The Multifaceted Role of Glutathione S-Transferases in Health and Disease.

In humans, the cytosolic glutathione S-transferase (GST) family of proteins is encoded by 16 genes presented in seven different classes. GSTs exhibit remarkable structural similarity with some overlapping functionalities. As a primary function, GSTs play a putative role in Phase II metabolism by protecting living cells against a wide variety of toxic molecules by conjugating them with the tripeptide glutathione. This conjugation reaction is extended to forming redox sensitive post-translational modifications on proteins: S-glutathionylation. Apart from these catalytic functions, specific GSTs are involved in the regulation of stress-induced signaling pathways that govern cell proliferation and apoptosis. Recently, studies on the effects of GST genetic polymorphisms on COVID-19 disease development revealed that the individuals with higher numbers of risk-associated genotypes showed higher risk of COVID-19 prevalence and severity. Furthermore, overexpression of GSTs in many tumors is frequently associated with drug resistance phenotypes. These functional properties make these proteins promising targets for therapeutics, and a number of GST inhibitors have progressed in clinical trials for the treatment of cancer and other diseases.

The benefits of index telephone consultations in patients referred on the two-week wait colorectal cancer pathway.

INTRODUCTION: The coronavirus disease 2019 (COVID-19) pandemic led to hospitals in the UK substituting face-to-face (FtF) clinics with virtual clinic (VC) appointments. We evaluated the use of virtual two-week wait (2-ww) lower gastrointestinal (LGI) clinic appointments, conducted using telephone calls at a district general hospital in England. METHODS: Patients undergoing index outpatient 2-ww LGI clinic assessment between 1 June 2019 and 31 October 2019 (FtF group) and 1 June 2020 and 31 October 2020 (VC group) were identified. Relevant data were obtained using electronic patient records. Compliance with national cancer waiting time targets was assessed. Environmental and financial impact analyses were performed. RESULTS: In total, 1,531 patients were analysed (median age=70, male=852, 55.6%). Of these, 757 (49.4%) were assessed virtually via telephone; the remainder were seen FtF (n=774, 50.6%). Ninety-two (6%, VC=44, FtF=48) patients had malignant pathology and 64 (4.2%) had colorectal cancer (CRC); of these, 46 (71.9%, VC=26, FtF=20) underwent treatment with curative intent. The median waiting times to index appointment, investigation and diagnosis were significantly lower following VC assessment (p<0.001). The cancer detection rates (p=0.749), treatments received (p=0.785) and median time to index treatment for CRC patients (p=0.156) were similar. A significantly higher proportion of patients were seen within two weeks of referral in the VC group (p<0.001). VC appointments saved patients a total of 9,288 miles, 0.7 metric tonnes of CO2 emissions and £7,482.97. Taxpayers saved £80,242.00 from VCs. No formal complaints were received from patients or staff in the VC group. CONCLUSION: Virtual 2-ww LGI clinics were effective, safe and were associated with tangible environmental and financial benefits.

Modeling and analysis of recovery time for the COVID-19 patients: a Bayesian approach

The ongoing pandemic of COVID-19 has changed every aspect of life. Most of the people who become a victim of COVID-19 experience mild to moderate symptoms, but some people may become seriously ill. This illness, sometimes, may lead to a very painful death. The Fréchet distribution is one of the flexible distribution for survival time. Hence, in this article, the recovery time of COVID-19 patients is modeled by a new Fréchet-exponential (FE) distribution, and the parameters of the distribution are estimated in the classical and Bayesian paradigms. Since the Bayes estimators using informative priors are not in the closed form, the Lindley and Tierney–Kadane approximation methods are used for their evaluation. The results obtained through simulation studies and the COVID-19 data set assess the superiority of the Bayes estimators over the classical estimators in terms of minimum risks. Mathematically and graphically, it is shown that our proposed model appropriately fits the data set. The minimum values of Akaike information criterion, Bayesian information criterion, corrected Akaike information criterion, and Hannan-Quinn information criterion proves that the FE distribution better fit than the competitors' distribution for the data set about the recovery time of COVID-19 patients. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the University of Bahrain.

Novel Coronavirus (SARS-CoV-2) in Water and Environment-A Scoping Review.

A pneumonia outbreak was primarily reported in the fall of 2019 in Wuhan, Hubei province, China, with the identity SARS-CoV-2, a novel coronavirus. It quickly grew from a local epidemic to a global pandemic and was declared a public health emergency by the WHO. A total of three prominent waves were identified across the globe, with a slight temporal variability as per the geographical locations, and has impacted several sectors which connect the world. By March 2022, the coronavirus had infected 444.12 million people and claimed 6.01 million human lives worldwide, and these numbers have not yet stabilized. Our paper enlightens readers on the seven strains of human coronaviruses, with special emphasis on the three severe deadliest outbreaks (SARS-2002, MERS-2012, and COVID-19). This work attempts a comprehensive understanding of the coronavirus and its impact on the possible sectors that link the world through the economic chain, climate conditions, SDGs, recycling of the event, and mitigations. There are many points that are raised by the authors in the possible sectors, which are emerging or are as yet unnoticed and thus have not been taken into consideration. This comprehension will leave sets of new challenges and opportunities for the researchers in various streams, especially in earth sciences. Science-integrated research may help to prevent upcoming disasters as a by-product of (existing) epidemics in the form of coronavirus.