Assessing and selecting gene expression signals based upon the quality of the measured dynamics

<p>Abstract</p> <p>Background</p> <p>One of the challenges with modeling the temporal progression of biological signals is dealing with the effect of noise and the limited number of replicates at each time point. Given the rising interest in utilizing predictive mathematical models to describe the biological response of an organism or analysis such as clustering and gene ontology enrichment, it is important to determine whether the dynamic progression of the data has been accurately captured despite the limited number of replicates, such that one can have confidence that the results of the analysis are capturing important salient dynamic features.</p> <p>Results</p> <p>By pre-selecting genes based upon quality before the identification of differential expression via algorithm such as EDGE, it was found that the percentage of statistically enriched ontologies (p < .05) was improved. Furthermore, it was found that a majority of the genes found via the proposed technique were also selected via an EDGE selection though the reverse was not necessarily true. It was also found that improvements offered by the proposed algorithm are anti-correlated with improvements in the various microarray platforms and the number of replicates. This is illustrated by the fact that newer arrays and experiments with more replicates show less improvement when the filtering for quality is first run before the selection of differentially expressed genes. This suggests that the increase in the number of replicates as well as improvements in array technologies are increase the confidence one has in the dynamics obtained from the experiment.</p> <p>Conclusion</p> <p>We have developed an algorithm that quantifies the quality of temporal biological signal rather than whether the signal illustrates a significant change over the experimental time course. Because the use of these temporal signals, whether it is in mathematical modeling or clustering, focuses upon the entire time series, it is necessary to develop a method to quantify and select for signals which conform to this ideal. By doing this, we have demonstrated a marked and consistent improvement in the results of a clustering exercise over multiple experiments, microarray platforms, and experimental designs.</p

A Panel of Serum MicroRNAs as Specific Biomarkers for Diagnosis of Compound- and Herb-Induced Liver Injury in Rats

Drug-induced liver injury (DILI) has been a public, economic and pharmaceutical issue for many years. Enormous effort has been made for discovering and developing novel biomarkers for diagnosing and monitoring both clinical and preclinical DILI at an early stage, though progress has been relatively slow. Additionally, herb-induced liver injury is an emerging cause of liver disease because herbal medicines are increasingly being used worldwide. Recently, circulating microRNAs (miRNAs) have shown potential to serve as novel, minimally invasive biomarkers to diagnose and monitor human cancers and other diseases at early stages.In order to identify candidate miRNAs as diagnostic biomarkers for DILI, miRNA expression profiles of serum and liver tissue from two parallel liver injury Sprague-Dawley rat models induced by a compound (acetaminophen, APAP) or an herb (Dioscorea bulbifera, DB) were screened in this study. The initial screens were performed on serum using a MicroRNA TaqMan low-density qPCR array and on liver tissue using a miRCURY LNA hybridization array and were followed by a TaqMan probe-based quantitative reverse transcription-PCR (qRT-PCR) assay to validate comparison with serum biochemical parameters and histopathological examination. Two sets of dysregulated miRNA candidates in serum and liver tissue were selected in the screening phase. After qRT-PCR validation, a panel of compound- and herb- related serum miRNAs was identified.We have demonstrated that this panel of serum miRNAs provides potential biomarkers for diagnosis of DILI with high sensitivity and specificity

Nitrosative and Oxidative Stresses Contribute to Post-Ischemic Liver Injury Following Severe Hemorrhagic Shock: The Role of Hypoxemic Resuscitation

Purpose: Hemorrhagic shock and resuscitation is frequently associated with liver ischemia-reperfusion injury. The aim of the study was to investigate whether hypoxemic resuscitation attenuates liver injury. Methods: Anesthetized, mechanically ventilated New Zealand white rabbits were exsanguinated to a mean arterial pressure of 30 mmHg for 60 minutes. Resuscitation under normoxemia (Normox-Res group, n = 16, PaO2 = 95–105 mmHg) or hypoxemia (Hypox-Res group, n = 15, PaO 2 = 35–40 mmHg) followed, modifying the FiO 2. Animals not subjected to shock constituted the sham group (n = 11, PaO 2 = 95–105 mmHg). Indices of the inflammatory, oxidative and nitrosative response were measured and histopathological and immunohistochemical studies of the liver were performed. Results: Normox-Res group animals exhibited increased serum alanine aminotransferase, tumor necrosis factor- alpha, interleukin (IL)-1b and IL-6 levels compared with Hypox-Res and sham groups. Reactive oxygen species generation, malondialdehyde formation and myeloperoxidase activity were all elevated in Normox-Res rabbits compared with Hypox-Res and sham groups. Similarly, endothelial NO synthase and inducible NO synthase mRNA expression was up-regulated and nitrotyrosine immunostaining increased in animals resuscitated normoxemically, indicating a more intense nitrosative stress. Hypox-Res animals demonstrated a less prominent histopathologic injury which was similar to sham animals. Conclusions: Hypoxemic resuscitation prevents liver reperfusion injury through attenuation of the inflammatory respons

Agent-Based Modeling of Endotoxin-Induced Acute Inflammatory Response in Human Blood Leukocytes

Inflammation is a highly complex biological response evoked by many stimuli. A persistent challenge in modeling this dynamic process has been the (nonlinear) nature of the response that precludes the single-variable assumption. Systems-based approaches offer a promising possibility for understanding inflammation in its homeostatic context. In order to study the underlying complexity of the acute inflammatory response, an agent-based framework is developed that models the emerging host response as the outcome of orchestrated interactions associated with intricate signaling cascades and intercellular immune system interactions.An agent-based modeling (ABM) framework is proposed to study the nonlinear dynamics of acute human inflammation. The model is implemented using NetLogo software. Interacting agents involve either inflammation-specific molecules or cells essential for the propagation of the inflammatory reaction across the system. Spatial orientation of molecule interactions involved in signaling cascades coupled with the cellular heterogeneity are further taken into account. The proposed in silico model is evaluated through its ability to successfully reproduce a self-limited inflammatory response as well as a series of scenarios indicative of the nonlinear dynamics of the response. Such scenarios involve either a persistent (non)infectious response or innate immune tolerance and potentiation effects followed by perturbations in intracellular signaling molecules and cascades.The ABM framework developed in this study provides insight on the stochastic interactions of the mediators involved in the propagation of endotoxin signaling at the cellular response level. The simulation results are in accordance with our prior research effort associated with the development of deterministic human inflammation models that include transcriptional dynamics, signaling, and physiological components. The hypothetical scenarios explored in this study would potentially improve our understanding of how manipulating the behavior of the molecular species could manifest into emergent behavior of the overall system

Long-Term Persistance of the Pathophysiologic Response to Severe Burn Injury

Main contributors to adverse outcomes in severely burned pediatric patients are profound and complex metabolic changes in response to the initial injury. It is currently unknown how long these conditions persist beyond the acute phase post-injury. The aim of the present study was to examine the persistence of abnormalities of various clinical parameters commonly utilized to assess the degree hypermetabolic and inflammatory alterations in severely burned children for up to three years post-burn to identify patient specific therapeutic needs and interventions. Nine-hundred seventy-seven severely burned pediatric patients with burns over 30% of the total body surface admitted to our institution between 1998 and 2008 were enrolled in this study and compared to a cohort non-burned, non-injured children. Demographics and clinical outcomes, hypermetabolism, body composition, organ function, inflammatory and acute phase responses were determined at admission and subsequent regular intervals for up to 36 months post-burn. Statistical analysis was performed using One-way ANOVA, Student's t-test with Bonferroni correction where appropriate with significance accepted at p<0.05. Resting energy expenditure, body composition, metabolic markers, cardiac and organ function clearly demonstrated that burn caused profound alterations for up to three years post-burn demonstrating marked and prolonged hypermetabolism, p<0.05. Along with increased hypermetabolism, significant elevation of cortisol, catecholamines, cytokines, and acute phase proteins indicate that burn patients are in a hyperinflammatory state for up to three years post-burn p<0.05. Severe burn injury leads to a much more profound and prolonged hypermetabolic and hyperinflammatory response than previously shown. Given the tremendous adverse events associated with the hypermetabolic and hyperinflamamtory responses, we now identified treatment needs for severely burned patients for a much more prolonged time

Computational Identification of Transcriptional Regulators in Human Endotoxemia

One of the great challenges in the post-genomic era is to decipher the underlying principles governing the dynamics of biological responses. As modulating gene expression levels is among the key regulatory responses of an organism to changes in its environment, identifying biologically relevant transcriptional regulators and their putative regulatory interactions with target genes is an essential step towards studying the complex dynamics of transcriptional regulation. We present an analysis that integrates various computational and biological aspects to explore the transcriptional regulation of systemic inflammatory responses through a human endotoxemia model. Given a high-dimensional transcriptional profiling dataset from human blood leukocytes, an elementary set of temporal dynamic responses which capture the essence of a pro-inflammatory phase, a counter-regulatory response and a dysregulation in leukocyte bioenergetics has been extracted. Upon identification of these expression patterns, fourteen inflammation-specific gene batteries that represent groups of hypothetically ‘coregulated’ genes are proposed. Subsequently, statistically significant cis-regulatory modules (CRMs) are identified and decomposed into a list of critical transcription factors (34) that are validated largely on primary literature. Finally, our analysis further allows for the construction of a dynamic representation of the temporal transcriptional regulatory program across the host, deciphering possible combinatorial interactions among factors under which they might be active. Although much remains to be explored, this study has computationally identified key transcription factors and proposed a putative time-dependent transcriptional regulatory program associated with critical transcriptional inflammatory responses. These results provide a solid foundation for future investigations to elucidate the underlying transcriptional regulatory mechanisms under the host inflammatory response. Also, the assumption that coexpressed genes that are functionally relevant are more likely to share some common transcriptional regulatory mechanism seems to be promising, making the proposed framework become essential in unravelling context-specific transcriptional regulatory interactions underlying diverse mammalian biological processes

Effects of cardiac versus circulatory angiotensin-converting enzyme inhibition on left ventricular diastolic function and coronary blood flow in hypertrophic obstructive cardiomyopathy

Background-Left ventricular (LV) diastolic function and coronary flow are impaired in hypertrophic obstructive cardiomyopathy (HOCM). This study was designed to evaluate the impact of cardiac and circulatory ACE inhibition on such derangements. Methods and Results-Twenty patients with HOCM underwent cardiac ACE inhibition with intracoronary (IC) enalaprilat (0.05 mg/min infused into the left anterior descending coronary artery for 15 minutes) followed by circulatory ACE inhibition with 25 mg sublingual (SL) captopril. Contrast ventriculography, pressure, and coronary flow measurements were performed at baseline, after IC enalaprilat infusion, and 45 minutes after SL captopril. Heart rate was not affected by the respective interventions (75+/-11 versus 76+/-13 versus 75+/-10 bpm; P=NS), whereas mean aortic pressure dropped slightly after IC enalaprilat and significantly after SL captopril (90+/-8 versus 85+/-10 versus 74+/-9 mm Hg; P&lt;.05). Compared with baseline, IC enalaprilat resulted in a decrease in LV end-diastolic pressure (17.6+/-5.9 versus 14.4+/-4.9 mm Hg; P&lt;.05), time constant of isovolumic LV pressure relaxation (tau(G)) (69+/-9 versus 52+/-10 ms; P&lt;.05), and outflow gradient (45.2+/-6.9 versus 24.4+/-3.7 mm Hg; P&lt;.05) and in an increase in coronary blood flow (107+/-10 versus 127+/-12 mL/min; P&lt;.05) and coronary flow reserve (2.2+/-0.4 versus 2.6+/-0.3; P&lt;.05). After SL captopril, tau(G), was prolonged (60+/-13 ms; P&lt;.05 versus IC enalaprilat), and LV outflow gradient, coronary blood flow, and coronary flow reserve values returned to baseline (45.5+/-5.3 mm Hg, 107+/-12 mL/min, and 2.2+/-0.5, respectively; P=NS versus baseline). Conclusions-Activation of the cardiac renin-angiotensin system contributes to LV diastolic dysfunction as well as to the decreased coronary blood flow and coronary flow reserve in HOCM. Cardiac ACE inhibition restores and circulatory ACE inhibition aggravates the above derangements