Project description:Coronavirus disease 2019 (COVID-19) is a new infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that belongs to the coronavirus family. The first case was reported in December 2019, and the disease has become a pandemic. Impaired immune regulation is one of the factors that play a role in its pathogenesis and results in poor outcomes of COVID-19 patients. There have been many studies with drug candidates used as antivirals or immunomodulators. However, the results of these investigations showed that the drug candidates were not significantly effective against the disease. Meanwhile, people believe that consuming herbal immunomodulators can prevent or even cure COVID-19. Unfortunately, specific preclinical and clinical trials to evaluate the effects of herbal immunoregulators have not been conducted. Certain natural compounds might be effective for the treatment of COVID-19 based on general concepts from previous experiments. This review discusses some herbal agents extracted from various plants, including Echinacea, Cinchona, Curcuma longa, and Curcuma xanthorrhiza, which are considered for the treatment of COVID-19. In addition, we discuss the pros and cons of utilising herbal medicine during the COVID-19 pandemic, draw some conclusions, and make recommendations at the end of the session.
Project description:A new kind of Pneumonia caused by new corona virus has been widespread in China since winter of 2019. No effective treatment for this disease was verified, so the morbidity and mortality rate were supposed higher than flu. The Traditional Chinese Medicine is widely used in clinical practice in China, but many other countries of the world to deal with diseases that remain clinically challenging.
Project description:COVID-19 has become one of the biggest health concern, along with huge economic burden. With no clear remedies to treat the disease, doctors are repurposing drugs like chloroquine and remdesivir to treat COVID-19 patients. In parallel, research institutes in collaboration with biotech companies have identified strategies to use viral proteins as vaccine candidates for COVID-19. Although this looks promising, they still need to pass the test of challenge studies in animal models. As various models for SARS-CoV-2 are under testing phase, biotech companies have bypassed animal studies and moved to Phase I clinical trials. In view of the present outbreak, this looks a justified approach, but the problem is that in the absence of animal studies, we can never predict the outcomes in humans. Since animal models are critical for vaccine development and SARS-CoV-2 has different transmission dynamics, in this review we compare different animal models of SARS-CoV-2 with humans for their pathogenic, immune response and transmission dynamics that make them ideal models for vaccine testing for COVID-19. Another issue of using animal model is the ethics of using animals for research; thus, we also discuss the pros and cons of using animals for vaccine development studies.
Project description:ContextDiabetes in neonates nearly always has a monogenic etiology. Earlier sulfonylurea therapy can improve glycemic control and potential neurodevelopmental outcomes in children with KCNJ11 or ABCC8 mutations, the most common gene causes.ObjectiveAssess the risks and benefits of initiating sulfonylurea therapy before genetic testing results become available.Design, setting, and patientsObservational retrospective study of subjects with neonatal diabetes within the University of Chicago Monogenic Diabetes Registry.Main outcome measuresResponse to sulfonylurea (determined by whether insulin could be discontinued) and treatment side effects in those treated empirically.ResultsA total of 154 subjects were diagnosed with diabetes before 6 months of age. A genetic diagnosis had been determined in 118 (77%), with 73 (47%) having a mutation in KCNJ11 or ABCC8. The median time from clinical diagnosis to genetic diagnosis was 10.4 weeks (range, 1.6 to 58.2 wk). In nine probands, an empiric sulfonylurea trial was initiated within 28 days of diabetes diagnosis. A genetic cause was subsequently found in eight cases, and insulin was discontinued within 14 days of sulfonylurea initiation in all of these cases.ConclusionsSulfonylurea therapy appears to be safe and often successful in neonatal diabetes patients before genetic testing results are available; however, larger numbers of cases must be studied. Given the potential beneficial effect on neurodevelopmental outcome, glycemic control, and the current barriers to expeditious acquisition of genetic testing, an empiric inpatient trial of sulfonylurea can be considered. However, obtaining a genetic diagnosis remains imperative to inform long-term management and prognosis.
Project description:With the advent of nanotechnology, the prospects for using engineered nanomaterials with diameters of < 100 nm in industrial applications, medical imaging, disease diagnoses, drug delivery, cancer treatment, gene therapy, and other areas have progressed rapidly. The potential for nanoparticles (NPs) in these areas is infinite, with novel new applications constantly being explored. The possible toxic health effects of these NPs associated with human exposure are unknown. Many fine particles generally considered "nuisance dusts" are likely to acquire unique surface properties when engineered to nanosize and may exhibit toxic biological effects. Consequently, the nuisance dust may be transported to distant sites and could induce adverse health effects. In addition the beneficial uses of NPs in drug delivery, cancer treatment, and gene therapy may cause unintentional human exposure. Because of our lack of knowledge about the health effects associated with NP exposure, we have an ethical duty to take precautionary measures regarding their use. In this review we highlight the possible toxic human health effects that can result from exposure to ultrafine particles (UFPs) generated by anthropogenic activities and their cardiopulmonary outcomes. The comparability of engineered NPs to UFPs suggests that the human health effects are likely to be similar. Therefore, it is prudent to elucidate their toxicologic effect to minimize occupational and environmental exposure. Highlighting the human health outcomes caused by UFPs is not intended to give a lesser importance to either the unprecedented technologic and industrial rewards of the nanotechnology or their beneficial human uses.
Project description:ObjectivesPopulation compliance greatly influences the effectiveness of vaccination and non-pharmaceutical interventions (NPIs) for the curtaining of COVID-19 transmission. We aimed to determine the conceptual framework of potential factors that influence compliance.Study designThis was a cross-sectional study.MethodsQuestionnaires were used to survey population attitudes toward vaccination and NPIs in China. Confirmatory factor analysis of the survey data by structural equation model was used to define the pros and cons factors of attitudes. The strength and direction of each factor's effect on population attitudes were illustrated by Bayesian network analysis.ResultsA total of 1700 respondents aged 18-70 years were surveyed with a panel of 34 questionnaires. Of these questionnaires, the confirmatory factor and structural equation model analysis identified five categories contributing to positive attitudes, including response efficiency, willingness and behavior, trust, cues to action, and knowledge, as well as four categories contributing to negative attitudes, including autonomy, perceived barriers, threat, and mental status. Bayesian networks revealed that cues to action produced a driving force for positive attitudes, followed by willingness and behavior, trust, response efficiency, and knowledge, whereas perceived barriers produced a driving force for negative attitudes, followed by autonomy and threat.ConclusionsThis study established a concise and representative list of questionnaires that could be applied to investigate the conceptual framework of potential pros and cons factors of attitudes toward vaccination and NPIs for COVID-19 prevention. The factors with driving forces should be addressed with a priority to effectively improve population compliance.
Project description:Coronavirus disease-2019 (COVID-19) has become a major global epidemic. Facilitated by HTS2 technology, we evaluated the effects of 578 herbs and all 338 reported anti-COVID-19 TCM formulae on cytokine storm-related signaling pathways, and identified the key targets of the relevant pathways and potential active ingredients in these herbs. This large-scale transcriptional study innovatively combines HTS2 technology with bioinformatics methods and computer-aided drug design. For the first time, it systematically explores the molecular mechanism of TCM in regulating the COVID-19-related cytokine storm, providing an important scientific basis for elucidating the mechanism of action of TCM in treating COVID-19.
Project description:Intracellular transport is one of the most confusing issues in the field of cell biology. Many different models and their combinations have been proposed to explain the experimental data on intracellular transport. Here, we analyse the data related to the mechanisms of endoplasmic reticulum-to-Golgi and intra-Golgi transport from the point of view of the main models of intracellular transport; namely: the vesicular model, the diffusion model, the compartment maturation-progression model, and the kiss-and-run model. This review initially describes our current understanding of Golgi function, while highlighting the recent progress that has been made. It then continues to discuss the outstanding questions and potential avenues for future research with regard to the models of these transport steps. To compare the power of these models, we have applied the method proposed by K. Popper; namely, the formulation of prohibitive observations according to, and the consecutive evaluation of, previous data, on the basis on the new models. The levels to which the different models can explain the experimental observations are different, and to date, the most powerful has been the kiss-and-run model, whereas the least powerful has been the diffusion model.