3 2.6 fibronectin leucine rich transmembrane protein 3 cell adhesion 212070_at GPR56 2.0 G protein coupled receptor 56 cell adhesion 207316_at HAS1 3.8 hyaluronan synthase 1 cell adhesion 2033 95_s_at HES1 2.8 hairy and enhancer of split 1, (Drosophila) cell adhesion 213620_s_at ICAM2 1.8 intercellular adhesion molecule 2 cell adhesion 225806_at JUB 1.6 jub, ajuba homolog (Xenopus laevis) cell adhesion 203780_at MPZL2 2.3 myelin protein zero like 2 cell adhesion 202149_at NEDD9 2.3 neural precursor cell expressed, developmentally down regulated 9 cell adhesion 225975_at PCDH18 2.3 protocadherin 18 cell adhesion 214212_x_at PLEKHC1 1.7 pleckstrin homology domain containing, family C (with FERM domain) member 1 cell adhesion 210809_s_at POSTN 1.8 periostin, osteoblast specific factor cell adhesion 212099_at RHOB 3.0 ras homolog gene family, member B cell adhesion 212724_at RND3 3.7 Rho family GTPase 3 cell adhesion 206211_at SELE 6.0 sel ectin E (endothelial adhesion molecule 1) cell adhesion 206026_s_at TNFAIP6 4.1 tumor necrosis factor, alpha induced protein 6 cell adhesion 202877_s_at CD93 2.7 CD93 molecule cell cell adhesion 202638_s_at ICAM1 3.4 intercellular adhesion molecule 1 (C D54), human rhinovirus receptor regulation of cell adhesion
110 Table A 7. Expression of cell differentiation, growth, and proliferation genes that are significantly different in the diaphragm after surgery Probe set Symbol Fold change Description Function 203725_at GADD45A 3.0 growth arrest and DNA damage inducible, alpha cell cycle arrest 202669_s_at EFNB2 1.6 ephrin B2 cell differentiation 209305_s_at GADD45B 10.2 growth arrest and DNA damage inducible, beta cell differentiation 204121_at GADD45G 4.3 g rowth arrest and DNA damage inducible, gamma cell differentiation 1559975_at BTG1 2.3 B cell translocation gene 1, anti proliferative cell growth 1555608_at CAPRIN2 1.7 caprin family member 2 cell growth 223377_x_at CISH 6.8 cytokine inducible SH2 conta ining protein cell growth 209074_s_at FAM107A 3.4 family with sequence similarity 107, member A cell growth 205302_at IGFBP1 1.6 insulin like growth factor binding protein 1 cell growth 201830_s_at NET1 3.0 neuroepithelial cell transforming gene 1 cell growth 222514_at RRAGC 1.5 Ras related GTP binding C cell growth 202912_at ADM 3.6 adrenomedullin cell proliferation 206170_at ADRB2 1.8 adrenergic, beta 2 receptor, surface cell proliferation 205290_s_at BMP2 3.8 bone morphogenetic protein 2 cell pr oliferation 228176_at C9orf47 2.8 chromosome 9 open reading frame 47 cell proliferation 204995_at CDK5R1 1.6 cyclin dependent kinase 5, regulatory subunit 1 (p35) cell proliferation 213183_s_at CDKN1C 1.7 cyclin dependent kinase inhibitor 1C (p57, Kip2 ) cell proliferation 207442_at CSF3 2.7 colony stimulating factor 3 (granulocyte) cell proliferation 210762_s_at DLC1 1.8 deleted in liver cancer 1 cell proliferation 213895_at EMP1 3.8 epithelial membrane protein 1 cell proliferation 238500_at EMP2 1. 5 epithelial membrane protein 2 cell proliferation 203643_at ERF 1.5 Ets2 repressor factor cell proliferation
111 Table A 7. Continued. Probe set Symbol Fold change Description Function 204420_at FOSL1 3.3 FOS like antigen 1 cell proliferation 1553613_s_a t FOXC1 2.6 forkhead box C1 cell proliferation 202723_s_at FOXO1 1.9 forkhead box O1 cell proliferation 237403_at GFI1B 2.2 growth factor independent 1B (potential regulator of CDKN1A, translocated in CML) cell proliferation 209524_at HDGFRP3 1.9 hepato ma derived growth factor, related protein 3 cell proliferation 201626_at INSIG1 2.7 insulin induced gene 1 cell proliferation 203275_at IRF2 1.6 interferon regulatory factor 2 cell proliferation 200712_s_at MAPRE1 1.4 microtubule associated protein, RP /EB family, member 1 cell proliferation 201502_s_at NFKBIA 3.7 nuclear factor of kappa light polypeptide gene enhancer in B cells inhibitor, alpha cell proliferation 201695_s_at NP 6.9 nucleoside phosphorylase cell proliferation 218718_at PDGFC 1.6 pla telet derived growth factor C cell proliferation 223394_at SERTAD1 3.0 SERTA domain containing 1 cell proliferation 203625_x_at SKP2 1.8 S phase kinase associated protein 2 (p45) cell proliferation 214597_at SSTR2 1.5 somatostatin receptor 2 cell proli feration 202286_s_at TACSTD2 2.6 tumor associated calcium signal transducer 2 cell proliferation 202241_at TRIB1 3.3 tribbles homolog 1 (Drosophila) cell proliferation 211527_x_at VEGFA 1.8 vascular endothelial growth factor A cell proliferation 201235 _s_at BTG2 6.0 BTG family, member 2 negative regulation of cell proliferation 213134_x_at BTG3 2.6 BTG family, member 3 negative regulation of cell proliferation 201329_s_at ETS2 4.9 v ets erythroblastosis virus E26 oncogene homolog 2 (avian) negative re gulation of cell proliferation 218062_x_at CDC42EP4 2.2 CDC42 effector protein (Rho GTPase binding) 4 regulation of cell shape
112 Table A 8 Expression of structural constituent or molecular activity genes that are significantly different in the diaphragm after surgery Probe set Symbol Fold change Description Function 229218_at COL1A2 2.2 collagen, type I, alpha 2 extracellular matrix structural constituent 1563536_at COL4A5 1.5 collagen, type IV, alpha 5 (Alport syndrome) extracellular matrix structural constituent 37022_at PRELP 1.6 proline/arginine rich end leucine rich repeat protein extracellular matrix structural constituent 212086_x_at LMNA 1.9 lamin A/C structrual molecule activity 230289_at EPB41L1 2.4 erythrocyte membrane protein band 4.1 lik e 1 structual molecular activity 203276_at LMNB1 4.0 lamin B1 structual molecular activity 235086_at THBS1 8.2 thrombospondin 1 structual molecular activity 1561705_at TTBK2 1.6 tau tubulin kinase 2 structual molecular activity 209251_x_at TUBA1C 1.5 t ubulin, alpha 1c structual molecular activity 208977_x_at TUBB2C 1.6 tubulin, beta 2C structual molecular activity 213476_x_at TUBB3 1.7 tubulin, beta 3 structual molecular activity 209191_at TUBB6 3.0 tubulin, beta 6 structual molecular activity 23185 3_at TUBD1 1.6 tubulin, delta 1 structual molecular activity 222142_at CYLD 1.4 cylindromatosis (turban tumor syndrome) structural constituent of ribosome
113 Table A 9 Expression of extracellular region, cell junction, and membrane genes that are signif icantly different in the diaphragm after surgery Probe set Symbol Fold change Description Function Extracellular region 228190_at ATG4C 1.8 ATG4 autophagy related 4 homolog C (S. cerevisiae) extracellular region 213528_at C1orf156 1.8 chromosome 1 ope n reading frame 156 extracellular region 224553_s_at TNFRSF18 1.6 tumor necrosis factor receptor superfamily, member 18 extracellular region 201858_s_at SRGN 4.2 serglycin extracellular region 219522_at FJX1 2.4 four jointed box 1 (Drosophila) extracel lular region 221541_at CRISPLD2 2.8 cysteine rich secretory protein LCCL domain containing 2 extracellular region 220975_s_at C1QTNF1 2.0 C1q and tumor necrosis factor related protein 1 extracellular region 229120_s_at C1orf56 2.2 chromosome 1 open read ing frame 56 extracellular region 223454_at CXCL16 2.0 chemokine (C X C motif) ligand 16 extracellular region 203592_s_at FSTL3 1.6 follistatin like 3 (secreted glycoprotein) extracellular region 221009_s_at ANGPTL4 2.6 angiopoietin like 4 extracellular region 205258_at INHBB 4.3 inhibin, beta B extracellular region 241557_x_at TMEFF2 1.7 transmembrane protein with EGF like and two follistatin like domains 2 extracellular region 213425_at WNT5A 2.0 wingless type MMTV integration site family, member 5 A extracellular region 226621_at FGG 3.0 fibrinogen gamma chain extracellular region 1570046_at SCRG1 1.5 scrapie responsive protein 1 extracellular region 226977_at LOC492311 1.6 similar to bovine IgA regulatory protein extracellular region 206552_s_ at TAC1 5.0 tachykinin, precursor 1 (substance K, substance P, neurokinin 1, neurokinin 2, neuromedin L, neurokinin alpha, neuropeptide K, neuropeptide gamma) extracellular region 204597_x_at STC1 7.8 stanniocalcin 1 extracellular region 209122_at ADFP 1 .9 adipose differentiation related protein extracellular region
114 Table A 9. Continued. Probe set Symbol Fold change Description Function Cell Junction 227439_at ANKS1B 1.8 ankyrin repeat and sterile alpha motif domain containing 1B cell junction 210090 _at ARC 10.7 activity regulated cytoskeleton associated protein cell junction 204715_at PANX1 1.9 pannexin 1 cell junction 228263_at GRASP 2.2 GRP1 (general receptor for phosphoinositides 1) associated scaffold protein cell junction 241771_at RIMBP2 1.9 RIMS binding protein 2 cell junction 214827_at PARD6B 1.8 par 6 partitioning defective 6 homolog beta (C. elegans) cell junction 202085_at TJP2 1.8 tight junction protein 2 (zona occludens 2) cell junction Membrane 1559258_a_at CXorf61 1.6 chrom osome X open reading frame 61 plasma membrane 219492_at CHIC2 1.8 cysteine rich hydrophobic domain 2 plasma membrane 217291_at CEACAM5 1.5 carcinoembryonic antigen related cell adhesion molecule 5 anchored to membrane 1558511_s_at FAM62B 1.6 family with sequence similarity 62 (C2 domain containing) member B plasma membrane 218361_at GOLPH3L 1.9 golgi phosphoprotein 3 like membrane 225222_at HIAT1 1.7 hippocampus abundant transcript 1 integral to membrane 202181_at KIAA0247 1.8 KIAA0247 integral to me mbrane 223800_s_at LIMS3 2.4 LIM and senescent cell antigen like domains 3 integral to membrane 229531_at MCART6 1.5 mitochondrial carrier triple repeat 6 mitochondrial inner membrane 228282_at MFSD8 1.7 major facilitator superfamily domain containing 8 lysosomal membrane 225673_at MYADM 1.7 myeloid associated differentiation marker integral to membrane 1569641_at PQLC1 1.5 PQ loop repeat containing 1 integral to membrane 226430_at RELL1 1.6 RELT like 1 integral to membrane 238829_at SPG11 1.5 spas tic paraplegia 11 (autosomal recessive) integral to membrane 216920_s_at TARP 1.8 TCR gamma alternate reading frame protein integral to membrane
115 Table A 9. Continue d Probe set Symbol Fold change Description Function 209387_s_at TM4SF1 2.3 transmembran e 4 L six family member 1 integral to membrane 226489_at TMCC3 1.7 transmembrane and coiled coil domain family 3 integral to membrane 226825_s_at TMEM165 2.0 transmembrane protein 165 integral to membrane 219253_at TMEM185B 1.6 transmembrane protein 185 B integral to membrane 218113_at TMEM2 3.3 transmembrane protein 2 integral to membrane 224917_at TMEM49 4.3 transmembrane protein 49 integral to membrane 1557520_a_at TMEM59 1.5 transmembrane protein 59 integral to membrane 219449_s_at TMEM70 1.5 tran smembrane protein 70 integral to membrane 223772_s_at TMEM87A 1.8 transmembrane protein 87A integral to membrane
116 Table A 10. Expression of neuronal factor, blood coagulation, catalytic activity, and miscellaneous genes that are significantly different i n the diaphragm after surgery Probe set Symbol Fold change Description Function Neuronal Factor 204622_x_at NR4A2 3.7 nuclear receptor subfamily 4, group A, member 2 neuron differentiation 241583_x_at SYT1 1.7 synaptotagmin I neurotransmitter secretion 241652_x_at LIN7A 2.1 lin 7 homolog A (C. elegans) neurotransmitter secretion 1569916_at SLC6A15 2.1 solute carrier family 6, member 15 neurotransmitter transport 204224_s_at GCH1 4.6 GTP cyclohydrolase 1 (dopa responsive dystonia) neurotransmitter meta bolic process 200815_s_at PAFAH1B1 1.4 platelet activating factor acetylhydrolase, isoform Ib, alpha subunit 45kDa synaptic transmission 1565638_at PMP22 1.6 peripheral myelin protein 22 synaptic transmission 203400_s_at TF 1.4 transferrin regulation of myelination Blood coagulation 205479_s_at PLAU 3.3 plasminogen activator, urokinase blood coagulation 210845_s_at PLAUR 4.2 plasminogen activator, urokinase receptor blood coagulation 202628_s_at SERPINE1 8.6 serpin peptidase inhibitor, clade E (nexin plasminogen activator inhibitor type 1), member 1 blood coagulation 203887_s_at THBD 6.7 thrombomodulin blood coagulation 218995_s_at EDN1 1.8 endothelin 1 regulation of blood coagulation Keratin filament 234639_x_at KRTAP9 8 1.7 keratin associated protein 9 8 keratin filament Ribokinase activity 1568768_s_at RBKS 6.7 ribokinase ribokinase activity
117 Table A 10. Continued. Probe set Symbol Fold change Description Function Helicase activity 1568815_a_at DDX50 1.7 DEAD (Asp Glu Ala Asp) box polypep tide 50 helicase activity 208152_s_at DDX21 3.1 DEAD (Asp Glu Ala Asp) box polypeptide 21 helicase activity 221031_s_at APOLD1 5.6 apolipoprotein L domain containing 1 helicase activity 211787_s_at EIF4A1 2.6 eukaryotic translation initiation factor 4A, isoform 1 helicase activity 208896_at DDX18 1.6 DEAD (Asp Glu Ala Asp) box polypeptide 18 helicase activity 204258_at CHD1 2.8 chromodomain helicase DNA binding protein 1 helicase activity 212515_s_at DDX3X 1.8 DEAD (Asp Glu Ala Asp) box polypeptide 3, X linked helicase activity 205000_at DDX3Y 2.0 DEAD (Asp Glu Ala Asp) box polypeptide 3, Y linked helicase activity Transferase activity 51146_at PIGV 1.8 phosphatidylinositol glycan anchor biosynthesis, class V transferase activity 209340_at UAP1 2. 8 UDP N acteylglucosamine pyrophosphorylase 1 transferase activity 221561_at SOAT1 2.0 sterol O acyltransferase (acyl Coenzyme A: cholesterol acyltransferase) 1 transferase activity 1552611_a_at JAK1 1.5 Janus kinase 1 (a protein tyrosine kinase) transfe rase activity 225420_at GPAM 1.8 glycerol 3 phosphate acyltransferase, mitochondrial transferase activity 202238_s_at NNMT 4.0 nicotinamide N methyltransferase transferase activity 224454_at ETNK1 4.0 ethanolamine kinase 1 transferase activity 203127_ s_at SPTLC2 1.7 serine palmitoyltransferase, long chain base subunit 2 transferase activity 203044_at CHSY1 3.9 carbohydrate (chondroitin) synthase 1 transferase activity 227361_at HS3ST3B1 2.0 heparan sulfate (glucosamine) 3 O sulfotransferase 3B1 trans ferase activity 228772_at HNMT 1.8 histamine N methyltransferase transferase activity 205077_s_at PIGF 1.5 phosphatidylinositol glycan anchor biosynthesis, class F transferase activity 1569136_at MGAT4A 2.3 mannosyl (alpha 1,3 ) glycoprotein beta 1,4 N acetylglucosaminyltransferase, isozyme A transferase activity 1559391_s_at B4GALT5 2.2 UDP Gal:betaGlcNAc beta 1,4 galactosyltransferase, polypeptide 5 transferase activity
118 Table A 10. Continued. Probe set Symbol Fold change Description Function 225 612_s_at B3GNT5 5.4 UDP GlcNAc:betaGal beta 1,3 N acetylglucosaminyltransferase 5 transferase activity 228762_at LFNG 2.0 LFNG O fucosylpeptide 3 beta N acetylglucosaminyltransferase transferase activity 203234_at UPP1 3.2 uridine phosphorylase 1 transf erase activity 238902_at PCMTD1 1.5 protein L isoaspartate (D aspartate) O methyltransferase domain containing 1 transferase activity 238346_s_at TGS1 1.6 trimethylguanosine synthase homolog (S. cerevisiae) transferase activity 206432_at HAS2 4.5 hyalu ronan synthase 2 transferase activity 204881_s_at UGCG 5.0 UDP glucose ceramide glucosyltransferase transferase activity 213988_s_at SAT1 2.8 spermidine/spermine N1 acetyltransferase 1 transferase activity Hydrolase activity 203708_at PDE4B 2.6 phospho diesterase 4B, cAMP specific (phosphodiesterase E4 dunce homolog, Drosophila) hydrolase activity 239516_at LYPLAL1 3.5 lysophospholipase like 1 hydrolase activity 209355_s_at PPAP2B 2.1 phosphatidic acid phosphatase type 2B hydrolase activity 209585_s_ at MINPP1 1.6 multiple inositol polyphosphate histidine phosphatase, 1 hydrolase activity 209457_at DUSP5 2.5 dual specificity phosphatase 5 hydrolase activity 208893_s_at DUSP6 2.5 dual specificity phosphatase 6 hydrolase activity 221752_at SSH1 1.5 s lingshot homolog 1 (Drosophila) hydrolase activity 215095_at ESD 1.5 esterase D/formylglutathione hydrolase hydrolase activity 201761_at MTHFD2 2.4 methylenetetrahydrofolate dehydrogenase (NADP+ dependent) 2, methenyltetrahydrofolate cyclohydrolase hydr olase activity 202716_at PTPN1 2.2 protein tyrosine phosphatase, non receptor type 1 hydrolase activity 224826_at RP5 1022P6.2 1.7 hypothetical protein KIAA1434 hydrolase activity 238419_at PHLDB2 2.0 pleckstrin homology like domain, family B, member 2 hydrolase activity 219003_s_at MANEA 1.5 mannosidase, endo alpha hydrolase activity 206177_s_at ARG1 4.5 arginase, liver hydrolase activity 204014_at DUSP4 1.8 dual specificity phosphatase 4 hydrolase activity
119 Table A 10. Continued. Probe set Symbol Fold change Description Function Ligase activity 200648_s_at GLUL 2.1 glutamate ammonia ligase (glutamine synthetase) ligase activity Lyase activity 201196_s_at AMD1 2.3 adenosylmethionine decarboxylase 1 lyase activity Spermatogenesis 214911_s_at BR D2 1.7 bromodomain containing 2 spermatogensis Regulation of translation 224692_at PPP1R15B 2.1 protein phosphatase 1, regulatory (inhibitor) subunit 15B regulation of translation
120 Table A 11. Expression of unknown function genes that are significantly different in the diaphragm after surgery Probe set Symbol Fold change Description Function 222333_at ALS2CL 1.9 ALS2 C terminal like unknown functions 231999_at ANKRD11 1.5 ankyrin repeat domain 11 unknown functions 225735_at ANKRD50 1.5 ankyrin repea t domain 50 unknown functions 205239_at AREG 5.7 amphiregulin (schwannoma derived growth factor) unknown functions 211947_s_at BAT2D1 1.5 BAT2 domain containing 1 unknown functions 229437_at BIC 2.7 BIC transcript unknown functions 226383_at C11orf46 1.7 chromosome 11 open reading frame 46 unknown functions 218214_at C12orf44 1.5 chromosome 12 open reading frame 44 unknown functions 227058_at C13orf33 4.0 chromosome 13 open reading frame 33 unknown functions 227446_s_at C14orf167 1.9 chromosome 14 open reading frame 167 unknown functions 223474_at C14orf4 1.6 chromosome 14 open reading frame 4 unknown functions 217682_at C16orf72 1.9 chromosome 16 open reading frame 72 unknown functions 1553338_at C1orf55 1.5 chromosome 1 open reading frame 55 un known functions 209020_at C20orf111 1.7 chromosome 20 open reading frame 111 unknown functions 1552605_s_at C21orf74 1.5 chromosome 21 open reading frame 74 unknown functions 228067_at C2orf55 2.4 chromosome 2 open reading frame 55 unknown functions 22 2309_at C6orf62 2.4 chromosome 6 open reading frame 62 unknown functions 236634_at C8orf48 1.6 chromosome 8 open reading frame 48 unknown functions 222706_at CCDC49 1.5 coiled coil domain containing 49 unknown functions 1553214_a_at CCDC7 1.7 coiled c oil domain containing 7 unknown functions 227517_s_at CENPL 2.0 centromere protein L unknown functions 224991_at CMIP 1.9 c Maf inducing protein unknown functions 219397_at COQ10B 1.9 coenzyme Q10 homolog B (S. cerevisiae) unknown functions 1557954_at CXorf15 1.4 chromosome X open reading frame 15 unknown functions
121 Table A 11. Continued. Probe set Symbol Fold change Description Function 1556113_at DKFZp451A 211 2.5 DKFZp451A211 protein unknown functions 1569987_at DLEU7 1.5 deleted in lymphocytic le ukemia, 7 unknown functions 236649_at DTWD1 1.8 DTW domain containing 1 unknown functions 1563315_s_at ERICH1 1.8 glutamate rich 1 unknown functions 219216_at ETAA1 2.0 Ewing tumor associated antigen 1 unknown functions 223038_s_at FAM60A 1.7 family with sequence similarity 60, member A unknown functions 244014_x_at FAM92A1 1.6 family with sequence similarity 92, member A1 unknown functions 1553797_a_at FLJ30594 2.3 hypothetical locus FLJ30594 unknown functions 229521_at FLJ36031 4.8 hypothetical protein FLJ36031 unknown functions 241858_at FPGT 2.0 fucose 1 phosphate guanylyltransferase unknown functions 232035_at HIST1H4H 2.2 histone cluster 1, H4h unknown functions 203023_at HSPC111 1.9 hypothetical protein HSPC111 unknown functions 202081 _at IER2 2.9 immediate early response 2 unknown functions 218611_at IER5 2.6 immediate early response 5 unknown functions 203144_s_at KIAA0040 3.1 KIAA0040 unknown functions 228325_at KIAA0146 5.6 KIAA0146 unknown functions 228334_x_at KIAA1712 1.6 KI AA1712 unknown functions 227099_s_at LOC387763 3.8 hypothetical LOC387763 unknown functions 225857_s_at LOC388796 1.8 hypothetical LOC388796 unknown functions 220770_s_at LOC63920 2.3 transposon derived Buster3 transposase like unknown functions
122 Tabl e A 11. Continued. Probe set Symbol Fold change Description Function 224558_s_at MALAT1 1.4 metastasis associated lung adenocarcinoma transcript 1 (non coding RNA) unknown functions 213761_at MDM1 1.6 Mdm4, transformed 3T3 cell double minute 1, p53 bind ing protein (mouse) unknown functions 211456_x_at MT1P2 3.2 metallothionein 1 pseudogene 2 unknown functions 236273_at NBPF1 1.4 neuroblastoma breakpoint family, member 1 unknown functions 218319_at PELI1 3.0 pellino homolog 1 (Drosophila) unknown func tions 219093_at PID1 1.8 phosphotyrosine interaction domain containing 1 unknown functions 225699_at SNORA9 2.5 small nucleolar RNA, H/ACA box 9 unknown functions 214965_at SPATA2L 1.9 spermatogenesis associated 2 like unknown functions 233242_at WDR7 3 1.5 WD repeat domain 73 unknown functions 218647_s_at YRDC 2.0 yrdC domain containing (E. coli) unknown functions 228280_at ZC3HAV1L 1.6 zinc finger CCCH type, antiviral 1 like unknown functions
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138 BIOGRAPHICAL SKETCH Tseng Tien Huang was born in Yuan -Lin town, Taiwan, and graduated salutatorian of his high school class in 1993. He received his bachelors degree in Physical Therapy from National Cheng-Kung University, Taina n, Taiwan in July of 1996. Then, he was on the military duty from 19961998 in Taiwan. In 2002, he began a masters program in physical t herap y at the Uni versity of Florida in Gainesville, Florida a nd received a master degree in physical t herapy in 2004. Deciding to focus his carrier in rehabilitation science research, Tseng began his doctoral work at the University of Florida in 2004 under the direction of A.D. Martin. Tseng focused his studies on pulmonary physiology and inspiratory muscle training in diff icult to wean patients. He receive d his PhD in May 2009.