Multidisciplinary Management of COVID-Associated Mucormycosis Syndemic in India.

Unlabelled: The study aimed to determine clinical presentation, contributing factors, medical and surgical management, and outcome of patients with coronavirus disease 2019 (COVID-19)-associated mucormycosis (CAM). A cross-sectional, single-center study was conducted on patients receiving multidisciplinary treatment for mucormycosis following the second wave of COVID-19 pandemic from April to June 2021 in India. Clinicoepidemiological factors were analyzed, 30-day overall survival and disease-specific survival were determined, and -test was used to determine the statistical significance.

Correction: Comparative analysis of various clinical specimens in detection of SARS-CoV-2 using rRT-PCR in new and follow up cases of COVID-19 infection: Quest for the best choice.

[This corrects the article DOI: 10.1371/journal.pone.

Comparative analysis of various clinical specimens in detection of SARS-CoV-2 using rRT-PCR in new and follow up cases of COVID-19 infection: Quest for the best choice.

Background: An appropriate specimen is of paramount importance in Real Time reverse transcription-polymerase chain reaction (rRT-PCR) based diagnosis of novel coronavirus (nCoV) disease (COVID-19). Thus, it's pertinent to evaluate various diversified clinical specimens' diagnostic utility in both diagnosis and follow-up of COVID-19.

Methods: A total of 924 initial specimens from 130 COVID-19 symptomatic cases before initiation of treatment and 665 follow up specimens from 15 randomly selected cases comprising of equal number of nasopharyngeal swab (NPS), oropharyngeal swab (OPS), combined NPS and OPS (Combined swab), sputum, plasma, serum and urine were evaluated by rRT-PCR.

Locomo-Net: A Low -Complex Deep Learning Framework for sEMG-Based Hand Movement Recognition for Prosthetic Control.

The enhancement in the performance of the myoelectric pattern recognition techniques based on deep learning algorithm possess computationally expensive and exhibit extensive memory behavior. Therefore, in this paper we report a deep learning framework named 'Low-Complex Movement recognition-Net' (LoCoMo-Net) built with convolution neural network (CNN) for recognition of wrist and finger flexion movements; grasping and functional movements; and force pattern from single channel surface electromyography (sEMG) recording. The network consists of a two-stage pipeline: 1) input data compression; 2) data-driven weight sharing.

Estimating the burden of enteric fever in Chhattisgarh: A single-center study on culture-positive cases from a newly built tertiary care hospital.

Background: Enteric fever is the most common cause of community acquired blood stream infections in under developed and developing countries. The enteric fever is exclusive to humans and transmitted through the faeco-oral route. Though India is an endemic zone for enteric fever, the data is very scarce from Central India.