Epidemiology and etiology of hand, foot, and mouth disease in Zhengzhou, China, from 2009 to 2021.

Background: Hand, foot, and mouth disease (HFMD) is a common childhood infectious disease caused by a variety of enteroviruses (EVs). To explore the epidemiological characteristics and etiology of HFMD in Zhengzhou, China, we conducted a systematic analysis of HFMD surveillance data from Zhengzhou Center for Disease Control and Prevention from January 2009 to December 2021 (https://wjw.zhengzhou.gov.cn/). Methods: Surveillance data were collected from Zhengzhou Center for Disease Control and Prevention from January 2009 to December 2021 (https://wjw.zhengzhou.gov.cn/). Cases were analyzed according to the time of onset, type of diagnosis, characteristics, viral serotype, and epidemiological trends. Results: We found that the primary causative agent responsible for the HFMD outbreaks in Zhengzhou was Enterovirus A71 (EVA-71) (48.56%) before 2014. After 2015, other EVs gradually became the dominant strains (57.68%). The data revealed that the HFMD epidemics in Zhengzhou displayed marked seasonality, with major peaks occurring from April to June, followed by secondary peaks from October to November, except in 2020. Both the severity and case-fatality ratio of HFMD decreased following the COVID-19 pandemic (severity ‰: 13.46 vs. 0.17; case-fatality ‰: 0.21 vs. 0, respectively). Most severe cases were observed in patients aged 1 year and below, accounting for 45.81%. Conclusions: Overall, the incidence rate of HFMD decreased in Zhengzhou following the introduction of the EVA-71 vaccine in 2016. However, it is crucial to acknowledge that HFMD prevalence continues to exhibit a distinct seasonal pattern and periodicity, and the occurrence of other EV infections poses a new challenge for children's health.

Online application for the diagnosis of atherosclerosis by six genes.

BACKGROUND: Atherosclerosis (AS) is a primary contributor to cardiovascular disease, leading to significant global mortality rates. Developing effective diagnostic indicators and models for AS holds the potential to substantially reduce the fatalities and disabilities associated with cardiovascular disease. Blood sample analysis has emerged as a promising avenue for facilitating diagnosis and assessing disease prognosis. Nonetheless, it lacks an accurate model or tool for AS diagnosis. Hence, the principal objective of this study is to develop a convenient, simple, and accurate model for the early detection of AS. METHODS: We downloaded the expression data of blood samples from GEO databases. By dividing the mean values of housekeeping genes (meanHGs) and applying the comBat function, we aimed to reduce the batch effect. After separating the datasets into training, evaluation, and testing sets, we applied differential expression analyses (DEA) between AS and control samples from the training dataset. Then, a gradient-boosting model was used to evaluate the importance of genes and identify the hub genes. Using different machine learning algorithms, we constructed a prediction model with the highest accuracy in the testing dataset. Finally, we make the machine learning models publicly accessible by shiny app construction. RESULTS: Seven datasets (GSE9874, GSE12288, GSE20129, GSE23746, GSE27034, GSE90074, and GSE202625), including 403 samples with AS and 325 healthy subjects, were obtained by comprehensive searching and filtering by specific requirements. The batch effect was successfully removed by dividing the meanHGs and applying the comBat function. 331 genes were found to be related to atherosclerosis by the DEA analysis between AS and health samples. The top 6 genes with the highest importance values from the gradient boosting model were identified. Out of the seven machine learning algorithms tested, the random forest model exhibited the most impressive performance in the testing datasets, achieving an accuracy exceeding 0.8. While the batch effect reduction analysis in our study could have contributed to the increased accuracy values, our comparison results further highlight the superiority of our model over the genes provided in published studies. This underscores the effectiveness of our approach in delivering superior predictive performance. The machine-learning models were then uploaded to the Shiny app's server, making it easy for users to distinguish AS samples from normal samples. CONCLUSIONS: A prognostic Shiny application, built upon six potential atherosclerosis-associated genes, has been developed, offering an accurate diagnosis of atherosclerosis.

Clinical and epidemiological characteristics of 96 pediatric human metapneumovirus infections in Henan, China after COVID-19 pandemic: a retrospective analysis.

BACKGROUND: In the aftermath of the COVID-19 pandemic, there has been a surge in human metapneumovirus (HMPV) transmission, surpassing pre-epidemic levels. We aim to elucidate the clinical and epidemiological characteristics of HMPV infections in the post-COVID-19 pandemic era. METHODS: In this retrospective single-center study, participants diagnosed with laboratory confirmed HMPV infection through Targeted Next Generation Sequencing were included. The study encompassed individuals admitted to Henan Children's Hospital between April 29 and June 5, 2023. Demographic information, clinical records, and laboratory indicators were analyzed. RESULTS: Between April 29 and June 5, 2023, 96 pediatric patients were identified as infected with HMPV with a median age of 33.5 months (interquartile range, 12 ~ 48 months). The majority (87.5%) of infected children were under 5 years old. Notably, severe cases were statistically younger. Predominant symptoms included fever (81.3%) and cough (92.7%), with wheezing more prevalent in the severe group (56% vs 21.1%). Coinfection with other viruses was observed in 43 patients, with Epstein-Barr virus (EBV) (15.6%) or human rhinovirus A (HRV type A) (12.5%) being the most common. Human respiratory syncytial virus (HRSV) coinfection rate was significantly higher in the severe group (20% vs 1.4%). Bacterial coinfection occurred in 74 patients, with Haemophilus influenzae (Hin) and Streptococcus pneumoniae (SNP) being the most prevalent (52.1% and 41.7%, respectively). Severe patients demonstrated evidence of multi-organ damage. Noteworthy alterations included lower concentration of IL-12p70, decreased lymphocytes percentages, and elevated B lymphocyte percentages in severe cases, with statistical significance. Moreover, most laboratory indicators exhibited significant changes approximately 4 to 5 days after onset. CONCLUSIONS: Our data systemically elucidated the clinical and epidemiological characteristics of pediatric patients with HMPV infection, which might be instructive to policy development for the prevention and control of HMPV infection and might provide important clues for future HMPV research endeavors.

Emerging concerns of atypical hand foot and mouth disease caused by recombinant Coxsackievirus A6 variants in Henan, China.

An increasing number of studies have reported that atypical hand, foot, and mouth disease (HFMD) is becoming a new concern for children's health. At present, there is no official definition for atypical HFMD, but some studies have defined that it occurs at anatomic sites not listed in the definition of HFMD issued by the World Health Organization. Several pathogens have been reported to cause atypical HFMD, such as Coxsackievirus (CV)A6. As one of the most prevalent enteroviruses in the world, CVA6 seems to affect a wider range of children and causes more severe and prolonged illness than other enteroviruses. The early lesions of atypical HFMD are very similar to the clinical presentations of other diseases, such as eczema, which poses a challenge for clinicians aiming to identify and diagnose HFMD in a timely manner. Here, we report on six atypical HFMD patients caused by recombinant CVA6 variants, and the atypical manifestations include eczema coxsackium, large herpes, rice-like red papules and herpes, purpuric rash, and onychomadesis, as well as and large red herpes on scalp, perianal, testicles, shoulders and neck, and other atypical eruption sites, hoping to draw the attention of other pediatricians. This study will provide scientific guidance for timely diagnosis of HFMD to prevent serious complications.

Value of NSE and S100 Protein of Kawasaki Disease with Aseptic Meningitis in Infant.

The cerebrospinal fluid content was examined for concentrations of S100 protein and neuron-specific enolase (NSE) in two diseases, Kawasaki disease (KD) with aseptic meningitis (1-3 months) and purulent meningitis (PM), to determine whether or not these measuremets could be used in early diagnosis. The content of cerebrospinal fluid S100 protein of KD with aseptic meningitis and PM were significantly higher than those in the control group. There was also a difference between KD and purulent meningitis (PM). The concentration of NSE was highest in the encephalitis group, which was statistically different from control group. However, there was no difference between the KD and control groups. The levels of S100 protein and NSE of KD with aseptic meningitis were lower than those in PM, indicating that the extent of neuronal damage is significantly lower than of the enchephalitis group. The area under the curve (AUCs) of the receiver operating characteristic (ROC) curve for S100 and NSE were both 0.972. The S100 threshold was 0.4315, the sensitivity was 92.1%, and the specificity was 100%, while the NSE threshold was 9.325, sensitivity 92.1%, and specificity 90%. The combined detection of NSE and S100 levels in the cerebrospinal fluid can be used for the differential diagnosis of KD with aseptic meningitis and purulent meningitis.