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.

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.

Objective:To explore the potential prognostic value of the HAMP(hepcidin)gene in gastric adenocarci-noma and its correlation with immune infiltration in gastric cancer.Methods:This study systematically analyzed the ex-pression characteristics of the HAMP gene using bioinformatics approaches based on mRNA data from 448 gastric ad-enocarcinoma tissues and non-tumor tissues in the TCGA database.Firstly,the cBioPortal platform was employed to analyze the genetic variation features of the HAMP gene,and the LinkedOmics database was used to evaluate the corre-lation between its methylation status and expression levels.Kaplan-Meier survival analysis with log-rank test was per-formed to assess the relationship between HAMP expression levels and patient prognosis.Furthermore,by integrating TIMER2.0 and TISIDB databases,we systematically evaluated the correlation between HAMP expression and immune-related genes as well as immune cell infiltration.Gene Set Enrichment Analysis(GSEA)was conducted to investigate HAMP-associated signaling pathway characteristics.Finally,STRING and Gepia databases were utilized to construct a protein-protein interaction network of HAMP and identify core interacting genes,comprehensively evaluating the role of HAMP in immune infiltration in gastric adenocarcinoma.Results:The expression level of HAMP was significantly higher in gastric adenocarcinoma tissues compared to normal tissues(P<0.01),and its elevated expression was strongly associ-ated with poor patient prognosis,manifested by significantly shorter overall survival(OS),progression-free survival(PFS),and post-progression survival(PPS)(all P<0.05).Genomic analysis revealed that HAMP mutations in gastric cancer were predominantly amplification-type,and its methylation level showed a positive correlation with mRNA expression(r=0.14,P<0.001).Immunological analysis demonstrated that high HAMP expression was significantly correlated with multiple key immune checkpoint molecules(PD-1:rho=0.274;PD-L1:rho=0.211;CTLA-4:rho=0.199,all P<0.001)and immune cell infiltration(dendritic cells:r=0.548;macrophages:r=0.414;neutrophils:r=0.374,all P<0.001).Pathway enrichment analy-sis indicated that the high HAMP expression group was significantly enriched in immune-related pathways including anti-gen presentation and NK cell-mediated cytotoxicity.Furthermore,protein-protein interaction network analysis identified core interacting genes such as TREM2 and TYROBP,suggesting that HAMP may participate in tumor immune regulation through specific molecular networks.Conclusion:HAMP is highly expressed in gastric cancer,and its high expression significantly reduces the survival time of gastric adenocarcinoma patients,demonstrating prognostic value.HAMP ex-pression is positively correlated with most immune-related genes in STAD and significantly associated with the abun-dance of multiple immune cell infiltration levels,serving as an independent prognostic factor related to immune infiltration.

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 explore the application of machine learning (ML) models based on radiomics and dosiomics to the assessment of hematologic toxicity (HT) in patients with locally advanced cervical cancer, and to preliminarily explore the comprehensive application of multi-omics features.Methods:A retrospective study was conducted on the clinical data, planning computed tomography (CT) images, and dose files of 205 patients with locally advanced cervical cancer who received concurrent chemoradiotherapy at the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, from January 2022 to June 2023. Patients were categorized according to the severity of HT. Radiomics and dosiomics features were extracted from the same regions of interest (ROIs), followed by feature selection utilizing a random forest algorithm. Then, radiomics, dosiomics, and hybrid models were established based on extreme gradient boosting (XGBoost). The classification performance of these models was assessed by calculating their sensitivity, specificity, and area under the receiver operating characteristic curve (AUC).Results:The radiomics model yielded sensitivity, specificity, and AUC of 0.42, 0.86, and 0.78, respectively. The dosiomics model exhibited sensitivity, specificity, and AUC of 0.50, 0.90, and 0.74, respectively. In contrast, the hybrid model achieved sensitivity, specificity, and AUC of 0.50, 0.83, and 0.83, respectively. These findings suggest that the hybrid model possessed an enhanced classification capability compared to the individual radiomics and dosiomics models.Conclusions:It is feasible to use ML models based on radiomics and dosiomics to conduct the classification and prediction of HT in patients with locally advanced cervical cancer treated with concurrent chemoradiotherapy. Furthermore, integrating both radiomics features and dosiomics features can improve the classification performance of relevant prediction models, thus holding application potentials to optimize treatment strategies for patients with locally advanced cervical cancer.

Objective To investigate the relationship between cognitive function and sleep quality in patients with Alzheimer's disease(AD).Methods A case-control trial was conducted on 151 patients admitted to our department from May 2024 to December 2024.The patients with mild-to-moderate AD were assigned into the AD group(59 cases),and the cognitively normal patients in-to the control group(92 cases).All patients received neuropsychological assessment and sleep quality evaluation,including mini-mental state examination(MMSE),Montreal cognitive assess-ment(MoCA)and Pittsburgh sleep quality index(PSQI).The general clinical data and sleep qual-ity were compared between the two groups.Spearman correlation analysis was applied to analyze the relationship between cognitive function and sleep quality in the AD patients.Results The education level,MMSE score,MoCA score,instant story recall(ISR)score,delayed story recall(DSR)score,clock dawning test(CDT)score and Boston naming test score were significantly lower,while the activity of daily living(ADL)score was obviously higher in the AD group than the cognitively normal group(P＜0.05,P＜0.01).The AD patients had notably higher total score of PSQI and scores of sleep efficiency,nocturnal sleep disturbance and daytime dysfunction than the cognitively normal patients(P＜0.05,P＜0.01).In the AD patients,the total sleep time was positively correlated with the DSR score and the CDT score(r=0.300,P=0.021;r=0.308,P=0.018);hypnotic medication was negatively correlated with MMSE score,ISR score,and DSR score,and positively with ADL score(r=-0.320,P=0.013;r=-0.400,P=0.002;r=-0.331,P=0.010;r=0.355,P=0.006).Multiple linear regression analysis showed that benzodiazepines use and education level were independent influencing factors for cognitive function in the AD patients(P＜0.05,P＜0.01).Conclusion In AD patients,sleep quality is closely associated with cognitive function,as manifested by decreased sleep quality,reduced sleep efficiency,and worsened nocturnal sleep disturbances and daytime dysfunction.Administration of benzodiazepines may exacerbate cognitive impairment in AD patients.So,it is recommended that AD patients should be cautious about taking such drugs.

Objective To investigate the associations of immune cells,CD8+and CD4+T cells,and high-sensitivity C-reactive protein(hs-CRP)with cognitive function,and to explore the relation-ships among immunity,chronic inflammation,and Alzheimer's disease-related cognitive impair-ment.Methods A cross-sectional study was conducted on 101 patients with primary complaints of memory decline who visited the Alzheimer's Disease Clinic of Dongzhimen Hospital from June to December 2024.Mini-Mental State Examination(MMSE)and Delayed Story Recall Task(DSR)were performed to assess their cognitive function,and according to the results,they were divided into observation group(cognitively impaired,60 cases)and control group(cognitively normal,41 cases).Peripheral blood levels of CD8+T cells,CD4+T cells,and hs-CRP were compared between the two groups.Results The observation group exhibited significantly lower total scores and scores of different dimensions of MMSE and DSR scores,but notably higher activities of daily liv-ing scores than the control group(P＜0.05,P＜0.01).Serum hs-CRP level was obviously elevated in the observation group than the control group(P＜0.05).Binary logistic regression analysis revealed that CD8+T cells(OR=0.998,95％CI:0.996-1.000,P=0.038)and body mass index(OR=0.843,95％CI:0.719-0.990,P=0.037)were protective factors,while hs-CRP(OR=2.004,95％CI:1.215-3.306,P=0.006)was an independent risk factor for cognitive impairment.Spearman's rank correlation analysis showed a significant positive correlation between hs-CRP and CD4+T cells(P=0.011),but no significant association with CD8+T cells(P＞0.05).Conclusion Chronic inflammation and immune dysregulation synergistically contribute to cogni-tive decline.Hs-CRP may serve as a potential screening biomarker for cognitive impairment in pri-mary care settings.

Objective To determine the effects of Bushen Huoxue Formula(BHF),a clinically vali-dated traditional Chinese herbal compound,on myelin integrity and cognitive function in mice with chronic cerebral hypoperfusion(CCH).Methods A total of 30 SPF male C57BL/6J mice were randomly divided into sham operation group(n=8)and model group(n=22).Bilateral com-mon carotid artery stenosis was inflicted to establish a mouse model of CCH,while the mice in the sham operation group only received separation of bilateral vagus nerves.In the model group,6 mice died in 2 d after surgery,the left 16 mice were then randomly divided into a model group and a treatment group,with 8 animals in each group.In 2 weeks after surgery,BHF(0.2 ml/d)or pure water was administered via gavage for 60 d to the corresponding groups.Cognitive function was assessed using the Morris water maze(MWM)test.White matter lesions were evaluated by diffu-sion tensor imaging-fractional anisotropy(DTI-FA).Demyelination in the corpus callosum was visualized using Luxol fast blue(LFB)staining,while neuronal damage in the hippocampal CA1 region was analyzed with Nissl staining.Results Compared to the sham group,the model group exhibited significantly prolonged swimming distance and escape latency on day 5 and reduced platform crossings on day 6 in Morris water maze test,decreased DTI-FA value,lower absorbance value of myelin in LFB staining,and fewer Nissl-stained neurons in the hippocampal region(P＜0.05,P＜0.01).In contrast,the treatment group showed significantly shorter swimming distance[188.14(105.19,342.00)cm vs 280.22(168.47,501.37)cm,P＜0.05]and escape latency[10.22(5.77,19.47)s vs 19.39(13.57,31.09)s,P＜0.01]on day 5,increased platform crossings on day 6[3.00(2.00,4.00)times vs 2.00(1.00,3.00)times,P＜0.05],elevated DTI-FA value(0.340±0.014 vs 0.313±0.012,P＜0.01),enhanced absorbance value of myelin[0.353(0.328,0.364)vs 0.305(0.290,0.350),P＜0.05],and greater neuronal counts(9.94±2.22 cells vs 7.11±2.02 cells,P＜0.01)when compared to the model group.Conclusion BHF can alleviate CCH-induced cogni-tive deficits in mice by promoting repair of white matter microstructure and rescue of neuronal loss.

Objective:To explore the effectiveness of digital health management in the management of community patients with essential hypertension comorbid with somatization symptom disorder.Methods:This was an intervention-controlled study. Patients with essential hypertension comorbid with somatization symptom disorder who visited the outpatient clinic of Jiangwan Town Community Health Service Center in Hongkou District, Shanghai from January to December 2022 were enrolled. Based on the time of initial diagnosis, patients were divided into a digital health management group (initial diagnosis from January to June 2022) and a control group (initial diagnosis from July to December 2022). Baseline clinical data were collected. The control group received conventional interventions, while the digital health management group utilized the Health Cloud APP 5.3.11 platform for online digital health management without altering the original medication regimen. The intervention lasted for 24 weeks. Before and after the intervention, the Somatization Symptom Scale (SSS), 9-item Patient Health Questionnaire (PHQ-9), and 7-item Generalized Anxiety Disorder Scale (GAD-7) were used to assess somatization symptoms, depression, and anxiety, respectively. The reduction rate in SSS scores was calculated, and blood pressure and heart rate were measured. The evaluation criteria for somatization symptom intervention effectiveness were as follows: at the endpoint of the intervention, SSS ≤29 or a reduction rate of SSS ≥ 75% was considered "cured"; a reduction rate of 50% to <75% was considered "markedly effective"; a reduction rate of 25% to <50% was considered "effective"; and a reduction rate of <25% was considered "ineffective".The overall effectiveness rate=(number of cured patients + number of markedly effective patients + number of effective patients)/total number of patients × 100%.Results:A total of 62 patients in the digital health management group and 65 patients in the control group were included in the final analysis. The mean age of the digital health management group was (50.5±3.5) years, with 30 males (48.4%), while the mean age of the control group was (50.2±3.2) years, with 31 males (47.7%). There were no statistically significant differences in the age or gender distribution between the two groups (both P>0.05). Before the intervention, there were no significant differences between the two groups in SSS sub-item scores, total SSS scores, PHQ-9 scores, GAD-7 scores, blood pressure, or heart rate (all P>0.05). After 24 weeks of intervention, all scores decreased in both groups, and did blood pressure and heart rate (all P<0.05). The differences in SSS sub-item scores, total SSS scores, PHQ-9 scores, GAD-7 scores, blood pressure, and heart rate before and after the intervention were greater in the digital health management group than in the control group (all P<0.05). The proportion of patients with effective intervention for somatization symptom was higher in the digital health management group than in the control group (57 cases (91.9%) vs. 38 cases (58.5%), P<0.001). Conclusion:Digital health management can improve somatization symptom disorder, blood pressure, and heart rate in patients with hypertension.