Biology subjects

Chaudhary, U.

Publications and source records attributed to Chaudhary, U..

4 recordsLinked to original sources

bioRxiv2022

Understanding the mechanism of the SARS CoV-2 coinfection with other respiratory viruses

Coinfections have a potential role in increased morbidity and mortality rates during pandemics. Our investigation is aimed at evaluating the viral coinfection prevalence in COVID-19 patients. Rapid diagnostic tests are tools with a paramount impact both on improving patient care. Particularly in the case of respiratory infections, it is of great importance to quickly confirm/exclude the involvement of pathogens. The COVID-19 pandemic has been associated with changes in respiratory virus infections worldwide, which have differed between virus types. In this paper, we systematically searched the percentage of coinfection of various respiratory viruses in COVID-19-positive samples. We included patients of all ages, in all settings. The main outcome was the proportion of patients with viral coinfection. By describing the differences in changes between viral species across different geographies over the course of the COVID-19 pandemic, we may better understand the complex factors involved in the community cocirculation of respiratory viruses.

genomics↗

bioRxiv2020

In silico multi-epitope vaccine against covid19 showing effective interaction with HLA-B*15:03

The recent outbreak of severe acute respiratory syndrome (SARS) coronavirus (CoV)-2 (SARS-CoV-2) causing coronavirus disease (covid19) has posed a great threat to human health. Previous outbreaks of SARS-CoV and Middle East respiratory Syndrome CoV (MERS-CoV) from the same CoV family had posed similar threat to human health and economic growth. To date, not even a single drug specific to any of these CoVs has been developed nor any anti-viral vaccine is available for the treatment of diseases caused by CoVs. Subunits present in spike glycoproteins of SARS-CoV and SARS-CoV-2 are involved in binding to human ACE2 Receptor which is the primary method of viral invasion. As it has been observed in the previous studies that there are very minor differences in the spike glycoproteins of SARS-CoV and SARS-CoV-2. SARS-CoV-2 has an additional furin cleavage site that makes it different from SARS-CoV (Walls et al., 2020). In this study, we have analyzed spike glycoproteins of SARS-CoV-2 and SARS-CoV phylogenetically and subjected them to selection pressure analysis. Selection pressure analysis has revealed some important sites in SARS-CoV-2 and SARS-CoV spike glycoproteins that might be involved in their pathogenicity. Further, we have developed a potential multi-epitope vaccine candidate against SARS-CoV-2 by analyzing its interactions with HLA-B*15:03 subtype. This vaccine consists of multiple T-helper (TH) cells, B-cells, and Cytotoxic T-cells (CTL) epitopes joined by linkers and an adjuvant to increase its immunogenicity. Conservation of selected epitopes in SARS, MERS, and human hosts, suggests that the designed vaccine could provide cross-protection. The vaccine is designed in silico by following a reverse vaccinology method acknowledging its antigenicity, immunogenicity, toxicity, and allergenicity. The vaccine candidate that we have designed as a result of this work shows promising result indicating its potential capability of simulating an immune response.

bioinformatics↗

bioRxiv2018

Development of algorithms for automated detection of cervical pre-cancers with a low-cost, point-of-care, Pocket Colposcope

GoalIn this work, we propose methods for (1) automatic feature extraction and classification for acetic acid and Lugols iodine cervigrams and (2) methods for combining features/diagnosis of different contrasts in cervigrams for improved performance.\n\nMethodsWe developed algorithms to pre-process pathology-labeled cervigrams and to extract simple but powerful color and textural-based features. The features were used to train a support vector machine model to classify cervigrams based on corresponding pathology for visual inspection with acetic acid, visual inspection with Lugols iodine, and a combination of the two contrasts.\n\nResultsThe proposed framework achieved a sensitivity, specificity, and accuracy of 81.3%, 78.6%, and 80.0%, respectively when used to distinguish cervical intraepithelial neoplasia (CIN+) relative to normal and benign tissues. This is superior to the average values achieved by three expert physicians on the same data set for discriminating normal/benign cases from CIN+ (77% sensitivity, 51% specificity, 63% accuracy).\n\nConclusionThe results suggest that utilizing simple color- and textural-based features from visual inspection with acetic acid and visual inspection with Lugols iodine images may provide unbiased automation of cervigrams.\n\nSignificanceThis would enable automated, expert-level diagnosis of cervical pre-cancer at the point-of-care.

bioinformatics↗

bioRxiv2017

Measurement of the mapping between intracranial EEG and fMRI recordings in the human brain

There are considerable gaps in our understanding of the relationship between human brain activity measured at different temporal and spatial scales by intracranial electroencephalography and fMRI. By comparing individual features and summary descriptions of intracranial EEG activity we determined which best predict fMRI changes in the sensorimotor cortex in two brain states: at rest and during motor performance. We also then examine the specificity of this relationship to spatial colocalisation of the two signals.\n\nWe acquired electrocorticography and fMRI simultaneously (ECoG-fMRI) in the sensorimotor cortex of 3 patients with epilepsy. During motor activity, high gamma power was the only frequency band where the electrophysiological response was colocalised with fMRI measures across all subjects. The best model of fMRI changes was its principal components, a parsimonious description of the entire ECoG spectrogram. This model performed much better than a model based on the classical frequency bands both during task and rest periods or models derived on a summary of cross spectral changes (e.g. root mean squared EEG frequency). This suggests that the region specific fMRI signal is reflected in spatially and spectrally distributed EEG activity.

neuroscience↗