A late-binding, distributed, NoSQL warehouse for integrating patient data from clinical trials.

Clinical trial data are typically collected through multiple systems developed by different vendors using different technologies and data standards. That data need to be integrated, standardized and transformed for a variety of monitoring and reporting purposes. The need to process large volumes of often inconsistent data in the presence of ever-changing requirements poses a significant technical challenge.

Mathematical modeling of the heat-shock response in HeLa cells.

The heat-shock response is a key factor in diverse stress scenarios, ranging from hyperthermia to protein folding diseases. However, the complex dynamics of this physiological response have eluded mathematical modeling efforts. Although several computational models have attempted to characterize the heat-shock response, they were unable to model its dynamics across diverse experimental datasets.

On heart rate variability and autonomic activity in homeostasis and in systemic inflammation.

Analysis of heart rate variability (HRV) is a promising diagnostic technique due to the noninvasive nature of the measurements involved and established correlations with disease severity, particularly in inflammation-linked disorders. However, the complexities underlying the interpretation of HRV complicate understanding the mechanisms that cause variability. Despite this, such interpretations are often found in literature.

Predicting critical transitions in a model of systemic inflammation.

The human body can be viewed as a dynamical system, with physiological states such as health and disease broadly representing steady states. From this perspective, and given inter- and intra-individual heterogeneity, an important task is identifying the propensity to transition from one steady state to another, which in practice can occur abruptly. Detecting impending transitions between steady states is of significant importance in many fields, and thus a variety of methods have been developed for this purpose, but lack of data has limited applications in physiology.

Translational applications of evaluating physiologic variability in human endotoxemia.

Dysregulation of the inflammatory response is a critical component of many clinically challenging disorders such as sepsis. Inflammation is a biological process designed to lead to healing and recovery, ultimately restoring homeostasis; however, the failure to fully achieve those beneficial results can leave a patient in a dangerous persistent inflammatory state. One of the primary challenges in developing novel therapies in this area is that inflammation is comprised of a complex network of interacting pathways.

Modeling physiologic variability in human endotoxemia.

The control and management of inflammation is a key aspect of clinical care for critical illnesses such as sepsis. In an ideal reaction to injury, the inflammatory response provokes a strong enough response to heal the injury and then restores homeostasis. When inflammation becomes dysregulated, a persistent inflammatory state can lead to significant deleterious effects and clinical challenges.

Linking Inflammation, Cardiorespiratory Variability, and Neural Control in Acute Inflammation via Computational Modeling.

Acute inflammation leads to organ failure by engaging catastrophic feedback loops in which stressed tissue evokes an inflammatory response and, in turn, inflammation damages tissue. Manifestations of this maladaptive inflammatory response include cardio-respiratory dysfunction that may be reflected in reduced heart rate and ventilatory pattern variabilities. We have developed signal-processing algorithms that quantify non-linear deterministic characteristics of variability in biologic signals.

Pulsatile glucocorticoid secretion: origins and downstream effects.

Glucocorticoids are steroid hormones which, among other functions, exert an antiinflammatory effect. Endogenous glucocorticoids are normally secreted by the adrenal gland in discrete bursts. It is becoming increasingly evident that this pulsatile secretion pattern, leading to ultradian rhythms of plasma glucocorticoid levels, may have important downstream regulatory effects on glucocorticoid-responsive genes.

Modeling autonomic regulation of cardiac function and heart rate variability in human endotoxemia.

Heart rate variability (HRV), the quantification of beat-to-beat variability, has been studied as a potential prognostic marker in inflammatory diseases such as sepsis. HRV normally reflects significant levels of variability in homeostasis, which can be lost under stress. Much effort has been placed in interpreting HRV from the perspective of quantitatively understanding how stressors alter HRV dynamics, but the molecular and cellular mechanisms that give rise to both homeostatic HRV and changes in HRV have received less focus.

Modeling the influence of circadian rhythms on the acute inflammatory response.

A wide variety of modeling techniques have been applied towards understanding inflammation. These models have broad potential applications, from optimizing clinical trials to improving clinical care. Models have been developed to study specific systems and diseases, but the effect of circadian rhythms on the inflammatory response has not been modeled.