PREHOST: Host prediction of coronaviridae family using machine learning.

Coronavirus, a zoonotic virus capable of transmitting infections from animals to humans, emerged as a pandemic recently. In such circumstances, it is essential to understand the virus's origin. In this study, we present a novel machine-learning pipeline for host prediction of the family, Coronaviridae.

Ayu-Characterization of healthy aging from neuroimaging data with deep learning and rsfMRI.

Estimating brain age and establishing functional biomarkers that are prescient of cognitive declines resulting from aging and different neurological diseases are still open research problems. Functional measures such as functional connectivity are gaining interest as potentially more subtle markers of neurodegeneration. However, brain functions are also affected by "normal" brain aging.

Clinico-Genomic Analysis Reveals Mutations Associated with COVID-19 Disease Severity: Possible Modulation by RNA Structure.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) manifests a broad spectrum of clinical presentations, varying in severity from asymptomatic to mortality. As the viral infection spread, it evolved and developed into many variants of concern. Understanding the impact of mutations in the SARS-CoV-2 genome on the clinical phenotype and associated co-morbidities is important for treatment and preventionas the pandemic progresses.

Utility of a novel chromogenic medium as a screening method in the detection of carbapenemase producing .

Introduction: With the emergence of multidrug resistant Gram-negative bugs, there is an urgent need for rapid detection of these resistant organisms.

Aim: This study was performed to assess the utility of a novel chromogenic medium in the detection of carbapenemase producing from various clinical specimens.

Materials And Methods: A total of 202 isolates of , which were resistant to meropenem (10 μg) disc by standard disc diffusion method, were analyzed over a period of 6 months.