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. Results Demographic analysis showed males (86) twice more affected by COVID-19 than females (44) (p = 0.00001). Combined swabs showed a positivity rate of 100% followed by NPS (91.5%), OPS (72.3%), sputum (63%), while nCoV was found undetected in urine, plasma and serum specimens. The lowest cycle threshold (Ct) values of targeted genes E, ORF1b and RdRP are 10.56, 10.14 and 12.26 respectively and their lowest average Ct values were found in combined swab which indicates high viral load in combined swab among all other specimen types. Analysis of 665 follow-up multi-varied specimens also showed combined swab as the last specimen among all specimen types to become negative, after an average 6.6 (range 4–10) days post-treatment, having lowest (15.48) and average (29.96) Ct values of ORF1b respectively indicating posterior nasopharyngeal tract as primary nCoV afflicted site with high viral load. Conclusion The combined swab may be recommended as a more appropriate specimen for both diagnosis and monitoring of COVID-19 treatment by rRT-PCR for assessing virus clearance to help physicians in taking evidence-based decision before discharging patients. Implementing combined swabs globally will definitely help in management and control of the pandemic, as it is the need of the hour.

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 t-test was used to determine the statistical significance. A total of 215 patients were included in the study, the cases were stratified into sino-nasal 95 (44.2%), sino-naso-orbital 32 (14.9%), sino-naso-palatal 55 (25.6%), sino-naso-cerebral 12 (5.6%), sino-naso-orbito-cerebral 16 (7.4%), and sino-naso-orbito-palato-cerebral 5 (2.3%) based on their presentation. A multidisciplinary team treated patients by surgical wound debridement and medical therapy with broad-spectrum antibiotics and amphotericin B. Across all disease stages, cumulative 30-day disease-specific survival is 94% (p < 0.001, intergroup comparison, Breslow (generalized Wilcoxon) CI 95%) and overall 30-day survival is 87.9% (p < 0.001, intergroup comparison, Breslow (generalized Wilcoxon) CI 95%) (censored). Early identification, triaging, and proper multidisciplinary team management with systemic antifungals, surgical debridement, and control of comorbidities lead to desirable outcomes in COVID-associated mucormycosis. The patients with intracranial involvement have a higher chance of mortality compared to the other group.

Background: 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. Methods: The proposed framework was validated on two different datasets-our own dataset (DS1) and publicly available NinaPro dataset (DS2) for 16 movements and 50 movements respectively. Further, we have prototyped the proposed LoCoMo-Net on Virtex-7 Xilinx field-programmable gate array (FPGA) platform and validated for 15 movements from DS1 to demonstrate its feasibility for real-time execution. Results: The effectiveness of the proposed LoCoMo-Net was verified by a comparative analysis against the benchmarked models using the same datasets wherein our proposed model outperformed Twin-Support Vector Machine (SVM) and existing CNN based model by an average classification accuracy of 8.5 % and 16.0 % respectively. In addition, hardware complexity analysis is done to reveal the advantages of the two-stage pipeline where approximately 27 %, 49 %, 50 %, 23 %, and 43 % savings achieved in lookup tables (LUT's), registers, memory, power consumption and computational time respectively. Conclusion: The clinical significance of such sEMG based accurate and lowcomplex movement recognition system can be favorable for the potential improvement in quality of life of an amputated persons.

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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. The present study was undertaken to determine the prevalence of enteric fever in this region and to know the antimicrobial susceptibility pattern of the isolated typhoidal Salmonellae. MATERIAL AND METHOD: We conducted a retrospective analysis of blood culture positive cases of enteric fever over a period of two years (December 2015 to December 2017). All blood cultures submitted for suspected enteric fever and associated symptoms were included in the study. Relevant demographic, clinical and laboratory data were analyzed. RESULT: A total of 51 cases (3.56%) were of typhoidal Salmonella from a total of 1430 blood culture submission. Salmonella Typhi were 70.5% while Salmonella Paratyphi A were 29.5% of the total isolated Salmonellae. The most vulnerable age group was 10-19years (41.2%). The mean minimum inhibitory concentration of ciprofloxacin for Salmonella Typhi and Salmonella Paratyphi A are 1.20 and 1.97 μg/ml respectively. All the isolates were susceptible to ceftriaxone. Highest isolation was in the July – September quarter (35.3%). CONCLUSION: There is a high prevalence of the disease which needs urgent focus on safe water, sanitation services and also to establish guidelines for empiric therapy for enteric fever.