The COVID-19 pandemic has caused havoc all around the world. The causative agent of COVID-19 is the novel form of the coronavirus (CoV) named SARS-CoV-2, which results in immune system disruption, increased inflammation, and acute respiratory distress syndrome (ARDS). T cells have been important components of the immune system, which decide the fate of the COVID-19 disease. Recent studies have reported an important subset of T cells known as regulatory T cells (Tregs), which possess immunosuppressive and immunoregulatory properties and play a crucial role in the prognosis of COVID-19 disease. Recent studies have shown that COVID-19 patients have considerably fewer Tregs than the general population. Such a decrement may have an impact on COVID-19 patients in a number of ways, including diminishing the effect of inflammatory inhibition, creating an inequality in the Treg/Th17 percentage, and raising the chance of respiratory failure. Having fewer Tregs may enhance the likelihood of long COVID development in addition to contributing to the disease’s poor prognosis. Additionally, tissue-resident Tregs provide tissue repair in addition to immunosuppressive and immunoregulatory activities, which may aid in the recovery of COVID-19 patients. The severity of the illness is also linked to abnormalities in the Tregs’ phenotype, such as reduced expression of FoxP3 and other immunosuppressive cytokines, including IL-10 and TGF-beta. Hence, in this review, we summarize the immunosuppressive mechanisms and their possible roles in the prognosis of COVID-19 disease. Furthermore, the perturbations in Tregs have been associated with disease severity. The roles of Tregs are also explained in the long COVID. This review also discusses the potential therapeutic roles of Tregs in the management of patients with COVID-19.

Adenium obesum commonly known as “desert rose” belongs to the family Apopcynaceae and has previously been reported for its anti-influenza, antimicrobial, and cytotoxic efficacies and well-known for their ethno-medicinal applications. In the present study, ethanolic extracts of A. obesum (AOE) were analyzed by gas chromatography-mass spectrometry (GC–MS) to identify the important phytochemical compounds. The GC–MS analysis of AOE detected the presence of 26 phytochemical compounds. This plant is traditionally used for the treatment of various diseases. In this report, the antioxidant, anti-inflammatory, and anticancer activities of ethanolic leaf extract from A. obesum (AOE) were studied. The antioxidant potential of ethanolic extract of AOE was examined by different antioxidant assays, such as antioxidant capacity by the DPPH, ABTS, superoxide, hydroxyl radical scavenging, and lipid peroxidation inhibition assays. The antioxidant activities of various reaction mixtures of AOE were compared with a reference or standard antioxidant (ascorbic acid). In addition, we also evaluated the anticancer activity of AOE, and it was observed that AOE was found to be cytotoxic against A549 lung cancer cells. It was found that AOE inhibited the viability of A549 lung cancer cells by inducing nuclear condensation and fragmentation. Furthermore, ethanolic AOE demonstrated the anti-inflammatory potential of AOE in murine alveolar macrophages (J774A.1) as an in vitro model system. AOE showed its potential in reducing the levels of inflammatory mediators including the proinflammatory cytokines and TNF-α. The results obtained in the present investigation established the antioxidant, anticancer, and anti-inflammatory potency of AOE, which may account for subsequent studies in the formulation of herbal-based medicine.

Poly [adenosine diphosphate (ADP)-ribose] polymerases (PARPs) are members of a family of 17 enzymes that performs several fundamental cellular processes. Aberrant activity (mutation) in PARP12 has been linked to various diseases including inflammation, cardiovascular disease, and cancer. Herein, a large library of compounds (ZINC-FDA database) has been screened virtually to identify potential PARP12 inhibitor(s). The best compounds were selected on the basis of binding affinity scores and poses. Molecular dynamics (MD) simulation and binding free energy calculation (MMGBSA) were carried out to delineate the stability and dynamics of the resulting complexes. To this end, root means deviations, relative fluctuation, atomic gyration, compactness, covariance, residue-residue contact map, and free energy landscapes were studied. These studies have revealed that compounds ZINC03830332, ZINC03830554, and ZINC03831186 are promising agents against mutated PARP12.

Electronics devices growth in the last decade of the twentieth century ushered in a revolution inside the electronics segment. Continuous micro-sizes and operation cause these devices to heat up, resulting in a reduction in their performance or damage to their parts. Because heat can decrease device performance and life span while also wasting energy, offering an incorporated and effective cooling system has become a significant part of the design of device equipment. One of the key challenges of modern generation technology is the cooling of electronic devices. Nanofluids have attracted attention in a broad range of engineering implementations due to their great properties, which may be used to effectively cool devices while also improving energy efficiency. In view of the above defects, this numerical research object to examine the chip surface temperature, heat transfer rate, thermal resistance, Darcy friction factor and reliability of microelectronic chips in minichannel heat sinks is scrutinized by utilizing a $${\text{TiO}}_{2}$$ TiO 2 /water nanofluid as a coolant and comparing the nanoliquid outcomes with the outcomes of water. $${\text{TiO}}_{2}$$ TiO 2 /Water nanofluids at 1%, 2% and 3% volume concentrations are employed for this scrutinization. Here, a commercial CFD ANSYS (R19.2) FLUENT software package is used to analyze the electronic chip performance. The CFD ANSYS (R19.2) FLUENT software package is used for modeling, meshing and simulation of the current study.

The thermal processes with inclusion of nanomaterials provide a wide range of applications pertaining to heat exchangers and cooling of compact heat density devices. The current research investigates the three-dimension flow of hybrid nanofluid comprising TC4(Ti-6A-14V) and Nichrome 80% Ni and 20% Cr nanoparticles mixed within engine oil as the base fluid for the enhancement of heat and mass transfer rate. The effects of homogeneous-heterogeneous processes and thermal radiation are incorporated. The heat transfer occurs due to a rotating inclined stretched sheet is discussed against prominent factors such as thermal radiation, inclined angle parameter, rotation parameter, and heat source/sink. The leading mathematical formulation consists of a set of PDEs, which are then transmuted into ordinary differential equations using suitable similarity transformation. The numerical solutions are obtained by using MATLAB's built-in function bvp4c. The results for velocity profile, temperature profile and concentration distribution are evaluated for suitable ranges of the controlling parameters. The graphical result shows that when the angle of inclination, magnetic parameter, and the volumetric concentration of hybrid nanomaterials increase the axial flow profile of the hybrid nanofluid is reduced. However, the rotation parameter reveals the opposite response. The temperature is intensified with an increment of heat source/sink, shape factors, and magnetic field parameter. For enhanced nanoparticle volumetric concentration, the temperature of the fluid rises up. The graphical validation is also illustrated using streamlines and statistical plots for hybrid nanofluid.

SARS-CoV-2 is a recently discovered virus that poses an urgent threat to global health. The disease caused by this virus is termed COVID-19. Death tolls in different countries remain to rise, leading to continuous social distancing and lockdowns. Patients of different ages are susceptible to severe disease, in particular those who have been admitted to an ICU. Machine learning (ML) predictive models based on medical data patterns are an emerging topic in areas such as the prediction of liver diseases. Prediction models that combine several variables or features to estimate the risk of people being infected or experiencing a poor outcome from infection could assist medical staff in the treatment of patients, especially those that develop organ failure such as that of the liver. In this paper, we propose a model called the detecting model for liver damage (DMLD) that predicts the risk of liver damage in COVID-19 ICU patients. The DMLD model applies machine learning algorithms in order to assess the risk of liver failure based on patient data. To assess the DMLD model, collected data were preprocessed and used as input for several classifiers. SVM, decision tree (DT), Naïve Bayes (NB), KNN, and ANN classifiers were tested for performance. SVM and DT performed the best in terms of predicting illness severity based on laboratory testing.

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Background: Toxoplasma gondii (T. gondii) is one of the most prevalent infectious parasites in humans worldwide. The diagnosis of toxoplasmosis is based on serological screening through the detection of anti-toxoplasmosis antibodies: IgG, which indicates previous exposure and the presence of active immunity, and IgM, which indicates a recent infection. We aimed to determine the prevalence of anti-toxoplasma antibodies in pregnant women at King Abdulaziz University Hospital (KAUH), Jeddah, Saudi Arabia, and explore the cost-effectiveness of antitoxoplasma screening. Method: This was an analytic retrospective study of women who underwent serology testing for anti-toxoplasmosis antibodies at KAUH in 2013-2018. Data were collected from hospital documentation and IBM Statistical Package for Social Sciences (SPSS Inc., Chicago, IL) version 22 was used for analysis. Result: Of the 9,098 pregnant women seen at KAUH, 2,754 had undergone the test, and 38 had a positive result, i.e., a seroprevalence rate of 1.4%. Most women were Saudis (57.9%), and almost all were multiparous. Of those with a positive result, 36.8% were in the third trimester. Most births were by spontaneous vaginal delivery (65.8%). Twelve (31.6%) of the women with toxoplasmosis experienced obstetric complications. The estimated total cost of screening the pregnancies was US $919,646.00 Conclusion: The prevalence of pregnant women with a positive anti-toxoplasmosis test result was low, and we believe there is no net benefit from screening all pregnant women for toxoplasmosis. Primary prevention should be through health education, and we recommend screening only women with high-risk pregnancies.