To analyze the disease burden of acute lymphoid leukemia(ALL) and its changing trends in China and globally from 1990 to 2021, aiming to provide a theoretical basis for disease prevention, treatment, and policy formulation.

OBJECTIVE: To develop a digital intelligent multimodal shift handover system for the intensive care unit (ICU) and evaluate its application effect in ICU shift handovers. METHODS: A research and development team was established, consisting of 1 department director, 1 head nurse, 3 information technology engineers, 3 nurses, and 2 doctors. Team members were assigned responsibilities including overall coordination and planning, platform design and maintenance, pre-application training, collection and organization of clinical feedback, and research investigation respectively. A digital intelligent multimodal shift handover system was developed for ICU based on the Shannon-Weaver linear transmission model. This innovative system integrated automated data collection, intelligent dynamic monitoring, multidimensional condition analysis and visual reporting functions. A cloud platform was used to gather data from multi-parameter vital signs monitors, infusion pumps, ventilators and other devices. Artificial intelligence algorithms were employed to standardize and analyze the data, providing personalized recommendations for healthcare professionals. A self-controlled before-after method was adopted. Before the application of the ICU digital intelligent multimodal shift handover system (from December 2023 to March 2024), the traditional verbal bedside handover was used; from June 2024 to March 2025, the ICU digital intelligent multimodal shift handover system was applied for shift handovers. Questionnaires before the application of the shift handover system were collected in April 2024, and those after the application were collected in April 2025. The shift handover time, handover quality (scored by the nursing handover evaluation scale), satisfaction with doctor-nurse communication (scored by the ICU doctor-nurse scale) before and after the application of the handover system were compared, and nurses' satisfaction with the shift handover system (scored by the clinical nursing information system effectiveness evaluation scale) was investigated. RESULTS: After the application of the ICU digital intelligent multimodal shift handover system, the shift handover time was significantly shorter than that before the application [minutes: 20 (15, 25) vs. 30 (22, 40)], the handover quality was significantly higher than that before the application [score: 84.0 (78.0, 88.5) vs. 71.0 (55.0, 79.0)], and the satisfaction with doctor-nurse communication was also significantly higher than that before the application (score: 84.58±6.79 vs. 74.50±11.30). All differences were statistically significant (all P < 0.05). In addition, the nurses' system effectiveness evaluation scale score was 102.30±10.56, which indicated that nurses had a very high level of satisfaction with the ICU digital intelligent multimodal shift handover system. CONCLUSIONS The application of the ICU digital intelligent multimodal shift handover system can shorten the shift handover time, improve the handover quality, and enhance the satisfaction with doctor-nurse communication. Nurses have a high level of satisfaction with this system.
Intensive Care Units ; Humans ; Patient Handoff ; Artificial Intelligence ; Algorithms

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

Objective: To establish a machine learning-based precision blood donor recruitment model at the county level and assess its generalizability and applicability. Methods: A retrospective study was conducted using blood donation and SMS recruitment data from the Taicang Branch of the Suzhou Blood Center between 2019 and 2024. Multiple machine learning algorithms were employed, including extreme gradient boosting, support vector machine, k-nearest neighbor, logistic regression, decision tree, random forest, and multilayer perceptron. These were combined with techniques such as synthetic minority oversampling, undersampling, and cost-sensitive learning (using MFE and MSFE loss functions). Model parameters were optimized through grid search to identify the best-performing model. Results: In a prospective comparative study against conventional methods, the machine learning models increased the recruitment success rate among high-willingness donors by an average of 129.15%, and the recruitment efficiency per SMS improved by 125.02% compared with the traditional method. Under full-scale SMS sending, the recruitment rate per SMS increased by 42.61%, and SMS sending efficiency improved by 31.77%, significantly enhancing recruitment performance. Conclusion: This study represents the first application of a machine learning-based precision donor recruitment model at the county-level in China. The precise recruitment framework not only improves recruitment efficiency and reduces recruitment costs but also demonstrates strong scalability and generalizability. It provides a scientific and feasible intelligent pathway to ensure the safety and sustainability of the blood supply.

Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is a complex disease that is often accompanied by mental health disorders. However, the potential mechanisms underlying the heterogeneous clinical presentation of CP/CPPS remain uncertain. This study analyzed widely targeted metabolomic data of expressed prostatic secretions (EPS) and plasma to reveal the underlying pathological mechanisms of CP/CPPS. A total of 24 CP/CPPS patients from The Second Nanning People's Hospital (Nanning, China), and 35 asymptomatic control individuals from First Affiliated Hospital of Guangxi Medical University (Nanning, China) were enrolled. The indicators related to CP/CPPS and psychiatric symptoms were recorded. Differential analysis, coexpression network analysis, and correlation analysis were performed to identify metabolites that were specifically altered in patients and associated with various phenotypes of CP/CPPS. The crucial links between EPS and plasma were further investigated. The metabolomic data of EPS from CP/CPPS patients were significantly different from those from control individuals. Pathway analysis revealed dysregulation of amino acid metabolism, lipid metabolism, and the citrate cycle in EPS. The tryptophan metabolic pathway was found to be the most significantly altered pathway associated with distinct CP/CPPS phenotypes. Moreover, the dysregulation of tryptophan and tyrosine metabolism and elevation of oxidative stress-related metabolites in plasma were found to effectively elucidate the development of depression in CP/CPPS. Overall, metabolomic alterations in the EPS and plasma of patients were primarily associated with oxidative damage, energy metabolism abnormalities, neurological impairment, and immune dysregulation. These alterations may be associated with chronic pain, voiding symptoms, reduced fertility, and depression in CP/CPPS. This study provides a local-global perspective for understanding the pathological mechanisms of CP/CPPS and offers potential diagnostic and therapeutic targets.
Humans ; Male ; Prostatitis/blood* ; Adult ; Pelvic Pain/blood* ; Metabolomics ; Prostate/metabolism* ; Middle Aged ; Chronic Pain/blood* ; Metabolome ; Case-Control Studies ; Tryptophan/blood* ; Depression/blood* ; Oxidative Stress/physiology* ; Chronic Disease ; Lipid Metabolism/physiology*

OBJECTIVES: To investigate the therapeutic effects and mechanisms of 2,6-dimethoxy-1,4-benzoquinone (2,6-DMBQ) in a mouse model of asthma. METHODS: SPF-grade BALB/c mice were randomly divided into 7 groups (n=8 each group): normal control group, ovalbumin (OVA) group, dimethyl sulfoxide+corn oil group, budesonide (BUD) group, and low, medium, and high dose 2,6-DMBQ groups. An asthma mouse model was established by OVA induction, followed by corresponding drug interventions. Non-invasive lung function tests were performed to measure airway hyperresponsiveness, and enzyme-linked immunosorbent assay was used to determine levels of interleukin (IL)-17, IL-10, and serum immunoglobulin E in bronchoalveolar lavage fluid. A cell counter was employed to detect eosinophil counts in bronchoalveolar lavage fluid, while hematoxylin-eosin staining and periodic acid-Schiff staining were used to assess lung tissue pathological changes. Western blot was conducted to examine the expression of proteins related to the mammalian target of rapamycin pathway (p-AKT/AKT and p-p70S6K/p70S6K), and a fully automated biochemical analyzer was used to evaluate liver and kidney functions. RESULTS: Compared with the normal control group, the OVA group showed increased enhanced pause values, inflammation scores from hematoxylin-eosin staining, positive area from periodic acid-Schiff staining, percentage of eosinophils, IL-17/IL-10 ratio, serum immunoglobulin E levels, and relative expression levels of p-AKT/AKT and p-p70S6K/p70S6K (P<0.05). The BUD group and the medium and high dose 2,6-DMBQ groups exhibited decreased values for these indicators compared to the OVA group (P<0.05). CONCLUSIONS 2,6-DMBQ can inhibit the mTOR pathway to alleviate airway inflammation in asthmatic mice, possibly by mitigating the imbalance between Th17 and regulatory T cells.
Animals ; Asthma/pathology* ; Mice, Inbred BALB C ; Signal Transduction/drug effects* ; Mice ; TOR Serine-Threonine Kinases/physiology* ; Female ; Benzoquinones/pharmacology* ; Immunoglobulin E/blood* ; Interleukin-10/analysis* ; Interleukin-17/analysis* ; Bronchoalveolar Lavage Fluid ; Lung/pathology*

OBJECTIVE: To investigate the relationship between angiotensin Ⅱ type 1 receptor autoantibody (AT1-AA) and semen parameters. Methods： The semen samples of 820 male patients who were treated in the Reproductive Medicine Center of Taiyuan Central Hospital from August 2022 to August 2023 were retrospectively analyzed. The levels of AT1-AA and Ang Ⅱ of semen were detected by ELISA, and the function of AT1-AA was detected by cardiomyocyte beating assay in suckling rats. The patients were divided into low group, median group and high group according to the OD values of AT1-AA. The differences in general data and semen parameters between different groups were analyzed. And the correlation between AT1-AA level and semen parameters in semen of all study subjects was analyzed by the method of Spearman analysis. And the relationships between AT1-AA OD value, Ang Ⅱ level and semen parameters in the AT1-AA high value group were analyzed as well. RESULTS: AT1-AA was present in semen with good function. There was no significant difference in the general data of patients in different AT1-AA levels (P>0.05). In the comparison of semen parameters among the groups with different levels of AT1-AA, there were differences in sperm concentration, PR concentration, NP％, and ALH among the three groups (P<0.05). And AT1-AA OD value was positively correlated with total sperm count, sperm concentration, PR concentration, and NP％, and negatively correlated with semen volume (P<0.05). In the AT1-AA high value group, the OD value of AT1-AA in semen was negatively correlated with inactive sperm, and positively correlated with total motility (［PR+NP］％), curve rate, mean path rate, and ALH. However, there was no correlation between the level of Ang Ⅱ in semen and semen parameters (P>0.05). CONCLUSION The presence of AT1-AA in semen may be associated with the promotion of sperm motility.
Male ; Humans ; Autoantibodies ; Sperm Motility ; Semen ; Retrospective Studies ; Receptor, Angiotensin, Type 1/immunology* ; Animals ; Rats ; Angiotensin II ; Adult ; Sperm Count ; Semen Analysis ; Receptor, Angiotensin, Type 2/immunology*

Despite that sleep disturbance and poor neurocognitive performance are common complaints among coronavirus disease 2019 (COVID-19) survivors, few studies have focused on the effect of post-COVID-19 sleep disturbance (PCSD) on cognitive function. This study aimed to identify the impact of PCSD on neurocognitive function and explore the associated risk factors for the worsening of this condition. This cross-sectional study was conducted via the web-based assessment in Chinese mainland. Neurocognitive function was evaluated by the modified online Integrated Cognitive Assessment (ICA) and the Number Ordering Test (NOT). Propensity score matching (PSM) was utilized to match the confounding factors between individuals with and without PCSD. Univariate analyses were performed to evaluate the effect of PCSD on neurocognitive function. The risk factors associated with worsened neurocognitive performance in PCSD individuals were explored using binary logistic regression. A total of 8692 individuals with COVID-19 diagnosis were selected for this study. Nearly half (48.80%) of the COVID-19 survivors reported sleep disturbance. After matching by PSM, a total of 3977 pairs (7954 individuals in total) were obtained. Univariate analyses revealed that PCSD was related to worse ICA and NOT performance (P<0.05). Underlying disease, upper respiratory infection, loss of smell or taste, severe pneumonia, and self-reported cognitive complaints were associated with worsened neurocognitive performance among PCSD individuals (P<0.05). Furthermore, aging, ethnicity (minority), and lower education level were found to be independent risk factors for worsened neurocognitive performance in PCSD individuals (P<0.05). PCSD was related to impaired neurocognitive performance. Therefore, appropriate prevention and intervention measures should be taken to minimize or prevent PCSD and eliminate its potential adverse effect on neurocognitive function.
Humans ; COVID-19/epidemiology* ; Male ; Female ; Sleep Wake Disorders/epidemiology* ; Propensity Score ; Middle Aged ; Cross-Sectional Studies ; Adult ; SARS-CoV-2 ; Aged ; Risk Factors ; China/epidemiology* ; Cognition ; Cognitive Dysfunction/etiology* ; Neuropsychological Tests