Background: Adrenocortical hormones, particularly 11-oxygenated androgens, are pivotal in female reproductive health and fertility. Standardized detection kits and population-specific reference intervals are lacking in China, hindering related clinical applications. Methods: A HPLC-tandem mass spectrometry (HPLC-MS/MS) pipeline was developed, rigorously validated, and applied to simultaneously quantify corticosterone, cortisone, cortisol, 18-OH cortisol, androstenedione (A4), 11β-hydroxyandrostenedione (11-OH A4), dehydroepiandrosterone, and dehydroepiandrosterone sulfate in serum samples from 455 reproductive-aged women (18–45 yrs) in Guangxi, China. Age-dependent concentration trends were analyzed, and reference intervals stratified by age (2.5th to 97.5th percentiles) were established. Correlations with body-composition metrics, ethnicity, and the menstrual cycle were investigated. Results: The HPLC-MS/MS method demonstrated high precision (intra- and inter-assay CVs < 15%), accuracy, and sensitivity. All eight hormones exhibited significant age-related declines (P < 0.001 for seven hormones; P = 0.001 for 11-OH A4). Notably, 11-OH A4 levels were significantly lower in the 35–45-yr (3.05 nmol/L) and 25–34-yr (3.09 nmol/L) age groups than in the 18–24-yr (3.57 nmol/L) age group, whereas no significant difference was observed between the 35–45-yr and 25–34-yr age groups. Weak negative correlations were observed between the body mass index and corticosterone and cortisone levels, whereas ethnicity and the menstrual cycle showed no significant associations with hormone levels. Conclusions We developed an HPLC-MS/MS-based method for simultaneously quantifying eight adrenocortical hormones, including 11-OH A4, and defined age-specific reference intervals for reproductive-aged Chinese women. These findings advance the clinical utility of adrenocortical hormones in diagnosing and managing reproductive disorders.

Lung transplantation is currently the only effective treatment for end-stage lung disease. However, the field of lung transplantation still faces numerous challenges, including donor shortage, primary graft dysfunction, rejection, infection and others. In 2025, scholars worldwide have made remarkable progress in clinical research on lung transplantation. This article systematically reviews the cutting-edge developments in clinical research on lung transplantation in 2025, focusing on the application of novel evaluation tools in donor lung screening, optimization of lung perfusion techniques, exploration of extracorporeal membrane oxygenation and robot-assisted minimally invasive surgery, as well as mechanistic research and intervention strategies for primary graft dysfunction, acute kidney injury and chronic lung allograft dysfunction. Meanwhile, hot topics such as the management of special populations, prevention and control of postoperative infections, and improvement of quality of life are summarized. This review aims to conclude the important annual research findings and provide references for the clinical practice and research development of lung transplantation in China.

ObjectiveTo investigate the current awareness and optimization recommendations on pneumonia with unknown etiology (PUE) surveillance among Shanghai healthcare professionals, and to provide evidence for the improvement of the surveillance system. MethodsIn December 2024, healthcare professional participants from diverse medical and health institutions were randomly selected within each stratum using a stratified cluster sampling method in all 16 districts of Shanghai for questionnaire surveys on their knowledge and suggestions for optimization of the PUE surveillance system. Descriptive statistics analyses, multivariate logistic regressions, and content analyses were used for data analyses. ResultsA total of 385 survey subjects were involved in the study, including 119 professional staffs from disease prevention and control centers and 266 from medical institutions. Those who understood the case definition for PUE correctly accounted for 67.01% (258/385). Multivariate regression model analyses showed that female gender (aOR=2.22, 95%CI: 1.36‒3.66), professionals from disease control institutions (aOR=2.02, 95%CI: 1.12‒3.72), and those who self-assessed as being familiar with the monitoring system (aOR=2.18, 95%CI:1.23‒3.89) had better understanding of the definition. Overall, 89.61% (345/385) of the survey subjects acknowledged the necessity of the surveillance system. Small number of cases meeting the case definition (54.46%, 214/379), insufficient diagnostic awareness (39.84%, 151/379), and lack of incentives for case reporting (29.29%, 111/379) were major problems for the current surveillance system, with variations observed across different types of institutions. Suggested segments for optimizing the surveillance system included monitoring purpose, case definition, form of monitoring and reporting procedure, organization mechanism, and epidemiological investigation and response. ConclusionThe necessity of PUE surveillance is commonly recognized among healthcare workers. However, the existing system falls short in terms of mastery of case definition and overall surveillance adaptability. There is an urgent need for optimization and improvement to enhance the capacity for preventing and controlling emerging and sudden respiratory infectious diseases.

Objective: To predict and screen potential biomarkers of systemic lupus eythematosus(SLE) based on machine learning algorithms and structural biology, and to reveal their mechanisms of action and to provide new targets for disease diagnosis and treatment. Methods: Four machine learning algorithms, random forest(RF), eXtreme gradient boosting(XGBoost), support vector machine(SVM), least absolute shrinkage and selection operator(LASSO), were used to analyze the gene expression data of SLE patients in GEO(datasets: GSE121239 and GSE11907) to analyze the gene expression data of SLE patients and screen key markers. Peripheral blood single nucleated cells(PBMCs) from SLE patients were collected and RT-qPCR was used to detect differential gene expression levels. Subsequently, GSEA enrichment analysis was used to identify biomarker-related pathways. CIBERSORT immune infiltration analysis and protein interactions network were applied to calculate the sample immune cell infiltration abundance. Single-cell data were analyzed for gene expression specificity in immune cells. Interaction relationships in combination with AlphaFold3(AF3) were predicted. Results: Multiple algorithms were screened together to identify the unique marker gene HERC5 , and expression analysis of multiple datasets showed that HERC5 was highly expressed in SLE compared to the normal group (P < 0. 05) , and RT⁃qPCR verified the same trend (P = 0. 006 2) . Functional enrichment analysis identified the major pathway promoted by HERC5 in SLE as the interferon receptor signalling pathway (P < 0. 05) . Immune infiltration analysis showed that HERC5 was closely associated with immune cells (Neutrophils : r = 0. 39 , P < 0. 05 ; Memory B cells : r = 0. 33 , P < 0. 05 ; Activated dendritic cell : r = 0. 52 , P < 0. 05) . Most HERC5 ⁃related interacting proteins were associated with SLE ,and potential transcription factors of HERC5 and its related genes were also significantly associated with immune responses. Conclusion The HERC5 gene is an important biomarker for SLE , which upregulates the interferon pathway to promote SLE progression and provides a new target for SLE diagnosis and treatment.

Objective: To analyze the nucleic acid load of human parvovirus B19 in major commercially available blood products in China, including human albumin, human intravenous immunoglobulin, human rabies immunoglobulin and various coagulation factor products, aiming to provide evidence for improving blood product manufacturing processes and quality control of source plasma. Methods: A total of 98 batches of coagulation factor products were tested for human parvovirus B19 nucleic acid using real-time fluorescent quantitative PCR, including 42 batches of human prothrombin complex, 35 batches of human coagulation factor Ⅷ, and 21 batches of human fibrinogen. Additionally, 6 batches of human albumin, 6 batches of human intravenous immunoglobulin, and 38 batches of human rabies immunoglobulin were tested for human parvovirus B19 nucleic acid. Results: Human parvovirus B19 nucleic acid were undetectable in human albumin, human intravenous immunoglobulin and human rabies immunoglobulin. Among the 98 batches of coagulation factor products tested for human parvovirus B19 nucleic acid, B19 nucleic acid reactivity rate was 69.0% (29/42) for human prothrombin complex batches, but nucleic acid concentration were all significantly lower than 10 IU/mL. The reactivity rate of B19 nucleic acid in 35 batches of human coagulation factor Ⅷ was 48.6% (17/35), with nucleic acid concentration all below 10 IU/mL. The reactivity rate of B19 nucleic acid in 21 batches of human fibrinogen was 61.9% (13/21), with nucleic acid concentration all below 10 IU/mL. Conclusion: No human parvovirus B19 has been detected in human albumin, human intravenous immunoglobulin, or human rabies immunoglobulin. Human parvovirus B19 nucleic acid may exist in commercially available coagulation factor products, highlighting the need for enhanced screening of human parvovirus B19 nucleic acid in these products. It is also recommended that B19 viral nucleic acid testing be conducted on source plasma, particularly for coagulation factor products.

Objective: To analyze the nucleic acid load of human parvovirus B19 in major commercially available blood products in China, including human albumin, human intravenous immunoglobulin, human rabies immunoglobulin and various coagulation factor products, aiming to provide evidence for improving blood product manufacturing processes and quality control of source plasma. Methods: A total of 98 batches of coagulation factor products were tested for human parvovirus B19 nucleic acid using real-time fluorescent quantitative PCR, including 42 batches of human prothrombin complex, 35 batches of human coagulation factor Ⅷ, and 21 batches of human fibrinogen. Additionally, 6 batches of human albumin, 6 batches of human intravenous immunoglobulin, and 38 batches of human rabies immunoglobulin were tested for human parvovirus B19 nucleic acid. Results: Human parvovirus B19 nucleic acid were undetectable in human albumin, human intravenous immunoglobulin and human rabies immunoglobulin. Among the 98 batches of coagulation factor products tested for human parvovirus B19 nucleic acid, B19 nucleic acid reactivity rate was 69.0% (29/42) for human prothrombin complex batches, but nucleic acid concentration were all significantly lower than 10 IU/mL. The reactivity rate of B19 nucleic acid in 35 batches of human coagulation factor Ⅷ was 48.6% (17/35), with nucleic acid concentration all below 10 IU/mL. The reactivity rate of B19 nucleic acid in 21 batches of human fibrinogen was 61.9% (13/21), with nucleic acid concentration all below 10 IU/mL. Conclusion: No human parvovirus B19 has been detected in human albumin, human intravenous immunoglobulin, or human rabies immunoglobulin. Human parvovirus B19 nucleic acid may exist in commercially available coagulation factor products, highlighting the need for enhanced screening of human parvovirus B19 nucleic acid in these products. It is also recommended that B19 viral nucleic acid testing be conducted on source plasma, particularly for coagulation factor products.

Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

Objective: To investigate the association between overweight, obesity, central obesity and hypertension, so as to provide the basis for formulating targeted hypertension prevention and control strategies. Methods: Permanent residents aged ≥18 years were selected in Wenzhou City, Zhejiang Province from June 2023 to August 2024 by a multistage cluster random sampling method. Data on demographic information, lifestyle, height, weight, waist circumference (WC), blood pressure, and blood biochemical indicators were collected through questionnaire surveys, physical examinations, and laboratory tests. The prevalence of hypertension was calculated and standardized using the data of the Sixth National Population Census in 2010. Body mass index (BMI) was calculated to determine overweight and obesity, while WC was used to identify central obesity. The association between overweight, obesity, central obesity and hypertension were analyzed using multivariable logistic regression models. Results: A total of 38 593 residents were surveyed, including 19 481 (50.48%) males and 19 112 (49.52%) females. The median age was 46.00 (interquartile range, 26.00) years. The rates of overweight, obesity, and central obesity were 32.74% (12 634 individuals), 10.27% (3 963 individuals), and 27.87% (10 755 individuals), respectively. There were 11 813 cases of hypertension, with a prevalence and standardized prevalence of 30.61% and 24.41%, respectively. Multivariable logistic regression analysis showed that after adjusting for demographic information, lifestyle, diabetes and dyslipidemia, the likelihood of hypertension in the overweight and obesity groups was 1.927 (95%CI: 1.815-2.045) times and 3.724 (95%CI: 3.404-4.073) times that of the normal BMI group, respectively. The likelihood of hypertension in the central obesity group was 2.346 (95%CI: 2.214-2.486) times that of the normal WC group. The likelihood of hypertension in the central obesity only, overweight only, overweight with central obesity, obesity only and obesity with central obesity groups was 1.586 (95%CI: 1.391-1.809), 1.704 (95%CI: 1.582-1.835), 2.433 (95%CI: 2.254-2.626), 1.768 (95%CI: 1.424-2.194), and 4.466 (95%CI: 4.053-4.921) times that of the normal BMI and WC group, respectively. Conclusions Overweight, obesity and central obesity were all associated with hypertension among adult residents. The highest likelihood of hypertension was observed among adult residents with both general obesity and central obesity.

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

Objective To conduct a scoping review of research on the relationship between 24-hour movement behaviours and cognitive function in the elderly,so as to provide references for future research.Methods Totally 8 Chinese and English databases were systematically searched.The search period spanned from the establishment of databases until November 30,2024.According to the scoping review framework,2 researchers independently screened the studies,extracted the data of the included studies,and collaborated on the final analysis.Results A total of 12 papers were included,and the distribution of 24-hour movement behaviors in the elderly was as follows:3.0-5.4 h/d for light physical activity,0.6-1.5 h/d for moderate vigorous physical activity,8.9-12.3 h/d for sedentary behaviour and 6.7-8.4 h/d for sleep.Measures included objective,subjective and subject-objective measures.There are complex interactions among physical activity,sedentary behavior,sleep and cognitive function,which jointly affect cognitive function in the elderly.Conclusion Despite current differences in the measurement of 24-hour movement behaviours,the decreased physical activity,the increased sedentary time,and insufficient or excessive sleep are common problems among the elderly.By increasing physical activity,reducing sedentary behavior and ensuring adequate sleep,the overall cognitive function,executive function of the elderly can be improved.In the future,we should pay attention to the time allocation of 24-hour movement behaviours of the elderly,develop accurate and standardized measurement methods,and promote research in this field.