COVID-19 severity and obesity: are MAIT cells a factor?

The proliferation of human mucosal-associated invariant T cells requires a MYC-SLC7A5-glycolysis metabolic axis

Mucosal-associated invariant T (MAIT) cells are an abundant population of innate T cells that recognize bacterial ligands and play a key role in host protection against bacterial and viral pathogens. Upon activation, MAIT cells undergo proliferative expansion and increase their production of effector molecules such as cytokines. In this study, we found that both mRNA and protein abundance of the key metabolism regulator and transcription factor MYC was increased in stimulated MAIT cells. Using quantitative mass spectrometry, we identified the activation of two MYC-controlled metabolic pathways, amino acid transport and glycolysis, both of which were necessary for MAIT cell proliferation. Last, we showed that MAIT cells isolated from people with obesity showed decreased MYC mRNA abundance upon activation, which was associated with defective MAIT cell proliferation and functional responses. Collectively, our data uncover the importance of MYC-regulated metabolism for MAIT cell proliferation and provide additional insight into the molecular basis for the functional defects of MAIT cells in obesity.

Emerging features of MAIT cells and other unconventional T cell populations in human viral disease and vaccination

MAIT cells are one representative of a group of related unconventional or pre-set T cells, and are particularly abundant in humans. While these unconventional T cell types, which also include populations of Vδ2 cells and iNKT cells, recognise quite distinct ligands, they share functional features including the ability to sense "danger" by integration of cytokine signals. Since such signals are common to many human pathologies, activation of MAIT cells in particular has been widely observed. In this review we will discuss recent trends in these data, for example the findings from patients with Covid-19 and responses to novel vaccines. Covid-19 is an example where MAIT cell activation has been correlated with disease severity by several groups, and the pathways leading to activation are being clarified, but the overall role of the cells in vivo requires further exploration. Given the potential wide functional responsiveness of these cells, which ranges from tissue repair to cytotoxicity, and likely impacts on the activity of many other cell populations, defining the role of these cells - not only as sensitive biomarkers but also as mediators - across human disease remains an important task.

Age- and Severity-Associated Humoral Immunity Response in COVID-19 Patients: A Cohort Study from Wuhan, China

Age has been found to be the single most significant factor in COVID-19 severity and outcome. However, the age-related severity factors of COVID-19 have not been definitively established. In this study, we detected SARS-CoV-2-specific antibody responses and infectious disease-related blood indicators in 2360 sera from 783 COVID-19 patients, with an age range of 1−92 years. In addition, we recorded the individual information and clinical symptoms of the patients. We found that the IgG responses for S1, N, and ORF3a and the IgM for NSP7 were associated with severe COVID-19 at different ages. The IgM responses for the S-protein peptides S1-113 (aa 673−684) and S2-97 (aa 1262−1273) were associated with severe COVID-19 in patients aged <60. Furthermore, we found that the IgM for S1-113 and NSP7 may play a protective role in patients aged <60 and >80, respectively. Regarding clinical parameters, we analyzed the diagnostic ability of five clinical parameters for severe COVID-19 in six age groups and identified three-target panel, glucose, IL-6, myoglobin, IL-6, and NT proBNP as the appropriate diagnostic markers for severe COVID-19 in patients aged <41, 41−50, 51−60, 61−70, 71−80, and >80, respectively. The age-associated severity factors revealed here will facilitate our understanding of COVID-19 immunity and diagnosis, and eventually provide meaningful information for combating the pandemic.

Polyphenols profile and enzyme inhibitory properties of Blumea lacera (Burm. f.) DC.: a potential candidate against obesity, aging, and skin disorder

Blumea lacera (Burm. f.) DC. is attracting scientific interest due to the diverse biological activities of its various parts and its use in folk medicine. The present study was undertaken to investigate the tissue-specific differential expression pattern of its total bioactive compounds. The study was further extended to whole plant phenolics profiling, in vitro enzyme inhibition activities, followed by in silico enzyme inhibition analysis to assess its potential as herbal medicine. The amount of total phenolics in different tissues was followed in decreasing order as old leaf, flower bud, root, young leaf, flower, old stem, and young stem, while that for the flavonoids was old leaf, root, young leaf, flower bud, flower, young stem, and old stem.  This study identified rosmarinic acid, quercetin, and kaempferol in this plant for the first time. The solvent extracts demonstrated strong inhibition of lipase and tyrosinase activity, along with varying degrees of inhibition of acetylcholinesterase and butyrylcholinesterase activity. Among the detected compounds, ten displayed strong in silico binding affinities with the tested enzymes. The findings provide a new insight into further investigation of the medicinal potential of this species against obesity, neurological disorders, and aberrant skin color.

Symptom-Based COVID-19 Prognosis through AI-Based IoT: A Bioinformatics Approach

Objective

Internet of Things (IoT) integrates several technologies where devices learn from the experience of each other thereby reducing human-intervened likely errors. Modern technologies like IoT and machine learning enable the conventional to patient-specific approach transition in healthcare. In conventional approach, the biggest challenge faced by healthcare professionals is to predict a disease by observing the symptoms, monitoring the remote area patient, and also attending to the patient all the time after being hospitalised. IoT provides real-time data, makes decision-making smarter, and provides far superior analytics, and all these to help improve the quality of healthcare. The main objective of the work was to create an IoT-based automated system using machine learning models for symptom-based COVID-19 prognosis.

Methods

Comparative analysis of predictive microbiology of COVID-19 from case symptoms using various machine learning classifiers like logistics regression, k-nearest neighbor, support vector machine, random forest, decision trees, Naïve Bayes, and gradient booster is reported here. For the sake of the validation and verification of the models, performance of each model based on the retrieved cloud-stored data was measured for accuracy.

Results

From the accuracy plot, it was concluded that k-NN was more accurate (97.97%) followed by decision tree (97.79), support vector machine (97.42), logistics regression (96.50), random forest (90.66), gradient boosting classifier (87.77), and Naïve Bayes (73.50) in COVID-19 prognosis.

Conclusion

The paper presents a health monitoring IoT framework having high clinical significance in real-time and remote healthcare monitoring. The findings reported here and the lessons learnt shall enable the healthcare system worldwide to counter not only this ongoing COVID but many other such global pandemics the humanity may suffer from time to come.

Influence of adipose tissue immune dysfunction on childhood obesity

In recent decades, a dramatic rise has been observed in the prevalence of obesity in childhood and adolescence, along with an increase in fetal microsomia rates. The increased risk of obesity during this key period in development negatively affects the health of the individual later in life. Immune cells residing and recruited to white adipose tissue have been highlighted as important factors contributing to the pathogenesis of childhood obesity. Immune dysfunction in the context of obesity begins early in childhood, which is different from the pathological characteristics and influencing factors of adipose immunity in adults. Here, we explore the current understanding of the roles of childhood and early life events that result in high risks for obesity by influencing adipose tissue immune dysfunction under the pathological condition of obesity. Such knowledge will help in determining the mechanisms of childhood and early life obesity in efforts to ameliorate chronic inflammation-related metabolic diseases.

COVID-19 Mortality in Europe, by Latitude and Obesity Status: A Geo-Spatial Analysis in 40 Countries

On 30 January 2020, the World Health Organization (WHO) declared the current novel coronavirus disease 2019 (COVID-19) as a public health emergency of international concern and later characterized it as a pandemic. New data show that excess body mass and vitamin D deficiency might be related to the disease severity and mortality. The aim of this study was to evaluate whether latitude, as a proxy of sunlight exposure and Vitamin D synthesis, and prevalent obesity among European populations, is related to COVID-19 spread and severity. European COVID-19 data (incidence and fatality), including information on the prevalence of obesity, social distancing, and others were obtained by the "Our World in Data" website on 17 April 2021. Adjusted analysis showed that higher COVID-19 incidence and fatality were pictured in countries being in higher latitude, both during the whole period, as well as, during the time period 1 November 2020-31 March 2021. Higher incidence and fatality of COVID-19 were observed where the prevalence of overweight/obesity was higher during the whole time period, whereas during the time period 1 November 2020-31 March 2021, only COVID-19 incidence was higher but not a fatality. The present results provide insights for targeted interventions and preventive strategies against COVID-19.

Anti-inflammatory effects of GLP-1 in patients with COVID-19

Introduction

Understanding the pathogenesis and risk factors to control the coronavirus disease 2019 (COVID-19) is necessary. Due to the importance of the inflammatory pathways in the pathogenesis of COVID-19 patients, evaluating the effects of anti-inflammatory medications is important. Glucagon-like peptide 1 receptor agonist (GLP-1 RA) is awell-known glucose-lowering agent with anti-inflammatory effects.

Areas covered

Resources were extracted from the PubMed database, using keywords such as glucagon-like peptide-1, GLP-1 RA, SARS-CoV-2, COVID-19, inflammation, in April2021. In this review, the effects of GLP-1RA in reducing inflammation and modifying risk factors of COVID-19 severe complications are discussed. However, GLP-1 is degraded by DPP-4 with aplasma half-life of about 2–5 minutes, which makes it difficult to measure GLP-1 plasma level in clinical settings.

Expert opinion

Since no definitive treatment is available for COVID-19 so far, determining promising targets to design and/or repurpose effective medications is necessary.

MAIT Cells in Respiratory Viral Infections in Mouse and Human

Mucosal associated invariant T (MAIT) cells were first identified as specific for bacterial, mycobacterial, and fungal organisms, which detect microbially-derived biosynthetic ligands presented by MHC-related protein 1 (MR1). More recently two unexpected, additional roles have been identified for these ancient and abundant cells: a TCR-depen-dent role in tissue repair and a TCR-independent role in antiviral host defence. Data from several classes of viral disease shows their capability for activation by the cytokines interleukin (IL)-12, IL-15, IL-18, and type I interferon. MAIT cells are abundant at mucosal surfaces, particularly in the lung, and it seems likely a primary reason for their striking evolutionary conservation is an important role in early innate defence against respiratory infections, including both bacteria and viruses. Here we review evidence for their TCR-independent activation, observational human data for their activation in influenza A virus, and in vivo murine evidence of their protection against severe influenza A infection, mediated at least partially via IFN-gamma. We then survey evidence emerging from other respiratory viral infections including recent evidence for an important adjuvant role in adenovirus infection, specifically chimpanzee adenoviruses used in recent coronavirus vaccines, and data for strong associations between MAIT cell responses and adverse outcomes from coronavirus-19 (COVID-19) disease. We speculate on potential translational implications of these findings, either using corticosteroids or inhibitory ligands to suppress deleterious MAIT cell responses, or the potential utility of stimulatory MR1 ligands to boost MAIT cell frequencies to enhance innate viral defences.