Large variability in vaccine acceptance and high vaccine hesitancy can influence the efforts to eliminate the COVID-19. Addressing the barriers and facilitators of vaccines will be crucial in implementing effective and tailored interventions to attain maximum vaccine coverage.Background The novel 2019 coronavirus disease (COVID-19) pandemic has spread rapidly worldwide and poses a global health threat. https://www.selleckchem.com/mTOR.html Aims This study assessed the prevalence of anxiety and depression symptoms in Chinese students during the COVID-19 pandemic and explored potential moderating factors. Methods We searched English and Chinese databases using pertinent keywords for articles published and unpublished, up until November 2020. The estimate of the overall prevalence of anxiety and depression was conducted through a random-effects model. Results A total of 31 cross-sectional studies were included. The overall prevalence of anxiety and depression symptoms in Chinese students during the COVID-19 pandemic was 24.0% (95% CI [20.0-29.0%]) and 22.0% (95% CI [18.0-27.0%]) respectively. Subgroup analyses revealed that Chinese middle school students were at heightened risk of anxiety, while university students were at heightened risk of depression. Students who lived in higher-risk areas presented severe anxiety and depression, especially during the late period of the COVID-19 epidemic. Conclusions Overall, during the COVID-19 pandemic, there was a high prevalence of anxiety in Chinese students and a high prevalence of depression among Chinese students in high-risk areas. Therefore, comprehensive and targeted psychological interventions should be developed to address the mental health of students in different grades, especially in high-risk areas and during the late period of the COVID-19 pandemic.Introduction Social capital, the effective functioning of social groups through networks of relationships, can affect mental health and may be affected by COVID-19. We aimed to examine the changes in social capital before and after the COVID-19 lockdown among the Chinese youth. Methods A national convenience sample of 10,540 high school, undergraduate, and graduate students, from the COVID-19 Impact on Lifestyle Change Survey (COINLICS), reported their demographic and social capital information before and after the COVID-19 lockdown. Social capital was retrospectively measured at four levels individual (ISC), family (FSC), community (CSC), and society (SSC). The changes of social capital were also compared across three educational levels. Results Overall, ISC and CSC scores generally decreased after lockdown (15.1 to 14.8 and 13.4 to 13.1, respectively), while FSC and SSC scores increased significantly (12.7 to 13.0 and 7.1 to 7.2, respectively). At the individual level, most participants showed a constant perceived social capital; more of the remaining participants showed decreased than increased ISC (30.5% vs. 17.0%) and CSC scores (28.4% vs. 19.1%), while more participants showed increased than decreased FSC (21.7% vs. 9.2%) and SSC scores (10.3% vs. 3.9%). Heterogeneities in social capital changes existed across educational levels. Conclusions Our findings would provide health professionals and policy-makers solid evidence on the changes in social capital of youths after lockdowns, and therefore help the design of future interventions to rebuild or improve their social capital after epidemics/disasters.The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has affected countries across the world. While the zoonotic aspects of SARS-CoV-2 are still under investigation, bats and pangolins are currently cited as the animal origin of the virus. Several types of vaccines against COVID-19 have been developed and are being used in vaccination drives across the world. A number of countries are experiencing second and third waves of the pandemic, which have claimed nearly four million lives out of the 180 million people infected globally as of June 2021. The emerging SARS-CoV-2 variants and mutants are posing high public health concerns owing to their rapid transmissibility, higher severity, and in some cases, ability to infect vaccinated people (vaccine breakthrough). Here in this mini-review, we specifically looked at the efforts and actions of the Egyptian government to slow down and control the spread of COVID-19. We also review the COVID-19 statistics in Egypt and the possible reasons behind the low prevalence and high case fatality rate (CFR%), comparing Egypt COVID-19 statistics with China (the epicenter of COVID-19 pandemic) and the USA, Brazil, India, Italy, and France (the first countries in which the numbers of patients infected with COVID-19). Additionally, we have summarized the SARS-CoV-2 variants, vaccines used in Egypt, and the use of medicinal plants as preventive and curative options.Higher-throughput, mode-of-action-based assays provide a valuable approach to expedite chemical evaluation for human health risk assessment. In this study, we combined the high-throughput alkaline DNA damage-sensing CometChip® assay with the TGx-DDI transcriptomic biomarker (DDI = DNA damage-inducing) using high-throughput TempO-Seq®, as an integrated genotoxicity testing approach. We used metabolically competent differentiated human HepaRG™ cell cultures to enable the identification of chemicals that require bioactivation to cause genotoxicity. We studied 12 chemicals (nine DDI, three non-DDI) in increasing concentrations to measure and classify chemicals based on their ability to damage DNA. The CometChip® classified 10/12 test chemicals correctly, missing a positive DDI call for aflatoxin B1 and propyl gallate. The poor detection of aflatoxin B1 adducts is consistent with the insensitivity of the standard alkaline comet assay to bulky lesions (a shortcoming that can be overcome by trapping repair intermedicultures.Rheumatoid arthritis (RA) is a chronic autoimmune disorder that commonly manifests as destructive joint inflammation but also affects multiple other organ systems. The pathogenesis of RA is complex where a variety of factors including comorbidities, demographic, and socioeconomic variables are known to associate with RA and influence the progress of the disease. In this work, we used a Bayesian logistic regression model to quantitatively assess how these factors influence the risk of RA, individually and through their interactions. Using cross-sectional data from the National Health and Nutrition Examination Survey (NHANES), a set of 11 well-known RA risk factors such as age, gender, ethnicity, body mass index (BMI), and depression were selected to predict RA. We considered up to third-order interactions between the risk factors and implemented factor analysis of mixed data (FAMD) to account for both the continuous and categorical natures of these variables. The model was further optimized over the area under the receiver operating characteristic curve (AUC) using a genetic algorithm (GA) with the optimal predictive model having a smoothed AUC of 0.826 (95% CI 0.801-0.850) on a validation dataset and 0.805 (95% CI 0.781-0.829) on a holdout test dataset. Apart from corroborating the influence of individual risk factors on RA, our model identified a strong association of RA with multiple second- and third-order interactions, many of which involve age or BMI as one of the factors. This observation suggests a potential role of risk-factor interactions in RA disease mechanism. Furthermore, our findings on the contribution of RA risk factors and their interactions to disease prediction could be useful in developing strategies for early diagnosis of RA.With the rapid development of electronic information in the past 30 years, technical achievements based on electromagnetism have been widely used in various fields pertaining to human production and life. Consequently, electromagnetic radiation (EMR) has become a substantial new pollution source in modern civilization. The biological effects of EMR have attracted considerable attention worldwide. The possible interaction of EMR with human organs, especially the brain, is currently where the most attention is focused. Many studies have shown that the nervous system is an important target organ system sensitive to EMR. In recent years, an increasing number of studies have focused on the neurobiological effects of EMR, including the metabolism and transport of neurotransmitters. As messengers of synaptic transmission, neurotransmitters play critical roles in cognitive and emotional behavior. Here, the effects of EMR on the metabolism and receptors of neurotransmitters in the brain are summarized.The world is currently gripped by the fear of the corona virus disease 2019 (COVID-19) pandemic. The causative agent of COVID-19 is a novel coronavirus known as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) that attacks humans without prejudice, and primarily targets the respiratory system. Pakistan is a developing country with a large population and a weak economy. Currently, it is facing a major challenge to cope with the outbreak of the COVID-19 pandemic, especially the third wave. This fatal virus has increased its presence many folds in Pakistan. On average, 100 deaths per day were being recorded in the late spring of 2021. Delay in the acquisition of vaccine has slowed down the vaccination program for this disease. This in turn will accelerate the spreading of virus, and thus will lead to a lockdown situation.The COVID-19 pandemic and the draconian measures applied to limit its spread have accelerated the process of digitalizing many activities, including those within the health sector. In Morocco, a developing country in northern Africa, digital health has been deployed extensively, and in a remarkable way, to support the management of the current health crisis. Morocco is taking significant measures to become a key player in the process of achieving Sustainable Development Goals (SDG) goal 3. The government has comprehensively integrated digital technology throughout its coordinated containment and mitigation processes. These processes encompass testing and diagnostics; virus genomic surveillance; telecare of suspected and chronic patients; COVID-19 patient contact tracing and tracking; a laboratory information system for medical material dispatching, biological sample collection, and data processing nationwide; and smart vaccination management. Moreover, the pace of amending legislation for enabling efficient telemedicine practice has been achieved at a record-breaking. The successful implementation of all of these digital health strategies testify to the effectiveness of digitalization for managing the health aspects of the pandemic and for the future development of health systems in Morocco and in the African continent, where digital health and telemedicine is set to become the cornerstone of medical practice.Driving cessation is a common transition experienced by aging adults that confers both a symbolic and literal loss of independence due to the central role of automobiles for mobility in the US. Prior research has shown that driving cessation has negative implications for mental health, social participation, and access to healthcare. Given these sequelae of driving cessation and prior work showing that late-life transitions related to independence (e.g., transitioning into residential care) are associated with suicide, we sought to estimate the frequency of driving cessation associated suicide. Data include suicide (n = 59,080) and undetermined (n = 6,862) deaths aged ≥55 from the National Violent Death Reporting System (NVDRS, 2003-2017). Each case in the NVDRS has both quantitative data (e.g., demographic characteristics) and qualitative text narratives, derived from coroner/medical examiner reports, which describe the most salient circumstances and features of each death. To identify cases associated with driving cessation, we employed a supervised random forest algorithm to develop a Natural Language Processing (NLP) classifier.