ObjectiveThe accuracy of Y-chromosome haplogroup assignment is crucial for tracing paternal lineage in male samples. With the advancement of high-throughput sequencing technologies, high-density Y-SNP genotyping from whole-genome or array-based data has become a standard method for determiningY-chromosome haplogroups. This study systematically evaluated the performance of 4 commonly used high-density SNP genotyping systems—namely, the Global Screening Array (GSA), Chinese Genotyping Array (CGA), Affymetrix array, and the 1240K capture panel—for haplogroup assignment. This work provides a reference for data comparison across different systems. MethodsWe extracted genotype data for the 4 Y-SNP panels from 30× whole-genome sequencing (WGS) data of 1 590 male samples from the 1000 Genomes Project. Additionally, GSA array genotype data from 384 relative pairs (spanning 1st- to 12th-degree relationships) from 109 Chinese Han families were collected. Haplogroup assignment was performed using Y-LineageTracker v1.3.0 software. We assessed the concordance and resolution of haplogroup assignments between the four Y-SNP panels and the WGS data. The consistency and resolution of haplogroup assignments were also evaluated for both the 1000 Genomes Project samples and the 109 family samples collected in this study. Furthermore, the impact of varying numbers of Y-SNPs on haplogroup assignment was examined. ResultsThe GSA and CGA panels demonstrated superior resolution and discrimination of haplogroup subclades compared with the other two panels. The haplogroup assignments from the GSA, CGA, and 1240K panels showed high concordance with WGS data, with consistency rates exceeding 88.70%, whereas the Affymetrix platform exhibited a significantly lower consistency rate of 61.89%. Specifically, the GSA and CGA panels consistently demonstrated superior performance compared with the other two panels in the assignment of haplogroups O-M175 and H-L901, achieving complete concordance (100%) for both haplogroups. In contrast, the Affymetrix panel erroneously assigned all individuals belonging to haplogroup O-M175 to haplogroup K2-M526. Furthermore, its accuracy for haplogroup H-L901 was exceedingly low, at merely 1.41%. This poor performance was characterized by the misassignment of 98.59% of H-L901 samples—specifically, 1.41% to J-M304 and a predominant 97.18% to F-M89. For haplogroup R-M207, all four panels exhibited uniformly high levels of consistency, with concordance values exceeding 94.00%. Notably, for haplogroup E-M96, the 1240K and Affymetrix panels outperformed the GSA and CGA panels in terms of concordance, representing the first instance in which these two panels surpassed the latter. Conversely, for haplogroups J-M304, Q-M242, and I-M170, all 4 panels showed relatively elevated misclassification rates, with the Affymetrix array demonstrating the poorest overall performance. None of the four panels showed any discordant haplogroup assignments among the familial relative pairs analyzed. A positive correlation was observed between the number of Y-SNPs (ranging from 1 000 to 10 000) and classification consistency; however, classification consistency plateaued when the number of Y-SNPs exceeded 10 000. Furthermore, a random sampling analysis conducted on the GSA and CGA panels demonstrated that the haplogroup misclassification rate exhibited negligible fluctuation across the Y-SNP range of 500 to 1 000. Conversely, a marked enhancement in classification consistency was observed as the number of markers increased from 1 000 to 5 000, ultimately reaching a plateau within the interval of 5 000 to 8 000 markers. ConclusionThese findings indicate that the GSA and CGA panels provide high resolution and concordance, delivering reliable Y-haplogroup assignment for forensic investigations.

ObjectiveThe accuracy of Y-chromosome haplogroup assignment is crucial for tracing paternal lineage in male samples. With the advancement of high-throughput sequencing technologies, high-density Y-SNP genotyping from whole-genome or array-based data has become a standard method for determiningY-chromosome haplogroups. This study systematically evaluated the performance of 4 commonly used high-density SNP genotyping systems—namely, the Global Screening Array (GSA), Chinese Genotyping Array (CGA), Affymetrix array, and the 1240K capture panel—for haplogroup assignment. This work provides a reference for data comparison across different systems. MethodsWe extracted genotype data for the 4 Y-SNP panels from 30× whole-genome sequencing (WGS) data of 1 590 male samples from the 1000 Genomes Project. Additionally, GSA array genotype data from 384 relative pairs (spanning 1st- to 12th-degree relationships) from 109 Chinese Han families were collected. Haplogroup assignment was performed using Y-LineageTracker v1.3.0 software. We assessed the concordance and resolution of haplogroup assignments between the four Y-SNP panels and the WGS data. The consistency and resolution of haplogroup assignments were also evaluated for both the 1000 Genomes Project samples and the 109 family samples collected in this study. Furthermore, the impact of varying numbers of Y-SNPs on haplogroup assignment was examined. ResultsThe GSA and CGA panels demonstrated superior resolution and discrimination of haplogroup subclades compared with the other two panels. The haplogroup assignments from the GSA, CGA, and 1240K panels showed high concordance with WGS data, with consistency rates exceeding 88.70%, whereas the Affymetrix platform exhibited a significantly lower consistency rate of 61.89%. Specifically, the GSA and CGA panels consistently demonstrated superior performance compared with the other two panels in the assignment of haplogroups O-M175 and H-L901, achieving complete concordance (100%) for both haplogroups. In contrast, the Affymetrix panel erroneously assigned all individuals belonging to haplogroup O-M175 to haplogroup K2-M526. Furthermore, its accuracy for haplogroup H-L901 was exceedingly low, at merely 1.41%. This poor performance was characterized by the misassignment of 98.59% of H-L901 samples—specifically, 1.41% to J-M304 and a predominant 97.18% to F-M89. For haplogroup R-M207, all four panels exhibited uniformly high levels of consistency, with concordance values exceeding 94.00%. Notably, for haplogroup E-M96, the 1240K and Affymetrix panels outperformed the GSA and CGA panels in terms of concordance, representing the first instance in which these two panels surpassed the latter. Conversely, for haplogroups J-M304, Q-M242, and I-M170, all 4 panels showed relatively elevated misclassification rates, with the Affymetrix array demonstrating the poorest overall performance. None of the four panels showed any discordant haplogroup assignments among the familial relative pairs analyzed. A positive correlation was observed between the number of Y-SNPs (ranging from 1 000 to 10 000) and classification consistency; however, classification consistency plateaued when the number of Y-SNPs exceeded 10 000. Furthermore, a random sampling analysis conducted on the GSA and CGA panels demonstrated that the haplogroup misclassification rate exhibited negligible fluctuation across the Y-SNP range of 500 to 1 000. Conversely, a marked enhancement in classification consistency was observed as the number of markers increased from 1 000 to 5 000, ultimately reaching a plateau within the interval of 5 000 to 8 000 markers. ConclusionThese findings indicate that the GSA and CGA panels provide high resolution and concordance, delivering reliable Y-haplogroup assignment for forensic investigations.

Objective: To understand the mosquito infestation status in schools in Jing an District of Shanghai from 2019 to 2025, so as to provide a basis for mosquito control work in schools. Methods: Four schools of each school type (colleges and secondary specialized schools, primary and secondary schools, nurseries and kindergartens) were respectively selected from Jing an District as the survey sites by combination of stratified sampling and convenience sampling. Mosquito breeding sites surveys (including small stagnant water and medium and large static water) and adult mosquito monitoring were carried out in schools every August, from 2019 to 2025. The breeding sites surveys were investigated by visual inspection and spoon trapping methods, and the adult mosquito monitoring was investigated by the human baited trapping. Chi square test was used for inter group comparison. Results: A total of 970 small stagnant water were surveyed from 2019 to 2025, with the positive rate of 17.01% for mosquito breeding. The highest positive rate was in colleges and secondary specialized schools (25.07%). The top three positive breeding sites for mosquito were unused containers(27.46%), waste tires (16.67%), and bonsai and aquatic plants (16.52%). There were statistically significant differences in the positive rates for mosquito breeding among different years, school types and waterlogging types ( χ 2=122.70, 28.48 , 24.80, all P <0.01). A total of 640 medium and large static water were surveyed, and the positive rate for mosquito breeding was 7.34%. There was a statistically significant difference for the positive rate among different years ( χ 2= 50.23 , P <0.01). The highest positive rate for mosquito breeding was in colleges and secondary specialized schools (9.63%), and there was no statistically significant difference for the positive rate among different school types ( χ 2=4.41, P =0.11). From 2019 to 2025, a total of 390 mosquitoes were captured in the time period from 16:30 to 17:00, all of which were Aedes albopictus; the adult mosquito density in colleges and secondary specialized schools was the highest, being 2.38 mosquitoes/(0.5 h ·person). A total of 210 mosquitoes were captured in the time period from 19:00 to 19:30 during 2019-2025, among which Aedes albopictus accounted for 74.76% and Culex pipiens pallens accounted for 25.24%. The adult mosquito density in colleges and secondary specialized schools was the highest, being 1.15 mosquitoes/(0.5 h ·person). In colleges and secondary specialized schools, the area with the largest number of captured mosquitoes was around the teaching buildings and libraries(44.78%). In primary and secondary schools, as well as nurseries and kindergartens, the area with the largest number of captured mosquitoes was around the school gates and playgrounds( 49.44% , 53.60%), the difference in mosquito distribution in different regions among different types of schools was statistically significant ( χ 2=111.39, P <0.01). Conclusions The mosquito density in Jing an District schools is generally higher during summer. It is recommended that the school strengthen the management of mosquito breeding sites and the control of adult mosquitoes before the start of autumn semester, so as to prevent insect infestation of mosquitoes.

The development of traditional Chinese medicine (TCM) diagnosis and treatment has undergone multiple paradigms, evolving from sporadic experiential practices to systematic approaches in syndrome differentiation and treatment and further integration of disease and syndrome frameworks. TCM is a vital component of the medical system, valued alongside Western medicine. Treatment based on syndrome differentiation embodies both personalized treatment and holistic approaches; however, the inconsistency and lack of stability in syndrome differentiation limit clinical efficacy. The existing integration of diseases and syndromes primarily relies on patchwork and embedded systems, where the full advantages of synergy between Chinese and Western medicine are not fully realized. Recently, driven by the development of diagnosis and treatment concepts and advances in analytical technology, Western medicine has been rapidly transforming from a traditional biological model to a precision medicine model. TCM faces a similar need to progress beyond traditional syndrome differentiation and disease-syndrome integration toward a more precise diagnosis and treatment paradigm. Unlike the micro-level precision trend of Western medicine, precision diagnosis and treatment in TCM is primarily reflected in data-driven applications that incorporate information at various levels, including precise syndrome differentiation, medication, disease management, and efficacy evaluation. The current priority is to accelerate the development of TCM precision diagnosis and treatment technology platforms and advance discipline construction in this area.

Lung function serves as a clinical indicator reflecting respiratory system function,ai-ding in the diagnosis and monitoring of pulmonary diseases.Both genetic and environmental factors ex-ert significant influences on lung function.A comprehensive understanding of the role of genetic factors in lung function is crucial for gaining deeper insights into the regulatory mechanisms of lung function.In recent years,with the application of advanced technologies such as genome-wide association stud-ies,whole-exome sequencing,whole-genome sequencing,and epigenome-wide association studies,numerous genetic loci related to lung function have been identified.This review aimed to summarize the current research progress in genetics related to lung function,providing a reference for subsequent in-depth exploration of the pathological and physiological mechanisms affecting lung function.

Objective: To explore the relationship between beverage dependence and sleep quality among college students, providing empirical evidence for improving their sleep quality. Methods: From December 2024 to January 2025, a convenience sampling method was used to conduct a questionnaire survey among 3 974 college students from four universities in Anhui Province. The Beverage Addiction Scale for College Students (BASCS) was used to assess beverage dependence, and the Self rating Scale of Sleep(SRSS) was used to evaluate sleep quality. A multivariate Logistic regression model was employed to analyze the relationship between beverage dependence and sleep quality, and a restricted cubic spline model was used to examine the dose response relationship between the two. Results: The positive rate of beverage dependence symptoms among college students was 7.6%, with positive rates of 9.6%, 13.8%, and 7.4% for the withdrawal symptoms, health effects, and dependence symptoms dimensions, respectively. The detection rate of sleep disorders was 23.6%. Multivariate Logistic regression analysis showed that after adjusting for covariates such as grade, gender, and body mass index, compared with the no beverage dependence group, students with positive beverage dependence symptoms had a higher risk of sleep disorders( OR =3.71, 95% CI =2.87-4.80, P <0.01). The OR (95% CI ) for sleep disorders among students with positive symptoms in the withdrawal symptoms, health effects, and dependence symptoms dimensions were 2.80(2.22-3.53), 2.38(1.95-2.91), and 2.45(1.89-3.18)(all P <0.01). Further analysis using a restricted cubic spline model revealed that the overall beverage dependence score and its three dimensional scores were approximately linearly related to the risk of sleep disorders among college students (all nonlinear P >0.05). Conclusions Beverage dependence is associated with sleep quality among college students. Schools should take multiple approaches, such as health education on beverage awareness, to improve students sleep quality.

Objective To study the plasma metabolomics of mice poisoned by different dosage of the combination of diazepam and ethanol,and to reveal the toxicological mechanisms of combined poisoning of diazepam and ethanol.Methods Female Kunming mice were randomly divided into blank group,single and combined poisoning group(n=6),Based on the LD50 of diazepam co-administered with graded ethanol doses,mice in the single-drug and combined groups received oral gavage at 1/2,1,and 2 × LD50.Retro-orbital blood samples(～500 μL)were collected within 24 hours post-administration and analyzed by UPLC-QE-MS technology.Principal component analysis and orthogonal partial least squares discriminant analysis were used to identify differential metabolites and associated metabolic pathways.Results A total of 387 differential metabolites were identified in the combined poisoning group of diazepam and ethanol implicating the key pathways including tryptophan metabolism,phenylalanine metabolism,arginine and proline metabolism,Glycerophospholipid metabolism,phenylalanine,tyrosine and tryptophan biosynthesis.Conclusion Combined diazepam and ethanol poisoning exerts significant systemic effects by disrupting neurotransmitters conduction,exacerbating oxidative stress response and dysregulating energy metabolism.

Objective:To summarize and analyze the clinical characteristics of systemic lupus erythematosus (SLE) combined with ischaemic stroke and the factors associated with poor prognosis.Methods:A total of 50 patients with SLE combined with ischaemic stroke in the First Affiliated Hospital of Xi′an Jiaotong University from January 2014 to June 2024 were included in the study, the clinical data of the patients were retrospectively collected and summarized, the Shapiro-Wilk test was used to assess the normality of data, and the factors related to poor prognosis were analyzed by logistic regression analyses.Results:Fifty patients with SLE combined with ischaemic stroke had a mean age of (47.1±15.5)years, 80.0%(40/50) were female, the duration of SLE was (5.6±6.3)years, the mean SLEDAI-2K score was (14.3±4.1), the rate of anticardiolipin antibody positivity was 30.0%(15/50), and the rate of β 2-glycoprotein Ⅰ antibody positivity was 28.0%(14/50). The most common clinical manifestations of stroke were impaired limb movement (34.0%) (17/50), cerebral infarction mainly in the cerebral hemisphere (82.0%)(41/50), combined with cerebral haemorrhage in 6.0%(3/50), cerebral leukoencephalopathy in 26.0%(13/50), and cerebral atrophy in 24.0%(12/50). In terms of treatment, the most used immunosuppressant was cyclophosphamide (34.0%, 17/50), 64.0%(32/50) of patients received aspirin, 32.0%(16/50) received clopidogrel and 14.0%(7/50) received anticoagulation. Four deaths and 12 cases of severe disability were found in 50 patients at follow-up, and SLEDAI-2000 scores were positively correlated with the above poor prognosis using univariate [ OR(95% CI)=1.407(1.123,1.764), P=0.003] and multivariate [ OR(95% CI)=1.388(1.097, 1.756), P=0.006] regression analyses. Conclusion:Patients with SLE combined with ischaemic stroke had high disease activity in SLE, and SLEDAI-2000 scores were positively associated with poor prognosis of death and severe disability.