A "trained immunity" inducer-adjuvanted nanovaccine reverses the growth of established tumors in mice.

Innate immune cells are critical in antitumor immune surveillance and the development of antitumor adaptive cellular immunity. Trained innate immune cells demonstrate immune memory-like characteristics, producing more vigorous immune responses to secondary homologous or heterologous stimuli. This study aimed to investigate whether inducing trained immunity is beneficial when using a tumor vaccine to promote antitumor adaptive immune responses. A biphasic delivery system was developed with the trained immunity inducer Muramyl Dipeptide (MDP) and specific tumor antigen human papillomavirus (HPV) E7 peptide encapsulated by poly(lactide-co-glycolide)-acid(PLGA) nanoparticles (NPs), and the NPs along with another trained immunity agonist, ß-glucan, were further embedded in a sodium alginate hydrogel. The nanovaccine formulation demonstrated a depot effect for E7 at the injection site and targeted delivery to the lymph nodes and dendritic cells (DCs). The antigen uptake and maturation of DCs were significantly promoted. A trained immunity phenotype, characterized by increased production of IL-1ß, IL-6, and TNF-α, was induced in vitro and in vivo in response to secondary homologous or heterologous stimulation. Furthermore, prior innate immune training enhanced the antigen-specific INF-γ-expressing immune cell response elicited by subsequent stimulation with the nanovaccine. Immunization with the nanovaccine completely inhibited the growth of TC-1 tumors and even abolished established tumors in mice. Mechanistically, the inclusion of ß-glucan and MDP significantly enhanced the responses of tumor-specific effector adaptive immune cells. The results strongly suggest that the controlled release and targeted delivery of an antigen and trained immunity inducers with an NP/hydrogel biphasic system can elicit robust adaptive immunity, which provides a promising tumor vaccination strategy.

Assessing COVID-19 pandemic policies and behaviours and their economic and educational trade-offs across US states from Jan 1, 2020, to July 31, 2022: an observational analysis.

BACKGROUND: The USA struggled in responding to the COVID-19 pandemic, but not all states struggled equally. Identifying the factors associated with cross-state variation in infection and mortality rates could help to improve responses to this and future pandemics. We sought to answer five key policy-relevant questions regarding the following: 1) what roles social, economic, and racial inequities had in interstate variation in COVID-19 outcomes; 2) whether states with greater health-care and public health capacity had better outcomes; 3) how politics influenced the results; 4) whether states that imposed more policy mandates and sustained them longer had better outcomes; and 5) whether there were trade-offs between a state having fewer cumulative SARS-CoV-2 infections and total COVID-19 deaths and its economic and educational outcomes. METHODS: Data disaggregated by US state were extracted from public databases, including COVID-19 infection and mortality estimates from the Institute for Health Metrics and Evaluation's (IHME) COVID-19 database; Bureau of Economic Analysis data on state gross domestic product (GDP); Federal Reserve economic data on employment rates; National Center for Education Statistics data on student standardised test scores; and US Census Bureau data on race and ethnicity by state. We standardised infection rates for population density and death rates for age and the prevalence of major comorbidities to facilitate comparison of states' successes in mitigating the effects of COVID-19. We regressed these health outcomes on prepandemic state characteristics (such as educational attainment and health spending per capita), policies adopted by states during the pandemic (such as mask mandates and business closures), and population-level behavioural responses (such as vaccine coverage and mobility). We explored potential mechanisms connecting state-level factors to individual-level behaviours using linear regression. We quantified reductions in state GDP, employment, and student test scores during the pandemic to identify policy and behavioural responses associated with these outcomes and to assess trade-offs between these outcomes and COVID-19 outcomes. Significance was defined as p<0·05. FINDINGS: Standardised cumulative COVID-19 death rates for the period from Jan 1, 2020, to July 31, 2022 varied across the USA (national rate 372 deaths per 100 000 population [95% uncertainty interval [UI] 364-379]), with the lowest standardised rates in Hawaii (147 deaths per 100 000 [127-196]) and New Hampshire (215 per 100 000 [183-271]) and the highest in Arizona (581 per 100 000 [509-672]) and Washington, DC (526 per 100 000 [425-631]). A lower poverty rate, higher mean number of years of education, and a greater proportion of people expressing interpersonal trust were statistically associated with lower infection and death rates, and states where larger percentages of the population identify as Black (non-Hispanic) or Hispanic were associated with higher cumulative death rates. Access to quality health care (measured by the IHME's Healthcare Access and Quality Index) was associated with fewer total COVID-19 deaths and SARS-CoV-2 infections, but higher public health spending and more public health personnel per capita were not, at the state level. The political affiliation of the state governor was not associated with lower SARS-CoV-2 infection or COVID-19 death rates, but worse COVID-19 outcomes were associated with the proportion of a state's voters who voted for the 2020 Republican presidential candidate. State governments' uses of protective mandates were associated with lower infection rates, as were mask use, lower mobility, and higher vaccination rate, while vaccination rates were associated with lower death rates. State GDP and student reading test scores were not associated with state COVD-19 policy responses, infection rates, or death rates. Employment, however, had a statistically significant relationship with restaurant closures and greater infections and deaths: on average, 1574 (95% UI 884-7107) additional infections per 10 000 population were associated in states with a one percentage point increase in employment rate. Several policy mandates and protective behaviours were associated with lower fourth-grade mathematics test scores, but our study results did not find a link to state-level estimates of school closures. INTERPRETATION: COVID-19 magnified the polarisation and persistent social, economic, and racial inequities that already existed across US society, but the next pandemic threat need not do the same. US states that mitigated those structural inequalities, deployed science-based interventions such as vaccination and targeted vaccine mandates, and promoted their adoption across society were able to match the best-performing nations in minimising COVID-19 death rates. These findings could contribute to the design and targeting of clinical and policy interventions to facilitate better health outcomes in future crises. FUNDING: Bill & Melinda Gates Foundation, J Stanton, T Gillespie, J and E Nordstrom, and Bloomberg Philanthropies.

Plasma kallikrein in inflammation

As an important component of kallikrein-kinin system(KKS), plasma kallikrein(pKal) is involved in inflammation process via KKS, complement system and renin-angiotensin system(RAS)and plays an important role in angioedema(HAE), rheumatoid arthritis(RA)and corona virus disease 2019(COVID-19). pKal maybe a therapeutic target against inflammatory diseases, and pKal inhibitors are being researched and developed for the prevention and treatment of inflammatory diseases such as HAE and RA, and may also be new agents for the prevention and treatment of COVID-19.

Challenges of epidemiological investigation work in the COVID-19 pandemic: a qualitative study of the epidemiology workforce in Guangdong Province, China.

OBJECTIVES: This study sought to identify the epidemiological investigation challenges of the COVID-19 pandemic and offer insights into the underlying issues. DESIGN: An exploratory qualitative study used thematic analysis of semistructured and in-depth individual interviews. SETTING: This study was conducted in Centers for Disease Control and Prevention in Guangdong Province. PARTICIPANTS: Twenty-four participants consented to participate in an in-depth interview. Transcribed recordings were managed using NVivo software and analysed using inductive thematic analysis. RESULTS: The qualitative analysis revealed five key themes: high-intensity epidemiological investigation task, emergency management requiring improvement in the early stage, respondent uncertainty, impact on work and social life and inadequate early-stage Joint Prevention and Control Mechanism. CONCLUSION: This survey focuses on the epidemiology workforce at the forefront of the COVID-19 pandemic and qualitatively describes their experiences, vocational issues and psychological stressors. We found that the problems of epidemiological investigation posed intense challenges to the epidemiology workforce. These findings highlight the epidemiological investigation challenges associated with this pandemic. We have provided some suggestions that may help improve the efficiency and quality of the epidemiology workforce in China.

Estimating the cause-specific relative risks of non-optimal temperature on daily mortality: a two-part modelling approach applied to the Global Burden of Disease Study.

BACKGROUND: Associations between high and low temperatures and increases in mortality and morbidity have been previously reported, yet no comprehensive assessment of disease burden has been done. Therefore, we aimed to estimate the global and regional burden due to non-optimal temperature exposure. METHODS: In part 1 of this study, we linked deaths to daily temperature estimates from the ERA5 reanalysis dataset. We modelled the cause-specific relative risks for 176 individual causes of death along daily temperature and 23 mean temperature zones using a two-dimensional spline within a Bayesian meta-regression framework. We then calculated the cause-specific and total temperature-attributable burden for the countries for which daily mortality data were available. In part 2, we applied cause-specific relative risks from part 1 to all locations globally. We combined exposure-response curves with daily gridded temperature and calculated the cause-specific burden based on the underlying burden of disease from the Global Burden of Diseases, Injuries, and Risk Factors Study, for the years 1990-2019. Uncertainty from all components of the modelling chain, including risks, temperature exposure, and theoretical minimum risk exposure levels, defined as the temperature of minimum mortality across all included causes, was propagated using posterior simulation of 1000 draws. FINDINGS: We included 64·9 million individual International Classification of Diseases-coded deaths from nine different countries, occurring between Jan 1, 1980, and Dec 31, 2016. 17 causes of death met the inclusion criteria. Ischaemic heart disease, stroke, cardiomyopathy and myocarditis, hypertensive heart disease, diabetes, chronic kidney disease, lower respiratory infection, and chronic obstructive pulmonary disease showed J-shaped relationships with daily temperature, whereas the risk of external causes (eg, homicide, suicide, drowning, and related to disasters, mechanical, transport, and other unintentional injuries) increased monotonically with temperature. The theoretical minimum risk exposure levels varied by location and year as a function of the underlying cause of death composition. Estimates for non-optimal temperature ranged from 7·98 deaths (95% uncertainty interval 7·10-8·85) per 100 000 and a population attributable fraction (PAF) of 1·2% (1·1-1·4) in Brazil to 35·1 deaths (29·9-40·3) per 100 000 and a PAF of 4·7% (4·3-5·1) in China. In 2019, the average cold-attributable mortality exceeded heat-attributable mortality in all countries for which data were available. Cold effects were most pronounced in China with PAFs of 4·3% (3·9-4·7) and attributable rates of 32·0 deaths (27·2-36·8) per 100 000 and in New Zealand with 3·4% (2·9-3·9) and 26·4 deaths (22·1-30·2). Heat effects were most pronounced in China with PAFs of 0·4% (0·3-0·6) and attributable rates of 3·25 deaths (2·39-4·24) per 100 000 and in Brazil with 0·4% (0·3-0·5) and 2·71 deaths (2·15-3·37). When applying our framework to all countries globally, we estimated that 1·69 million (1·52-1·83) deaths were attributable to non-optimal temperature globally in 2019. The highest heat-attributable burdens were observed in south and southeast Asia, sub-Saharan Africa, and North Africa and the Middle East, and the highest cold-attributable burdens in eastern and central Europe, and central Asia. INTERPRETATION: Acute heat and cold exposure can increase or decrease the risk of mortality for a diverse set of causes of death. Although in most regions cold effects dominate, locations with high prevailing temperatures can exhibit substantial heat effects far exceeding cold-attributable burden. Particularly, a high burden of external causes of death contributed to strong heat impacts, but cardiorespiratory diseases and metabolic diseases could also be substantial contributors. Changes in both exposures and the composition of causes of death drove changes in risk over time. Steady increases in exposure to the risk of high temperature are of increasing concern for health. FUNDING: Bill & Melinda Gates Foundation.

Parental education and inequalities in child mortality: a global systematic review and meta-analysis.

BACKGROUND: The educational attainment of parents, particularly mothers, has been associated with lower levels of child mortality, yet there is no consensus on the magnitude of this relationship globally. We aimed to estimate the total reductions in under-5 mortality that are associated with increased maternal and paternal education, during distinct age intervals. METHODS: This study is a comprehensive global systematic review and meta-analysis of all existing studies of the effects of parental education on neonatal, infant, and under-5 child mortality, combined with primary analyses of Demographic and Health Survey (DHS) data. The literature search of seven databases (CINAHL, Embase, MEDLINE, PsycINFO, PubMed, Scopus, and Web of Science) was done between Jan 23 and Feb 8, 2019, and updated on Jan 7, 2021, with no language or publication date restrictions. Teams of independent reviewers assessed each record for its inclusion of individual-level data on parental education and child mortality and excluded articles on the basis of study design and availability of relevant statistics. Full-text screening was done in 15 languages. Data extracted from these studies were combined with primary microdata from the DHS for meta-analyses relating maternal or paternal education with mortality at six age intervals: 0-27 days, 1-11 months, 1-4 years, 0-4 years, 0-11 months, and 1 month to 4 years. Novel mixed-effects meta-regression models were implemented to address heterogeneity in referent and exposure measures among the studies and to adjust for study-level covariates (wealth or income, partner's years of schooling, and sex of the child). This study was registered with PROSPERO (CRD42020141731). FINDINGS: The systematic review returned 5339 unique records, yielding 186 included studies after exclusions. DHS data were compiled from 114 unique surveys, capturing 3 112 474 livebirths. Data extracted from the systematic review were synthesized together with primary DHS data, for meta-analysis on a total of 300 studies from 92 countries. Both increased maternal and paternal education showed a dose-response relationship linked to reduced under-5 mortality, with maternal education emerging as a stronger predictor. We observed a reduction in under-5 mortality of 31·0% (95% CI 29·0-32·6) for children born to mothers with 12 years of education (ie, completed secondary education) and 17·3% (15·0-18·8) for children born to fathers with 12 years of education, compared with those born to a parent with no education. We also showed that a single additional year of schooling was, on average, associated with a reduction in under-5 mortality of 3·04% (2·82-3·23) for maternal education and 1·57% (1·35-1·72) for paternal education. The association between higher parental education and lower child mortality was significant for both parents at all ages studied and was largest after the first month of life. The meta-analysis framework incorporated uncertainty associated with each individual effect size into the model fitting process, in an effort to decrease the risk of bias introduced by study design and quality. INTERPRETATION: To our knowledge, this study is the first effort to systematically quantify the transgenerational importance of education for child survival at the global level. The results showed that lower maternal and paternal education are both risk factors for child mortality, even after controlling for other markers of family socioeconomic status. This study provides robust evidence for universal quality education as a mechanism to achieve the Sustainable Development Goal target 3.2 of reducing neonatal and child mortality. FUNDING: Research Council of Norway, Bill & Melinda Gates Foundation, and Rockefeller Foundation-Boston University Commission on Social Determinants, Data, and Decision Making (3-D Commission).

Label-Free Spectroscopic SARS-CoV-2 Detection on Versatile Nanoimprinted Substrates.

Widespread testing and isolation of infected patients is a cornerstone of viral outbreak management, as underscored during the ongoing COVID-19 pandemic. Here, we report a large-area and label-free testing platform that combines surface-enhanced Raman spectroscopy and machine learning for the rapid and accurate detection of SARS-CoV-2. Spectroscopic signatures acquired from virus samples on metal-insulator-metal nanostructures, fabricated using nanoimprint lithography and transfer printing, can provide test results within 25 min. Not only can our technique accurately distinguish between different respiratory and nonrespiratory viruses, but it can also detect virus signatures in physiologically relevant matrices such as human saliva without any additional sample preparation. Furthermore, our large area nanopatterning approach allows sensors to be fabricated on flexible surfaces allowing them to be mounted on any surface or used as wearables. We envision that our versatile and portable label-free spectroscopic platform will offer an important tool for virus detection and future outbreak preparedness.

Evolutionary Game Analysis of Co-Opetition Strategy in Energy Big Data Ecosystem under Government Intervention

This study discusses how to facilitate the barrier-free circulation of energy big data among multiple entities and how to balance the energy big data ecosystem under government supervision using dynamic game theory. First, we define the related concepts and summarize the recent studies and developments of energy big data. Second, evolutionary game theory is applied to examine the interaction mechanism of complex behaviors between power grid enterprises and third-party enterprises in the energy big data ecosystem, with and without the supervision of government. Finally, a sensitivity analysis is conducted on the main factors affecting co-opetition, such as the initial participation willingness, distribution of benefits, free-riding behavior, government funding, and punitive liquidated damages. The results show that both government supervision measures and the participants’ own will have an impact on the stable evolution of the energy big data ecosystem in the dynamic evolution process, and the effect of parameter changes on the evolution is more significant under the state of no government supervision. In addition, the effectiveness of the developed model in this work is verified by simulated analysis. The present model can provide an important reference for overall planning and efficient operation of the energy big data ecosystem.

Estimating global and regional disruptions to routine childhood vaccine coverage during the COVID-19 pandemic in 2020: a modelling study.

BACKGROUND: The COVID-19 pandemic and efforts to reduce SARS-CoV-2 transmission substantially affected health services worldwide. To better understand the impact of the pandemic on childhood routine immunisation, we estimated disruptions in vaccine coverage associated with the pandemic in 2020, globally and by Global Burden of Disease (GBD) super-region. METHODS: For this analysis we used a two-step hierarchical random spline modelling approach to estimate global and regional disruptions to routine immunisation using administrative data and reports from electronic immunisation systems, with mobility data as a model input. Paired with estimates of vaccine coverage expected in the absence of COVID-19, which were derived from vaccine coverage models from GBD 2020, Release 1 (GBD 2020 R1), we estimated the number of children who missed routinely delivered doses of the third-dose diphtheria-tetanus-pertussis (DTP3) vaccine and first-dose measles-containing vaccine (MCV1) in 2020. FINDINGS: Globally, in 2020, estimated vaccine coverage was 76·7% (95% uncertainty interval 74·3-78·6) for DTP3 and 78·9% (74·8-81·9) for MCV1, representing relative reductions of 7·7% (6·0-10·1) for DTP3 and 7·9% (5·2-11·7) for MCV1, compared to expected doses delivered in the absence of the COVID-19 pandemic. From January to December, 2020, we estimated that 30·0 million (27·6-33·1) children missed doses of DTP3 and 27·2 million (23·4-32·5) children missed MCV1 doses. Compared to expected gaps in coverage for eligible children in 2020, these estimates represented an additional 8·5 million (6·5-11·6) children not routinely vaccinated with DTP3 and an additional 8·9 million (5·7-13·7) children not routinely vaccinated with MCV1 attributable to the COVID-19 pandemic. Globally, monthly disruptions were highest in April, 2020, across all GBD super-regions, with 4·6 million (4·0-5·4) children missing doses of DTP3 and 4·4 million (3·7-5·2) children missing doses of MCV1. Every GBD super-region saw reductions in vaccine coverage in March and April, with the most severe annual impacts in north Africa and the Middle East, south Asia, and Latin America and the Caribbean. We estimated the lowest annual reductions in vaccine delivery in sub-Saharan Africa, where disruptions remained minimal throughout the year. For some super-regions, including southeast Asia, east Asia, and Oceania for both DTP3 and MCV1, the high-income super-region for DTP3, and south Asia for MCV1, estimates suggest that monthly doses were delivered at or above expected levels during the second half of 2020. INTERPRETATION: Routine immunisation services faced stark challenges in 2020, with the COVID-19 pandemic causing the most widespread and largest global disruption in recent history. Although the latest coverage trajectories point towards recovery in some regions, a combination of lagging catch-up immunisation services, continued SARS-CoV-2 transmission, and persistent gaps in vaccine coverage before the pandemic still left millions of children under-vaccinated or unvaccinated against preventable diseases at the end of 2020, and these gaps are likely to extend throughout 2021. Strengthening routine immunisation data systems and efforts to target resources and outreach will be essential to minimise the risk of vaccine-preventable disease outbreaks, reach children who missed routine vaccine doses during the pandemic, and accelerate progress towards higher and more equitable vaccination coverage over the next decade. FUNDING: Bill & Melinda Gates Foundation.

Shifting moods on Sina Weibo: The first 12 weeks of COVID-19 in Wuhan

Better understanding of social media uses in crisis situations can help improve disaster management by policy-makers, organizations, businesses, and members of the public. It can also build theoretical understanding of how social life and citizenship incorporate social media usage. This study tracks the evolution of public sentiment in Wuhan, China, during the first 12?weeks after the identification of COVID-19 on the Chinese microblogging platform Sina Weibo. Data consist of 133,079 original Sina Weibo posts dealing with the novel coronavirus. The relative prevalence of eight different emotion groups is traced longitudinally using the ROST Content Mining System and the Emotion Vocabulary of Dalian University of Technology. The study finds a progression from confusion/fear, to disappointment/frustration, to depressionxiety, then finally to happiness/gratitude. It argues that this progression indexes the changing affective energies of digital medical citizenship, which in turn indicates the context for intervention in future crises.

N501Y mutation of spike protein in SARS-CoV-2 strengthens its binding to receptor ACE2.

SARS-CoV-2 has been spreading around the world for the past year. Recently, several variants such as B.1.1.7 (alpha), B.1.351 (beta), and P.1 (gamma), which share a key mutation N501Y on the receptor-binding domain (RBD), appear to be more infectious to humans. To understand the underlying mechanism, we used a cell surface-binding assay, a kinetics study, a single-molecule technique, and a computational method to investigate the interaction between these RBD (mutations) and ACE2. Remarkably, RBD with the N501Y mutation exhibited a considerably stronger interaction, with a faster association rate and a slower dissociation rate. Atomic force microscopy (AFM)-based single-molecule force microscopy (SMFS) consistently quantified the interaction strength of RBD with the mutation as having increased binding probability and requiring increased unbinding force. Molecular dynamics simulations of RBD-ACE2 complexes indicated that the N501Y mutation introduced additional π-π and π-cation interactions that could explain the changes observed by force microscopy. Taken together, these results suggest that the reinforced RBD-ACE2 interaction that results from the N501Y mutation in the RBD should play an essential role in the higher rate of transmission of SARS-CoV-2 variants, and that future mutations in the RBD of the virus should be under surveillance.

Residual olfactory dysfunction in coronavirus disease 2019 patients after long term recovery.

INTRODUCTION: Hyposmia is among the most common symptoms of COVID-19 patients. Previous research has mainly described this issue at the disease's early stages. Because olfactory impairment can indicate neurological degeneration, we investigated the possibility of permanent olfactory damage by assessing hyposmia during the late recovery stage of COVID-19 patients. METHODS: Ninety-five patients were assessed with the Brief Smell Identification Test for Chinese (B-SITC) and Hyposmia Rating Scale (HRS) after 16 weeks from disease onset. Five weeks later, 41 patients were retested with B-SITC. RESULTS: At the first visit, hyposmia was identified in 26/82 (31.7%) and 22/95 (23.2%) of participants by HRS (HRS score ≤22) and B-SITC (B-SITC score <8), respectively. The rates of hyposmia in patients who performed B-SITC after 14-15 weeks, 16-17 weeks, and ≥18 weeks from disease onset were 7/25 (28%), 8/35 (23%) and 7/35 (20%), respectively, which demonstrated a trend of olfaction improvement as recovery time prolonging. Hyposmia percentages decreased from the first visit (34.1%) to the second visit (24.4%) for the 41 patients who completed 2 visits. B-SITC scores of the first-visit hyposmia participants increased significantly at the second visit (5.29 ± 2.02 to 8.29 ± 2.40; n = 14, P = 0.001). Severe cases tended to recover less than common cases. CONCLUSIONS: Hyposmia was present in up to one-third of COVID-19 patients after about 3 months from disease onset. Notable recovery of olfactory function was observed at a next 5-weeks follow-up. Clinical severity had little influence on olfactory impairment and recovery.

RBD-Modified Bacterial Vesicles Elicited Potential Protective Immunity against SARS-CoV-2.

The disease caused by SARS-CoV-2 infection threatens human health. In this study, we used high-pressure homogenization technology not only to efficiently drive the bacterial membrane to produce artificial vesicles but also to force the fusion protein ClyA-receptor binding domain (RBD) to pass through gaps in the bacterial membrane to increase the contact between ClyA-RBD and the membrane. Therefore, the load of ClyA-RBD on the membrane is substantially increased. Using this technology, we constructed a "ring-like" bacterial biomimetic vesicle (BBV) loaded with polymerized RBD (RBD-BBV). RBD-BBVs injected subcutaneously can accumulate in lymph nodes, promote antigen uptake and processing, and elicit SARS-CoV-2-specific humoral and cellular immune responses in mice. In conclusion, we evaluated the potential of this novel bacterial vesicle as a vaccine delivery system and provided a new idea for the development of SARS-CoV-2 vaccines.

Endosomal acidification inhibitors broadly inhibit influenza virus and coronavirus in vivo (preprint)

Influenza virus, coronavirus, and drug-resistant viruses are long-term threats to public health because of lacking effective antivirals. Thus, chemicals with broad-spectrum antiviral activities and low possibility to induce drug resistance are urgently needed. Here, we identify a peptidic inhibitor P16 significantly inhibiting influenza A/B virus by binding to HA to block viral fusion. Moreover, P16 antagonizes endosomal acidification to suppress influenza virus and SARS-CoV-2 entry through the endocytic pathway. Importantly, endosomal acidification inhibitor P16 or chloroquine can broadly inhibit A(H1N1) virus, SARS-CoV and SARS-CoV-2 replication in mice and hamsters when administrated through intranasal inoculation or atomization inhalation, contrary to reported treatment failure by systemic route. Chloroquine can significantly inhibit SARS-CoV-2 replication in ex vivo human lung tissues. In conclusion, endosomal acidification inhibitors (P16 and chloroquine) can broadly inhibit influenza virus and coronavirus replication in vivo, which supports atomization inhalation of chloroquine for treating coronavirus and influenza patients in clinical trials.

Clinical symptoms between severe and non-severe COVID-19 pneumonia: A protocol for systematic review and meta-analysis.

BACKGROUND: Coronavirus disease 2019, (COVID-19) is a major problem in public health in the world. Up to June, 2020, the number of infections arising to 8,690,000 and cause 410,000 deaths all over the world. Identification the clinical symptoms from non-severe to severe is important for clinician. This meta-analysis aimed to compare the clinical symptoms between severe and non-severe COVID-19 pneumonia. METHODS: Electronic databases including PubMed, EMBASE, Web of Science, China National Knowledge Infrastructure database, Wanfang Database and Chinese Biomedical Literature Database were searched from its inception to June 21, 2020. We only included severe versus non-severe COVID-19 pneumonia patients and pooled results were summarized by STATA 12.0 software.Two researchers independently selected the study and assessed the quality of the included studies. The heterogeneity was measured by I tests (I < 50 indicates little heterogeneity, I≥50 indicates high heterogeneity). Publication bias was ruled out by funnel plot and statistically assessed by Begg test (P > .05 as no publication bias). RESULTS: Results will be published in relevant peer-reviewed journals. CONCLUSION: Our study aims to systematically present the clinical symptoms between non-severe and severe of COVID-19 patients, which will be provide clinical guidance for COVID-19 patients.

Assessment of the quality of systematic reviews on COVID-19: A comparative study of previous coronavirus outbreaks.

Several systematic reviews (SRs) have been conducted on the COVID-19 outbreak, which together with the SRs on previous coronavirus outbreaks, form important sources of evidence for clinical decision and policy making. Here, we investigated the methodological quality of SRs on COVID-19, severe acute respiratory syndrome (SARS), and Middle East respiratory syndrome (MERS). Online searches were performed to obtain SRs on COVID-19, SARS, and MERS. The methodological quality of the included SRs was assessed using the AMSTAR-2 tool. Descriptive statistics were used to present the data. In total, of 49 SRs that were finally included in our study, 17, 16, and 16 SRs were specifically on COVID-19, MERS, and SARS, respectively. The growth rate of SRs on COVID-19 was the highest (4.54/month) presently. Of the included SRs, 6, 12, and 31 SRs were of moderate, low, and critically low quality, respectively. SRs on SARS showed the optimum quality among the SRs on the three diseases. Subgroup analyses showed that the SR topic (P < .001), the involvement of a methodologist (P < .001), and funding support (P = .046) were significantly associated with the methodological quality of the SR. According to the adherence scores, adherence to AMSTAR-2 items sequentially decreased in SRs on SARS, MERS, and COVID-19. The methodological quality of most SRs on coronavirus outbreaks is unsatisfactory, and those on COVID-19 have higher risks of poor quality, despite the rapid actions taken to conduct SRs. The quality of SRs should be improved in the future. Readers must exercise caution in accepting and using the results of these SRs.