Antimicrobial Therapy and COVID-19 - the 'Great Confrontation'

The problem of antimicrobial therapy (AMT) for the new coronavirus infection has been the cornerstone of practical healthcare since its emergence to the present day. The article summarizes a number of problems concerning the unjustified prescription of AMT based on the data of foreign and domestic studies, as well as actual clinical practice. On the one hand, viral damage to the lung tissue during COVID-19 is difficult to distinguish from community-acquired or secondary bacterial pneumonia;it prompts clinicians to prevent possible bacterial complications in the lungs by prescribing broad-spectrum antibiotics starting from the first day. On the other hand, the presence of clear clinical and biological markers of bacterial pneumonia;and COVID-19 makes it possible not to use antibiotics in routine practice, at least in the early stages of treatment. The introduction of procalcitonin as a biomarker of bacterial infection in COVID-19 into everyday clinical practice has a reasonable, methodical, and scientific approach to prescribing antibiotics.

Ambient fine particulate matter exposures and oxidative protein damage in early pregnant women

The association between oxidative protein damage in early pregnant women and ambient fine particulate matter (PM2.5) is unknown. We estimated the effect of PM2.5 exposures within seven days before blood collection on serum 3-nitrotyrosine (3-NT) and advanced oxidation protein products (AOPP) in 100 women with normal early pregnancy (NEP) and 100 women with clinically recognized early pregnancy loss (CREPL). Temporally-adjusted land use regression model was applied for estimation of maternal daily PM2.5 exposure. Daily nitrogen dioxide (NO2) exposure of each participant was estimated using city-level concentrations of NO2. Single-day lag effect of PM2.5 was analyzed using multivariable linear regression model. Net cumulative effect and distributed lag effect of PM2.5 and NO2 within seven days were analyzed using distributed lag non-linear model. In all 200 subjects, the serum 3-NT were significantly increased with the single-day lag effects (4.72%–8.04% increased at lag 0–2), distributed lag effects (2.32%–3.49% increased at lag 0–2), and cumulative effect within seven days (16.91% increased). The single-day lag effects (7.41%–10.48% increased at lag 0–1), distributed lag effects (3.42%–5.52% increased at lag 0–2), and cumulative effect within seven days (24.51% increased) of PM2.5 significantly increased serum 3-NT in CREPL group but not in NEP group. The distributed lag effects (2.62%–4.54% increased at lag 0–2) and cumulative effect within seven days (20.25% increased) of PM2.5 significantly increased serum AOPP in early pregnant women before the coronavirus disease (COVID-19) pandemic but not after that, similarly to the effects of NO2 exposures. In conclusion, PM2.5 exposures were associated with oxidative stress to protein in pregnant women in the first trimester, especially in CREPL women. Analysis of NO2 exposures suggested that combustion PM2.5 was the crucial PM2.5 component. Wearing masks may be potentially preventive in PM2.5 exposure and its related oxidative protein damage. © 2022 Elsevier Ltd

URINARY BIOMARKER ANALYSES ON JAPANESE, MEDITERRANEAN AND EURO-WESTERN POPULATIONS: WHICH IS BETTER FOR POSTPANDEMIC LONGEVITY?

Objective: Since nutrition could extend lifespan even in stroke-prone rats developing stroke genetically, our WHO-Collaborating Center for Primary Prevention of Cardio-vascular Diseases (CVD) started world-wide hearth examination to investigate nutrition good for healthy longevity by collecting 24-hour urine (24U) samples. Design: Urinary biomarkers of nutritions, sodium for salt, potassium (K) for vegetables and fruits, isoflavones(Is) for soy, taurine(Ta) for fish and magnesium (Mg) for beans and nuts were analyzed in 24U among 4211 participants (49.7% females(F)), aged 48-56 years in 50 populations from 22 countries according to WHO-CARDIAC(Cardiovascular Diseases and Alimentary Compression) Study Protocol, and studied comparatively in 6 Japanese(J), 6 Mediterranean(M) populations from Greece, Italy(2), Spain(2), Portugal and 6 Euro-Western(EW) populations from Sweden, Ireland, Scotland, Canada, Australia, New Zealand. Results with Discussion: The quintile analyses of Ta and Mg/creatine ratio in the world were inversely associated with CVD risks. The Odds ratios of obesity, hypercholesterolemia and hypertension in the lowest quintile of both Ta and Mg were 6.3, 4.6 and 1.8, respectively. J and M populations had significantly higher Ta and Mg therefore, lower CVD risks than EW, but J and M took more salt increasing the risk of stroke (Table 1). Despite the high salt intake, M had the merit of significantly high K intake to attenuate the adverse salt effect. J had a merit to take Is from soy containing Mg. Since Is intake was inversely associated with lower BMI in the world populations, high Japanese Mg intake was related to high Is intake which was inversely associated with obesity in Japan. In fact, the Japanese populations who took significantly higher T and Mg had lower BMI as well as higher HDL and folic acid in the blood, expected to prevent atherosclerosis and dementia. In contrast to M and EW, particularly severe obesity over BMI 30 was obviously less in J, ranking 182nd among 190 populations (WHO). The mortality rates of COVID-19 were significantly positively related to the ratio of severe obesity among 20 major countries in the world and this mortality was obviously lower in J, suggestive of the potential of J diet for post-pandemic longevity. Conclusion: 24U biomarker analyses indicated low-salted J and M diets are recommendable for CVD prevention. J diet is so far better than M diet because of lower CVD risks such as obesity and lipidemia, which were proven by urinary biomarkers to be related with traditional fish and soy intakes.

The application of nano-biosensors in the detection of 2019-nCoV

The pandemic of 2019 novel coronavirus (2019-nCoV) infection since 2020 caused Coronavirus Disease 2019 (COVID-19) leads the serious threaten to global public health. It is urgent to diagnose COVID-19, guide epidemiological measures, control the infection rates, research/develop the antiviral treatment and promote the vaccine research. The application of nano-material based biosensors (the nano-biosensors) has achieved the high-performance detection of a variety of biomarkers due to their small device size, label free detection, high sensitivity, good specificity, short detection time, and has been considered as great potential to become a point-of-care testing tool for detecting 2019-nCoV. Therefore, by summarizing the working principle and classification of nano-biosensors, and focusing on the research progress of nano-biosensors in the detection of 2019-nCoV reported in the recent years, our review provides the challenges and future development prospects of the nano-biosensor in clinical laboratory.

THE RS17713054 AND RS1800629 POLYMORPHISMS OF GENES LZTFL1 AND TNF ARE ASSOCIATED WITH COVID-19 SEVERITY

Both genetic and non-genetic factors are responsible for high interindividual variability in response to SARS-CoV-2. Despite the fact that multiple genetic polymorphisms have been identified as risk factors of severe COVID-19, such polymorphisms are still insufficiently studied in the Russian population. The study was aimed to identify genetic determinants associated with severe COVID-19 in the sample of patients from the Russian Federation. The correlation of the rs17713054 polymorphism in gene LZTFL1 and rs1800629 polymorphism in gene TNF (tumor necrosis factor) with the COVID-19 severity was assessed. DNA samples obtained from 713 patients (324 males and 389 females) aged 18-95 with COVID-19 of varying severity were analyzed. The rs1800629 polymorphism of gene TNF (OR = 1.5;p = 0.02) and rs17713054 polymorphism of gene LZTFL1 (OR = 1.60;p = 0.0043) were identified as risk factors of severe disease. The TNF polymorphism rs1800629 and LZTFL1 polymorphism rs17713054 could be considered as potential predictive biomarkers. The rs17713054 G > A polymorphism was strongly associated with severe disease. In the future the findings may provide the basis for the development of test-systems for prediction of the risk of severe viral respiratory diseases.

The platelet-to-lymphocyte ratio versus neutrophil-to-lymphocyte ratio in prediction of COVID-19 outcome

Clinical presentation is an undependable prognostic indicator of COVID-19 (COronaVIrus Disease 2019). So, a more objective predictor is needed to precisely evaluate and classify the prognosis. Immune dysregulation to lymphocytes, mainly T-lymphocytes, have been noticed between COVID-19 patients. The aim. This study was planned to determine the role of platelet-to-lymphocyte count ratio and neutrophil-to-lymphocyte ratio in assessment of COVID-19 prognosis. Methods. 70 hospitalized patients with confirmed COVID-19 were included in this study. All included patients underwent a consistent clinical, radiological and blood examination. Laboratory analysis was made by means of a commercially accessible kit. Blood cells ratios were computed by dividing their absolute counts. Results. Non-significant association was found between laboratory data and COVID-19 clinical severity. A significant association between CT classification and platelet-to-lymphocyte count ratio (higher value in L type;p = 0.001) was detected. Platelet-to-lymphocyte count ratio was significantly higher among intubated cases. However, Non-significant association was found between neutrophil-to-lymphocyte ratio and need of endotracheal intubation. Conclusion. Routine blood values are abnormal in patients with COVID-19. Platelet-to-lymphocyte count ratio ratios could be used as more meaningful biomarker than other values in predicting the prognosis of COVID-19. LMR helpful in COVID-19 severity.

Retrospective Analysis of C - Reactive Protein, Haematological Biomarkers and Coagulation Profile in Patients of SARS-Cov-2 in a Tertiary Care Hospital of Eastern India

Introduction: Blood tests play an important role in the early detection of disease given that they provide doctors with information about inflammatory processes. A complete blood count (CBC) is easy and inexpensive to perform. These parameters can be used alone as markers of inflammation. Their mutual ratio is also an indicator of early inflammation.4 In light of previous studies, the use of circulating biomarkers instead of inflammation and immune system has been considered a prognostic indicator for COVID-19 positive patients. Aims/ objective: To examines the role of biomarkers from peripheral blood samples in the diagnosis of hospitalized COVID-19 patients with a history of fever. Materials and Method: Haematological biomarkers and coagulation profile was compared between RT-PCR positive and negative patients. Systemic inflammatory index (SII) was calculated by multiplying thrombocyte count with neutrophil count and dividing the value by lymphocyte count. Neutrophil lymphocyte ratio (NLR) was calculated by dividing absolute neutrophil count by absolute lymphocyte count. Platelet lymphocyte ratio (PLR) was calculated by dividing absolute platelet by absolute lymphocyte count. Fisher exact test and unpaired t-test were used to compare categorical and continuous data respectively. Results: Analysis was done on 57 retrospective cases of RT-PCR positive patients and 61 RT-PCR negative patients with history of fever. COVID-19 positive patients showed leukopenia, neutropenia, thrombocytopenia, and lymphocytosis. SII and NLR decreased and PLR increased. PT and APTT were generally within normal limits in most of the patients. There was significant difference between two groups with respect to lymphocyte counts and PLR. Conclusion: The most standardized non-invasive and inexpensive tests such as CBC, coagulation and biochemical tests are available to assess disease severity for wise allocation of medical resources in developing countries such as India where resources and care are limited.

Trace determination of the hydrogen sulfide biomarker thiosulfate in human urine by HPLC coupled with element selective ICPMS/MS detection

Hydrogen sulfide is a toxic gas but also established as a naturally occurring gaseous signaling molecule in humans, playing key physiological roles with particular involvement in lung disease including COVID-19. Thiosulfate is the conventional biomarker of hydrogen sulfide and is excreted in human urine at low micromolar levels. Thiosulfate is amenable to detection by the element-selective inductively coupled plasma tandem mass spectrometry (ICPMS/MS), but sulfur speciation in human samples at trace levels is challenging due to the high complexity of human sulfur metabolome and the utility of this detector under such settings has not been demonstrated. We report a method for thiosulfate determination in human urine at trace physiological levels by HPLC-ICPMS/MS. The method involved one-step derivatization to improve chromatographic behavior followed by direct injection. The instrumental limit of detection was 1.4 μg S L−1 (0.02 μM or 0.1 pmol). In a group of samples from volunteers (n = 24), measured thiosulfate concentrations in the diluted urine matrix were down to 8.0 μg S L−1 with a signal-to-noise ratio >10. The method was validated for recovery (80–110%), repeatability (RSD% <5%), and linearity (r2 = 0.9999, at a tested working concentration range of 0.01–1.0 mg S L−1), and the accuracy was assessed by comparing with HPLC-ESIMS/MS which showed agreement within ±20%. This work demonstrates the applicability of HPLC-ICPMS/MS for sulfur speciation at trace levels in a matrix with complex sulfur metabolome as human urine and provides a sensitive method for the determination of the hydrogen sulfide biomarker. © 2022 The Authors

Safety of Pharmacotherapy in COVID-19 Patients: A Literature Review

The safety of COVID-19 pharmacotherapy is a relevant issue, first of all, because of the current lack of experience with using particular medicinal products and with off-label prescribing. The aim of the study was to analyse information on potential adverse drug reactions (ADRs) and their predictors in etiology- and pathogenesis-oriented COVID-19 therapy. According to literature data, the main clinically significant risk factors for COVID-19 patients to develop an ADR are the duration of their hospital stay, combined use of antivirals, polypharmacy, and their history of drug allergies. The most common adverse reactions to antivirals, to virus-neutralising antibodies, and to human anti-COVID-19 immunoglobulin and convalescent plasma are, respectively, gastrointestinal and hepatobiliary disorders;gastrointestinal disorders, neurological disorders, and allergic reactions;and transfusion reactions (fever, chills, etc.). For pathogenesis-oriented therapy with systemic glucocorticosteroids, the most characteristic ADR is hyperglycaemia. Janus kinase inhibitors and interleukin inhibitors are most often associated with gastrointestinal disorders and hypertransaminasemia;neutropenia is also characteristic of a number of interleukin inhibitors. Haemostatic adverse reactions to anticoagulants depend on the patient's dosing regimen and condition. Drug-drug interactions are a common problem in COVID-19 treatment, with the combination of nirmatrelvir and ritonavir showing the largest number of significant interactions attributed to their pharmacokinetics. Currently, there is data on the role of pharmacogenetic biomarkers in the safety and clinical outcomes of COVID-19 therapy. Thus, to improve the safety of COVID-19 therapy, an integrated approach is needed that will take into account both the clinical, demographic, and pharmacogenetic predictors of ADRs and the risk of drug-drug interactions.

Emergence of SARS CoV-2 Variant B.1.1.7 in a Pandemic Hospital

Introduction: A clinically significant variant of SARS-CoV-2 was identified in the UK in December 2020 and was designated VOC‐202012/01 (lineage B.1.1.7) on 14 December 2020. Our study aimed to evaluate the lineage B.1.1.7 prevalence over time and demographic, hematological, coagulation, inflammation characteristics in hospitalized patients with B.1.1.7 during February-March 2021. Materials and Methods: Between 5 February and 20 March 2021, 182 inpatients with B.1.1.7 were included in this study. Bio-Speedy, SARS-CoV-2 Double Gene RT-qPCR (Bioeksen, Ístanbul, Türkiye) kit was used to diagnose COVID-19. Cycle threshold< 27 samples were taken into mutation study with Bio-Speedy SARS-CoV-2 Variant Plus kit. Results: Of the 5187 SARS-CoV-2 positive cases, 2288 (69.65%) were evaluated as variant B.1.1.7 positive. Throughout the study, the case number's daily increase rate was 8.78% in SARS CoV-2, 13.16% in B.1.1.7;the case number's doubling time was calculated as 7.9 days in SARS CoV-2 and 5.27 days in B.1.1.7. In ICU patients, hemoglobin (p< 0.001), platelet (p= 0.034) and lymphocyte (p< 0.001) levels were lower but neutrophil (p= 0.025), monocyte/lymphocyte ratio (MLR) (p= 0.002), neutrophil/lymphocyte (NLR) (p< 0.001) ratio and D-dimer (p= 0.008) levels were dedected higher than non-ICU patients. Conclusion: Our study demonstrated that the infectiousness of B.1.1.7 was higher than previous variants and became the dominant SARS-CoV-2 in six weeks in our region. Therefore, urgent and decisive measures should be taken to minimize morbidity and mortality associated with COVID-19. In addition, our findings indicate that first hematologic markers of the patients can be an important biomarker for the prognosis of COVID-19 disease.

Cardiac Biomarkers in 2022 - A Vital Tool for Emergency Care

The role of cardiac biomarkers in diagnosing acute myocardial infarction is undoubted. In the 2020 guidelines of the European Society of Cardiology, the measurement of cardiac peptides to gain prognostic information has a class IIa indication in all patients with ACS. In emergency care, ruling out a non-ST elevation myocardial infarction requires documentation of normal levels of cardiac biomarkers, which remain stable or have very small variations within several hours. This review aims to summarize the current knowledge and recent progresses in the field of cardiac biomarker discovery, from their routine use in emergency rooms to their prognostic roles in modern risk assessment tools. Integrated approaches combining cardiac troponin with other biomarkers of ventricular dysfunction or inflammation, or with modern cardiac imaging in emergency care are also presented, as well as the role of modern algorithms for serial troponin measurement in the modern management of emergency departments.

METABOLIC BIOLOGICAL MARKERS FOR DIAGNOSING AND MONITORING THE COURSE OF TUBERCULOSIS.

The international biomedical community has been currently facing a need to find a simple and most accessible type of analysis that helps to diagnose tuberculosis (TB) with the maximum reliability even before the onset of clinical manifestations. Tuberculosis results in more deaths than any other pathogen, second only to pneumonia caused by the SARS-CoV-2 virus, but the majority of infected people remain asymptomatic. In addition, it is important to develop methods to distinguish various forms of tuberculosis infection course at early stages and to reliably stratify patients into appropriate groups (persons with a rapidly progressing infection, chronic course, latent infection carriers). Immunometabolism investigates a relationship between bioenergetic pathways and specific functions of immune cells that has recently become increasingly important in scientific research. The host anti-mycobacteria immune response in tuberculosis is regulated by a number of metabolic networks that can interact both cooperatively and antagonistically, influencing an outcome of the disease. The balance between inflammatory and immune reactions limits the spread of mycobacteria in vivo and protects from developing tuberculosis. Cytokines are essential for host defense, but if uncontrolled, some mediators may contribute to developing disease and pathology. Differences in plasma levels of metabolites between individuals with advanced infection, LTBI and healthy individuals can be detected long before the onset of the major related clinical signs. Changes in amino acid and cortisol level may be detected as early as 12 months before the onset of the disease and become more prominent at verifying clinical diagnosis. Assessing serum level of certain amino acids and their ratios may be used as additional diagnostic markers of active pulmonary TB. Metabolites, including serum fatty acids, amino acids and lipids may contribute to detecting active TB. Metabolic profiles indicate about increased indolamine 2.3-di-oxygenase 1 (IDO1) activity, decreased phospholipase activity, increased adenosine metabolite level, and fibrous lesions in active vs. latent infection. TB treatment can be adjusted based on individual patient metabolism and biomarker profiles. Thus, exploring immunometabolism in tuberculosis is necessary for development of new therapeutic strategies. Copyright © 2022 Saint Petersburg Pasteur Institute. All rights reserved.

Molecular mechanisms underlying regulatory T cell deficiency and potential drugs in COVID-19

Background/Purpose: The 2019 outbreak of coronavirus disease COVID-19 causes immune system disruption. Recent studies reported that the decrease or depletion of regulatory T cell (Treg) may be responsible for overstimulation of the immune system and lung damage in patients with severe COVID-19. This study aims to find the molecular mechanisms and genetic biomarkers associated with Tregs in COVID-19, providing new ideas for the treatment of COVID-19. Method(s): RNA sequencing data of peripheral blood mononuclear cells (PBMC) from 252 COVID-19 infected patients and 69 healthy controls (HC) were obtained from the GEO database. The Tregs composition of COVID-19 samples was quantified using the CIBERSORT deconvolution method. The differential genes (DEGs) were identified by the limma R package. Gene co-expression network analysis (WGCNA) was used to identify the gene. Differentially expressed Tregs-related genes (DETregRGs) were obtained by intersecting DEGs with the highly related modular genes obtained in the previous step. The potential biological functions and pathways of DETregRGs were then explored. Protein-protein interaction (PPI) networks were subsequently constructed to identify hub genes. In addition, the prediction of small molecule drugs for the potential treatment of COVID-19 was made using the CMap database. Result(s): After the weighted gene co-expression network analysis (WGCNA), the turquoise module was highly correlated with Treg expression and a total of 134 DEGs was identified as DETregRGs. These genes were mainly involved in GO biological processes, such as the inflammatory response, and T cell differentiation of thymus. Then, 11 hub genes (including RPS12, RPL21, RPS3A, CD8B, CD3D, TRAT1, RPS6, CD3E, CD28, RPL3, and CD4) were ranked based on Molecular Complex Detection (MCODE) analysis. The TregRG score of COVID-19 patients showed significantly lower than HC, calculated by the 'singscore' algorithms. After the signature query of the CMap database, the KU-0063794, an mTOR inhibitor ranked second in the negative enrichment score, may restore immune system dysregulation caused by increased Th17 differentiation and decreased Treg differentiation during SARS-CoV- 2 infection. Conclusion(s): Our study examined in detail the molecular mechanisms underlying the inadequacy of Tregs in patients with COVID-19 infection. mTOR inhibitors may improve COVID-19 symptoms by expanding Tregs which may be one of the potential therapeutic methods that need further investigation. (Figure Presented).

Predictive Value of Specific Cytokines for Lethal Covid-19 Outcome

In our study, we aimed to evaluate the significance of specific cytokines in blood plasma as predictive markers of COVID-associated mortality. Materials and methods. In plasma samples of 29 patients with PCR-confirmed COVID-19 we measured the concentrations of 47 molecules. These molecules included: interleukins and selected pro-inflammatory cytokines (IL-1alpha, IL-1beta, IL-2, IL-3, IL-4, IL-5, IL-6, IL-7, IL-9, IL-12 (p40), IL-12 (p70), IL-13, IL-15, IL-17A/CTLA8, IL-17-E/IL-25, IL-17F, IL-18, IL-22, IL-27, IFNalpha2, IFNgamma, TNFalpha, TNFbeta/Lymphotoxin-alpha(LTA));chemokines (CCL2/MCP-1, CCL3/MIP-1alpha, CCL4/MIP-1beta, CCL7/MCP-3, CCL11/Eotaxin, CCL22/MDC, CXCL1/GROalpha, CXCL8/IL-8, CXCL9/MIG, CXCL10/IP-10, CX3CL1/Fractalkine);anti-inflammatory cytokines (IL-1Ra, IL-10);growth factors (EGF, FGF-2/FGF-basic, Flt-3 Ligand, G-CSF, M-CSF, GM-CSF, PDGF-AA, PDGFAB/BB, TGFalpha, VEGF-A);and sCD40L. We used multiplex analysis based on xMAP technology (Luminex, USA) using Luminex MagPix. As controls, we used plasma samples of 20 healthy individuals. Based on the results, we applied Receiver Operating Characteristic (ROC) analysis and Area Under Curve (AUC) values to compare two different predictive tests and to choose the optimal division point for disease outcome (survivors/non-survivors). To find optimal biomarker combinations, we as used cytokines concentrations as dependent variables to grow a regression tree using JMP 16 Software.Results. Out of 47 studied cytokines/chemokines/growth factors, we picked four pro-inflammatory cytokines as having high significance in evaluation of COVID-19 outcome: IL-6, IL-8, IL-15, and IL-18. Based on the results received, we assume that the highest significance in terms of predicting the outcome of acute COVID-19 belongs to IL-6 and IL-18. Conclusion. Analyzing concentrations of IL-6 and IL-18 before administering treatment may prove valuable in terms of outcome prognosis. Copyright © Arsentieva N.A. et al., 2022.

24th Asia-Pacific League of Associations for Rheumatology Congress, APLAR

The proceedings contain 539 papers. The topics discussed include: advances in the understanding and management of atherosclerosis in inflammatory arthritis;long-term safety and efficacy of voclosporin in Asian patients with lupus nephritis;clinical profile of four children with juvenile dermatomyositis and anti-SAE antibody positivity: a single center experience from north India;the MMP degraded and citrullinated vimentin (VICM) is a diagnostic and treatment response biomarker;incidence and outcome of covid-19 in AIRD patients on concomitant treatment with tofacitinib- results from KRA covid cohort (KRACC) subset;are we treating-to-target in spondyloarthritis (SPA)? a cross-sectional analysis from the Asia Pacific league of associations for rheumatology (APLAR) SPA registry;utilities of low-dose computed tomography (LDCT) on identifying patient with axial psoriatic arthritis (AXPSA) a cross-sectional study;age-related genes USP2 and ARG2 are involved in the reduction of immune cell infiltration in elderly patients with rheumatoid arthritis;and MICRORNA-27a-3p inhibits lung and skin fibrosis of systemic sclerosis by negatively regulating SPP1.

Identification of shared genes and possible therapeutic target between systemic lupus erythematosus and COVID-19

Background/purpose: Coronavirus disease 2019 (COVID-19) has led to a rapid increase in mortality worldwide. Systemic lupus erythematosus (SLE) was a high-risk factor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV- 2) infection, Whereas the molecular mechanisms underlying SLE and CVOID-19 are not well understood. This study aims to discover the common molecular mechanisms and genetic biomarkers of SLE and COVID-19, providing new ideas for the treatment of COVID-19. Method(s): RNA sequencing data of peripheral blood mononuclear cells (PBMC) from 6 SLE datasets and 8 COVID-19 datasets were obtained from the GEO database. Highly related modular genes associated with COVID-19 and SLE were identified by weighted gene co-expression network analysis (WGCNA). The differentially expressed genes (DEGs) between patients and healthy controls (HCs) were identified by the limma package. Common shared DEGs from COVID-19 and SLE were identified. Cytoscape and MCODE plugin were utilized for exploring the protein-protein interaction network (PPI) and identifying shared hub genes. Potential biological functions and pathways were also explored from the common DEGs. For better analysis of detailed biological mechanisms, both xCell algorithm and the cMap in CLUE (https://clue.io/) were utilized for discovering immune cell infiltration and predicting potential drugs that negatively regulate the highly expressed genes. Result(s): With identified 498 up-regulated common DEGs in SLE and COVID-19 related genes, total 11 and 13 gene modules of SLE and COVID-19 were identified espectively After overlapping differential genes, the final intersection gene set contains 218 genes. The PPI, especially the functional subnet module consists of upregulated genes by MCODE showed a great deal IFN related genes involved in the regulation of immunity. GO biological processes also showed possible functions were defense response to virus and mitotic cell cycle. Moreover, changes of most immune cells were strongly consistent between SLE and COVID-19. CDK inhibitors identified may be more likely to inhibit two diseases. Conclusion(s): Our study examined in detail the common molecular mechanisms of SLE and COVID-19, in which cellular response to cytokine stimulus, like regulating IFN, which might be the key target of both diseases. CDK is associated with the progression of SLE and COVID-19, which may be the potential therapeutic drug for SLE patients with COVID-19 infection.

Internet of Medical Things - The Future of Healthcare

Background: The Internet of Medical Things (IoMT) is now being connected to medical equipment to make patients more comfortable, offer better and more affordable health care options, and make it easier for people to get good care in the comfort of their own homes. Objective(s): The primary purpose of this study is to highlight the architecture and use of IoMT (Internet of Medical Things) technology in the healthcare system. Method(s): Several sources were used to acquire the material, including review articles published in various journals that had keywords such as, Internet of Medical Things, Wireless Fidelity, Remote Healthcare Monitoring (RHM), Point-of-care testing (POCT), and Sensors. Result(s): IoMT has succeeded in lowering both the cost of digital healthcare systems and the amount of energy they use. Sensors are used to measure a wide range of things, from physiological to emotional responses. They can be used to predict illness before it happens. Conclusion(s): The term "Internet of Medical Things" refers to the broad adoption of healthcare solutions that may be provided in the home. Making such systems intelligent and efficient for timely prediction of important illnesses has the potential to save millions of lives while decreasing the burden on conventional healthcare institutions, such as hospitals. patients and physicians may now access real-time data due to advancements in IoM. Copyright © 2022 Wal et al.

Evaluating Persistent Symptoms of SARS-CoV-2 Infection by Precision Medicine

During these two years, the SARS-CoV-2 pandemic spread fast, killing people as surely as the global war. Step by step, research revealed several aspects of this plague. Understanding the essential etio-pathological characteristics of SARS-CoV-2 infection is necessary to outline discuss and assess its pathogenic mechanism and proceed with proper viral be-haviours assessment. Coronaviruses are enveloped by positive-sense and negative-sense RNA viruses. Their characteristic is a characteristic long spike protein projecting from the surface. These viruses have an unusual huge RNA genome (that is up to 33.5 kilobases). These viruses are the largest Noroviruses;the order includes Coronaviridiae and includes the order which includes the Coronaviridae, Arteriviridneae, Mesonivirideae, and Ronivirideae families. Coronaviruses have two subfamilies, Corinaviridea Orthocoronavirinae and Torviridiae Letovirinae. The taxonomy subdivides Orthocoronavirinae Coronaviridiae into different genera, e.g., the alfa, the beta, and gamma Coronaviruses. The coronavirus virion structure of coronaviruses is spherical with a diameter of 125 nm. Copyright © 2022 Phcog.Net. All rights reserved.