Novel antioxidant protein target therapy to counter the prevalence and severity of SARS-CoV-2

BackgroundThis review analyzed the magnitude of the COVID-19 pandemic globally and in India and the measures to counter its effect using natural and innate immune booster molecules. The study focuses on two phases: the first focuses on the magnitude, and the second on the effect of antioxidants (natural compounds) on SARS-CoV-2.MethodsThe magnitude of the prevalence, mortality, and comorbidities was acquired from the World Health Organization (WHO) report, media, a report from the Ministry of Health and Family Welfare (MoHFW), newspapers, and the National Centre of Disease Control (NCDC). Research articles from PubMed as well as other sites/journals and databases were accessed to gather literature on the effect of antioxidants.ResultsIn the elderly and any chronic diseases, the declined level of antioxidant molecules enhanced the reactive oxygen species, which in turn deprived the immune system.ConclusionInnate antioxidant proteins like sirtuin and sestrin play a vital role in enhancing immunity. Herbal products and holistic approaches can also be alternative solutions for everyday life to boost the immune system by improving the redox balance in COVID-19 attack. This review analyzed the counteractive effect of alternative therapy to boost the immune system against the magnitude of the COVID-19 pandemic

A study of abnormal Calcium Phosphorus Product in Chronic Kidney Disease in Kerala population and its correlation with Acute Coronary Syndrome

Objective: To determine the cutoff value for Calcium Phosphorus Product (CPP) in Chronic Kidney Disease (CKD) patients, above which there is a high risk of Acute Coronary Syndrome(ACS). Methods: Ninety five CKD patients on maintenance dialysis [2 to 3 sessions weekly] were followed up at AIMS, Kochi for a period of 2 years and any new onset acute coronary event during the following period were diagnosed and noted. All the relevant biochemical tests were performed including ECG and 2D Echocardiography. Standard statistical tests with multivariate regression analysis and ROC were performed to arrive at conclusion. Results: Out of 95 patients, 28 patients (29.5%) had ACS, with majority number of patients above 50 years of age [27(96.4%)]. Out of 95 patients 25(26.3%) were females and 70(73.7%) males. Out of 25 female patients 6(24%) had ACS. Out of 70 male patients, 22(31.4%) had ACS. The mean CPP was calculated for each patient and grouped into 4 groups [70]. Patients with CPP>70mg2/dl2 had highest incidence of ACS with 92.3% patients involved [Pvalue55mg2/dl2 had odds ratio of 18.214 after multivariate regression analysis. ROC curve for CPP showed a cutoff point of 51.4mg2/dl2 with sensitivity of 78.6% and specificity of 73.1% for predicting ACS. Conclusion: This study shows that the cutoff value for CPP above which ACS is common is 51.49mg2/dl2 for the local population, which is quite less than the recommended KDOQI guidelines. Therefore a stricter control among the local population is recommended

IVC filters - Indications for placement and retrieval trends– experience from a tertiary referral centre in India type of submission- full paper

Objectives: There is wide variation in the practice of IVC filter placement and retrievals. We conducted a retrospective study to identify the trends in placement and retrievals of IVC filters in a tertiary referral centre in India. Methods: The data of patients obtained from our hospital records, in whom IVC filter was placed between 2010 and 2018, were analysed for demographics, indications for placement of IVC filter, underlying comorbidities, characteristics of the filters as well as the retrieval rates. Results: IVC filters were placed in 50 patients, and data was retrieved for 31 patients (mean - 51.24 years, 67.74% males). According to ACCP/AHA guidelines, 24 (77.42%) had an absolute indication for IVC filter. All 31 IVC filters were temporary, 23 (74.19%) of which were placed via femoral access. 29(93.55%) patients had infrarenal IVC filter placement. The average tilt at deployment was 3.71°, whereas it was 5.3° at retrieval. There were no periprocedural complications or filter migrations during placement or retrieval. Retrieval was attempted in 11 (35.48%) patients and was successful in 10. The mean indwelling time in this group was 158.55 days (range 55–366 days). Conclusion: Our study reveals low IVC filter implantation rates which are predominantly for absolute rather than relative indications. Though in sync with the worldwide trend, the poor retrieval rates reflect the urgent need for better patient and physician awareness. Periodic follow up is imperative to improve the IVC filter retrieval rate and to prevent complication rates

Early postoperative CRP predicts major complications following cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC)

Cytoreductive surgery (CRS) and heated intraperitoneal chemotherapy (HIPEC) is associated with significant postoperative complications. Early detection of at-risk patients may lead to improved outcomes. The role of C-reactive protein (CRP) in predicting postoperative complications has only been recently investigated

[53] Modified Genetic Algorithm with Deep Learning for Fraud Transactions of Ethereum Smart Contract.

 Recently, the Ethereum smart contracts have seen a surge in interest  from the scientific community and new commercial uses. However, as  online trade expands, other fraudulent practices—including phishing,  bribery, and money laundering—emerge as significant challenges to trade  security. This study is useful for reliably detecting fraudulent  transactions; this work developed a deep learning model using a unique  metaheuristic optimization strategy. The new optimization method to  overcome the challenges, Optimized Genetic Algorithm-Cuckoo Search  (GA-CS), is combined with deep learning. In this research, a Genetic  Algorithm (GA) is used in the phase of exploration in the Cuckoo Search  (CS) technique to address a deficiency in CS. A comprehensive experiment  was conducted to appraise the efficiency and performance of the  suggested strategies compared with those of various popular techniques,  such as k-nearest neighbors (KNN), logistic regression (LR), multi-layer  perceptron (MLP), XGBoost, light gradient boosting machine (LGBM),  random forest (RF), and support vector classification (SVC), in terms of  restricted features and we compared their performance and efficiency  metrics to the suggested approach in detecting fraudulent behavior on  Ethereum. The suggested technique and SVC models outperform the rest of  the models, with the highest accuracy, while deep learning with the  proposed optimization strategy outperforms the RF model, with slightly  higher performance of 99.71% versus 98.33%. </p

Metadata record for: HIT-COVID, a global database tracking public health interventions to COVID-19

This dataset contains key characteristics about the data described in the Data Descriptor HIT-COVID, a global database tracking public health interventions to COVID-19. Contents: 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON forma