Objective To analyze the disease burden and trends of bladder cancer in China and globally from 1992 to 2021.  Methods Using the GBD 2021 database, the incidence, prevalence, mortality, and disability-adjusted life years (DALYs) rates of bladder cancer in China and globally from 1992–2021 were analyzed. Average annual percentage change (AAPC) was calculated using Joinpoint regression. Subgroup analyses by sex and age were conducted, and a Bayesian age-period-cohort (BAPC) model was used to predict trends in age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR) for the next 15 years.  Results In 2021, China reported 106 000 new cases (ASIR: 5.14/100 000), 571 000 prevalent cases (age-standardized prevalence rate, ASPR: 26.61/100 000), 43 000 deaths (ASMR: 2.34/100 000), and a DALY rate of 45.31/100 000. From 1992–2021, China showed upward trends in ASIR and ASPR but declines in ASMR and DALYs, while global ASIR, ASMR, and DALYs decreased overall with slow ASPR growth. The peak cases in China and globally were both concentrated in the 65-79 age group, with a significantly higher burden on males than females. In China, smoking-related ASMR and ASDR exceeded global averages and rose, whereas high glucose-related indexes were lower and declined. Projections for 2021–2036 indicated that the global incidence and mortality rates would be rising, but ASIR/ASPR would be declining, while in China, the incidence rate would continue to rise, and the mortality rate will stabilize, with a significant increase in ASIR and a gradual decrease in ASPR.  Conclusion From 1992 to 2021, the incidence of bladder cancer in China has shown a continuous upward trend and is projected to persist in the future, with significant gender and age differences. Particular attention should be given to elderly males aged 85-89. The disease burden of bladder cancer attributable to smoking continues to rise, highlighting the urgent need to strengthen tobacco control policies.

INTRODUCTION: The rising rate of adolescent suicide, and the burden of self-harm and mental health disorders, pose significant threats to Singapore's future health outcomes and human potential. This study sought to examine the risk profile and healthcare utilisation patterns of Singaporean adolescents who presented to the emergency department (ED) for suicidal or self-harm behaviour. METHOD: A retrospective review of medical records for patients aged 10 to 19 years who visited Singapore's KK Women's and Children's Hospital ED for suicidal or self-harm attempts from January to December 2021 was conducted. RESULTS: A total of 221 patients were identified, with a predominance of female patients (85.5%) over males (14.5%). The mean age was 14.2 ± 1.4 years. Intentional drug overdose (52.0%) was the most commonly used method. Significantly more females presented for intentional paracetamol overdose (46.6% versus [vs] 28.1%, P=0.049), whereas jumping from a height was more common among males (18.8% vs 5.8%, P=0.022). The most frequently observed mental health challenges were stress-related and emotional coping difficulties (50.7%), followed by mood and anxiety symptoms (53.4%). A history of self-harm and suicidal behaviours were the most common psychosocial risk factors. Within the year prior to their ED presentation, 15.4% had accessed healthcare services for mild medical ailments, 19.5% for medically unexplained symptoms, and 17.2% for previous self-harm or suicide attempts. CONCLUSION Most cases involved psychosocial and emotional regulation difficulties, some of which displayed sex-specific patterns, rather than complex psychiatric disorders. The identified predictive factors can help inform Singapore's National Mental Health and Well-being Strategy, to guide targeted and transdiagnostic interventions in schools and community settings.
Humans ; Adolescent ; Singapore/epidemiology* ; Female ; Male ; Suicide, Attempted/psychology* ; Emergency Service, Hospital/statistics & numerical data* ; Self-Injurious Behavior/psychology* ; Retrospective Studies ; Child ; Young Adult ; Drug Overdose/epidemiology* ; Risk Factors ; Acetaminophen/poisoning* ; Patient Acceptance of Health Care/statistics & numerical data* ; Sex Factors

As a common neurological disease in China, stroke has an extremely high rate of death and disability, of which 80% is ischemic stroke (IS), causing a serious burden to individuals and society. Neuronal death is an important factor in the pathogenesis of stroke. Studies have shown that mitochondrial dynamics, as a key mechanism regulating intracellular energy metabolism and cell death, plays an important role in the pathogenesis of IS. In recent years, targeting mitochondrial dynamics has become an emerging therapeutic tool to improve neurological impairment after stroke. This paper reviews the research advance in recent years in IS mitochondrial dynamics, summarizing and discussing the overview of mitochondrial dynamics, the role of mitochondrial dynamics in IS, and the studies on mitochondrial dynamics-based treatment of IS. This paper helps to explore the mechanism of the role of mitochondrial dynamics in IS and effective interventions, and provides a theoretical strategy for targeting mitochondrial dynamics to treat IS in the clinic.
Humans ; Mitochondrial Dynamics/physiology* ; Ischemic Stroke/metabolism* ; Mitochondria/physiology* ; Animals ; Brain Ischemia/physiopathology* ; Energy Metabolism

OBJECTIVE: To assess health equity in the Yangtze River region to improve understanding of the correlation between hand, foot, and mouth disease (HFMD) and socioeconomic factors. METHODS: From 2014-2016, data on HFMD incidence, population statistics, economic indicators, and meteorology from 26 cities along the Yangtze River were analyzed. A multi-city random-effects meta-analysis was performed to study the relationship between temperature and HFMD transmission, and health equity was assessed with respect to socio-economic impact. RESULTS: Over the study period, 919,458 HFMD cases were reported, with Shanghai (162,303) having the highest incidence and Tongling (5,513) having the lowest. Males were more commonly affected (male-to-female ratio, 1.49:1). The exposure-response relationship had an M-shaped curve, with two HFMD peaks occurring at 4 °C and 26 °C. The relative risk had two peaks at 1.30 °C (1.834, 95% CI: 1.204-2.794) and 31.4 °C (1.143, 95% CI: 0.901-1.451), forming an M shape, with the first peak higher than the second. The most significant impact of temperature on HFMD was observed between -2 °C and 18.1 °C. The concentration index (0.2463) indicated moderate concentration differences, whereas the Theil index (0.0418) showed low inequality in distribution. CONCLUSION The incidence of HFMD varied across cities, particularly with changes in temperature. Economically prosperous areas showed higher risks, indicating disparities. Targeted interventions in these areas are crucial for mitigating the risk of HFMD.
Female ; Humans ; Male ; China/epidemiology* ; Cities/epidemiology* ; Hand, Foot and Mouth Disease/transmission* ; Incidence ; Risk Factors ; Temperature

OBJECTIVE: Pneumoconiosis, a lung disease caused by irreversible fibrosis, represents a significant public health burden. This study investigates the causal relationships between gut microbiota, gene methylation, gene expression, protein levels, and pneumoconiosis using a multi-omics approach and Mendelian randomization (MR). METHODS: We analyzed gut microbiota data from MiBioGen and Esteban et al. to assess their potential causal effects on pneumoconiosis subtypes (asbestosis, silicosis, and inorganic pneumoconiosis) using conventional and summary-data-based MR (SMR). Gene methylation and expression data from Genotype-Tissue Expression and eQTLGen, along with protein level data from deCODE and UK Biobank Pharma Proteomics Project, were examined in relation to pneumoconiosis data from FinnGen. To validate our findings, we assessed self-measured gut flora from a pneumoconiosis cohort and performed fine mapping, drug prediction, molecular docking, and Phenome-Wide Association Studies to explore relevant phenotypes of key genes. RESULTS: Three core gut microorganisms were identified: Romboutsia ( OR = 0.249) as a protective factor against silicosis, Pasteurellaceae ( OR = 3.207) and Haemophilus parainfluenzae ( OR = 2.343) as risk factors for inorganic pneumoconiosis. Additionally, mapping and quantitative trait loci analyses revealed that the genes VIM, STX8, and MIF were significantly associated with pneumoconiosis risk. CONCLUSIONS This multi-omics study highlights the associations between gut microbiota and key genes ( VIM, STX8, MIF) with pneumoconiosis, offering insights into potential therapeutic targets and personalized treatment strategies.
Humans ; Male ; East Asian People/genetics* ; Europe ; Gastrointestinal Microbiome ; Lung ; Macrophage Migration-Inhibitory Factors/metabolism* ; Mendelian Randomization Analysis ; Multiomics ; Pneumoconiosis/microbiology* ; Intramolecular Oxidoreductases

Medical equipment, as an important indicator of smart hospital evaluation, plays a vital role in hospital operations. To ensure the safe and efficient operation of medical equipment, a reasonable performance evaluation system is indispensable. This study introduces a platform based on Internet of Things (IoT) technology that connects medical devices and collects data, achieving standardized and structured data processing, and supporting online operational supervision. Through the Delphi method, a performance evaluation system for large medical equipment is constructed, including 4 primary indicators and 22 secondary indicators. DICOM data acquisition devices are used to achieve functions such as efficiency analysis, benefit analysis, usage evaluation, and decision-making support for medical equipment. The study is still in its early stages, and in the future, it is expected to integrate more types of equipment, achieve rational resource allocation, and significantly impact decision-making for the development of public hospitals.
Internet of Things ; Delphi Technique

Drug resistance is one of the key factors affecting the effectiveness of cancer treatment methods, including chemotherapy, radiotherapy, and immunotherapy. Its occurrence is related to factors such as mRNA expression and methylation within cancer cells. If drug resistance in patients can be accurately identified early, doctors can devise more effective treatment plans, which is of great significance for improving patients' survival rates and quality of life. Cancer drug resistance prediction based on artificial intelligence (AI) technology has emerged as a current research hotspot, demonstrating promising application prospects in guiding clinical individualized and precise medication for cancer patients. This review aims to comprehensively summarize the research progress in utilizing AI algorithms to analyze multi-omics data including genomics, transcriptomics, epigenomics, proteomics, metabolomics, radiomics, and histopathology, for predicting cancer drug resistance. It provides a detailed exposition of the processes involved in data processing and model construction, examines the current challenges faced in this field and future development directions, with the aim of better advancing the progress of precision medicine.