Browsing by Author "Kumar, Kamal"
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- Item2B-Alert App: A mobile application for real-time individualized prediction of alertness.(0000-00-00) Reifman, Jaques; Ramakrishnan, Sridhar; Liu, Jianbo; Kapela, Adam; Doty, Tracy J; Balkin, Thomas J; Kumar, Kamal; Khitrov, Maxim YKnowing how an individual responds to sleep deprivation is a requirement for developing personalized fatigue management strategies Here we describe and validate the 2B Alert App the first mobile application that progressively learns an individual s trait like response to sleep deprivation in real time to generate increasingly more accurate individualized predictions of alertness We incorporated a Bayesian learning algorithm within the validated Unified Model of Performance to automatically and gradually adapt the model parameters to an individual after each psychomotor vigilance test We implemented the resulting model and the psychomotor vigilance test as a smartphone application 2B Alert App and prospectively validated its performance in a 62 hr total sleep deprivation study in which 21 participants used the app to perform psychomotor vigilance tests every 3 hr and obtain real time individualized predictions after each test The temporal profiles of reaction times on the app conducted psychomotor vigilance tests were well correlated with and as sensitive as those obtained with a previously characterized psychomotor vigilance test device The app progressively learned each individual s trait like response to sleep deprivation throughout the study yielding increasingly more accurate predictions of alertness for the last 24 hr of total sleep deprivation as the number of psychomotor vigilance tests increased After only 12 psychomotor vigilance tests the accuracy of the model predictions was comparable to the peak accuracy obtained using all psychomotor vigilance tests With the ability to make real time individualized predictions of the effects of sleep deprivation on future alertness the 2B Alert App can be used to tailor personalized fatigue management strategies facilitating self management of alertness and safety in operational and non operational settings
- ItemAGeS: a software system for microbial genome sequence annotation.(2011-03-16) Kumar, Kamal; Desai, Valmik; Cheng, Li; Khitrov, Maxim; Grover, Deepak; Satya, Ravi Vijaya; Yu, Chenggang; Zavaljevski, Nela; Reifman, JaquesThe annotation of genomes from next generation sequencing platforms needs to be rapid high throughput and fully integrated and automated Although a few Web based annotation services have recently become available they may not be the best solution for researchers that need to annotate a large number of genomes possibly including proprietary data and store them locally for further analysis To address this need we developed a standalone software application the Annotation of microbial Genome Sequences AGeS system which incorporates publicly available and in house developed bioinformatics tools and databases many of which are parallelized for high throughput performance
- ItemCharacterization of chemically induced liver injuries using gene co-expression modules.(2014-09-17) Tawa, Gregory J; AbdulHameed, Mohamed Diwan M; Yu, Xueping; Kumar, Kamal; Ippolito, Danielle L; Lewis, John A; Stallings, Jonathan D; Wallqvist, AndersLiver injuries due to ingestion or exposure to chemicals and industrial toxicants pose a serious health risk that may be hard to assess due to a lack of non invasive diagnostic tests Mapping chemical injuries to organ specific damage and clinical outcomes via biomarkers or biomarker panels will provide the foundation for highly specific and robust diagnostic tests Here we have used DrugMatrix a toxicogenomics database containing organ specific gene expression data matched to dose dependent chemical exposures and adverse clinical pathology assessments in Sprague Dawley rats to identify groups of co expressed genes modules specific to injury endpoints in the liver We identified 78 such gene co expression modules associated with 25 diverse injury endpoints categorized from clinical pathology organ weight changes and histopathology Using gene expression data associated with an injury condition we showed that these modules exhibited different patterns of activation characteristic of each injury We further showed that specific module genes mapped to 1 known biochemical pathways associated with liver injuries and 2 clinically used diagnostic tests for liver fibrosis As such the gene modules have characteristics of both generalized and specific toxic response pathways Using these results we proposed three gene signature sets characteristic of liver fibrosis steatosis and general liver injury based on genes from the co expression modules Out of all 92 identified genes 18 20 genes have well documented relationships with liver disease whereas the rest are novel and have not previously been associated with liver disease In conclusion identifying gene co expression modules associated with chemically induced liver injuries aids in generating testable hypotheses and has the potential to identify putative biomarkers of adverse health effects
- ItemDBSecSys: a database of Burkholderia mallei secretion systems.(2014-07-25) Memišević, Vesna; Kumar, Kamal; Cheng, Li; Zavaljevski, Nela; DeShazer, David; Wallqvist, Anders; Reifman, JaquesBacterial pathogenicity represents a major public health concern worldwide Secretion systems are a key component of bacterial pathogenicity as they provide the means for bacterial proteins to penetrate host cell membranes and insert themselves directly into the host cells cytosol Burkholderia mallei is a Gram negative bacterium that uses multiple secretion systems during its host infection life cycle To date the identities of secretion system proteins for B mallei are not well known and their pathogenic mechanisms of action and host factors are largely uncharacterized
- ItemDOVIS: an implementation for high-throughput virtual screening using AutoDock.(2008-03-27) Zhang, Shuxing; Kumar, Kamal; Jiang, Xiaohui; Wallqvist, Anders; Reifman, JaquesMolecular docking based virtual screening is an important tool in drug discovery that is used to significantly reduce the number of possible chemical compounds to be investigated In addition to the selection of a sound docking strategy with appropriate scoring functions another technical challenge is to in silico screen millions of compounds in a reasonable time To meet this challenge it is necessary to use high performance computing HPC platforms and techniques However the development of an integrated HPC system that makes efficient use of its elements is not trivial
- ItemA high-throughput pipeline for designing microarray-based pathogen diagnostic assays.(2008-04-30) Vijaya Satya, Ravi; Zavaljevski, Nela; Kumar, Kamal; Reifman, JaquesWe present a methodology for high throughput design of oligonucleotide fingerprints for microarray based pathogen diagnostic assays The oligonucleotide fingerprints or DNA microarray probes are designed for identifying target organisms in environmental or clinical samples The design process is implemented in a high performance computing software pipeline that incorporates major algorithmic improvements over a previous version to both reduce computation time and improve specificity assessment
- ItemPC-PVT 2.0: An updated platform for psychomotor vigilance task testing, analysis, prediction, and visualization.(0000-00-00) Reifman, Jaques; Kumar, Kamal; Khitrov, Maxim Y; Liu, Jianbo; Ramakrishnan, SridharBACKGROUND The psychomotor vigilance task PVT has been widely used to assess the effects of sleep deprivation on human neurobehavioral performance To facilitate research in this field we previously developed the PC PVT a freely available software system analogous to the gold standard PVT 192 that in addition to allowing for simple visual reaction time RT tests also allows for near real time PVT analysis prediction and visualization in a personal computer PC NEW METHOD Here we present the PC PVT 2 0 for Windows 10 operating system which has the capability to couple PVT tests of a study protocol with the study s sleep wake and caffeine schedules and make real time individualized predictions of PVT performance for such schedules We characterized the accuracy and precision of the software in measuring RT using 44 distinct combinations of PC hardware system configurations RESULTS We found that 15 system configurations measured RTs with an average delay of less than 10 ms an error comparable to that of the PVT 192 To achieve such small delays the system configuration should always use a gaming mouse as the means to respond to visual stimuli We recommend using a discrete graphical processing unit for desktop PCs and an external monitor for laptop PCs COMPARISON WITH EXISTING METHOD This update integrates a study s sleep wake and caffeine schedules with the testing software facilitating testing and outcome visualization and provides near real time individualized PVT predictions for any sleep loss condition considering caffeine effects CONCLUSIONS The software with its enhanced PVT analysis visualization and prediction capabilities can be freely downloaded from https pcpvt bhsai org
- ItemThe physiology analysis system: an integrated approach for warehousing, management and analysis of time-series physiology data.(2007-03-12) McKenna, Thomas M; Bawa, Gagandeep; Kumar, Kamal; Reifman, JaquesThe physiology analysis system PAS was developed as a resource to support the efficient warehousing management and analysis of physiology data particularly continuous time series data that may be extensive of variable quality and distributed across many files The PAS incorporates time series data collected by many types of data acquisition devices and it is designed to free users from data management burdens This Web based system allows both discrete attribute and time series ordered data to be manipulated visualized and analyzed via a client s Web browser All processes occur on a server so that the client does not have to download data or any application programs and the PAS is independent of the client s computer operating system The PAS contains a library of functions written in different computer languages that the client can add to and use to perform specific data operations Functions from the library are sequentially inserted into a function chain based logical structure to construct sophisticated data operators from simple function building blocks affording ad hoc query and analysis of time series data These features support advanced mining of physiology data
- ItemPrehospital heart rate and blood pressure increase the positive predictive value of the Glasgow Coma Scale for high-mortality traumatic brain injury.(2014-05-08) Reisner, Andrew; Chen, Xiaoxiao; Kumar, Kamal; Reifman, JaquesWe hypothesized that vital signs could be used to improve the association between a trauma patient s prehospital Glasgow Coma Scale GCS score and his or her clinical condition Previously abnormally low and high blood pressures have both been associated with higher mortality for patients with traumatic brain injury TBI We undertook a retrospective analysis of 1384 adult prehospital trauma patients Vital sign data were electronically archived and analyzed We examined the relative risk of severe head Abbreviated Injury Scale AIS 5 6 as a function of the GCS systolic blood pressure SBP heart rate HR and respiratory rate RR We created multi variate logistic regression models and using DeLong s test compared their area under receiver operating characteristic curves ROC AUCs for three outcomes head AIS 5 6 all cause mortality and either head AIS 5 6 or neurosurgical procedure We found significant bimodal relationships between head AIS 5 6 versus SBP and HR but not RR When the GCS was Under15 ROC AUCs were significantly higher for a multi variate regression model GCS SBP and HR versus GCS alone In particular patients with abnormalities in all parameters GCS SBP and HR were significantly more likely to have high mortality TBI versus those with abnormalities in GCS alone This could be useful for mobilizing resources e g neurosurgeons and operating rooms at the receiving hospital and might enable new prehospital management protocols where therapies are selected based on TBI mortality risk
- ItemSystems level analysis and identification of pathways and networks associated with liver fibrosis.(2014-11-08) AbdulHameed, Mohamed Diwan M; Tawa, Gregory J; Kumar, Kamal; Ippolito, Danielle L; Lewis, John A; Stallings, Jonathan D; Wallqvist, AndersToxic liver injury causes necrosis and fibrosis which may lead to cirrhosis and liver failure Despite recent progress in understanding the mechanism of liver fibrosis our knowledge of the molecular level details of this disease is still incomplete The elucidation of networks and pathways associated with liver fibrosis can provide insight into the underlying molecular mechanisms of the disease as well as identify potential diagnostic or prognostic biomarkers Towards this end we analyzed rat gene expression data from a range of chemical exposures that produced observable periportal liver fibrosis as documented in DrugMatrix a publicly available toxicogenomics database We identified genes relevant to liver fibrosis using standard differential expression and co expression analyses and then used these genes in pathway enrichment and protein protein interaction PPI network analyses We identified a PPI network module associated with liver fibrosis that includes known liver fibrosis relevant genes such as tissue inhibitor of metalloproteinase 1 galectin 3 connective tissue growth factor and lipocalin 2 We also identified several new genes such as perilipin 3 legumain and myocilin which were associated with liver fibrosis We further analyzed the expression pattern of the genes in the PPI network module across a wide range of 640 chemical exposure conditions in DrugMatrix and identified early indications of liver fibrosis for carbon tetrachloride and lipopolysaccharide exposures Although it is well known that carbon tetrachloride and lipopolysaccharide can cause liver fibrosis our network analysis was able to link these compounds to potential fibrotic damage before histopathological changes associated with liver fibrosis appeared These results demonstrated that our approach is capable of identifying early stage indicators of liver fibrosis and underscore its potential to aid in predictive toxicity biomarker identification and to generally identify disease relevant pathways