ABSTRACT
Coronavirus disease (COVID-19) has infected over 603 million confirmed cases as of September 2022, and its rapid spread has raised concerns worldwide. More than 6.4 million fatalities in confirmed patients have been reported. According to reports, the COVID-19 virus causes lung damage and rapidly mutates before the patient receives any diagnosis-specific medicine. Daily increasing COVID-19 cases and the limited number of diagnosis tool kits encourage the use of deep learning (DL) models to assist health care practitioners using chest X-ray (CXR) images. The CXR is a low radiation radiography tool available in hospitals to diagnose COVID-19 and combat this spread. We propose a Multi-Textural Multi-Class (MTMC) UNet-based Recurrent Residual Convolutional Neural Network (MTMC-UR2CNet) and MTMC-UR2CNet with attention mechanism (MTMC-AUR2CNet) for multi-class lung lobe segmentation of CXR images. The lung lobe segmentation output of MTMC-UR2CNet and MTMC-AUR2CNet are mapped individually with their input CXRs to generate the region of interest (ROI). The multi-textural features are extracted from the ROI of each proposed MTMC network. The extracted multi-textural features from ROI are fused and are trained to the Whale optimization algorithm (WOA) based DeepCNN classifier on classifying the CXR images into normal (healthy), COVID-19, viral pneumonia, and lung opacity. The experimental result shows that the MTMC-AUR2CNet has superior performance in multi-class lung lobe segmentation of CXR images with an accuracy of 99.47%, followed by MTMC-UR2CNet with an accuracy of 98.39%. Also, MTMC-AUR2CNet improves the multi-textural multi-class classification accuracy of the WOA-based DeepCNN classifier to 97.60% compared to MTMC-UR2CNet.
ABSTRACT
Introduction: Emotional stress and anxiety during COVID-19 pandemic has gained a lot of attention. The capacity to withstand from the manipulated thinking and COVID-19 related stress and anxiety depends on the resilience level of an individual. Cognitive behavioral therapy (CBT) has patronizing benefits for people affected with altered mental health. Relieving COVID-19 related anxiety using CBT has beneficial impact on health and improves quality of life of people. Objective: Aimed to relieve the anxiety of Omani population during COVID-19 pandemic using CBT. Methods: This research utilized a pre-experimental one group pre-test post-test design. A non-probability convenient sampling technique was used to select 96 Omani people who fulfilled the inclusion criteria. The pre-anxiety level was assessed using CAS (Corona virus Anxiety Scale). The participants who scored above nine in the scale were given three sessions of CBT. Post-anxiety level was assessed using CAS after three CBT sessions. Results: The study revealed that the level of anxiety reduced during post-test (6.35) after intervention when compared to pre-test (13.22). The CBT intervention was effective in reducing the anxiety in the post-test at p ≤ .000. Conclusion: CBT is effective in reducing COVID-19 related anxiety among the Omani population. Therefore, this strategy is highly recommended in people having mental health issues.
ABSTRACT
The World Health Organization (WHO) has set forth a global call for eradicating malaria, caused majorly by the protozoan parasites Plasmodium falciparum and Plasmodium vivax. The lack of diagnostic biomarkers for P. vivax, especially those that differentiate the parasite from P. falciparum, significantly hinders P. vivax elimination. Here, we show that P. vivax tryptophan-rich antigen (PvTRAg) can be a diagnostic biomarker for diagnosing P. vivax in malaria patients. We report that polyclonal antibodies against purified PvTRAg protein show interactions with purified PvTRAg and native PvTRAg using Western blots and indirect enzyme-linked immunosorbent assay (ELISA). We also developed an antibody-antigen-based qualitative assay using biolayer interferometry (BLI) to detect vivax infection using plasma samples from patients with different febrile diseases and healthy controls. The polyclonal anti-PvTRAg antibodies were used to capture free native PvTRAg from the patient plasma samples using BLI, providing a new expansion range to make the assay quick, accurate, sensitive, and high-throughput. The data presented in this report provides a proof of concept for PvTRAg, a new antigen, for developing a diagnostic assay for P. vivax identification and differentiation from the rest of the Plasmodium species and, at a later stage, translating the BLI assay into affordable, point-of-care formats to make it more accessible.
ABSTRACT
Four rounds of serological surveys were conducted, spanning two COVID waves (October 2020 and April-May 2021), in Tamil Nadu (population 72 million) state in India. Each round included representative populations in each district of the state, totaling ≥20,000 persons per round. State-level seroprevalence was 31.5% in round 1 (October-November 2020), after India’s first COVID wave. Seroprevalence fell to 22.9% in 2 (April 2021), consistent with waning of SARS-Cov-2 antibodies from natural infection. Seroprevalence rose to 67.1% by round 3 (June-July 2021), reflecting infections from the Delta-variant induced second COVID wave. Seroprevalence rose to 93.1% by round 4 (December 2021-January 2022), reflecting higher vaccination rates. Antibodies also appear to wane after vaccination. Seroprevalence in urban areas was higher than in rural areas, but the gap shrunk over time (35.7 v. 25.7% in round 1, 89.8% v. 91.4% in round 4) as the epidemic spread even in low-density rural areas. The study documents substantial waning of SARS-CoV-2 antibodies at the population level and demonstrates how to calculate the extent to which infection and vaccination separately contribute to seroprevalence estimates.
ABSTRACT
With the increasing number of critically ill patients being admitted to intensive care units (ICUs), newer techniques and treatment modalities continue to evolve for their adequate management. Thus, it has become imperative to understand existing tools and resources, and utilise or repurpose them to achieve better results that can decrease morbidity and mortality. In this writeup, we chose five areas of interest, including analgosedation, role of colloids, recent advancements in the management of respiratory failure, the role of extracorporeal membrane oxygenation, and newer antimicrobials. The role of analgosedation in the critically ill has gained importance with focus on post-ICU syndromes, and albumin has re-entered the fray as a possible repairer of the injured glycocalyx. The coronavirus disease 2019 (COVID-19) pandemic forced us to relook at various ventilator strategies and mechanical support for the failing circulation has now become more common with clear end-points. Rising microbial antibiotic resistance has opened up the research on newer antibiotics.
ABSTRACT
COVID-19 is a drastic air-way tract infection that set off a global pandemic recently. Most infected people with mild and moderate symptoms have recovered with naturally acquired immunity. In the interim, the defensive mechanism of vaccines helps to suppress the viral complications of the pathogenic spread. Besides effective vaccination, vaccine breakthrough infections occurred rapidly due to noxious exposure to contagions. This paper proposes a new epidemiological control model in terms of Atangana Baleanu Caputo (ABC) type fractional order differ integrals for the reported cases of COVID-19 outburst. The qualitative theoretical and numerical analysis of the aforesaid mathematical model in terms of three compartments namely susceptible, vaccinated, and infected population are exhibited through non-linear functional analysis. The hysteresis kernel involved in AB integral inherits the long-term memory of the dynamical trajectory of the epidemics. Hyer-Ulam's stability of the system is studied by the dichotomy operator. The most effective approximate solution is derived by numerical interpolation to our proposed model. An extensive analysis of the vigorous vaccination and the proportion of vaccinated individuals are explored through graphical simulations. The efficacious enforcement of this vaccination control mechanism will mitigate the contagious spread and severity.