OBJECTIVE: To explore the application value of artificial intelligence (AI)-assisted chromosomal karyotype analysis in the diagnosis of prenatal chromosomal mosaicism. METHODS: A retrospective analysis was conducted on 172 pregnant women who underwent amniocentesis at the Department of Medical Genetics and Prenatal Diagnosis, the Third Affiliated Hospital of Zhengzhou University between January 2019 and December 2024. All cases whose fetuses were diagnosed with chromosomal mosaicism via karyotype analysis and stratified into two groups based on the analytical software employed: the conventional analysis group (n = 70), which utilized Leica analysis software for karyotype image recognition and cell counting; and the AI-assisted analysis group (n = 102), which utilized AI-assisted software for the same procedures. The clinical performance of AI-assisted karyotype analysis in diagnosing chromosomal mosaicism was comprehensively evaluated by comparing the types of mosaic karyotypes, distribution of mosaic ratios, and verification outcomes of different detection modalities between the two groups. This study was approved by the Medical Ethics Committee of the Third Affiliated Hospital of Zhengzhou University (Ethics No.: 2024-406-01). RESULTS: No statistically significant difference was observed in baseline characteristics (maternal age, gestational week, and indications for prenatal diagnosis) between the two groups. Regarding the detection efficacy for numerical and structural mosaicisms, no significant difference was found in the detection of numerical mosaicism. However, the conventional analysis group exhibited a significantly higher detection rate of autosomal structural mosaicism compared to the AI-assisted group (11.43% vs. 0.98%, P < 0.05). Numerical mosaicism cases were further verified using copy number variation sequencing (CNV-seq) and/or fluorescence in situ hybridization (FISH). The AI-assisted group demonstrated a significantly lower inconsistency rate (5.56% vs. 20.41%, P < 0.05) compared to the conventional group. For low-proportion (< 10%) chromosomal mosaicism, the AI-assisted group had a significantly lower detection rate (13.25% vs. 29.69%, P < 0.05). Subsequent validation of low-proportion mosaicism by CNV-seq and/or FISH showed a higher consistency rate in the AI-assisted group (81.82% vs. 54.55%), though the difference did not reach statistical significance (P = 0.360). CONCLUSION For the karyotyping analysis of prenatal chromosomal mosaicism, AI-assisted karyotype analysis shows high accuracy and consistency in identifying numerical chromosomal mosaicism, particularly in reducing the detection of low-proportion (< 10%) mosaicism while improving verification accuracy. AI-assisted analysis can significantly improve the detection accuracy of numerical mosaicism and mitigate the risk of misclassification for low-proportion (< 10%) mosaicism, thereby providing more precise clinical evidence for the prenatal diagnosis of chromosomal mosaicisms.
Humans ; Female ; Mosaicism ; Pregnancy ; Karyotyping/methods* ; Artificial Intelligence ; Prenatal Diagnosis/methods* ; Adult ; Retrospective Studies ; Chromosome Disorders/genetics* ; Amniocentesis

ObjectiveTo explore the role of the histone deacetylase Sirtuin-1 （SIRT1）/p53 signaling pathway in promoting apoptosis of non-small cell lung cancer cells （NSCLC） induced by the co-stimulatory molecule B7 homolog 3 （B7-H3）. MethodsThe GEPIA 2 platform was used for survival analysis of NSCLC patients based on B7⁃H3 gene expression levels. The Gene Enrichment Analysis （GSEA） method was used to analyze the enrichment characteristics of B7⁃H3 molecules in the gene set of cell apoptosis. In the non-small cell lung cancer A549 cell line， B7⁃H3 was knocked down， and the protein expression levels of SIRT1 and p53 were detected by Western blot. B7⁃H3 was overexpressed in A549 cells and the apoptosis rate was analyzed by flow cytometry after Annexin V/PI double staining. Overexpression of B7⁃H3 and knockdown of SIRT1 were performed in A549 cell line. The expression levels of p53 and apoptosis-related proteins B-cell lymphoma/leukemia-2 （Bcl-2） and Bcl-2-associated X protein （Bax） were detected respectively by Western blot. Cell apoptosis rate was analyzed by flow cytometry after Annexin V/PI double staining. ResultsThe overall survival of the B7-H3 high-expression group was significantly lower than that of the low-expression group （P<0.01）. B7-H3 was significantly enriched in the cell apoptosis signaling pathway and the p53 signaling pathway （P<0.05）. Compared with the control group， the expression of SIRT1 was significantly downregulated， and p53 was significantly upregulated in the B7⁃H3 knockdown group （both P<0.001）. Overexpression of B7-H3 significantly up-regulated SIRT1 protein expression （P<0.05）， down-regulated p53 expression （P<0.01）， and markedly increased the Bcl-2/Bax ratio of apoptosis-related proteins （P<0.001）. The results of Annexin V/PI double staining showed that the apoptosis rate of A549 cells with overexpressed B7⁃H3 decreased （the apoptosis rate of the control group was 26.72%±4.13%， while that of the B7⁃H3 overexpression group was 13.87%±0.82%； P<0.01）. In B7-H3-overexpressing cell lines， SIRT1 knockdown significantly reversed apoptosis （P<0.05）， up-regulated p53 protein expression （P<0.001）， and markedly reduced the Bcl-2/Bax ratio （P<0.001）. ConclusionB7-H3 molecule inhibits the apoptosis of non-small cell lung cancer cells via the SIRT1/p53 signaling pathway.

Objective: To investigate the incidence, characteristics, and influencing factors of resolution discrepancies within the minipool (MP) testing model across Chinese blood station laboratories in 2024. Methods: A nationwide, multicenter, cross-sectional study was conducted, including 334 blood station laboratories that reported nucleic acid reactive data among enzyme immunoassay non-reactive samples. Of these, 296 laboratories adopted the pool resolution model, with a total of 12 536 273 samples tested. Systematic analysis was performed on resolution data, focusing on the MP-NAT reactivity rate, the pool resolution concordance rate, and the resolution discrepancy rate. Subgroup analyses were conducted based on reagent types, viral targets, and Ct values. Potential causes were further explored through laboratory surveys and re-examination of raw amplification curves. Results: In 2024, the national average MP-NAT reactivity rate was 0.15%. The overall pool resolution concordance rate was 57.86%, which showed a gradual decline as Ct values increased across all reagents. The national average resolution discrepancy rate was 0.081‱(102/12 536 273), with 17.91%(53/296) of laboratories reporting at least one discrepancy. Nine reagent types were associated with these events, exhibiting reagent-specific patterns. For Reagent A2, the predominant discrepancy was HBV reactive pools resolving as HIV (36.36%); for Reagent D1, HBV pools frequently resolved as HCV (38.89%); and for Reagent E, the most common pattern was HIV pools resolving as HBV (48.00%). These resolution discrepancies were strongly associated with high Ct values: the median pool Ct for HBV exceeded 38, while those for HCV and HIV both exceeded 40. Investigations across 16 laboratories revealed that most discrepant samples exhibited “tailing” amplification curves, with some cases linked to cross-contamination or reagent batch-specific issues. Conclusion: While the incidence of resolution discrepancies in the MP-NAT model remains low in China, variations exist across different reagents and laboratories. These discrepancies are closely associated with low viral load, reagent performance, and laboratory operational practices.

Background: and Purpose Live cell-based assays (LCBA) are increasingly used for serological antibody detection due to their ability to preserve antigen conformation, offering moderately higher sensitivity than fixed cell-based assays. However, the clinical necessity of prioritizing LCBA for the detection of aquaporin-4 immunoglobulin G (AQP4-IgG) in neuromyelitis optica spectrum disorder (NMOSD) remains unclear, especially when compared to its established role in diagnosing myelin oligodendrocyte glycoprotein antibody-associated disease. Methods: We compared the performance of live cell-based assays using immunofluorescence (LCBA-IF) and fixed cell-based assays using immunofluorescence (FCBA-IF) in detecting AQP4-IgG in 90 cases of NMOSD meeting 2015 International Panel for Neuromyelitis Optica Diagnosis criteria, alongside 40 controls. Additionally, we further investigated the relationship between AQP4-IgG titers as measured by LCBA-IF and FCBA-IF and clinical parameters in NMOSD patients. Results: Results showed 96.9% agreement between LCBA-IF and FCBA-IF (Cohen’s κ=0.935), with a strong Spearman correlation (0.977, p<0.001). Both methods demonstrated 100% specificity, with LCBA-IF showing slightly higher sensitivity compared to FCBA-IF. Within LCBAIF-tested groups, statistically significant differences in annualized relapse rates were observed across all pairwise comparisons (low-titer vs. moderate-titer, low-titer vs. high-titer, and moderate-titer vs. high-titer; all p<0.050). However, this association reached statistical significance in some FCBA-IF-tested groups. Conclusions Overall, there is a strong concordance between LCBA-IF and FCBA-IF in detecting AQP4-IgG, where LCBA-IF shows slightly higher sensitivity. Furthermore, there is a potential link between elevated AQP4-IgG titers and an increased risk of relapse, and this correlation may appear more pronounced when using LCBA-IF.

Metabolic dysfunction-associated fatty liver disease （MAFLD） is a chronic metabolic liver disorder with complex etiologies. Different clinical phenotypes of MAFLD （such as obesity， hyperlipidemia， type 2 diabetes mellitus， the postmenopausal state， and chronic hepatitis B） have different mechanisms of action in the development and progression of MAFLD， leading to high heterogeneity in its clinical progression and prognosis. This article systematically reviews the pathogeneses and clinical features of the above five clinical phenotypes of MAFLD and elaborates on the corresponding individualized diagnosis and treatment regimens integrating traditional Chinese medicine and Western medicine， in order to provide a reference for clinical practice and improve clinical diagnosis and treatment.

Objective To analyze the global pattern, long-term trends, and regional and population heterogeneity in the burden of 375 diseases and injuries and 88 risk factors from 1990 to 2023 using data from the Global Burden of Disease Study 2023 (GBD 2023). Methods Publicly available GBD 2023 estimates were extracted for incidence, deaths, years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted life years (DALYs), and age-standardized rates at the global level and by socio-demographic index (SDI), GBD region, age group, and sex. Descriptive analysis, ranking comparison, stratified analysis, and trend analysis were performed, and 95% uncertainty interval was used to assess the stability of estimates. Results In 2023, non-communicable diseases were the leading contributor to global DALYs, accounting for 64.39% of DALYs across the three major disease and injury groups (communicable, maternal, neonatal, and nutritional diseases, non-communicable diseases, and injuries), and also had the highest age-standardized DALYs rate. From 1990 to 2023, age-standardized DALYs rates declined for three major disease and injury groups, with estimated annual percentage changes of −2.69%, −0.78%, and −1.47%, respectively. Cardiovascular diseases ranked first by both DALYs and deaths in 2023, whereas respiratory infections and tuberculosis ranked first by incidence. Non-communicable diseases were the leading cause of disease burden across all SDI strata. As the SDI level declined, the burden of communicable, maternal, neonatal, and nutritional diseases, as well as injuries, increased markedly. Behavioral and metabolic risks remained the main contributors to attributable deaths and DALYs. Conclusion From 1990 to 2023, the global burden of disease continues to shift toward non-communicable diseases; however, some regions still face a double burden of infectious, maternal and child, injury-related, and chronic diseases. Integrating deaths, DALYs, YLLs, YLDs, and risk-attributable burden helps identify priority areas for prevention and resource allocation across regions and populations.

To address the challenges of fragmented data, inconsistent standards, and delayed feedback in the full-cycle competency development process at teaching hospitals, this paper proposes the LEADS data governance system for Precision Medical Education (LEADS-PME), drawing on the practical experience of building the integrated medical education management platform at Zhongshan Hospital, Fudan University. The LEADS-PME framework comprises five interconnected core components: Longitudinal foundation, Evidence-chain generation, Analytics and profiling, Decision-support and prediction, and Simulation and digital-twin governance. Currently, Zhongshan Hospital has established a full-cycle educational data infrastructure and achieved multi-system data integration and competency-based profiling and evaluation, while the prediction and simulation modules are still in the prototype exploration phase. A mixed-methods evaluation will be subsequently conducted from the perspectives of data quality, management effectiveness, and predictive intervention. As a locally adapted framework, LEADS-PME can transform operational data derived from clinical practice, teaching, assessment, and management processes into traceable, interpretable, and reusable evidence of competency development. It is expected to facilitate the transformation of medical education management from a outcome-oriented approach to process monitoring, evidence-driven decision-making, and precision governance, thereby providing both a theoretical framework and practical reference for precision medical education in Chinese teaching hospitals.

Objective To characterize the species composition and distribution patterns of ticks in 17 counties and cities of Yunnan Province, thereby furnishing fundamental data for the prediction, prevention, and control of local tick-borne diseases. Methods Tick specimens deposited in Yunnan Institute of Endemic Disease Control and Prevention (YIEDC) collected from 17 counties or cities during 1957-2024 were thoroughly trimmed and morphological identified based on diagnostic characters. Results A total of 2 923 tick specimens were taxonomically identified and classified into 18 species within 6 genera in the Ixodidae family. Specifically, the genus Haemaphysalis comprised 6 species with 154 specimens, the genus Rhipicephalus included 3 species with 2 444 specimens, the genus Ixodes consisted of 4 species with 236 specimens, the genus Amblyomma included 3 species with 49 specimens, the genus Dermacentor contained 1 species with 12 specimens, and the genus Hyalomma included 1 species with 28 specimens. A wide range of host animals were found, including livestock, wild avian species, wild mammalian species, reptiles (including pythons), and humans. Conclusions Ticks were found on a wide array of host animals within the 17 counties and cities of Yunnan Province, demonstrating high host species diversity. Our data suggest a need to strengthen the monitoring of tick-borne diseases and provide health education for the general population in Yunnan Province.

Pre-admission is a critical initiative to optimize medical service processes and alleviate the challenge of "difficult access to healthcare. "However, there is currently a lack of standardized protocols for pre-admission procedures. This study aims to systematically analyze key nodes and risk factors in pre-admission process design and propose optimization strategies, providing a foundation for policy formulation and hospital practices. By constructing a "forward-reverse" dual-process model of pre-admission and identifying risk points based on stakeholder theory (patients, hospitals, healthcare administration, and insurance), the study reveals that while pre-admission can reduce the average length of stay, improve bed turnover rates, and enhance patient satisfaction, it also presents risks such as cross-period financial settlement, challenges in insurance policy adaptability, demands for information system integration, and the need for defining medical safety boundaries. To optimize the pre-admission process and mitigate these risks, this study explores framework improvements in areas including eligibility criteria, mode selection, cost settlement, transition between pre-admission and inpatient status, and cancellation of pre-admission, offering practical guidance for public hospitals. The authors argue that pre-admission requires tripartite collaboration among hospitals, insurers, and healthcare administrations: hospitals should establish top-level design, continuously refine processes, and implement dynamic risk assessment mechanisms; insurance providers should support cross-period settlement policies; and healthcare administrations should issue guiding policies or standardized protocols. Through multi-department coordination and collaborative efforts, the optimization and innovation of pre-admission processes can be advanced, ultimately delivering more efficient and convenient healthcare experiences for patients.

Objective To investigate the levels of gross α and gross β activities in different water types within a 40-kilometer radius around the Zhangzhou Nuclear Power Plant prior to its operation. Methods In 2018, drinking water samples were collected from the area surrounding the nuclear power plant during both the wet and dry seasons, including source water, treated water, tap water, and well water. The gross α and gross β activity concentrations were measured using a low-background α/β counter, followed by statistical analysis. Results A total of 80 water samples from different sources around the Zhangzhou Nuclear Power Plant were collected. The average gross α and gross β activity concentrations during the wet season were (0.110 ± 0.036) Bq/L and (0.643 ± 0.028) Bq/L, respectively, while those during the dry season were (0.124 ± 0.032) Bq/L and (0.624 ± 0.026) Bq/L, respectively. There were no significant differences in the gross α and gross β activity concentrations between the wet and dry seasons for the overall sample set (P > 0.05). However, there were statistically significant differences in the gross α and gross β activity concentrations between the wet and dry seasons for source water and well water (Z_wet = −2.005, −2.123; Z_dry = −1.943, −3.090; P < 0.05). Conclusion The radioactivity levels in different water types within various ranges around the Zhangzhou Nuclear Power Plant before its operation were determined. The measured activity concentrations were at the same level as those from previous investigations in other regions of Fujian Province.