Scrutinizing different predictive modeling validation methodologies and data-partitioning strategies: new insights using groundwater modeling case study.

Groundwater salinity is a critical factor affecting water quality and ecosystem health, with implications for various sectors including agriculture, industry, and public health. Hence, the reliability and accuracy of groundwater salinity predictive models are paramount for effective decision-making in managing groundwater resources. This pioneering study presents the validation of a predictive model aimed at forecasting groundwater salinity levels using three different validation methods and various data partitioning strategies. This study tests three different data validation methodologies with different data-partitioning strategies while developing a group method of data handling (GMDH)-based model for predicting groundwater salinity concentrations in a coastal aquifer system. The three different methods are the hold-out strategy (last and random selection), k-fold cross-validation, and the leave-one-out method. In addition, various combinations of data-partitioning strategies are also used while using these three validation methodologies. The prediction model's validation results are assessed using various statistical indices such as root mean square error (RMSE), means squared error (MSE), and coefficient of determination (R2). The results indicate that for monitoring wells 1, 2, and 3, the hold-out (random) with 40% data partitioning strategy gave the most accurate predictive model in terms of RMSE statistical indices. Also, the results suggested that the GMDH-based models behave differently with different validation methodologies and data-partitioning strategies giving better salinity predictive capabilities. In general, the results justify that various model validation methodologies and data-partitioning strategies yield different results due to their inherent differences in how they partition the data, assess model performance, and handle sources of bias and variance. Therefore, it is important to use them in conjunction to obtain a comprehensive understanding of the groundwater salinity prediction model's behavior and performance.

Investigation of bio-active Amaryllidaceae alkaloidal small molecules as putative SARS-CoV-2 main protease and host TMPRSS2 inhibitors: interpretation by in-silico simulation study.

The novel coronavirus disease 2019 (Covid-19) outburst is still threatening global health. This highly contagious viral disease is caused by the infection of SARS-CoV-2 virus. Covid-19 and post-Covid-19 complications induce noteworthy mortality. Potential chemical hits and leads against SARS-CoV-2 for combating Covid-19 are urgently required. In the present study, a virtual-screening protocol was executed on potential Amaryllidaceae alkaloids from a pool of natural compound library against SARS-CoV-2 main protease (Mpro) and transmembrane serine protease (TMPRSS2). For the collected 1016 alkaloids from the curated library, initially, molecular docking using AutoDock Vina (ADV), and thereafter 100 ns molecular-dynamic (MD) simulation has been executed for the best top-ranked binding affinity compounds for both the viral and host proteins. Comprehensive intermolecular-binding interactions profile of Amaryllidaceae alkaloids suggested that phyto-compounds Galantamine, Lycorenine, and Neronine as potent modulators of SARS-CoV-2 Mpro and host TMPRSS2 protein. All atomistic long range 100 ns MD simulation studies of each top ranked complex in triplicates also illustrated strong binding affinity of three compounds towards Mpro and TMPRSS2. Identified compounds might be recommended as prospective anti-viral agents for future drug development selectively targeting the SARS-CoV-2 Mpro or blocking host TMPRSS2 receptor, subjected to pre-clinical and clinical assessment for a better understanding of in-vitro molecular interaction and in-vivo validation.Communicated by Ramaswamy H. Sarma.

Selective inhibition of peptidyl-arginine deiminase (PAD): can it control multiple inflammatory disorders as a promising therapeutic strategy?

Peptidyl arginine deiminases (PADs) are a family of post-translational modification enzymes that irreversibly citrullinate (deiminate) arginine residues of protein and convert them to a non-classical amino acid citrulline in the presence of calcium ions. It has five isotypes, such as PAD1, PAD2, PAD3, PAD4, and PAD6, found in mammalian species. It has been suggested that increased PAD expression in various tissues contributes to the development of multiple inflammatory diseases, including rheumatoid arthritis (RA), cancer, diabetes, and neurological disorders. Elevation of PAD enzyme expression depends on several factors like rising intracellular Ca2+ levels, oxidative stress, and proinflammatory cytokines. PAD inhibitors originating from natural or synthetic sources can be used as a novel therapeutic approach concerning inflammatory disorders. Here, we review the pathological role of PAD in several inflammatory disorders, factors that trigger PAD expression, epigenetic role and finally, decipher the therapeutic approach of PAD inhibitors in multiple inflammatory disorders.

Biosensors based detection of novel biomarkers associated with COVID-19: Current progress and future promise.

The pandemic situation of COVID-19 has caused global alarm in health care, devastating loss of lives, strangled economy, and paralysis of normal livelihood. The high inter-individual transmission rate created havoc in the global community. Although tremendous efforts are pitching in from across the globe to understand this disease, the clinical features seemed to have a wide range including fever, cough, and fatigue are the prominent features. Congestion, rhinorrhea, sore throat, and diarrhea are other less common features observed. The challenge of this disease lies in the difficulty in maneuvering the clinical course causing severe complications. One of the major causative factors for multi-organ failure in patients with severe COVID-19 complications is systemic vasculitis and cytokine-mediated coagulation disorders. Hence, effective markers trailing the disease severity and disease prognosis are urgently required for prompt medical treatment. In this review article, we have emphasized currently identified inflammatory, hematological, immunological, and biochemical biomarkers of COVID-19. We also discussed currently available biosensors for the detection of COVID-19-associated biomarkers & risk factors and the detection methods as well as their performances. These could be effective tools for rapid and more promising diagnoses in the current pandemic situation. Effective biomarkers and their rapid, scalable, & sensitive detection might be beneficial for the prevention of serious complications and the clinical management of the disease.

Evidence of prenatal toxicity of herbal based indigenous formulations for sex selection in rat models.

Indigenous preparations(IPs) for a male child is reported from some parts of India. The present study aims to explore the effects of IPs for sex selection or sex selection drugs (SSDs) on pregnancy outcomes in rat models. SSDs contain Bryonia laciniosa, Quercus infectoria and Putranjiva roxburghii along with other ingredients. METHODS: An experimental design with successfully mated female rats were randomized into control and treatment groups. Phase 1 had 2 interventional arms while phase 2 had 3 interventional arms (12 rats/arm) besides control arm. In phase-1, pregnant females were dosed two SSDs(1000 mg/kg) on gestation days 1-5 whereas, in phase-2, on gestation days 6-19 to correlate the effect of the SSDs (500/1000/1500 mg/kg) consumption during different stages of pregnancy. Pregnant females were observed for clinical signs following treatment. The rats were sacrificed one day before expected day of delivery for evaluation. Pregnancy rate, gestation index, number of corpora lutea, and litter size were assessed. Foetuses were examined for sex, skeletal and soft tissue alterations. DISCUSSION AND CONCLUSION: In phase 1, no appreciable findings were there with SSD exposure. In phase 2, intrauterine growth and survival of foetuses were affected when SSDs were administered during organogenesis period. Decreased number of live foetuses and increased incidence of early and late resorption, reduced fetal growth with significant alteration in skeleton and viscera were found in treatment groups in a dose-dependent manner. This correlates well with findings from observational studies in pregnant women. However, such treatment at any dose did not effect sex differentiation.

Chemoimmunotherapeutic approach to prolonged survival time in combination with immunization and glutamic Acid derivatives with antitumor activity in tumor-bearing mice.

Cancer is one of the major causes of death. For cancer, the general conventional treatment and standard of care for clinical oncology remains surgery followed by radiation and/or systemic chemotherapy as deemed appropriate based on the clinical findings. Chemoimmunotherapy is an approach to treat cancer where chemotherapy is given along with immunotherapy. Chemoimmunotherapy may be useful to enhance survival time in cancer by improve immunity of the patients. This approach may enhance the therapeutic efficacy. A comparative study was done to assess the therapeutic efficacy of the whole cell vaccine and the tumor extract with or without combination chemotherapy with the synthesized glutamine and glutamic acid derivatives and analogs as well as the standard drug etoposide against Ehrlich Ascites Carcinoma (EAC) cells in Swiss Albino mice. The study showed promising results with the compound 5-N-n-hexyl-2-(4-iso-butylbenzenesulphonyl)glutamine. The compound when combined with the whole cell vaccine as well as the tumor extract increases the survival time and the therapeutic efficacy which is comparable with that of standard drug etoposide.