Using a personal computer (PC) for simple visual reaction time testing is advantageous because of the relatively low hardware cost, user familiarity, and relative ease software development specific neurobehavioral protocols. However, general-purpose computers are not designed with millisecond-level accuracy operation required such applications. Software that does control various sources delay may return values substantially different from true times. We have developed characterized freely...

Accurate estimation of expression levels from RNA-Seq data entails precise mapping the sequence reads to a reference genome. Because standard genome contains only one allele at any given locus, overlapping polymorphic loci that carry non-reference are least mismatch away and, hence, less likely be mapped. This bias in read leads inaccurate estimates allele-specific (ASE). To address this read-mapping bias, we propose construction an enhanced includes alternative alleles known loci. We show...

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> The combination of predictive data-driven models with frequent glucose measurements may provide for an early warning impending excursions and proactive regulatory interventions diabetes patients. However, from a modeling perspective, before the benefits such strategy can be attained, we must first able to quantitatively characterize behavior model coefficients as well predictions function...

This paper tests the hypothesis that a ¿universal,¿ data-driven model can be developed based on glucose data from one diabetic subject, and subsequently applied to predict subcutaneous concentrations of other subjects, even those with different types diabetes. We employed three separate studies, each utilizing continuous monitoring (CGM) device, verify model's universality. Two out studies involved subjects type 1 diabetes 2 first filtered concentration by imposing constraints their rate...

Background: Recent developments and expected near-future improvements in continuous glucose monitoring (CGM) devices provide opportunities to couple them with mathematical forecasting models produce predictive systems for early, proactive glycemia management of diabetes mellitus patients before levels drift undesirable levels. This article assesses the feasibility data-driven serve as engine systems. Methods: We investigated capabilities autoregressive (AR) (1) capture correlations...

Abstract Background Identification of canonical pathways through enrichment differentially expressed genes in a given pathway is widely used method for interpreting gene lists generated from high-throughput experimental studies. However, most algorithms treat as sets genes, disregarding any inter- and intra-pathway connectivity information, do not provide insights beyond identifying pathways. Results We developed an algorithm (PathNet) that utilizes the information descriptions to help...

Obstructive lung diseases in the lower airways are a leading health concern worldwide. To improve our understanding of pathophysiology airways, we studied airflow characteristics between 8th and 14th generations using three-dimensional computational fluid dynamics model, where compared normal obstructed for range breathing conditions. We employed novel technique based on computing Pearson׳s correlation coefficient to quantitatively characterize differences patterns airways. found that...

A hallmark of Pseudomonas aeruginosa is its ability to establish biofilm-based infections that are difficult eradicate. Biofilms less susceptible host inflammatory and immune responses have higher antibiotic tolerance than free-living planktonic cells. Developing treatments against biofilms requires an understanding bacterial biofilm-specific physiological traits. Research efforts started elucidate the intricate mechanisms underlying biofilm development. However, many aspects these still...

A deep neural network-based artificial intelligence (AI) model was assessed for its utility in predicting vital signs of hemorrhage patients and optimizing the management fluid resuscitation mass casualties. With use a cardio-respiratory computational to generate synthetic data casualties, an application created where limited stream (the initial 10 min vital-sign monitoring) could be used predict outcomes different allocations 60 into future. The predicted were then select optimal allocation...

Objective: The development and application of data-driven decision-support systems for medical triage, diagnostics, prognostics pose special requirements on physiologic data. In particular, that data are reliable in order to produce meaningful results. authors describe a method automatically estimates the reliability reference heart rates (HRr) derived from electrocardiogram (ECG) waveforms photoplethysmogram (PPG) recorded by vital-signs monitors. is quantitatively expressed through quality...

Molecular-docking-based virtual screening is an important tool in drug discovery that used to significantly reduce the number of possible chemical compounds be investigated. In addition selection a sound docking strategy with appropriate scoring functions, another technical challenge silico screen millions reasonable time. To meet this challenge, it necessary use high performance computing (HPC) platforms and techniques. However, development integrated HPC system makes efficient its elements...

Small-molecule docking is an important tool in studying receptor-ligand interactions and identifying potential drug candidates. Previously, we developed a software (DOVIS) to perform large-scale virtual screening of small molecules parallel on Linux clusters, using AutoDock 3.05 as the engine. DOVIS enables seamless millions compounds high-performance computing platforms. In this paper, report significant advances implementation 2.0, including enhanced capability, improved file system...

Chronic inflammation is rapidly becoming recognized as a key contributor to numerous pathologies. Despite detailed investigations, understanding of the molecular mechanisms regulating incomplete. Knowledge such critical regulatory processes and informative indicators chronic necessary for efficacious therapeutic interventions diagnostic support clinicians. We used computational modeling approach elucidate factors responsible identify robust inflammatory conditions. Our kinetic model...

The ability to adapt different conditions is key for Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), successfully infect human hosts. Adaptations allow organism evade host immune responses during acute infections and persist an extended period time latent infectious stage. In latently infected individuals, estimated include one-third population, exists in a variety metabolic states, which impedes development simple strategy controlling or eradicating this disease....

Abstract Polyvalent vaccines use a mixture of Ags representing distinct pathogen strains to induce an immune response that is cross-reactive and protective. However, such approaches often have mixed results, it unclear how polyvalency alters the fine specificity Ab what those consequences might be for protection. In this article, we present coarse-grain theoretical model B cell affinity maturation during monovalent polyvalent vaccinations predicts cross-reactivity response. We stochastically...

Performance prediction models based on the classical two-process model of sleep regulation are reasonably effective at predicting alertness and neurocognitive performance during total deprivation (TSD). However, restriction (partial loss) predictions such have been found to be less accurate. Because most modern operational environments predominantly characterized by chronic (CSR) rather than episodic TSD, practical utility this class has limited. To better quantify both CSR we developed a...

A comprehensive understanding of thrombus formation as a physicochemical process that has evolved to protect the integrity human vasculature is critical our ability predict and control pathological states caused by malfunctioning blood coagulation system. Despite numerous investigations, spatial temporal details growth multicomponent are not fully understood. Here, we used computational modeling investigate changes in distributions key enzymatic (i.e., thrombin) structural platelets fibrin)...

The expanded use of multiple drugs has increased the occurrence adverse drug reactions (ADRs) induced by drug-drug interactions (DDIs). However, such are typically not observed in clinical drug-development studies because most them focus on single-drug therapies. ADR reporting systems collect information health effects caused both single and DDIs. A major challenge is to unambiguously identify DDIs attribute specific interactions. computational method that provides prospective predictions...

Active lower-body exoskeleton devices can decrease the energy requirement of human body by providing mechanical assistance to muscles. However, they also alter gait kinematics and kinetics, it is not well understood whether such alterations are detrimental or beneficial body. In this pilot study, we investigated impact walking with an ankle device on biomechanics men while carrying a heavy load. We collected computed tomography images motion-capture data for five young, healthy who walked 5...

Data that characterize primary and tertiary structures of proteins are now accumulating at a rapid accelerating rate require automated computational tools to extract critical information relating amino acid changes with the spectrum functionally attributes exhibited by protein. We propose immunoglobulin-type beta-domains, which found in approximate 400 distinct forms humans alone, provide immense genetic variation within limited conformational might facilitate development new tools. As an...

Abstract In this article, we present a new method termed CatFam (Catalytic Families) to automatically infer the functions of catalytic proteins, which account for 20–40% all proteins in living organisms and play critical role variety biological processes. is sequence‐based that generates sequence profiles represent protein functions. through stepwise procedure carefully controls profile quality employs nonenzymes as negative samples establish profile‐specific thresholds associated with...