Objectives: Sarcopenia, an age-related skeletal muscle disorder, is assessed by handgrip strength, gait speed, and muscle mass, yet population-specific reference data and standardized scores for Asian adults remain limited. We aimed to establish sex- and age-specific normative reference distributions, smoothed centile curves, and modelbased standardized T scores for these indicators in Asian adults. Methods: We retrospectively analyzed adults aged ≥ 40 years attending a tertiary-center Adult Preventive Health Program in 2023–2024. To assess construct validity, we compared sarcopenia indicators across age groups using analysis of variance (ANOVA). Sex- and age-specific reference distributions were estimated using Generalized Additive Models for Location, Scale, and Shape (GAMLSS), from which smooth model-based age-specific centiles (5th–95th) were derived. Individual values were standardized to model-based Z scores and transformed to T scores on an approximate 100-point scale. Asian Working Group for Sarcopenia (AWGS) cut-offs were used in receiver operating characteristic (ROC) analyses to determine corresponding T-score thresholds. Results: Among 8095 participants, model-based mean handgrip strength, gait speed, and skeletal muscle mass were 20.03±5 kg, 1.12±0.37 m/s, and 6.93±1.43 kg/m² in women and 30.69±7.46 kg, 1.12±0.37 m/s, and 8.79±1.95 kg/m² in men. GAMLSS-derived centile curves demonstrated age-related declines in strength and gait speed and milder changes in muscle mass. AWGS cut-offs corresponded to T scores in the mid-40s for strength and gait and around 40–41 for muscle mass. Conclusions We established sex- and age-specific normative values and GAMLSS-based reference distributions, and derived model-based Z and T scores that provide standardized sarcopenia metrics in Asian adults, align with AWGS thresholds, and support detection of muscle decline and risk stratification.

Background: This study examines whether stronger corporate governance is associated with workplace mental health practices and whether this relationship is mediated by a structured sequence of occupational safety and health (OSH) engagement: recognition, goal-setting, and implementation. Methods: We analyzed 134 listed companies in Taiwan that published sustainability reports and received corporate governance evaluations between 2014 and 2023. Governance scores―based on shareholder rights, board functioning, transparency, and sustainability―were dichotomized into high vs. low categories. Workplace mental health practices were measured using 24 binary indicators across planning, provision, and reporting. OSH engagement was conceptualized in three stages based on Global Reporting Initiative 403 guidelines, with composite indicators derived via grouped weighted quantile sum regression. Associations were analyzed using generalized linear mixed-effects and serial mediation models. Results: Compared to companies ranked low in corporate governance, those ranked high had a higher likelihood of adopting mental health practices. OSH goal-setting and implementation showed significant positive associations, whereas recognition did not. Serial mediation analysis showed that 83% of the total effect of corporate governance on mental health practices was direct, while 17% was mediated through structured OSH engagement, primarily via implementation. Recognition showed a nonsignificant effect but initiated significant sequential pathways via goal-setting and implementation.Goal-setting functioned as a bridge within these chains. Conclusion Corporate governance plays a central role in advancing workplace mental health practices.While most effects are direct, structured OSH engagement helps translate governance priorities into sustained organizational actions that embed mental health into routine practice.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

Alzheimer’s disease (AD) is a prevalent neurodegenerative condition characterized by progressive cognitive decline and memory loss. As the incidence of AD continues to rise annually, researchers have shown keen interest in the active components found in natural plants and their neuroprotective effects against AD. Quercetin, a flavonol widely present in fruits and vegetables, has multiple biological effects including anticancer, anti-inflammatory, and antioxidant. Oxidative stress plays a central role in the pathogenesis of AD, and the antioxidant properties of quercetin are essential for its neuroprotective function. Quercetin can modulate multiple signaling pathways related to AD, such as Nrf2-ARE, JNK, p38 MAPK, PON2, PI3K/Akt, and PKC, all of which are closely related to oxidative stress. Furthermore, quercetin is capable of inhibiting the aggregation of β‑amyloid protein (Aβ) and the phosphorylation of tau protein, as well as the activity of β‑secretase 1 and acetylcholinesterase, thus slowing down the progression of the disease.The review also provides insights into the pharmacokinetic properties of quercetin, including its absorption, metabolism, and excretion, as well as its bioavailability challenges and clinical applications. To improve the bioavailability and enhance the targeting of quercetin, the potential of quercetin nanomedicine delivery systems in the treatment of AD is also discussed. In summary, the multifaceted mechanisms of quercetin against AD provide a new perspective for drug development. However, translating these findings into clinical practice requires overcoming current limitations and ongoing research. In this way, its therapeutic potential in the treatment of AD can be fully utilized.

Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8+T cell immune infiltration and immune suppression.We constructed a CD8+T cells related risk score model to pre-dict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8+T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS2,and TN-FRSF1B was constructed.The risk score model was well validated through an independent external validation co-hort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differ-ences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P＜0.0001)and lower CD8+T cells infiltration(P＜0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P＜0.01).Drug sensitivity a-nalysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene mod-el was verified by immunohistochemistry.In summary,the establishment and validation of a CD8+T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Objective:To explore the relationship between medical students'family function and anxiety/depression,and the mediating role of loneliness in this relationship.Methods:A total of 577 medical students were surveyed using stratified cluster sampling.Questionnaires assessed family function,loneliness,anxiety,and depression.Spearman correlation analysis was used to examine the relationships among family function,loneliness,anxiety,and depression.The mediating effects were tested using SPSS 26.0 PROCESS program model 4.Results:Medical students'family function,loneliness,anxiety,and depression scores were 8.00(5.00,10.00),16.00(12.00,19.00),3.00(2.00,4.00),and 3.00(2.00,4.00),respectively.Spearman correlation analysis showed that family function was negatively correlated with loneliness(r=-0.337),anxiety(r=-0.237),and depression(r=-0.257)(all P＜0.01).Loneliness was positively correlated with anxiety(r=0.394)and depression(r=0.392)(both P＜0.01).Anxiety was positively correlated with depression(r=0.746,P＜0.01).Family function negatively predicted anxiety(β=-0.118,P＜0.01),depression(β=-0.105,P＜0.01),and loneliness(β=-0.322,P＜0.01).Loneliness positively predicted anxiety(β=0.348,P＜0.01)and depression(β=0.346,P＜0.01).Loneliness played a partial mediating role in the relationship of family function with anxiety and depression among medical students,with mediating effects of 49.0%and 43.2%,respectively.Conclusions:Family function not only directly affects medical students'anxiety and depression but also indirectly affects them by influencing loneliness.Therefore,improving medical students'family function can effectively reduce their loneliness,thereby helping to alleviate anxiety and depression.

Purpose: Plasmablastic lymphoma (PBL) is a rare, aggressive lymphoma that is characterized by terminal B-cell differ‑ entiation. In the West, PBL usually occurs in patients with immunodeficiencies, particularly those induced by human immunodeficiency virus (HIV) infection. We investigated the clinicopathological features of PBL at a single institute in Taiwan, where HIV infection is rare. Methods: This retrospective chart review identified PBL cases that were treated at a single institute in southern Tai‑ wan between 2008 and 2024. Results: We identified nine patients (four males and five females; median age 71 years). Of the eight patients tested for HIV, only one tested positive. Pathologically, the tumors showed plasmablastic morphology and immunopheno‑ type, and three (33%) cases tested positive for Epstein–Barr virus. Six (67%) patients presented with Stage IV disease, including five (56%) with malignant effusion. Six patients were treated with chemotherapy and the remaining three received only supportive care. During a median follow-up of 10 months, five patients died of progressive disease, two died of unrelated diseases, and two were alive with PBL relapse. Conclusion In Taiwan, PBL constitutes a rare and aggressive clinical condition and is frequently associated with malignant effusion. In contrast to Western patients, the PBL in most patients from Taiwan was unrelated to HIV infection.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.