Metformin Protects against Radiation-Induced Pneumonitis and Fibrosis and Attenuates Upregulation of Dual Oxidase Genes Expression

Purpose: Lung tissue is one of the most sensitive organs to ionizing radiation (IR). Early and late side effects of exposure to IR can limit the radiation doses delivered to tumors that are within or adjacent to this organ. Pneumonitis and fibrosis are the main side effects of radiotherapy for this organ. IL-4 and IL-13 have a key role in the development of pneumonitis and fibrosis. Metformin is a potent anti-fibrosis and redox modulatory agent that has shown radioprotective effects. In this study, we aimed to evaluate possible upregulation of these cytokines and subsequent cascades such as IL4-R1, IL-13R1, Dual oxidase 1 (DUOX1) and DUOX2. In addition, we examined the potential protective effect of metformin in these cytokines and genes, as well as histopathological changes in rat’s lung tissues. Methods: 20 rats were divided into 4 groups: control; metformin treated; radiation + metformin; and radiation. Irradiation was performed with a 60Co source delivering 15 Gray (Gy) to the chest area. After 10 weeks, rats were sacrificed and their lung tissues were removed for histopathological, real-time PCR and ELISA assays. Results: Irradiation of lung was associated with an increase in IL-4 cytokine level, as well as the expression of IL-4 receptor-a1 (IL4ra1) and DUOX2 genes. However, there was no change in the level of IL-13 and its downstream gene including IL-13 receptor-a2 (IL13ra2). Moreover, histopathological evaluations showed significant infiltration of lymphocytes and macrophages, fibrosis, as well as vascular and alveolar damages. Treatment with metformin caused suppression of upregulated genes and IL-4 cytokine level, associated with amelioration of pathological changes. Conclusion: Results of this study showed remarkable pathological damages, an increase in the levels of IL-4, IL4Ra1 and Duox2, while that of IL-13 decreased. Treatment with metformin showed ability to attenuate upregulation of IL-4–DUOX2 pathway and other pathological damages to the lung after exposure to a high dose of IR

The global case fatality rate due to COVID-19 in hospitalized elderly patients by sex, year, gross domestic product, and continent: A systematic review, meta-analysis, and meta-regression

Background: Although elderly people are at a huge risk of mortality due to COVID-19, the Case Fatality Rate (CFR) in hospitalized elderly patients is poorly investigated. This meta-analysis and meta-regression aimed to generate pooled CFR due to COVID-19 in hospitalized elderly patients by sex, Gross Domestic Product (GDP), year, and continent and also to explain the potential source of the heterogeneity and variations in the pooled estimation of COVID-19 CFR. Methods: We systematically searched PubMed, Scopus, Web of Science, CINAHL, and Embase up to 31 July 2022. Eligibility assessment of records was performed independently in a blinded, standardized way by two reviewers. Meta-analysis and Meta-regression analysis were carried out to estimate pooled CFR and the potential sources of the heterogeneity. Results: The study included 5683 confirmed hospitalized elderly COVID-19 patients, 1809 deaths, and 19 original articles from 10 countries. The pooled estimate of the overall CFR, and by male and female sexes were 29%, 34%, and 24%, respectively. We found CFR was decreased by increasing female sex proportion, GDP, and year of publication. Multivariate meta-regression analysis indicated that the age and sex of patients, continent, GDP, and year of the publication together explained the majority of the heterogeneity and variations in the pooled estimate of the hospitalized elderly COVID-19 CFR. Conclusions: This review provided reliable pooled CFR measures for hospitalized elderly patients with COVID-19. Although COVID-19 fatality has decreased in hospitalized elderly patients over time, it is still high in hospitalized elderly patients and needs advanced treatment support

The relationship between metabolic syndrome and its components with bladder cancer: a systematic review and meta-analysis of cohort studies

A previous meta-analysis, entitled “The association between metabolic syndrome and bladder cancer susceptibility and prognosis: an updated comprehensive evidence synthesis of 95 observational studies involving 97,795,299 subjects,” focused on all observational studies, whereas in the present meta-analysis, we focused on cohort studies to obtain more accurate and stronger evidence to evaluate the association between metabolic syndrome and its components with bladder cancer. PubMed, Embase, Scopus, and Web of Science were searched to identify studies on the association between metabolic syndrome and its components with bladder cancer from January 1, 2000 through May 23, 2021. The pooled relative risk (RR) and 95% confidence intervals (CI) were used to measure this relationship using a random-effects meta-analytic model. Quality appraisal was undertaken using the Newcastle-Ottawa Scale. In total, 56 studies were included. A statistically significant relationship was found between metabolic syndrome and bladder cancer 1.09 (95% CI, 1.02 to 1.17), and there was evidence of moderate heterogeneity among these studies. Our findings also indicated statistically significant relationships between diabetes (RR, 1.23; 95% CI, 1.16 to 1.31) and hypertension (RR, 1.07; 95% CI, 1.01 to 1.13) with bladder cancer, but obesity and overweight did not present a statistically significant relationship with bladder cancer. We found no evidence of publication bias. Our analysis demonstrated statistically significant relationships between metabolic syndrome and the risk of bladder cancer. Furthermore, diabetes and hypertension were associated with the risk of bladder cancer

A Systematic Review and Meta-analysis of Toxocariasis in Iran: Is it Time to Take it Seriously?

Background: Toxocariasis is one of the neglected zoonosis with considerable public health importance around the world. The current study aimed to elucidate the overall prevalence of Toxocara infection in human and definitive hosts and also the contamination of soil and raw vegetables with the ova of these parasites, in Iran, using systematic review and meta-analysis. Methods: Six English and Persian databases were explored from 2000 to 2017 using the terms toxocariasis, Toxocara spp., visceral larva migrans, Iran, epidemiology, and prevalence. This meta-analysis conducted using STATA, and for all statistical tests, a p value less than 0.05 was considered significant. The random-effects model was used to the report of the pooled prevalence with a 95% confidence interval (CI). Results: The pooled prevalence of toxocariasis in human was calculated as 11% (95% CI 8–13%). In terms of definitive hosts, the pooled prevalence of Toxocara infection in dogs and cats were calculated as 17% (95% CI 14–20%) and 37% (95% CI 26–48%), respectively. Also, the pooled prevalence of Toxocara spp. eggs in the soil and raw vegetable samples were calculated as 18% (95% CI 13–23%) and 2% (95% CI 1–3%), respectively. Conclusions: The results of current study demonstrate that toxocariasis should be taken more seriously by health authorities. Implementing an appropriate control program is necessary to reduce the incidence of this disease in Iran

The effect of smoking on latent hazard classes of metabolic syndrome using latent class causal analysis method in the Iranian population

Background: The prevalence of metabolic syndrome is increasing worldwide. Clinical guidelines consider metabolic syndrome as an all or none medical condition. One proposed method for classifying metabolic syndrome is latent class analysis (LCA). One approach to causal inference in LCA is using propensity score (PS) methods. The aim of this study was to investigate the causal effect of smoking on latent hazard classes of metabolic syndrome using the method of latent class causal analysis. Methods: In this study, we used data from the Tehran Lipid and Glucose Cohort Study (TLGS). 4857 participants aged over 20 years with complete information on exposure (smoking) and confounders in the third phase (2005–2008) were included. Metabolic syndrome was evaluated as outcome and latent variable in LCA in the data of the fifth phase (2014–2015). The step-by-step procedure for conducting causal inference in LCA included: (1) PS estimation and evaluation of overlap, (2) calculation of inverse probability-of-treatment weighting (IPTW), (3) PS matching, (4) evaluating balance of confounding variables between exposure groups, and (5) conducting LCA using the weighted or matched data set. Results: Based on the results of IPTW which compared the low, medium and high risk classes of metabolic syndrome (compared to a class without metabolic syndrome), no association was found between smoking and the metabolic syndrome latent classes. PS matching which compared low and moderate risk classes compared to class without metabolic syndrome, showed that smoking increases the probability of being in the low-risk class of metabolic syndrome (OR: 2.19; 95% CI: 1.32, 3.63). In the unadjusted analysis, smoking increased the chances of being in the low-risk (OR: 1.45; 95% CI: 1.01, 2.08) and moderate-risk (OR: 1.68; 95% CI: 1.18, 2.40) classes of metabolic syndrome compared to the class without metabolic syndrome. Conclusions: Based on the results, the causal effect of smoking on latent hazard classes of metabolic syndrome can be different based on the type of PS method. In adjusted analysis, no relationship was observed between smoking and moderate-risk and high-risk classes of metabolic syndrome.Medicine, Faculty ofNon UBCOphthalmology and Visual Sciences, Department ofReviewedFacultyResearche

Prescribing pattern of antibiotics by family physicians in primary health care

Abstract Purpose Irrational prescription of antibiotics is an ongoing global public health concern, leading to antibiotic resistance. Understanding the prescribing pattern of antibiotics is important to tackling mal-prescription and antibiotic resistance. We aimed to investigate the pattern and factors affecting outpatients’ antibiotic prescribing by family physicians in Primary Health Care (PHC). Methods A cross-sectional study was conducted in 19 PHC facilities in Alborz province. Prescribing pattern of antibiotics was evaluated among 1068 prescriptions by family physicians. Prescribing pattern of antibiotics included prescriptions containing antibiotics, the number of antibiotics per prescription, type, name of antibiotic, and mal-prescription. Multiple logistic regression analysis was used to estimate the adjusted odds ratios and 95% confidence intervals. Results Overall, 57% of the prescriptions had ≥ 1 antibiotic and the average number of antibiotics per prescription was 1.27. Amoxicillin was the commonly prescribed antibiotic. There was a significant relationship between age, sex, type of health insurance, work experience of the physician, and seasons with antibiotic prescribing (P < 0.05). In 59.31% of antibiotic prescriptions at least one of the scientific criteria was not fulfilled. In the final analysis, after adjusting for the potential confounders, field experts of physicians (OR = 1.59; 95% CI: 1.08–6.17), female sex (OR = 2.23; 95% CI: 1.18–4.21), and winter season (OR = 3.34; 95% CI: 1.26–8.15) were found associated factors with antibiotic prescribing. Conclusion The average number of antibiotics per prescription and the percentage of irrational prescriptions were relatively high in this study. There is need to improve antibiotic prescribing patterns among family physicians working in primary health care

Mapping the human genetic architecture of COVID-19

The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3–7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease