To expand our understanding of the epidemiology of avian coronavirus (ACoV) in China, the risk-based active surveillance was carried out in China in 2024. A total of 7,699 avian swab samples were collected from 153 sampling sites in 13 provinces. One thousand fifty hundred and eighty-six ACoVs were detected and identified by RT-PCR and sequencing with a positive rate of 20.60 %, including 1,125 strains of avian infectious bronchitis virus (IBV), 278 strains of duck coronavirus (DuCoV), 182 strains of pigeon coronavirus (PiCoV), and 1 strain of deltacoronavirus. Most ACoVs were detected from chickens, followed by pigeons, while others were collected from ducks and geese. The positivity rates for ACoV in poultry ranged from 2.91 % to 32.27 %. The viruses were detected from 86 sampling sites (56.21 %) in all 13 provinces surveyed. The positivity rates of ACoV in retail markets (98.08 %) and wholesale markets (100 %) were much higher than those in slaughterhouses (80.00 %) and poultry farms (20.25 %). 231 representative IBV strains from different regions were selected for S1 gene sequencing and genetic evolution analysis. The results revealed that the prevalent IBV in China comprised ten genotypes, meanwhile the recombinant variants were also detected. The viruses in GI-19 (35.06 %) and GVI-1 (33.77 %) were the predominant strains in China. Importantly, no cases of SARS-CoV-2 were found in the detected poultry samples. This study reveals the prevalence, distribution, genetic and phylogenetic characteristics of ACoV in China, and extends our understanding of the epidemiological context of ACoV in China.

This cross-sectional study presents socioecological, epidemiological aspects, and the seroprevalence of immunoglobulin G (IgG) against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a group of quilombola (afro-derived) communities in the states of Pará and Tocantins, in the Brazilian Amazon, to evaluate the impact of SARS-CoV-2 prevalence among them.

A total of 551 individuals participated. The detection of anti-SARS-CoV-2 antibodies was performed using an enzyme immunoassay. Socioeconomic and ecological data was collected from all participants 7 years of age or older who were not previously vaccinated.

The seroprevalence of antibodies in both states was 40.7% and was associated with factors such as age group, contact with infected individuals, and being in lockdown inside the quilombos. In Pará, a statistically significant association was observed between seroprevalence and females, and the age group of 12-18 years. In addition, seroprevalence in Pará was higher than in Tocantins, and the reported use of masks was a protective factor, while in Tocantins, the reported use of masks was associated with the presence of antibodies. There was no association between the prevalence of antibodies and the presence of COVID-19 symptoms in Pará. However, in Tocantins, diarrhea and loss of taste were associated with infection.

Quilombola are highly vulnerable groups due to the long history of enslavement in Brazil. This is the first investigation of SARS-CoV-2 seroprevalence and its impact in these groups in the Amazon. The study helps us to understand the relationship of socioecological differences, behavioral characteristics, and the dynamics of viral transmission associated with the risk of infection by SARS-CoV-2 among traditional populations, and can be useful to the planning of more culturally adequate public health policies for future epidemics.

ObjectivesTo meet the high demand for polymerase chain reaction (PCR) tests to diagnose COVID-19 and rapidly control the outbreak, an efficient and safe molecular diagnostic protocol is necessary. In this study, we evaluated the efficacy and safety of the medical robot developed for non-face-to-face nasopharyngeal swab specimen collection.MethodsIn a nonclinical study, an otorhinolaryngologist collected swab specimens manually and using a medical robot. In a single-institution, randomized, open-label, prospective, exploratory clinical trial, nasopharyngeal swab specimens were collected from the enrolled participants both manually and by using the medical robot.ResultsEvaluation of the efficacy and safety of nasopharyngeal swab collection using a medical robot was assessed. After the operation of the robot, subjective discomfort experienced by the participants and any side effects or abnormalities in the nose were also monitored. Preliminary nonclinical data revealed comparable results between robotic and manual methods in terms of RNA metrics and cytokeratin-8 expression. Minor initial damage to A549 cells by the robot improved with subsequent use. In the clinical setting, the robot-assisted technique yielded a 92.31% detection rate for human RNase P, while the manual method achieved 100%. Post-swabbing discomfort reported by participants was similar for both methods and resolved within 48 h.ConclusionsThe medical robot system could efficiently, safely, and accurately collect nasopharyngeal swab samples in a non-face-to-face manner. Its installation in respiratory clinics, airports, or ports could minimize the infection risk between individuals and healthcare workers, thereby contributing to an efficient distribution of medical resources.

Efficient antibody responses are crucial for combating infectious diseases and vaccination remains a cornerstone of this effort. This study introduces a novel approach for enhancing immune responses in wild-type mice by utilizing pre-formed immune complexes, using the receptor-binding domain (RBD) of SARS-CoV-2 as a model antigen to illustrate the broader potential of the concept. Specifically, we found that pre-treating the antigen with bis-maleimide, a chemical linker that facilitates protein cross-linking, significantly enhances antibody production. Moreover, in vitro cross-linking of antigen to unrelated IgG using bis-maleimide generated immune complexes that markedly enhanced antigen-specific antibody responses, likely by mimicking natural memory-like mechanisms, suggesting that bis-maleimide pre-treated antigens may similarly engage IgG in vivo. In contrast, antigen crosslinking with IgA or IgM did not yield comparable effects, highlighting the unique capacity of IgG to boost immunogenicity. By leveraging the principles of immune memory, this study demonstrates the potential of pre-formed immune complexes to significantly enhance vaccine efficacy using an antigen-independent strategy broadly applicable to diverse pathogens.

The emergence of new human viruses with epidemic or pandemic potential has reaffirmed the urgency to develop effective broad-spectrum antivirals (BSAs) as part of a strategic framework for pandemic prevention and preparedness. To this end, the host nucleotide metabolic pathway has been subject to intense investigation in the search for host-targeting agents (HTAs) with potential BSA activity. In particular, human dihydroorotate dehydrogenase (hDHODH), a rate-limiting enzyme in the de novo pyrimidine biosynthetic pathway, has been identified as a preferential target of new HTAs. Viral replication in fact relies on cellular pyrimidine replenishment, making hDHODH an ideal HTA target. The depletion of the host pyrimidine pool that ensues the pharmacological inhibition of hDHODH activity elicits effective BSA activity through three distinct mechanisms: it blocks viral DNA and RNA synthesis; it activates effector mechanisms of the host innate antiviral response; and it mitigates the virus-induced inflammatory response. However, despite the spectacular results obtained in vitro, the hDHODH inhibitors examined as mono-drug therapies in animal models of human viral infections and in clinical trials have produced disappointing levels of overall antiviral efficacy. To overcome this inherent limitation, pharmacological strategies based on multi-drug combination treatments should be considered to enable efficacy of hDHODH-targeted antiviral therapies. Here, we review the state-of-the-art of antiviral applications of hDHODH inhibitors, discuss the challenges that have emerged from their testing in animal models and human clinical trials and consider how they might be addressed to advance the development of hDHODH inhibitors as BSA for the treatment of viral diseases.

Since SARS-CoV-2 has caused unprecedented changes in the epidemiology of other infectious diseases, investigations on coinfection between SARS-CoV-2 and one of the famous vector-borne diseases, malaria, are crucial for disease control, especially in malaria-endemic areas. The clinical profiles, possible mechanisms for interactions, and representative control measures of COVID-19 and malaria coinfections have recently garnered public attention. The overlap in epidemiology, infection incubation, and clinical symptoms between COVID-19 and malaria coinfections has been thoroughly discussed to provide a detailed diagnostic procedure for coinfections, thereby guiding appropriate clinical interventions. Immunological and genetic evidence has shown that previous malaria exposure may protect the body from the poor prognosis of COVID-19. ACE2 downregulation and TLR-induced pathways play a role in this protective effect, as do CD8 + and CD4 + T-cell activation and coinhibitory receptor upregulation, which help maintain a balance of immune reactions. Finally, multiple control measures for coinfections were discussed, and malaria control efforts were enriched in the context of COVID-19. These efforts included (1) developing vaccinations; (2) evaluating the efficacy of anti-malarial drugs in the SARS-CoV-2 treatment; (3) exploring recent advances in natural products that are potentially useful for coinfection treatment; (4) researching and implementing bioinsecticides for malaria control, such as gene-driven mosquitoes, fungi, and bacterial symbionts; and (5) improving national electronic disease surveillance platforms in malaria-endemic regions. At last, the above findings summarized valuable lessons about malaria and COVID-19 control and expedite further investigations on coinfections with complex clinical presentations.

Inter-kingdom communication between human microbiota and mast cells (MCs), as sentinels of innate immunity, is crucial in determining health and disease. This complex signaling hub involves micro-organisms and, more importantly, their metabolic products. Gut microbiota is the host's largest symbiotic ecosystem and, under physiological conditions, it plays a vital role in mediating MCs tolerogenic priming, thus ensuring immune homeostasis across organs. Conversely, intestinal dysbiosis of various etiologies promotes MC-oriented inflammation along major body axes, including gut-skin, gut-lung, gut-liver, and gut-brain. This review of international scientific literature provides a comprehensive overview of the cross-talk under investigation. This process is a key biological event involved in disease development across clinical fields, with significant prognostic and therapeutic implications for future research.

The rapid evolution of the COVID-19 virus has led to the development of different vaccine shots, each designed to combat specific variants and enhance overall efficacy. While vaccines have been crucial in controlling the spread of the virus, they can also cause adverse events (AEs). Understanding these relationships is vital for vaccine safety monitoring and surveillance.

In our study, we collected data from the Vaccine Adverse Event Reporting System (VAERS) and social media platforms (Twitter and Reddit) to extract relationships between COVID-19 vaccine shots and adverse events. The dataset comprised 771 relation pairs, enabling a comprehensive analysis of adverse event patterns. We employed state-of-the-art GPT models, including GPT-3.5 and GPT-4, alongside traditional models such as Recurrent Neural Networks (RNNs) and BioBERT, to extract these relationships. Additionally, we used two sets of post-processing rules to further refine the extracted relations. Evaluation metrics including precision, recall, and F1-score were used to assess the performance of our models in extracting these relationships accurately.

The most commonly reported AEs following the primary series of COVID-19 vaccines include arm soreness, fatigue, and headache, while the spectrum of AEs following boosters is more diverse. In relation extraction, fine-tuned GPT-3.5 with Sentence-based Relation Identification achieved the highest precision of 0.94 and a perfect recall of 1, resulting in an impressive F1 score of 0.97.

This study advances biomedical informatics by showing how large language models and deep learning models can extract relationships between vaccine shots and adverse events from VAERS and social media. These findings improve vaccine safety monitoring and clinical practice by enhancing our understanding of post-vaccination symptoms. The study sets a precedent for future research in natural language processing and biomedical informatics, with potential applications in pharmacovigilance and clinical decision-making.

This study updates the COVID-19 pandemic surveillance in East Asia and the Pacific region that we first conducted in 2020 with 2 additional years of data for the region.

First, we aimed to measure whether there was an expansion or contraction of the pandemic in East Asia and the Pacific region when the World Health Organization (WHO) declared the end of the COVID-19 public health emergency of international concern on May 5, 2023. Second, we used dynamic and genomic surveillance methods to describe the dynamic history of the pandemic in the region and situate the window of the WHO declaration within the broader history. Finally, we aimed to provide historical context for the course of the pandemic in East Asia and the Pacific region.

In addition to updates of traditional surveillance data and dynamic panel estimates from the original study, this study used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data to identify the appearance and duration of variants of concern. We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Finally, we conducted a 1-sided t test to determine whether the regional weekly speed was greater than an outbreak threshold of 10. We ran the test iteratively with 6 months of data across the sample period.

Several countries in East Asia and the Pacific region had COVID-19 transmission rates above an outbreak threshold at the point of the WHO declaration (Brunei, New Zealand, Australia, and South Korea). However, the regional transmission rate had remained below the outbreak threshold for 4 months. In the rolling 6-month window t test for regional outbreak status, the final P value ≤.10 implies a rejection of the null hypothesis (at the α=.10 level) that the region as a whole was not in an outbreak for the period from November 5, 2022, to May 5, 2023. From January 2022 onward, nearly every sequenced SARS-CoV-2 specimen in the region was identified as the Omicron variant.

While COVID-19 continued to circulate in East Asia and the Pacific region, transmission rates had fallen below outbreak status by the time of the WHO declaration. Compared to other global regions, East Asia and the Pacific region had the latest outbreaks driven by the Omicron variant. COVID-19 appears to be endemic in the region, no longer reaching the threshold for a pandemic definition. However, the late outbreaks raise uncertainty about whether the pandemic was truly over in the region at the time of the WHO declaration.

This study aims to investigate the potential association between non-selective RET kinase inhibitors and thyroid dysfunction (TD) by conducting a pharmacovigilance analysis using data from the US FDA Adverse Event Reporting System (FAERS).

Data for non-selective RET MKIs were obtained from the FAERS database, spanning the first quarter of 2015 to the fourth quarter of 2023. Disproportionality analysis was used to quantify the AE signals associated with non-selective RET MKIs and to identify TD AEs. Subgroup analyses and multivariate logistic regressions were used to assess the factors influencing the occurrence of TD AEs. Time-to-onset (TTO) analysis and the Weibull Shape Parameter (WSP) test were also performed.

Descriptive analysis revealed an increasing trend in TD adverse events linked to non-selective RET MKIs, with a notable proportion of serious reactions reported. Disproportionality analysis using ROR, PRR, BCPNN, and EBGM algorithms consistently demonstrated a positive association between Sunitinib, Cabozantinib, and Lenvatinib with TD adverse events. Subgroup analyses highlighted differential susceptibility to TD based on age, gender, and weight, with varying patterns observed for each inhibitor. Logistic regression analyses identified factors independently influencing the occurrence of TD adverse events, emphasizing the importance of age, gender, and weight in patient stratification. Time-to-onset analysis indicated early manifestation of TD adverse events following treatment with non-selective RET MKIs, with a decreasing risk over time.

The results of our study indicate a correlation between the use of non-selective RET MKIs and the occurrence of TD AEs. This may provide support for the clinical monitoring and risk identification of non-selective RET MKIs. Nevertheless, further clinical studies are required to substantiate the findings of this study.

During the COVID-19 pandemic, global health systems faced unprecedented challenges, as well as in maternal and neonatal health, thus this study aims to clarify the impacts of COVID-19 on maternal and neonatal disorders (MNDs), regional variations, and the role of economic support.

We have developed a counterfactual model integrating Autoregressive Integrated Moving Average and Long Short-Term Memory models to forecast the burden of MNDs from 2020 To et al., 2021, which was compared with the actual burden to quantify the specific impact of the COVID-19 pandemic on MNDs.

During the COVID-19 pandemic, the burden of MNDs surpassed predictions, particularly in Russia, where incidence was about 10.20% higher than expected. In Tokelau, neonatal disorders increased by 412.35% in DALYs. The incidence of maternal disorders in Russia has increased by 12.00%, with maternal abortion and miscarriage increasing by 23.08%. The incidence and prevalence of maternal hypertensive disorders, the incidence of hemolytic disease and other neonatal jaundice and neonatal preterm birth accelerated. In low and low-middle Socio-demographic Index countries, mortality rates from maternal abortion and miscarriage, maternal obstructed labor and uterine rupture, neonatal encephalopathy due to birth asphyxia and trauma significantly increased. Similarly, countries with a low economic support index saw higher burden for these conditions, with the burden decreasing as economic support improved.

The COVID-19 pandemic has disproportionately increased the burden of MNDs in countries with lower economic support, highlighting the critical need for strengthened global economic support, particularly in low- and middle-income countries.

This study aims to identify the risk factors associated with clinical outcomes and the proteomic changes in organs related to fatal SARS-CoV-2 infection within the super-elderly population. This retrospective analysis included all elderly individuals with COVID-19 admitted to the Second Medical Center of PLA General Hospital from December 2022 to January 2023. The follow-up period ended on March 30, 2023. During this time, epidemiological, demographic, laboratory, and outcome data were analyzed descriptively. Proteomic sequencing was performed on super-elderly patients who died from COVID-19 at different stages of the disease. A total of 352 elderly COVID-19 patients, with a mean age of 89.84 ± 8.54 years, were included in this study. During a median follow-up period of 98 days, 79 patients died. Deceased patients were older and more likely to have cardiovascular and cerebrovascular diseases, with a lower prevalence of lipid-lowering therapy. The number of deaths in the acute and post-acute phases were 34 and 45, respectively. Proteomics data suggest that the immune systems of patients who died in the acute phase underwent a more rapid and severe onslaught. Patients in the post-acute phase showed higher levels of viral genome replication and a more robust immune response. However, the over-activation of the immune system led to systemic organ dysfunction. Effective management of comorbidities may improve the prognosis of COVID-19 in super-elderly patients. The continuous replication of the SARS-CoV-2 virus and its subsequent impact on the immune system are critical determinants of survival time in this demographic.

We constructed a rapid infection risk assessment model for contacts of COVID-19. The improved Wells-Riley model was used to estimate the probability of infection for contacts of COVID-19 in the same place and evaluate their risk grades. We used COVID-19 outbreaks that were documented to validate the accuracy of the model. We analyzed the relationship between controllable factors and infection probability and constructed common scenarios to analyze the infection risk of contacts in different scenarios. The model showed the robustness of the fitting (mean relative error = 5.89%, mean absolute error = 2.03%, root mean squared error = 2.03%, R2 = 0.991). We found that improving ventilation from poorly ventilated to naturally ventilated and wearing masks can reduce the probability of infection by about two times. Contacts in places of light activity, loud talking or singing, and heavy exercise, oral breathing (e.g., gyms, KTV, choirs) were at higher risk of infection. The model constructed in this study can quickly and accurately assess the infection risk grades of COVID-19 contacts. Simply opening doors and windows for ventilation can significantly reduce the risk of infection in certain places. The places of light activity, loud talking or singing, and heavy exercise, oral breathing, should pay more attention to prevent and control transmission of the epidemic.

This review evaluated the frequency of, and outcomes associated with, bacterial, fungal, and viral coinfection with SARS-CoV-2 in Middle Eastern countries via a PubMed search through February 2023. Ninety articles reported bacterial (n = 57), fungal (n = 32), and viral (n = 32) coinfections. High frequencies of coinfection with COVID-19 were identified, with rates and outcomes varying by setting, pathogen, surveillance/detection method, population characteristics, and drug-resistance status. Mortality rates were higher in patients with community-acquired (10.0 -42.9 %) and hospital-acquired (51.5 -66 %) bacterial coinfection versus those without (10.5 -21.7 %). Outcomes were worse with than without fungal coinfection, and fatality rates with mucormycosis coinfection reached 66.7 %. Outcomes with viral coinfection were highly variable; however, some data suggested a positive corelation between COVID-19 severity and influenza A and adenovirus coinfection. The negative outcomes associated with bacterial, fungal and some viral coinfections in individuals with COVID-19 support regular vaccination against vaccine-preventable diseases caused by these pathogens, especially among at-risk populations.

The outbreak of the COVID-19 has seriously affected the whole society, and vaccines were the most effective means to contain the epidemic. This paper aims to determine the top 100 articles cited most frequently in COVID-19 vaccines and to analyze the research status and hot spots in this field through bibliometrics, to provide a reference for future research. We conducted a comprehensive search of the Web of Science Core Collection database on November 29, 2023, and identified the top 100 articles by ranking them from highest to lowest citation frequency. In addition, we analyzed the year of publication, citation, author, country, institution, journal, and keywords with Microsoft Excel 2019 and VOSviewer 1.6.18. Research focused on vaccine immunogenicity and safety, vaccine hesitancy, and vaccination intention.

This manuscript details the application of Isothermal Titration Calorimetry (ITC) to characterize the kinetics of 3CLpro, the main protease from the Severe Acute Respiratory Syndrome CoronaVirus-2 (SARS-CoV-2), and its inhibition by Ensitrelvir, a known non-covalent inhibitor. 3CLpro is essential for producing the proteins necessary for viral infection, which led to the COVID-19 pandemic. The ITC-based assay provided rapid and reliable measurements of 3CLpro activity, allowing for the direct derivation of the kinetic enzymatic constants KM and kcat by monitoring the thermal power required to maintain a constant temperature as the substrate is consumed. The manuscript highlights several advantages of the proposed ITC-based assay over traditional methods used to study 3CLpro, such as Förster Resonance Energy Transfer (FRET) and Liquid Chromatography-Mass Spectrometry (LC-MS) and overcomes the need for non-biological substrates or discontinuous post-reaction steps. The ease of application of the ITC method allowed for the determination of the temperature dependence of the catalytic constants, enabling the estimation of the reaction activation energy. Additionally, the assay was used to determine the inhibition mode and kinetic parameters for 3CLpro inhibition by Ensitrelvir. This molecule was revealed to act as a slow- and tight-binding inhibitor that forms an initial E•I complex (KI = 9.9 ± 0.7 nM) quickly transitioning to a tighter E•I* assembly (KI* = 1.1 ± 0.2 nM). This versatile calorimetric method is proposed for general use in the discovery and development of drugs targeting 3CLpro.

The COVID-19 pandemic, driven by the SARS-CoV-2 virus, necessitates the development of effective therapeutics. The main protease of the virus, Mpro, is a key target due to its crucial role in viral replication. Our study presents a novel approach combining ligand-based pharmacophore modeling with structure-based advanced virtual screening to identify potential inhibitors of Mpro. We screened around 200 million compounds using this integrated methodology, resulting in a shortlist of promising compounds. These were further scrutinized through molecular dynamics simulations, revealing their interaction dynamics with Mpro. Subsequent in vitro assays using the Mpro enzyme identified two compounds exhibiting significant micromolar inhibitory activity. These findings provide valuable scaffolds for the development of advanced therapeutics targeting Mpro. The comprehensive nature of our approach, spanning computational predictions to experimental validations, offers a robust pathway for rapid and efficient identification of potential drug candidates against COVID-19.

Interferon-induced protein 44-like (IFI44L) is regarded as an immune-related gene and is a member of interferon-stimulated genes (ISGs). They participate in network transduction, and its own epigenetic modifications, apoptosis, cell-matrix formation, and many other pathways in tumors, autoimmune diseases, and viral infections. The current review provides a comprehensive overview of the onset and biological mechanisms of IFI44L and its potential clinical applications in malignant tumors and non-neoplastic diseases.

This study aimed to describe the temporal trends in the age and sex burdens of lower respiratory infections (LRIs) in China and globally from 1990 to 2021 and to analyze their epidemiological characteristics to formulate corresponding strategies to control LRIs.

This study utilized open data from the Global Burden of Disease (GBD) database from 1990 to 2021 to assess the burden of disease based on the prevalence, incidence, mortality, years lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) of LRIs in China and globally. Moreover, a comprehensive comparative analysis of the epidemiological characteristics of LRIs in China and globally was conducted via the Joinpoint regression model, age-period-cohort model (APC model), and stratified analysis of the study method from multiple dimensions, such as age, sex, and period. Finally, we used an autoregressive integrated moving average (ARIMA) model to predict the disease burden in LRIs over the next 15 years.

From 1990 to 2021, China's age-standardized incidence, deaths, and disability-adjusted life year (DALY) rates per 100,000 people decreased from 5,481.13 (95% CI: 5,149.05, 5,836.35) to 2,853.81 (95% CI: 2,663.94, 3,067.55), from 60.65 (95% CI. 52.96, 66.66) to 14.03 (95% CI: 11.68, 17) and from 3,128.39 (95% CI: 2,724.11, 3,579.57) to 347.67 (95% CI: 301.28, 402.94). The global age-standardized incidence, deaths, and DALY rates per 100,000 people, on the other hand, decreased from 6,373.17 (95% CI: 5,993.51, 6,746.04) to 4,283.61 (95% CI: 4,057.03, 4,524.89) and from 61.81 (95% CI: 56.66, 66.74) to 28.67 (95% CI: 25.92, 31.07) and from 3,472.9 (95% CI: 3,090.71, 3,872.11) to 1,168.8 (95% CI: 1,016.96, 1,336.95). The decline in the aforementioned indicators is greater in the female population than in the male population, and the decrease in China is more pronounced than the global trend. In China, the age-standardized incidence and mortality rates of LRIs showed an annual average percentage change (AAPC) of -2.12 (95% CI: -2.20, -2.03) and -4.77 (95% CI: -5.14, -4.39), respectively. Globally, the age-standardized incidence and mortality rates for LRIs decreased by -1.28 (95% CI: -1.37, -1.18) and -2.47 (95% CI: -2.61, -2.32). By 2036, the incidence of lower respiratory infections (LRI) among men and women in China is projected to decrease by 36.55 and 46.87%, respectively, while the mortality rates are expected to decline to 12.67% for men and increase by 71.85% for women. In comparison, the global decline in LRI incidence is lower than that observed in China, yet the reduction in mortality rates is greater globally than in China.

Age-standardized incidence, mortality and disability-adjusted life years (DALYs) decreased more in China than at the global level between 1990 and 2021. Compared with the previous period, the COVID-19 pandemic has led to a significant decrease in the disease burden of LRIs. As the population continues to age, the disease burden of LRIs in the old adult population will become a major new public health challenge.

In the field of public health, the prevention and management of infectious diseases in rural regions have always been crucial. This study aims to analyze the factors influencing rural residents' Knowledge, Attitude, and Practices and their correlation with infection risk during the late stage of an epidemic, with a focus on the COVID-19 case.

A cross-sectional study was conducted in rural regions of China's Guangdong province, using a multi-stage sampling technique to select rural residents for a validated questionnaire survey in February 2023. Descriptive statistical method was used to describe the infection status of rural residents and Chi-Square Test was used to explore the influencing factors of Knowledge, Attitude and Practice in this population. Multivariable binary logistic regression analysis was conducted to determine the presence of a statistically significant association between explanatory variables and outcome variables at corresponding 95% CI.

A total of 3,125 rural residents were investigated, of whom 805 had never been infected with COVID-19. The survey participants had an average score of 5.84 ± 1.419 for COVID-19 knowledge. (The total score range is from 0 to 8. A score greater than 6.4 indicates good knowledge acquisition.) Regarding the attitude and practice sections, the average scores were 23.68 ± 3.169 and 23.45 ± 5.030, respectively. (The total score range of both these sections is from 0 to 32. A score greater than 25.6 represents positive attitudes and good practices.) The reduction of COVID-19 risk is significantly associated with an increase in Knowledge scores (p trend < 0.01). In stratified analyses, the Knowledge, Attitudes, and Practices scores of residents in each region have varying degrees of correlation with the risk of SARS-CoV-2 infection.

Rural residents' Knowledge, Attitudes, and Practices on COVID-19 prevention and control requires improvement. Efforts to promote their' perceptions and habits regarding COVID-19 prevention and control are crucial in reducing the risk of infection.

Metal ions perform important functions in the body and their concentrations in cells and tissues are tightly controlled. Alterations in metal homeostasis can occur in certain disease states including infection. In this study urinary excretion of several metals including calcium, cadmium, cobalt, copper, iron, magnesium, nickel, selenium, and zinc in Covid-19 patients (n=35) and control (n=60) individuals, spanning ages and sexes.

Urinary samples were analysed using ICP-MS and the differences in metal concentrations between the Covid-19-infected and control groups were assessed using multivariate data analysis and univariate data analysis employing Student's t-test and Pearson's correlation, with significance set at p<0.05.

The urinary concentrations of all metals analysed were significantly higher in the Covid-infected group (compared to controls), with the exception of copper, which was markedly reduced. The increase in calcium excretion was lower and magnesium excretion greater in Covid-19-positive individuals aged 41 or over compared to those aged 40 or lower. Whilst the increase in iron excretion was lower, and cobalt excretion greater in Covid-19-positive males compared to females.

The study highlights significant alterations in the handling of a range of metals in the body during Covid-19 infection. It also highlights both age and sex-specific differences in metal homeostasis. The results suggest an important role for copper in the body during Covid-19 infection and suggests that urinary concentrations of copper and other metals may serve as markers to predict progression of the disease.

The Coronavirus disease 2019 (COVID-19) pandemic has brought a heavy burden to the world, interestingly, it shares many clinical symptoms with systemic lupus erythematosus (SLE). It is unclear whether there is a similar pathological process between COVID-9 and SLE. In addition, we don't know how to treat SLE patients with COVID-19. In this study, we analyse the potential similar pathogenesis between SLE and COVID-19 and explore their possible drug regimens using bioinformatics and systems biology approaches.

The common differentially expressed genes (DEGs) were extracted from the COVID-19 datasets and the SLE datasets for functional enrichment, pathway analysis and candidate drug analysis.

Based on the two transcriptome datasets between COVID-19 and SLE, 325 common DEGs were selected. Hub genes were identified by protein-protein interaction (PPI) analysis. few found a variety of similar functional changes between COVID-19 and SLE, which may be related to the pathogenesis of COVID-19. Besides, we explored the related regulatory networks. Then, through drug target matching, we found many candidate drugs for patients with COVID-19 only or COVID-19 combined with SLE.

COVID-19 and SLE patients share many common hub genes, related pathways and regulatory networks. Based on these common targets, we found many potential drugs that could be used in treating patient with COVID-19 or COVID-19 combined with SLE.

Coronaviruses (CoVs) pose a threat to human health globally, as highlighted by severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS) and the COVID-19 pandemic. Bats from the Greater Mekong Subregion (GMS) are an important natural reservoir for CoVs. Here we report the differential prevalence of CoVs in bats within Yunnan Province across biological and ecological variables. We also show the coexistence of CoVs in individual bats and identify an additional putative host for SARS-related CoV, with higher dispersal capacity than other known hosts. Notably, 11 SARS-related coronaviruses (SARSr-CoVs) were discovered in horseshoe bats (family Rhinolophidae) and a Chinese water myotis bat (Myotis laniger) by pan-CoV detection and Illumina sequencing. Our findings facilitate an understanding of the fundamental features of the distribution and circulation of CoVs in nature as well as zoonotic spillover risk in the One health framework.

The coronavirus disease 2019 (COVID-19) has exhibited escalating contagion and resistance to immunity, resulting in a surge in infections and severe cases. This study endeavors to formulate two nomogram predictive models aimed at discerning patients at heightened risk of severe and fatal outcomes upon hospital admission. The primary objective is to enhance clinical management protocols and mitigate the incidence of severe illness and mortality associated with COVID-19.

1600 patients diagnosed with COVID-19 and discharged from Fujian Provincial Hospital were chosen as the subjects of this study. These patients were categorized into three groups: mild group (n = 940), severe group (n = 433), and fatal group (n = 227). The patients were randomly divided into training and validation cohorts in a 7:3 ratio. COVID-19 symptoms were treated as dependent variables, and univariate regression analysis was conducted for the laboratory indicators. Risk factors with p-values greater than 0.05 in the univariate regression analysis were eliminated. The remaining risk factors were then analyzed using direct multiple regression analysis to establish an unadjusted model. Subsequently, risk factors with p-values greater than 0.05 were further removed. Clinical characteristics were added to the model as adjustment factors, and the method of multiple stepwise regression analysis was employed to derive the final fully adjusted model. The severe and fatal COVID-19 models were converted into nomograms, respectively. Receiver operating characteristic (ROC) curves were utilized to evaluate the discrimination of the nomogram models. Calibration was assessed using the Hosmer-Lemeshow test and calibration curves. Clinical benefit was evaluated by decision curve analysis.

Compared to the mild group, individuals in the severe COVID-19 group exhibited significant increases in age, neutrophil (NEU), and lactate dehydrogenase (LDH) levels, alongside notable decreases in lymphocyte (LYM) and albumin (ALB) levels. Nomogram model incorporating age, NEU, LDH, LYM, and ALB demonstrated efficacy in predicting the onset of severe COVID-19 (AUC = 0.771). Furthermore, history of cerebral infarction and cancer, LDH and ALB as risk factors for fatal COVID-19 cases compared to the severe group. The nomogram model comprising these factors was capable of early identification of COVID-19 fatalities (AUC = 0.748).

Elevated age, NEU, and LDH levels, along with decreased LYM and albumin (ALB) levels, are risk factors for severe illness in hospitalized patients with COVID-19. A history of cerebral infarction and tumors, along with elevated LDH and decreased ALB levels, are risk factors for death in critically ill patients. The nomogram model based on these factors can effectively predict the risk of severe or fatal illness from COVID-19, thereby assisting clinicians in timely interventions to reduce the rates of severe illness and mortality among hospitalized patients. However, the model faces challenges in processing longitudinal data and specific points in time, indicating that there is room for improvement.

Remdesivir (Veklury, Gilead Sciences, Foster City, CA, USA) and nirmatrelvir-ritonavir (Paxlovid, Pfizer, New York, NY, USA) were reported to improve the outcome of patients with mild-to-moderate COVID-19 symptoms. Preclinical data suggest that nirmatrelvir-ritonavir might be more effective than remdesivir alone or in combination with nirmatrelvir-ritonavir for people at high risk of severe COVID-19. We aimed to assess the safety and effectiveness of combining remdesivir and nirmatrelvir-ritonavir compared with using each drug alone for adults hospitalised with COVID-19.

In this target trial emulation study, we used electronic health records of patients aged 18 years or older who received either combination treatment of nirmatrelvir-ritonavir and remdesivir or monotherapy of either drug between March 16 and Dec 31, 2022, within 5 days of hospitalisation for COVID-19 in Hong Kong. Inverse probability of treatment weighting was applied to balance baseline patient characteristics across the treatment groups. The primary outcome was all-cause mortality. Cox proportional hazards regression adjusting weighting was used to compare the risk of all-cause mortality, intensive care unit (ICU) admission, or ventilatory support for 90 days of follow-up between groups.

Between March 16 and Dec 31, 2022, 18 196 participants were identified from electronic health records and assigned to receive remdesivir (n=4232), nirmatrelvir-ritonavir (n=13 656), or nirmatrelvir-ritonavir and remdesivir (n=308). By applying an inverse probability of treatment weighting, a weighted sample composed of 18 410 recipients of nirmatrelvir-ritonavir and remdesivir combination treatment, 18 178 recipients of remdesivir monotherapy, and 18 287 recipients of nirmatrelvir-ritonavir monotherapy was obtained. After a median follow-up of 84 days (IQR 45-90), risk of mortality was lower in patients who received nirmatrelvir-ritonavir monotherapy (hazard ratio [HR] 0·18 [95% CI 0·15 to 0·20]; absolute risk reduction [ARR] -16·33% [95% CI -16·98 to -15·68]) or remdesivir and nirmatrelvir-ritonavir combination therapy (HR 0·66 [95% CI 0·49 to 0·89]; ARR -6·52% [95% CI -7·29 to -5·74]) than in patients who received remdesivir monotherapy. Similar results were observed for ICU admission or ventilatory support (nirmatrelvir-ritonavir monotherapy: HR 0·09 [95% CI 0·07 to 0·11]; ARR -10·04% [95% CI -10·53 to -9·56]; combination therapy: HR 0·68 [95% CI 0·42 to 1·12]; ARR -3·24% [95% CI -3·84 to -2·64]). Compared with combination therapy, nirmatrelvir-ritonavir monotherapy was associated with lower risk of mortality (HR 0·27 [95% CI 0·20 to 0·37]; ARR -9·81% [95% CI -10·39 to -9·24]) and ICU admission or ventilatory support (HR 0·13 [95% CI 0·08 to 0·22]; ARR -6·80% [95% CI -7·22 to -6·39]).

Our study highlighted the potential for reduced risk of mortality, ICU admission, or the need for ventilatory support in patients hospitalised with COVID-19 treated with nirmatrelvir-ritonavir as a monotherapy compared with treatment regimens based on nirmatrelvir-ritonavir and remdesivir combination therapy or remdesivir monotherapy. Further randomised controlled trials are needed to support the validity of the current results.

The Health and Medical Research Fund Commissioned Research on COVID-19.

For the Chinese translation of the abstract see Supplementary Materials section.

We aimed to describe the clinical characteristics associated with severity in children hospitalized with COVID-19.

This was an epidemiological cohort study conducted in two hospitals, one of which was a reference center for the treatment of COVID-19 cases. Data were collected from the reports generated by the hospital epidemiology centers and the medical records of patients aged between 0 and 14 years with a diagnosis of COVID-19, hospitalized between March 2020 and June 2021. To analyze the association between the clinical profile and severity, the cases were classified as severe (severe and critical) and non-severe (asymptomatic, mild, and moderate).

Of the 191 children followed up in the cohort, 73.3% developed the severe form. The percentage of children with oxygen saturation below 95% was 46.6%. In the multivariate analysis, a higher risk of severity was estimated among children with uncontrolled asthma (RR = 13.2), who were overweight or obese (RR = 3.21), who had cough symptoms (RR = 2.72), and those aged under one year (RR = 3.23).

This result underscores the need to improve healthcare at every level for children and for the management of asthma and nutrition when considering children with this clinical profile who are diagnosed with COVID-19.

The coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has killed millions of people and continues to wreak havoc across the globe. This sudden and deadly pandemic emphasizes the necessity for anti-viral drug development that can be rapidly administered to reduce morbidity, mortality, and virus propagation. Thus, lacking efficient anti-COVID-19 treatment, and especially given the lengthy drug development process as well as the critical death tool that has been associated with SARS-CoV-2 since its outbreak, drug repurposing (or repositioning) constitutes so far, the ideal and ready-to-go best approach in mitigating viral spread, containing the infection, and reducing the COVID-19-associated death rate. Indeed, based on the molecular similarity approach of SARS-CoV-2 with previous coronaviruses (CoVs), repurposed drugs have been reported to hamper SARS-CoV-2 replication. Therefore, understanding the inhibition mechanisms of viral replication by repurposed anti-viral drugs and chemicals known to block CoV and SARS-CoV-2 multiplication is crucial, and it opens the way for particular treatment options and COVID-19 therapeutics. In this review, we highlighted molecular basics underlying drug-repurposing strategies against SARS-CoV-2. Notably, we discussed inhibition mechanisms of viral replication, involving and including inhibition of SARS-CoV-2 proteases (3C-like protease, 3CLpro or Papain-like protease, PLpro) by protease inhibitors such as Carmofur, Ebselen, and GRL017, polymerases (RNA-dependent RNA-polymerase, RdRp) by drugs like Suramin, Remdesivir, or Favipiravir, and proteins/peptides inhibiting virus-cell fusion and host cell replication pathways, such as Disulfiram, GC376, and Molnupiravir. When applicable, comparisons with SARS-CoV inhibitors approved for clinical use were made to provide further insights to understand molecular basics in inhibiting SARS-CoV-2 replication and draw conclusions for future drug discovery research.

The aim of this study is to ascertain whether COVID-19 Omicron infection is associated with exacerbations in these myasthenia gravis (MG) patients.

In total, 289 MG patients (comprising 60% females, with an average age of 46 ± 15 years) were enrolled. A total of 80.9% of MG patients reported a COVID-19 infection, with the majority experiencing a benign course (88%). MG patients who experienced COVID-19 infection demonstrated a higher likelihood of MG exacerbation, compared to those without the infection (18.8% vs. 7.3%, p = 0.039). In the survival analysis, after adjusting for confounding factors, the hazard ratio (HR) for exacerbation post-infection was found to be 3.38 (95% CI 1.20-9.53, p = 0.021). Compared to the exacerbation rates observed in JTA21, an increase was noted in DTM23 among COVID-19-infected MG patients (4.4% vs. 17.2%, p < 0.001).

The COVID-19 is the risk of MG exacerbation.

Epidemics caused by pathogenic viruses are a severe threat to public health worldwide. Electromagnetic waves are a type of noncontact and nonionizing radiation technology that has emerged as an effective tool for inactivating bacterial pathogens. In this study, we used a 9.375 GHz electromagnetic wave to study the inactivation effect and mechanism of electromagnetic waves on MHV-A59, a substitute virus for pathogenic human coronavirus, and to evaluate the inactivation efficiency on different surface materials. We showed that 9.375 GHz electromagnetic waves inactivate MHV-A59 by destroying viral particles, envelopes, or genomes. We also found that 9.375 GHz electromagnetic waves can decrease the infectivity of viruses on the surface of inanimate materials such as plastic, glass, cloth, and wood. In conclusion, our results suggested that the 9.375 GHz electromagnetic wave is a promising disinfection technique for preventing the spread and infection of pathogenic viruses.

The international healthcare community has encountered several difficulties because of the COVID-19 pandemic brought on by SARS-CoV-2. COVID-19 can lead to an abnormal immune response that features excessive inflammation, so targeting the vagus nerve through non-invasive vagus nerve stimulation (nVNS) may hold promise as an intervention. This meta-analysis aimed to examine the outcomes of using nVNS on different inflammatory biomarkers in COVID-19 patients. Up until May 2023, we performed a review of online databases. We included randomized controlled trials (RCTs) that discussed how nVNS affected patients with COVID-19's clinical outcomes. Using the Revman 5.4 software (Cochrane, London, United Kingdom), a meta-analysis was carried out to find the pooled mean difference (MD), with 95% confidence intervals (CIs), of nVNS effects on different inflammatory biomarkers, including interleukin-10 (IL-10), C-reactive protein (CRP), IL-6, and cortisol levels. The review included four RCTs involving 180 COVID-19 patients. Following nVNS treatment, there was a significant increase in IL-10 levels (MD = 1.53, 95% CI: 0.77, 2.29; p < 0.001). CRP levels (MD = -2.24, 95% CI: -4.52, 0.05; p = 0.06), IL-6 levels (MD = 4.07, 95% CI: -3.16, 11.32; p = 0.27), cortisol levels (MD = 1.45, 95% CI: -11.67, 14.57; p = 0.83), and D-dimer levels (MD = -0.47, 95% CI: -1.31, 0.38; p = 0.28) did not differ significantly. These findings suggest that nVNS may positively impact certain inflammatory markers in COVID-19 patients, suggesting that nVNS could be a beneficial adjunctive treatment.

It is estimated that there are 544.9 million people suffering from chronic respiratory diseases in the world, which is the third largest chronic disease. Although there are various clinical treatment methods, there is no specific drug for chronic pulmonary diseases, including chronic obstructive pulmonary disease (COPD), interstitial lung disease (ILD) and idiopathic pulmonary fibrosis (IPF). Therefore, it is urgent to clarify the pathological mechanism and medication development. Single-cell transcriptome data of human and mouse from GEO database were integrated by "Harmony" algorithm. The data was standardized and normalized by using "Seurat" package, and "SingleR" algorithm was used for cell grouping annotation. The "Findmarker" function is used to find differentially expressed genes (DEGs), which were enriched and analyzed by using "clusterProfiler", and a protein interaction network was constructed for DEGs, and four algorithms are used to find the hub genes. The expression of hub genes were analyzed in independent human and mouse single-cell transcriptome data. Bulk RNA data were used to integrate by the "SVA" function, verify the expression levels of hub genes and build a diagnostic model. The L1000FWD platform was used to screen potential drugs. Through exploring the similarities and differences by integrated single-cell atlas, we found that the lung parenchymal cells showed abnormal oxidative stress, cell matrix adhesion and ubiquitination in COPD, corona virus disease 2019 (COVID-19), ILD and IPF. Meanwhile, the lung resident immune cells showed abnormal Toll-like receptor signals, interferon signals and ubiquitination. However, unlike acute pneumonia (COVID-19), chronic pulmonary disease shows enhanced ubiquitination. This phenomenon was confirmed in independent external human single-cell atlas, but unfortunately, it was not confirmed in mouse single-cell atlas of bleomycin-induced pulmonary fibrosis model and influenza virus-infected mouse model, which means that the model needs to be optimized. In addition, the bulk RNA-Seq data of COVID-19, ILD and IPF was integrated, and we found that the immune infiltration of lung tissue was enhanced, consistent with the single-cell level, UBA52, UBB and UBC were low expressed in COVID-19 and high expressed in ILD, and had a strong correlation with the expression of cell matrix adhesion genes. UBA52 and UBB have good diagnostic efficacy, and salermide and SSR-69071 can be used as their candidate drugs. Our study found that the disorder of protein ubiquitination in chronic pulmonary diseases is an important cause of pathological phenotype of pulmonary fibrosis by integrating scRNA-Seq and bulk RNA-Seq, which provides a new horizons for clinicopathology, diagnosis and treatment.

Understanding and addressing the dynamics of infectious diseases, such as coronavirus disease 2019, are essential for effectively managing the current situation and developing intervention strategies. Epidemiologists commonly use mathematical models, known as epidemiological equations (EE), to simulate disease spread. However, accurately estimating the parameters of these models can be challenging due to factors like variations in social distancing policies and intervention strategies. In this study, we propose a novel method called deep dynamic epidemiological modeling (DDE) to address these challenges. The DDE method combines the strengths of EE with the capabilities of deep neural networks to improve the accuracy of fitting real-world data. In DDE, we apply neural ordinary differential equations to solve variant-specific equations, ensuring a more precise fit for disease progression in different geographic regions. In the experiment, we tested the performance of the DDE method and other state-of-the-art methods using real-world data from five diverse geographic entities: the USA, Colombia, South Africa, Wuhan in China, and Piedmont in Italy. Compared to the state-of-the-art method, DDE significantly improved accuracy, with an average fitting Pearson coefficient exceeding 0.97 across the five geographic entities. In summary, the DDE method enhances the accuracy of parameter fitting in epidemiological models and provides a foundation for constructing simpler models adaptable to different geographic areas.

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a significant socioeconomic burden, and combating COVID-19 is imperative. Blocking the SARS-CoV-2 RBD-ACE2 interaction is a promising therapeutic approach for viral infections, as SARS-CoV-2 binds to the ACE2 receptors of host cells via the RBD of spike proteins to infiltrate these cells. We used computer-aided drug design technology and cellular experiments to screen for peptide S4 with high affinity and specificity for the human ACE2 receptor through structural analysis of SARS-CoV-2 and ACE2 interactions. Cellular experiments revealed that peptide S4 effectively inhibited SARS-CoV-2 and HCoV-NL63 viruses from infecting host cells and was safe for cells at effective concentrations. Based on these findings, peptide S4 may be a potential pharmaceutical agent for clinical application in the treatment of the ongoing SARS-CoV-2 pandemic.