Genomic epidemiology of CVA10 in Guangdong, China, 2013-2021.

Hand, Foot and Mouth Disease (HFMD) is a highly contagious viral illness primarily affecting children globally. A significant epidemiological transition has been noted in mainland China, characterized by a substantial increase in HFMD cases caused by non-Enterovirus A71 (EV-A71) and non-Coxsackievirus A16 (CVA16) enteroviruses (EVs). Our study conducts a retrospective examination of 36,461 EV-positive specimens collected from Guangdong, China, from 2013 to 2021. Epidemiological trends suggest that, following 2013, Coxsackievirus A6 (CVA6) and Coxsackievirus A10 (CVA10) have emerged as the primary etiological agents for HFMD. In stark contrast, the incidence of EV-A71 has sharply declined, nearing extinction after 2018. Notably, cases of CVA10 infection were considerably younger, with a median age of 1.8 years, compared to 2.3 years for those with EV-A71 infections, possibly indicating accumulated EV-A71-specific herd immunity among young children. Through extensive genomic sequencing and analysis, we identified the N136D mutation in the 2 A protein, contributing to a predominant subcluster within genogroup C of CVA10 circulating in Guangdong since 2017. Additionally, a high frequency of recombination events was observed in genogroup F of CVA10, suggesting that the prevalence of this lineage might be underrecognized. The dynamic landscape of EV genotypes, along with their potential to cause outbreaks, underscores the need to broaden surveillance efforts to include a more diverse spectrum of EV genotypes. Moreover, given the shifting dominance of EV genotypes, it may be prudent to re-evaluate and optimize existing vaccination strategies, which are currently focused primarily target EV-A71.

Auriculasin induces mitochondrial oxidative stress and drives ferroptosis by inhibiting PI3K/Akt pathway in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) accounts for the majority of cases of lung cancer with poor outcomes. Auriculasin is a prenylated isoflavone abundant in the root of F. philippinensis with multiple pharmacological effects, including anticancer role. However, its roles in NSCLC remain largely unknown. NSCLC A549 cells were treated with auriculasin in vitro, and used to induce xenograft models. Cell viability was detected via CCK-8 assay. Mitochondrial oxidative stress was analyzed by JC-1 staining, ROS staining, and levels of MDA, SOD and GSH. Ferroptosis was assessed via iron content, and levels of ACSL4, PTGS2, FSP1 and GPX4. The phosphorylation levels of PI3K and Akt were measured by western blot. Auriculasin reduced NSCLC cell viability. Auriculasin promoted mitochondrial oxidative stress by reducing mitochondrial membrane potential, SOD and GSH levels, and enhancing ROS and MDA contents. In addition, auriculasin induced ferroptosis via increasing iron, ACSL4 and PTGS3 levels, and decreasing FSP1 and GPX4 levels. Furthermore, the potential targets of auriculasin in NSCLC were enriched in PI3K/Akt signaling. Auriculasin blunted PI3K/Akt pathway activation by blocking the phosphorylation. Activated PI3K/Akt signaling by activator 740Y-P reversed the effects of auriculasin on mitochondrial oxidative stress and ferroptosis. Finally, auriculasin reduced NSCLC cell growth in xenograft models. Auriculasin facilitates mitochondrial oxidative stress and induces ferroptosis through inhibiting PI3K/Akt pathway in NSCLC.

Understanding risky driving behaviors among young novice drivers in Nigeria: A latent class analysis coupled with association rule mining approach.

Traffic crashes are significant public health concern in Nigeria, particularly among young drivers. The study aims to explore the underlying pattern of risky driving behaviors and the associations with demographic factors among young drivers in Nigeria. A combined approach of Latent Class Analysis (LCA) and Association Rule Mining is applied to the dataset comprising responses from 684 young drivers who complete the "Behavior of Young Novice Drivers Scale" (BYND) questionnaires. The LCA identifies four distinct classes of drivers based on the risky behavior profiles: Reckless-Speedsters, Cautious Drivers, Distracted Multitaskers, and Emotion-impacted Drivers. Association rule mining further connects these driver classes to demographic and driving history variables, uncovering intriguing insights. Reckless-Speedsters predominantly consist of young males who engage in riskier driving behaviors, including exceeding speed limits and disregarding traffic rules. Conversely, Cautious Drivers, also predominantly young males, exhibit a safer driving profile marked by rule adherence and a notably lower crash rate. Distracted Multitaskers, sharing a demographic profile with Cautious Drivers, diverge significantly due to their higher crash involvement, hinting at a propensity for distracted driving practices. Lastly, Emotion-Impacted Drivers, primarily comprising young employed males, display behaviors influenced by emotions, shorter driving distances, and prior unsupervised driving experience. Most of the behaviors are attributed to inadequate traffic control, absence of traffic signs in most of the roads, preferential treatment, and lack of strict law enforcement in the country. The findings hold substantial implications for road safety interventions in Nigeria, urging targeted approaches to address the unique challenges presented by each driver class. With acknowledging the study limitations and advocating for future research in objective measures and emotion-behavior interactions, the comprehensive approach provides a robust foundation for enhancing road safety in the Nigerian context.

Construction of a predictive model of 2-3 cm ground-glass nodules developing into invasive lung adenocarcinoma using high-resolution CT.

Background: The purpose of this study was to analyze the imaging risk factors for the development of 2-3 cm ground-glass nodules (GGN) for invasive lung adenocarcinoma and to establish a nomogram prediction model to provide a reference for the pathological prediction of 2-3 cm GGN and the selection of surgical procedures. Methods: We reviewed the demographic, imaging, and pathological information of 596 adult patients who underwent 2-3 cm GGN resection, between 2018 and 2022, in the Department of Thoracic Surgery, Second Affiliated Hospital of the Air Force Medical University. Based on single factor analysis, the regression method was used to analyze multiple factors, and a nomogram prediction model for 2-3 cm GGN was established. Results: (1) The risk factors for the development of 2-3 cm GGN during the invasion stage of the lung adenocarcinoma were pleural depression sign (OR = 1.687, 95%CI: 1.010-2.820), vacuole (OR = 2.334, 95%CI: 1.222-4.460), burr sign (OR = 2.617, 95%CI: 1.008-6.795), lobulated sign (OR = 3.006, 95%CI: 1.098-8.227), bronchial sign (OR = 3.134, 95%CI: 1.556-6.310), diameter of GGN (OR = 3.118, 95%CI: 1.151-8.445), and CTR (OR = 172.517, 95%CI: 48.023-619.745). (2) The 2-3 cm GGN risk prediction model was developed based on the risk factors with an AUC of 0.839; the calibration curve Y was close to the X-line, and the decision curve was drawn in the range of 0.0-1.0. Conclusion: We analyzed the risk factors for the development of 2-3 cm GGN during the invasion stage of the lung adenocarcinoma. The predictive model developed based on the above factors had some clinical significance.

[Ecological characteristics and seasonal changes of macrozoobenthos in the waters of Miaodao Archipelago, China]. / åº™å²›ç¾¤å²›æµ·åŸŸå¤§åž‹åº•æ –åŠ¨ç‰©ç”Ÿæ€ç‰¹å¾åŠå­£èŠ‚å˜åŒ–.

To understand the macrozoobenthic community composition and spatial-temporal distribution characteristics of macrobenthos in the waters of Miaodao Archipelago, Yantai, Shandong and its response to habitat changes, we conducted surveys of macrobenthos and environmental elements in the waters of Miaodao Islands in May (spring), August (summer), and October (autumn) in 2022. Results showed that a total of 127 macrozoobenthic species were recorded, with Mollusca and Annelida (Polychaeta) as the dominant taxa, consisting of 47 and 45 species, respectively. The key dominant species included Sternaspis chinensis, Glycinde bonhourei, Moerella hilaris, and Amphioplus (Lymanella) japonicus. The average annual density and biomass of macrozoobenthos were 190 ind·m-2 and 28.69 g·m-2, respectively. There was no significant seasonal differences in density and biomass. The Shannon diversity index (H), evenness index (J), and richness index (D) averaged 3.10, 0.90, and 2.40, respectively. Cluster analysis results showed low similarity coefficients of community among the three seasons, suggesting a distinct distribution pattern. Factors such as bottom seawater temperature, chlorophyll a, nutrient, sediment grain size, and organic matter content could significantly influence the structure and diversity of macrozoobenthic community. Compared with historical research data, the Changdao National Wetland Nature Reserve and the implementation of enclosure aquaculture have led to notable changes in the dominant species of macrobenthos. Specifically, there was a noticeable decline in both density and H, and an increase in biomass and J. Additionally, body size of benthic fauna was transitioning from small to big.

Pulmonary Tuberculosis Notification Rate Within Shenzhen, China, 2010-2019: Spatial-Temporal Analysis.

BACKGROUND: Pulmonary tuberculosis (PTB) is a chronic communicable disease of major public health and social concern. Although spatial-temporal analysis has been widely used to describe distribution characteristics and transmission patterns, few studies have revealed the changes in the small-scale clustering of PTB at the street level. OBJECTIVE: The aim of this study was to analyze the temporal and spatial distribution characteristics and clusters of PTB at the street level in the Shenzhen municipality of China to provide a reference for PTB prevention and control. METHODS: Data of reported PTB cases in Shenzhen from January 2010 to December 2019 were extracted from the China Information System for Disease Control and Prevention to describe the epidemiological characteristics. Time-series, spatial-autocorrelation, and spatial-temporal scanning analyses were performed to identify the spatial and temporal patterns and high-risk areas at the street level. RESULTS: A total of 58,122 PTB cases from 2010 to 2019 were notified in Shenzhen. The annual notification rate of PTB decreased significantly from 64.97 per 100,000 population in 2010 to 43.43 per 100,000 population in 2019. PTB cases exhibited seasonal variations with peaks in late spring and summer each year. The PTB notification rate was nonrandomly distributed and spatially clustered with a Moran I value of 0.134 (P=.02). One most-likely cluster and 10 secondary clusters were detected, and the most-likely clustering area was centered at Nanshan Street of Nanshan District covering 6 streets, with the clustering time spanning from January 2010 to November 2012. CONCLUSIONS: This study identified seasonal patterns and spatial-temporal clusters of PTB cases at the street level in the Shenzhen municipality of China. Resources should be prioritized to the identified high-risk areas for PTB prevention and control.

Characterizing Infections in Two Epidemic Waves of SARS-CoV-2 Omicron Variants: A Cohort Study in Guangzhou, China.

BACKGROUND: After the adjustment of COVID-19 epidemic policy, mainland China experienced two consecutive waves of Omicron variants within a seven-month period. In Guangzhou city, as one of the most populous regions, the viral infection characteristics, molecular epidemiology, and the dynamic of population immunity are still elusive. METHODS: We launched a prospective cohort study in the Guangdong Provincial CDC from December 2022 to July 2023. Fifty participants who received the same vaccination regimen and had no previous infection were recruited. RESULTS: 90% of individuals were infected with Omicron BA.5* variants within three weeks in the first wave. Thirteen cases (28.26%) experienced infection with XBB.1* variants, occurring from 14 weeks to 21 weeks after the first wave. BA.5* infections exhibited higher viral loads in nasopharyngeal sites compared to oropharyngeal sites. Compared to BA.5* infections, the XBB.1* infections had significantly milder clinical symptoms, lower viral loads, and shorter durations of virus positivity. The infection with the BA.5* variant elicited varying levels of neutralizing antibodies against XBB.1* among different individuals, even with similar levels of BA.5* antibodies. The level of neutralizing antibodies specific to XBB.1* determined the risk of reinfection. CONCLUSIONS: The rapid large-scale infections of the Omicron variants have quickly established herd immunity among the population in mainland China. In the future of the COVID-19 epidemic, a lower infection rate but a longer duration can be expected. Given the large population size and ongoing diversified herd immunity, it remains crucial to closely monitor the molecular epidemiology of SARS-CoV-2 for the emergence of new variants of concern in this region. Additionally, the timely evaluation of the immune status across different age groups is essential for informing future vaccination strategies and intervention policies.

Molecular epidemiology and population immunity of SARS-CoV-2 in Guangdong (2022-2023) following a pivotal shift in the pandemic.

The SARS-CoV-2 Omicron variant sparked the largest wave of infections worldwide. Mainland China eased its strict COVID-19 measures in late 2022 and experienced two nationwide Omicron waves in 2023. Here, we investigated lineage distribution and virus evolution in Guangdong, China, 2022-2023 by comparing 5813 local viral genomes with the datasets from other regions of China and worldwide. Additionally, we conducted three large-scale serological surveys involving 1696 participants to measure their immune response to the BA.5 and XBB.1.9 before and after the corresponding waves. Our findings revealed the Omicron variants, mainly the BA.5.2.48 lineage, causing infections in over 90% of individuals across different age groups within a month. This rapid spread led to the establishment of widespread immunity, limiting the virus's ability to further adaptive mutation and dissemination. While similar immune responses to BA.5 were observed across all age groups after the initial wave, children aged 3 to 11 developed a stronger cross immune response to the XBB.1.9 strain, possibly explaining their lower infection rates in the following XBB.1 wave. Reinfection with Omicron XBB.1 variant triggered a more potent neutralizing immune response among older adults. These findings highlight the impact of age-specific immune responses on viral spread in potential future waves.