Use of non-invasive continuous monitoring of blood glucose and self-monitored blood glucose in children with type 1 diabetes mellitus in a resource limited setting during COVID-19 pandemic

Introduction: COVID-19 pandemic has affected everyone's life, especially children with Type 1 DM with a poor economic background. Monitoring of blood glucose and their follow up with the health care professionals were badly affected during these times. Objective(s): To assess the effectiveness of continuous blood glucose monitoring and SMBG on HbA1c level in children with Type 1 diabetes mellitus in COVID-19 pandemic. Method(s): All children diagnosed with Type 1 Diabetes mellitus with poor economic background aged between 3 and 18 years attending the diabetic OPD in a tertiary care Government hospital in south India were included in this study. Participants were randomized to study arm (CGMS+SMBG) and control arm (SMBG alone). Subjects in study group were placed on ProCGM for 14 days along with regular SMBG and control group were asked to use SMBG and data were analyzed and used to titrate the insulin dose. Result(s): There were 62 children in both the groups. In the intervention group, 30 were boys and 32 were girls. In the control group, 20 were boys and 42 were girls. In the intervention group, baseline and follow-up values of HbA1c were 11.232 +/- 1.53 and 10.14 +/- 1.99;hyperglycemia were 61.42 +/- 24.35 and 55.12 +/- 22.14;and hypoglycemia were 3.12 +/- 0.215 and 3.10 +/- 0.96 respectively. In the control group, baseline and follow-up values of HbA1c were 11.62 +/- 1.62 and 11.78 +/- 1.57;hyperglycemia were 49.92 +/- 24.64 and 53.34 +/- 17.23;and hypoglycemia were 3.09 +/- 5.01 and 3.45 +/- 7.97 respectively. There was a reduction in HbA1C levels (1.09 +/- 0.31) and in incidences of hyperglycemia and hypoglycemia in the intervention group. Conclusion(s): In resource limited settings, use of ProCGMS once in 2 or 3 months will help in understanding the factors affecting glycemic variability. It can reduce school absenteeism for hospital visits and also can be used as an educational tool for families in the management of diabetes.

Face mask detection using OpenCV

This paper proposes a Face Mask Detection Using OpenCV. This pandemic is causing an overall crisis in medical services. This infection especially spreads through beads which rise out of somebody contaminated with Covid and represents a danger to other people. The danger of transference is most elevated in gathering. one of the agreeable lifestyle choices protected from getting kindled is conveying a facial covering in open domains as proposed by world heath association on this pandemic. We will fabricate a continuous framework to distinguish regardless of whether the individual on the webcam is wearing a mask. we will prepare the facial covering finder model utilizing keras and openCv. A boundary container drawn over the face of the individual portrays weather the man or lady is conveying a mask or not. Assuming an individual's face is saved inside the data set, it distinguishes the name of the individual that isn't conveying facial coverings and an email may be shipped off that singular wariness them that they are not wearing a veils as a method for avoiding potential risk. © 2022 Universidad Tecnica de Manabi. All rights reserved.

COVID-19 Detection from X-rays using Deep Learning Model

Currently, COVID-19 has posed a significant threat to everyone, including the health professionals and administrations worldwide, from its detection to its treatment. The whole world is facing a lockdown-like situation because of the COVID-19 pandemic. The researchers are making efforts to obtain the possible solutions to control this pandemic in their respective areas. The researchers’ most common and efficient methods are the use of CT-scans and X-rays images to analyze the images of lungs for COVID-19 detection. A strategy based on artificial intelligence is used to detect COVID-19 patients utilizing the actual world datasets of X-ray CT scan chest pictures, based on a deep learning neural coexistence network. In order to detect such patients, we study chest X-ray pictures. Our results show that such an analysis is useful in determining COVID-19, as X-rays are readily obtainable at cheap prices and promptly. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Knowledge, Attitude, and Practice Related to OMICRON among Health-Care Personnel: An Original Research.

Introduction: At the time when the world was unprepared for the corona pandemic, the health-care workers faced the challenge with great effort. Recently, the OMICRON has been burdening the medical fraternity. Hence, in our study, we aimed to evaluate the "knowledge, attitude, and practices" related to OMICRON among the medical health-care staff. Materials and Methods: We piloted an online cross-sectional questionnaire study using Google Forms among 1000 medical staff working at various levels of public and private sections. The questions were formulated to test for the practices, attitude, and knowledge of the new variant OMICRON. The data collected were compared using the Chi-square test, deliberating P < 0.05 as significant. Results: We observed that majority were male participants, with significant number at the ages of 20-40 years. There was lower knowledge, although good practice and positive attitude were noted among the medical health staff. Conclusion: The medical health-care personnel possessed less knowledge regarding the new variant OMICRON, although positive practices and attitudes were noted. Hence, the governments should take necessary steps to implement the training about the new variant.

Advances in Incorporation of Nanomaterials onto Fabrics

Textile is a necessary commodity and is of paramount importance in a variety of areas. The properties of textiles can be further enhanced and the horizon of their applications can be broadened by the incorporation of nanoparticles using nanotechnology. Nanoproducts ranging from nanofibers, nanocomposite fibers, and intelligent polymeric nanocoatings are frequently incorporated in conventional textiles to provide improved performance and new functionality. Nanocoatings offer numerous specific properties like antimicrobial, wrinkle resistance, and protection against UV radiations. These properties lead to a variety of textile applications including medicinal textiles, and sportswear. In the COVID-19 pandemic situation, nanotechnology has paved the way for need-based customization such as antiviral masks, PPE kits, etc. This paper provides an overview of the nanomaterials suitable for the textile industry, enhancement in the properties of fabrics due to incorporation of nanomaterials, advantages, disadvantages, and a few applications. © The Electrochemical Society

COVID-19 Patterns Identification using Advanced Machine Learning and Deep Neural Network Implementation

Predictive analysis and Therapeutic analysis are solitaries in the field of investigation with huge dimensions, which predict a range of diseases. Recently, the effect of the Covid-19 is massive and the virus constantly is mutating. The Generative Adversarial Network (GAN) is the modern efficiency technique used by advanced neural networks to analyze data in cavernous environment. This paper reviews the issues in datasets of Covid, that enables patients to be diagnosed and predicted. The GANs are used to produce, transform, and view datasets profound that trends in medical database. The general prediction research can be highly performing with the incorporation of GANs in comparison with classical neural networks in multiple layers. This research manuscript is projected so that the prediction of mining and the exploration of information can be done more effectively. © 2022 IEEE.

Using an Administrative and Clinical Database to Determine the Early Spread of COVID-19 at the US Department of Veterans Affairs during the Beginning of the 2019-2020 Flu Season: A Retrospective Longitudinal Study.

BACKGROUND: Previous studies examining the early spread of COVID-19 have used influenza-like illnesses (ILIs) to determine the early spread of COVID-19. We used COVID-19 case definition to identify COVID-like symptoms (CLS) independently of other influenza-like illnesses (ILIs). METHODS: Using data from Emergency Department (ED) visits at VA Medical Centers in CA, TX, and FL, we compared weekly rates of CLS, ILIs, and non-influenza ILIs encounters during five consecutive flu seasons (2015-2020) and estimated the risk of developing each illness during the first 23 weeks of the 2019-2020 season compared to previous seasons. RESULTS: Patients with CLS were significantly more likely to visit the ED during the first 23 weeks of the 2019-2020 compared to prior seasons, while ED visits for influenza and non-influenza ILIs did not differ substantially. Adjusted CLS risk was significantly lower for all seasons relative to the 2019-2020 season: RR15-16 = 0.72, 0.75, 0.72; RR16-17 = 0.81, 0.77, 0.79; RR17-18 = 0.80, 0.89, 0.83; RR18-19 = 0.82, 0.96, 0.81, in CA, TX, and FL, respectively. CONCLUSIONS: The observed increase in ED visits for CLS indicates the likely spread of COVID-19 in the US earlier than previously reported. VA data could potentially help identify emerging infectious diseases and supplement existing syndromic surveillance systems.

Awareness, Views, and Expectations about COVID-19 Vaccinations: A Cross-Sectional Study of Dental Clinic Patients in India

Introduction: Several vaccines against coronavirus disease 2019 (COVID-19) have been licensed and are being administered worldwide in various countries. However, the awareness, behaviors, and expectations of COVID-19 vaccines among dental clinic patients are poorly understood. Methods: An e-survey was carried out among 1800 patients who visited dental clinics in India. The survey was carried out using a questionnaire of four parts and informed consent (i.e. sociodemographics, knowledge, attitudes, and perceptions). The investigators used Internet methods for data collection during the pandemic. Results: The mean awareness score was significantly higher among participants who reported having a university/higher level of schooling, being in the upper socioeconomic status community, living in cities, and having previously received all required vaccines. The mean attitude score was slightly higher for participants who reported being female and had a history of getting all required vaccinations. Just over half (52%) of participants felt everyone should be vaccinated. This interpretation was slightly higher among females than males (56.9% vs. 47.9%, P = 0.004). Conclusions: The results indicate that patients attending dental clinics in India have insufficient awareness but more optimistic attitudes about the COVID-19 vaccine. Immediate health promotion campaigns must be implemented before vaccine schedules in order to increase awareness.

Case study on nCOV-19 pandemic effect on indian economy and geographic impact

COVID-19 is a disease caused by severe acute respiratory syndrome corona Virus-2 (SARS-COV-2), which emerged in Wuhan city, Hubei province of China, and has now spread its roots over 220 countries and territories around the world. A few vaccines developed for this contagious disease till date have shown promising results. As a consequence of the COVID-19 pandemic, there is a tremendous impact on the economy, mortality rate, and environment of the affected countries, including India. The present study carried out shows that the lockdown had a negative impact on the Indian economy and human life. Surprisingly, the Air Quality Index (AQI) has significantly improved in most Indian cities and around the world due to a decline in pollution levels due to the closure of all industrial and construction activities, reduced vehicular traffic, etc. Also, levels of critical parameters like pH, dissolved Oxygen) and biological Oxygen Demand) have shown improvement in water quality of major Indian rivers. In this paper, an attempt is made to address the impact of lockdown and human life index with current data and presented in graphical form. © 2021 Ecological Society of India. All rights reserved.

Mortality Benefit of Convalescent Plasma in COVID-19: A Systematic Review and Meta-Analysis.

Importance/Background: With a scarcity of high-grade evidence for COVID-19 treatment, researchers and health care providers across the world have resorted to classical and historical interventions. Immunotherapy with convalescent plasma (CPT) is one such therapeutic option. Methods: A systematized search was conducted for articles published between December 2019 and 18th January 2021 focusing on convalescent plasma efficacy and safety in COVID-19. The primary outcomes were defined as mortality benefit in patients treated with convalescent plasma compared to standard therapy/placebo. The secondary outcome was pooled mortality rate and the adverse event rate in convalescent plasma-treated patients. Results: A total of 27,706 patients were included in the qualitative analysis, and a total of 3,262 (2,127 in convalescent plasma-treated patients and 1,135 in the non-convalescent plasma/control group) patients died. The quantitative synthesis in 23 studies showed that the odds of mortality in patients who received plasma therapy were significantly lower than those in patients who did not receive plasma therapy [odds ratio (OR) 0.65, 95% confidence interval (CI) 0.53-0.80, p < 0.0001, I 2 = 15%). The mortality benefit remains the same even for 14 trials/prospective studies (OR 0.59, 95% CI 0.43-0.81, p = 0.001, I 2 = 22%) as well as for nine case series/retrospective observational studies (OR 0.78, 95% CI 0.65-0.94, p = 0.01, I 2 = 0%). However, in a subgroup analysis for 10 randomized controlled trials (RCTs), there was no statistically significant reduction in mortality between the CPT group compared to the non-CPT group (OR 0.76, 95% CI 0.53-1.08, p = 0.13, I 2 = 7%). Furthermore, the sensitivity analysis of 10 RCTs, excluding the study with the highest statistical weight, displayed a lower mortality rate compared to that of non-CPT COVID-19 patients (OR 0.64, 95% CI 0.42-0.97, p = 0.04, I 2 = 0%). The observed pooled mortality rate was 12.9% (95% CI 9.7-16.9%), and the pooled adverse event rate was 6.1% (95% CI 3.2-11.6), with significant heterogeneity. Conclusions and Relevance: Our systemic review and meta-analysis suggests that CPT could be an effective therapeutic option with promising evidence on the safety and reduced mortality in concomitant treatment for COVID-19 along with antiviral/antimicrobial drugs, steroids, and other supportive care. Future exploratory studies could benefit from more standardized reporting, especially in terms of the timing of interventions and clinically relevant outcomes, like days until discharge from the hospital and improvement of clinical symptoms.

Mortality Benefit of Remdesivir in COVID-19: A Systematic Review and Meta-Analysis.

Importance/Background: During current public health emergency of COVID-19 pandemic, repurposing of existing antiviral drugs may be an efficient strategy since there is no proven effective treatment. Published literature shows Remdesivir has broad-spectrum antiviral activity against numerous RNA viruses and has been recently recognized as a promising therapy against SARS-CoV-2. Methods: A systematic search was conducted for full length manuscripts published between inception and July 19th, 2020 focussing on efficacy and safety of Remdesivir in COVID-19. The primary outcomes were defined as mortality rate and median days to recovery based on the available pooled data. The secondary outcome was adverse events rate and drug discontinuation rate. Statistical Analysis: All outcomes were performed using Comprehensive Meta-Analysis software package (Bio stat, Englewood, NJ, USA). Results: A total of 1,895 patients from 9 studies were included in this qualitative synthesis. In patients treated with Remdesivir, the mean recovery time was 15.84 days (95% CI 11.68-20, SE 2.12; I 2 = 97.24) and the pooled mortality rate was 11.3% (95% CI 7.9-16%; I 2 = 74.85). However, treatment with Remdesivir was associated with adverse effects (55.3%, 95% CI 31.5-76.9%; I 2 = 97.66) eventually warranting the discontinuation of the drug (17.8%, 95% CI 8.6-33.1%; I 2 = 95.64). The meta-analysis of three clinical trials indicated that administration of Remdesivir significantly reduces the mortality compared to the placebo (OR 0.70, 95% CI 0.58-0.84, p ≤ 0.001; I 2 = 16.6). Conclusions and Relevance: The result of contemporary meta-analysis suggests mortality benefit with Remdesivir in COVID-19 and median recovery time was over 2 weeks. The pooled mortality with Remdesivir was found to be very low, and this analysis can shed light on this potential treatment for COVID-19 patients.

Pulmonary delivery of nanostructured lipid carriers for effective repurposing of salinomycin as an antiviral agent.

Coronavirus disease outbreak caused a severe public health burden all over the world. Salinomycin (SAL) is a broad-spectrum antibiotic that had drawn attention in selective targeting of cancer and viral infections. Recent drug screen identified SAL as a potent antiviral agent against SARS-CoV-2. In this hypothesis, we discuss the potential of pulmonary delivery of SAL using nanostructured lipid carriers (NLCs) against SARS-CoV-2.

Plausible mechanisms of Niclosamide as an antiviral agent against COVID-19.

Corona virus disease 2019 (COVID-19) pandemic caused 18 440 deaths world wide as of 25 March 2020 and posing a serious threat to public health. There is a need, therefore, for effective therapeutic strategies to cure this disease. However, high attrition rates, substantial costs and slow pace are the major limitations of novel drug discovery. Drug repurposing, by employing 'old' drugs to treat 'new' diseases is an attractive approach in drug discovery. Niclosamide (NIC) is an approved anti-helminthic drug with diverse antiviral mechanisms. In this work we hypothesize, the potential antiviral mechanisms of NIC against COVID-19.