Objective: To investigate the status and associated factors of sports supplement usage among grade 9 students, so as to provide a scientific basis for targeted supervision and health education regarding sports supplement usage among junior high school students. Methods: From June to September 2025, a stratified cluster random sampling method was used to select 2 261 grade 9 students from 10 provinces (autonomous regions, municipalities) in China. A questionnaire survey was conducted on their sports supplement usage and related factors. The Chi square test was used to compare the usage rates of sports supplements among different groups of students, and binary Logistic regression analysis was employed to investigate the related factors of sports supplement usage among grade 9 students. Results: Totally 59.7% of the grade 9 students used sports supplements. The usage rate (62.5%) was higher among boys than girls (56.3%), higher among students from rural areas and towns/counties (66.5%, 66.2%) than those from urban districts (52.9%), higher among boarding students (65.2%) than non resident students (54.3%), higher among students whose parents occupations were businessmen and workers (fathers: 65.0%, 63.7%; mothers: 63.6%, 61.1%) than those whose parents were farmers and civil servants (fathers: 57.5%, 54.1%; mothers: 58.8%, 55.7%), higher among students with a monthly family income of 5 000- 10 000 yuan (66.3%) than those in other income groups, and higher among students in the high score zone for the entrance physical examination to senior high school (67.7%) than those in the medium and low score zones ( 56.3% , 56.5%) ( χ 2=8.99, 42.21, 27.98, 20.55, 8.20, 22.74, 24.70, respectively, all P <0.05). Binary Logistic regression analysis showed that boys ( OR =1.26), those from rural areas ( OR =1.59), boarding students ( OR =1.36), those with a monthly family income of 5 000- 10 000 yuan ( OR =1.41), and those in the high score zone for entrance physical examination to senior high school ( OR =1.34) were more likely to use sports supplements during the entrance physical examination to senior high school; the probability of sports supplement usage was lower among students whose fathers were civil servants ( OR =0.74) (all P <0.05). Conclusions The usage of sports supplements is relatively common among grade 9 students. Intervention measures should be targeted at specific populations to reduce the risk of misuse.

Objective: To investigate the status of condom use and its influencing factors among men who have sex with men (MSM), so as to provide a basis for improving condom utilization rates and AIDS prevention and control in this population. Methods: From May to October 2024, a snowball sampling method was employed to recruit MSM in Songjiang District, Shanghai Municipality. Self-administered questionnaires were used to collect data on demographic characteristics, AIDS-related knowledge, sexual behaviors, pre-exposure prophylaxis (PrEP) and post-exposure prophylaxis (PEP), and condom use in the past six months. Multivariable logistic regression model was used to analyze the influencing factors for consistent condom use. Results: A total of 921 MSM were surveyed, with a median age of 29.00 (interquartile range, 9.00) years. Among them, 697 (75.68%) were aware of AIDS-related knowledge, 826 (89.69%) expressed willingness to use PrEP, and 835 (90.66%) were willing to use PEP. Additionally, 787 (85.45%) MSM reported their age at first homosexual intercourse as ≥18 years, while 519 (56.35%) reported consistent condom use in the past six months. Multivariable logistic regression analysis revealed that MSM who were aware of AIDS-related knowledge (OR=0.582, 95% CI: 0.423-0.801), willing to use PrEP (OR =0.611, 95% CI: 0.385-0.969), and whose age at first homosexual intercourse was <18 years (OR=0.480, 95% CI: 0.330-0.700) were less likely to consistent use condoms. Conclusion The proportion of consistent condom use among the MSM remains relatively low, which is primarily associated with AIDS-related knowledge, willingness to use PrEP, and the age at first homosexual intercourse.

ObjectiveHepatocellular carcinoma (HCC) represents 90% of all primary liver cancers. The main risk factors associated with HCC include viral hepatitis (B and/or C), alcohol abuse, and metabolic dysfunction-associated steatotic liver disease (MASLD), which progressively advance to liver fibrosis, cirrhosis, and ultimately evolve into HCC. Surgical resection represents the most effective treatment for HCC, while recent advances in immunotherapy, including immune checkpoint inhibitors and adoptive cell therapies, have provided improved treatment prospects for patients with unresectable HCC. However, the complex metabolic heterogeneity of HCC limits the therapeutic efficacy. Metabolic intermediates acyl-CoA not only provide energy and substrates for numerous biochemical reactions but also serve as donors for protein lysine acylation, a major class of post-translational modification (PTM). Therefore, a deeper understanding of the molecular mechanisms underlying protein lysine acylation and hepatocarcinogenesis is urgently needed. MethodsThe levels of protein lysine acylation and silence information regulator 5 (SIRT5) expression levels in clinical HCC samples were analyzed by Western blot. Quantitative malonylome and succinylome of HCC samples were analyzed by antibody-based affinity enrichment coupled with tandem mass spectrometry. The proliferation of HCC cells was analyzed with Cell Counting Kit-8 (CCK-8) assays, the apoptosis was quantified by Annexin V-FITC/propidium iodide (PI) staining coupled with flow cytometry, and the ability of cells to migrate was assayed by Transwell assays. The enzymatic activity of glutathione S-transferase Mu 1 (GSTM1) was quantified. Transgenic mice with hepatic overexpression of SIRT5 were constructed using CRISPR-Cas9, and primary hepatocarcinogenesis was induced by administration of diethylnitrosamine. ResultsWestern blot analysis indicated that the expression level of SIRT5 was elevated in clinical samples from HCC patients, and the levels of lysine malonylation, glutarylation, and succinylation were significantly reduced in HCC tissues. Knockout of SIRT5 in MHCC-97H and MHCC-97L hepatoma cells suppressed cell proliferation, and increased the percentage of apoptotic cells significantly. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the differentially malonylome and succinylome of HCC samples revealed significant enrichment in two major classes of biological processes: core energy metabolism (e.g., glycolysis/gluconeogenesis, tricarboxylic acid metabolic process, fatty acid beta oxidation) and detoxification and oxidative stress response (e.g., response to toxic substance, chemical carcinogenesis, reactive oxygen species (ROS)). SIRT5 removes malonylation from lysine residues in GSTM1 and restores its detoxification activity, which is crucial for the survival of hepatocytes under stressed conditions. More importantly, in vivo experiment indicated that hepatic-specific overexpression of SIRT5 in mice accelerated diethylnitrosamine-induced liver fibrosis and hepatocarcinogenesis, indicating the critical role of SIRT5 in HCC progression. ConclusionThis study highlights the previously unrecognized SIRT5-GSTM1 axis as a key regulator in hepatocarcinogenesis, and suggests a potential target for the treatment of patients with HCC.

Intra-abdominal Hernia with Bowel Obstruction Triggering Multi-organ Failure: The Role of Preoperative Enteritis This report details the clinical course of a 41-year-old male who developed fulminant multiple organ dysfunction syndrome following emergency surgery for a strangulated intra-abdominal hernia. Preoperative manifestations, including diarrhea and marked leukocytosis, pointed towards an underlying infectious enteritis. We posited that surgical release of the obstructed, ischemic bowel segment precipitated a massive systemic influx of endotoxins and inflammatory mediators, triggering septic shock and rapid sequential organ failure. This case underscored the critical need to suspect concomitant gastrointestinal infection in patients presenting with mechanical bowel obstruction accompanied by infectious signs. Aggressive perioperative sepsis management encompassing early empiric antimicrobial therapy, vigilant hemodynamic monitoring, and preparedness for advanced organ support is essential to mitigate this severe complication.

Objective We reviewed and analyzed the epidemiological data of 83 imported dengue fever cases reported in Fengtai District, Beijing, from 2007 to 2025, to delineate their epidemiological characteristics and guide the dengue fever prevention and control strategy in the future. Methods Data on dengue fever cases in Fengtai District from 2007 to 2025 were collected to identify the epidemic factors and characteristics using descriptive epidemiological method. Results All 83 dengue fever cases reported in this region over the past two decades have been imported from abroad or other domestic areas, with Southeast Asian countries being identified as the primary source of imported infections, accounting for 42 cases (50.60%), followed by 15 cases (18.07%) from Chinese provinces other than Beijing. The remaining import sources included 13 cases from South Asia,8 from African countries, and each from Oceania, South America, and Europe. Disease onset was found concentrated between May and November. The sex ratio (male-to-female) is 1.59:1. The age of onset ranged from 14 to 61 years old, with a median age of 36. The largest proportion of cases was observed among cadres and office workers (31 cases, 37.35%), followed by businessmen (13 cases, 15.67%), and householders or the unemployed (10 cases,12.05%). Travel visit was identified as the primary reason for their exposure history. Conclusions All dengue fever cases reported in Fengtai from 2007 to 2025 were imported, with an increasing trend of imported cases in Beijing originating from other Chinese provinces. It is essential to strengthen health education for foreign travelers and returning residents, enhance clinical diagnosis and treatment training for medical personnel, eliminate mosquito breeding sites, and reduce mosquito density through active patriotic health campaigns.

Objective To understand the distribution, species composition, seasonal fluctuations, and presence of Dabie bandavirus in ticks in Tai'an City, providing a basis for assessing tick-borne disease risks and formulating prevention strategies. Methods Free-living ticks were monitored using the flagging method, whereas parasitic ticks were monitored through host surface examination. Reverse transcription-polymerase chain reaction (RT-qPCR) was used to detect the presence of Bandavirus dabieense in tick specimens. Results The density of free-living ticks in Tai'an City showed a continuous decreasing trend over the 3 years from 2021 to 2023, with an average tick density of 0.43 ticks/(flag·100 m). The dominant habitats were scenic areas and forests, and the seasonal fluctuations exhibited a bimodal pattern, peaking in March and August. The only free-living tick species captured was Haemaphysalis longicornis. Over the 3 years, the average tick index for parasitic ticks was 1.85, with sheep as the primary host. Seasonal fluctuations also followed a bimodal pattern, peaking in March and August. The primary parasitic tick species captured were H. longicornis and Rhipicephalus sanguineus. No Dabie bandavirus was detected in the tick specimens. Conclusions Tick density in Tai'an City remains relatively high, necessitating continued efforts to enhance tick surveillance and implement targeted prevention measures in rural environments to further reduce the health risks posed by tick-borne diseases.

ObjectiveAbnormal intestinal angiogenesis and dysregulation of the mucosal immune microenvironment are important mechanisms underlying the occurrence and progression of ulcerative colitis (UC). This study aimed to identify biomarkers associated with angiogenesis in UC through integrated bioinformatics analysis and to validate their expression patterns and effects on vascular endothelial cell function through in vivo and in vitro experiments. MethodsSix UC-related datasets were retrieved from the GEO database. GSE48959, GSE59071, and GSE73661 were batch-corrected using the ComBat algorithm and used as the discovery cohort, while GSE47908, GSE92415, and GSE206285 were used as independent external validation cohorts. Differentially expressed genes were identified using the limma package, and a weighted gene co-expression network was constructed using WGCNA. The DEGs, WGCNA core module genes, and angiogenesis-related genes were intersected to obtain candidate genes. Multiple machine learning methods were further integrated to screen candidate features, followed by DNN and SHAP-based analysis of candidate gene feature contributions. PPI network topology analysis was further performed to identify hub genes, and the CIBERSORT algorithm was used to evaluate candidate genes and immune infiltration features. In addition, a DSS-induced mouse model of colitis and a TNF-α-stimulated HUVECs inflammatory model were established for experimental validation, combined with hematoxylin and eosin staining, immunofluorescence staining, Western blotting, wound healing assays, Transwell invasion assays, and Matrigel tube formation assays. ResultsA total of 481 upregulated and 285 downregulated genes were identified in the discovery cohort, and these genes were mainly enriched in pathways related to leukocyte migration and the complement and coagulation cascades. WGCNA identified the yellow module as the module most strongly associated with UC. The intersection of DEGs, WGCNA core module genes, and angiogenesis-related genes yielded 26 candidate genes. Four machine learning algorithms further identified C2, TIMP1, and TGM2 as common candidate features, while DNN-SHAP analysis and PPI network topology analysis further highlighted TIMP1 as a key hub gene. After multi-step screening, TIMP1 was ultimately identified as a key candidate gene. Validation across multiple datasets showed that TIMP1 was significantly upregulated in UC tissues and exhibited favorable discriminatory performance (all AUCs>0.85). In the DNN model, TIMP1 showed a relatively high feature contribution, supporting its potential relevance to UC classification. CIBERSORT analysis indicated that TIMP1 expression was positively correlated with neutrophils and resting NK cells, but negatively correlated with regulatory T cells and CD8⁺ T cells. In vivo and in vitro experiments further confirmed that TIMP1 expression was markedly increased under inflammatory conditions. In DSS-induced colitis mice, increased CD31-positive vascular signals were accompanied by elevated TIMP1 expression and reduced VE-cadherin expression. Moreover, TIMP1 knockdown significantly inhibited endothelial cell migration, invasion, and tube formation, accompanied by decreased expression of VEGFA, VEGFR-2, and VEGFR-3. ConclusionTIMP1 may participate in UC-associated abnormal angiogenesis and changes in vascular endothelial cell function under inflammatory conditions, highlighting its potential as a biomarker and a candidate for further therapeutic investigation.

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

OBJECTIVES

During the early COVID-19 pandemic (2020 to mid-2021), the Philippine government relied on nonpharmaceutical interventions such as lockdowns and Enhanced Community Quarantine (ECQ). With the emergency use authorization of vaccines, assessing their potential impact became essential. This study develops a Philippine model to evaluate the epidemiologic and economic effects of COVID-19 vaccination, estimating its impact on mortality, hospitalization, and mild/asymptomatic cases under various prioritization strategies, including booster doses and the presence of variants of concern.

A dynamic transmission model (DTM) with an SEIR (Susceptible-Exposed-Infected-Recovered) structure was calibrated using local data, including case numbers, deaths, seroprevalence, vaccination coverage, and intervention costs. The model’s outputs informed a cost-effectiveness analysis (CEA) from health system and societal perspectives over a two-year horizon. Incremental Cost-Effectiveness Ratios (ICERs) were calculated, with costs adjusted to 2020 prices and discount rates of 3%-10% applied. Sensitivity analyses, including one-way and probabilistic approaches, assessed robustness, while a budget impact analysis (BIA) estimated government expenditures in 2020 and 2021.

Without vaccination, daily cases could have peaked at 400,000 between February and May 2021. A vaccination campaign was projected to reduce cases to around 20,000, significantly lowering mortality.  

From the health system perspective, the estimated cost without vaccination was PhP 14.46 trillion, with 93.83 million QALYs. With vaccination, costs dropped to PhP 2.36 trillion, while QALYs increased to 101.79 million. From the societal perspective, costs were PhP 14.68 trillion without vaccination and PhP 2.38 trillion with vaccination, with the same QALY outcomes.

CEA results confirmed that vaccination was cost-saving, with ICERs of -PhP 1,520,727.28 per QALY (health system) and -PhP 1,546,171.63 per QALY (societal). Sensitivity analyses supported these findings, with oneway sensitivity analysis showing minimal impact from parameter changes and probabilistic sensitivity analysis confirming cost-saving outcomes. The BIA estimated government expenditures of PhP 983.45 billion in 2020 and PhP 1.47 trillion in 2021 for the vaccine scenario, lower than the no-vaccine scenario.

Indeed, our modeling has shown that COVID-19 vaccines could mitigate the spread of COVID-19 and provide good value for money.

Neurological diseases are a major health concern, and brain injury is a typical pathological process in various neurological disorders. Different biomarkers in the blood or the cerebrospinal fluid are associated with specific physiological and pathological processes. They are vital in identifying, diagnosing, and treating brain injuries. In this review, we described biomarkers for neuronal cell body injury (neuron-specific enolase, ubiquitin C-terminal hydrolase-L1, αII-spectrin), axonal injury (neurofilament proteins, tau), astrocyte injury (S100β, glial fibrillary acidic protein), demyelination (myelin basic protein), autoantibodies, and other emerging biomarkers (extracellular vesicles, microRNAs). We aimed to summarize the applications of these biomarkers and their related interests and limits in the diagnosis and prognosis for neurological diseases, including traumatic brain injury, status epilepticus, stroke, Alzheimer's disease, and infection. In addition, a reasonable outlook for brain injury biomarkers as ideal detection tools for neurological diseases is presented.
Humans ; Biomarkers/cerebrospinal fluid* ; Nervous System Diseases/diagnosis* ; Brain Injuries/metabolism* ; Phosphopyruvate Hydratase/cerebrospinal fluid* ; Glial Fibrillary Acidic Protein/blood* ; S100 Calcium Binding Protein beta Subunit/blood* ; tau Proteins/cerebrospinal fluid* ; Ubiquitin Thiolesterase/blood* ; Myelin Basic Protein/cerebrospinal fluid* ; Neurofilament Proteins/blood* ; MicroRNAs/blood* ; Brain Injuries, Traumatic/metabolism*