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.

Childhood simple obesity has become a significant public health issue in China. Modern medicine primarily relies on lifestyle interventions and often suffers from poor long-term compliance， while pharmacological options are limited and associated with potential adverse effects. Traditional Chinese Medicine （TCM） has a long history in the prevention and management of this condition， demonstrating eight distinct advantages， including systematic theoretical foundation， diversified therapeutic approaches， definite therapeutic efficacy， high safety profile， good patient compliance， comprehensive intervention strategies， emphasis on prevention， and stepwise treatment protocols. Additionally， TCM is characterized by six distinctive features： the use of natural medicinal substances， non-invasive external therapies， integration of medicinal dietetics， simple exercise regimens， precise syndrome differentiation， and diverse dosage forms. By combining internal and external treatments， TCM facilitates individualized regimen adjustment and holistic regulation， demonstrating remarkable effects in improving obesity-related metabolic indicators， regulating constitutional imbalance， and promoting healthy behaviors. However， challenges remain， such as inconsistent operational standards， insufficient high-quality clinical evidence， and a gap between basic research and clinical application. Future efforts should focus on accelerating the standardization of TCM diagnosis and treatment， conducting multicenter randomized controlled trials， and fostering interdisciplinary integration， so as to enhance the scientific validity and international recognition of TCM in the prevention and treatment of childhood obesity.

Toxoplasmosis, a zoonotic disease caused by the obligate intracellular parasite Toxoplasma gondii, is widely prevalent across the world. The life cycle of T. gondii involves definitive hosts (cats and felines), intermediate hosts (humans, livestock, and wild animals), and the environment (such as soil and water). The One Health concept brings together the health of humans, animals, and the environment, with aims to pursue the optimal health outcomes through coordinated management. Management of toxoplasmosis from a One Health perspective may provide key insights into formulation of interventions for toxoplasmosis control. This article reviews the complex biological characteristics and life cycle of T. gondii, as well as the importance of felines as definitive hosts in the transmission of toxoplasmosis, analyzes the epidemiology, ecological impact and economic burden of toxoplasmosis, and discusses the bottlenecks in diagnostic and monitoring systems, environmental management technologies, and One Health interdisciplinary collaboration. In addition, toxoplasmosis control strategies are proposed based on the One Health concept, covering public health interventions, management of animal sources, multi-sector collaboration, and development of novel vaccines. These strategies provide insights into interruption of toxoplasmosis transmission and maintenance of the global public health security.

Objective This study aims to explore the application value of spectral CT and perfusion CT parameters in the pathological classification and prognostic assessment of lung cancer.Methods A total of 94 lung cancer patients confirmed by pathology at Shanghai Chest Hospital from January 2023 to November 2024 were included in the study,including 49 cases of lung adenocarcinoma(LUAD),30 cases of lung squamous cell carci-noma(LUSC),and 15 cases of small cell lung cancer(SCLC).All patients underwent spectral CT combined with perfusion scanning using a 256-slice Revolution Apex from GE.Two radiologists independently measured the spectral and perfusion parameters of the three groups of images,including spectral curve slope(K),iodine concentration in the lesion area(ICL),effective atomic number(Zeff),surface permeability(PS),and perfusion index(PI),and established a lung cancer pathological subtype discrimination prediction model based on spectral CT radiomics features.All subjects were randomly divided into a training group and a validation group at a ratio of 3∶1.The discrimination efficacy of the spectral discrimination model between different pathological subtypes and the discrimination efficacy of arterial and venous phase images were compared in multiple dimensions.The performance of the model was evaluated using the receiver operating characteristic(ROC)curve.Results Statistical analysis showed that the spectral curve slope,ICL,NIC,and Zeff of LUAD patients were significantly higher than those of LUSC and SCLC patients(P<0.05),while there were no significant differences in these parameters between LUSC and SCLC patients(P>0.05).Among the perfusion CT parameters,surface permeability(PS)showed significant differences among the three groups(P<0.05),while blood volume(BV),blood flow(BF),perfusion index(PI),time to peak(TTP),and mean transit time(MTT)did not show statistical differences.The multi-factor logistic regression model based on spectral parameters showed strong discriminatory performance:the area under the curve(AUC)of the LUAD and LUSC discrimination model was 0.806/0.77(training group/test group)in the arterial phase and 0.867/0.9(training group/test group)in the venous phase;the AUC of the LUAD and SCLC discrimination model was 0.885/0.883(training group/test group)in the arterial phase and 0.851/0.776(training group/test group)in the venous phase.Conclusion This study indicates that the multi-dimensional functional metabolic analysis indicators of spectral and perfusion CT imaging have significant value in the differential diagnosis of lung cancer pathological subtypes.The diagnostic model constructed by combining multiple spectral parameters can significantly improve the discrimination efficacy of lung adenocarcinoma,squamous cell carcinoma,and small cell lung cancer,providing precise imaging evidence for the formulation of individualized treatment plans.

Objective·To monitor postoperative blood glucose(BG)and blood lipids(BL)at multiple time points in pediatric patients undergoing liver transplantation(LT)and to analyze the influencing factors.Methods·An observational study was conducted,including pediatric LT patients from the Hepatic Surgery Department of Renji Hospital,Shanghai Jiao Tong University School of Medicine.Blood samples were collected one day before surgery and on days 1,7,and 14 after surgery.Basic patient information and laboratory indicators were recorded,including complete blood count(CBC),cytochrome P450(CYP)genotyping,tacrolimus dosage(TD),tacrolimus serum drug level(TSDL),fasting blood glucose(FBG),2-hour postprandial blood glucose(PBG),and biochemical testing for liver transplantation(BTLT).BTLT included the following indicators:total protein(TP),albumin(ALB),alanine aminotransferase(ALT),aspartate aminotransferase(AST),alkaline phosphatase(AKP),transglutaminase(GGT),direct bilirubin(DBil),total bilirubin(TBil),creatinine(Cr),triglyceride(TAG),total cholesterol(TC),prothrombin time(PT),and international normalized ratio(INR).The t-test or Mann-Whitney U test was used to analyze factors influencing PBG,Cox regression analysis was used to analyze factors influencing FBG,and logistic regression analysis was used to analyze factors influencing TC.Results·A total of 82 pediatric LT patients were included,with 45 males(54.9%)and 37 females(45.1%).The average age was 7 months,average height was 65 cm,and average body weight was 7.15 kg.FBG[(6.54±1.71)mmol/L]and PBG[(7.42±2.19)mmol/L]reached their highest values on the first postoperative day and gradually decreased to normal levels.There were 59 patients in the normal FBG and PBG groups and 23 in the abnormal groups.TAG[(0.93±0.63)mmol/L]and TC[(1.91±1.08)mmol/L]reached their lowest values on the first postoperative day and then slowly increased.The t-test indicated that TP(P=0.050),AKP(P=0.020),GGT(P=0.002),TC(P=0.017),and TD(P=0.028)showed statistically significant differences between the normal and abnormal PBG groups.Cox regression analysis showed that gender(HR=0.501,95%CI 0.184?1.361),age(HR=0.972,95%CI 0.876?1.079),height(HR=1.012,95%CI 0.903?1.135),body weight(HR=1.067,95%CI 0.720?1.579),and blood type(A type HR=1.294,95%CI 0.464?3.612;B type HR=1.303,95%CI 0.456?3.723;AB type HR=1.520,95%CI 0.310?7.441)did not significantly affect the BG's time change process.Logistic regression analysis showed that the patient's CYP(1×3 OR=9.332,95%CI 0.960?90.719;3×3 OR=18.083,95%CI 1.414?231.219)was a factor influencing TC.Conclusion·TD is a factor influencing PBG on the first postoperative day,and the patient's CYP is a factor influencing TC on the same day.

Aim To investigate the antidepressant mechanism of hyperforin via the utilization of single-cell sequencing technology.Methods C57BL/6 mice were randomly divided into the control group,depres-sion model group,and hyperforin intervention group.The chronic unpredictable mild stress(CUMS)model was induced and drug interventions were administered for 28 d.Behavioral experiments were conducted to as-sess depressive symptoms,and hippocampal tissue was collected for single-cell RNA sequencing.Key cell populations and differentially expressed genes across groups were identified,followed by PPI network,GO,and KEGG enrichment analysis.Results Behavioral experiments indicated that CUMS successfully induced depressive symptoms in mice,while hyperforin im-proved depressive behavior.In the depression model group,the proportion of brain perivascular macrophages(PVM)increased,and this proportion decreased after hyperforin intervention,approaching the level seen in the control group.The top 20 common differentially ex-pressed genes in the PVM subpopulation were Saa3,Hbb-bs and Ccl24.PPI network analysis identified core targets,including Ccl2,Dhx9,C3,Msr1,Cxcl2 and Cx3cr1.KEGG enrichment analysis revealed pathways related to chemokines,phagosome formation,and inosi-tol phosphate metabolism.Conclusion The antide-pressant mechanism of hyperforin may be related to the regulation of Ccl24 and its related chemokine signaling pathway by PVM.

OBJECTIVE: To identify prognostic genes associated with lysosome-dependent cell death (LDCD) in patients with gastric cancer (GC). METHODS: Differentially expressed genes (DEGs) were identified using The Cancer Genome Atlas - Stomach Adenocarcinoma. Weighted gene co-expression network analysis was performed to identify the key module genes associated with LDCD score. Candidate genes were identified by DEGs and key module genes. Univariate Cox regression analysis, and least absolute shrinkage and selection operator regression and multivariate Cox regression analyses were performed for the selection of prognostic genes, and risk module was established. Subsequently, key cells were identified in the single-cell dataset (GSE183904), and prognostic gene expression was analyzed. Cell proliferation and migration were assessed using the Cell Counting Kit-8 assay and the wound healing assay. RESULTS: A total of 4,465 DEGs, 95 candidate genes, and 4 prognostic genes, including C19orf59, BATF2, TNFAIP2, and TNFSF18, were identified in the analysis. Receiver operating characteristic curves indicated the excellent predictive power of the risk model. Three key cell types (B cells, chief cells, and endothelial/pericyte cells) were identified in the GSE183904 dataset. C19orf59 and TNFAIP2 exhibited predominant expression in macrophage species, whereas TNFAIP2 evolved over time in endothelial/pericyte cells and chief cells. Functional experiments confirmed that interfering with C19orf59 inhibited proliferation and migration in GC cells. CONCLUSION C19orf59, BATF2, TNFAIP2, and TNFSF18 are prognostic genes associated with LDCD in GC. Furthermore, the risk model established in this study showed robust predictive power.
Stomach Neoplasms/pathology* ; Humans ; Prognosis ; Lysosomes/physiology* ; RNA-Seq ; Cell Death ; Single-Cell Analysis ; Gene Expression Regulation, Neoplastic ; Cell Proliferation ; Single-Cell Gene Expression Analysis

Objective·To monitor postoperative blood glucose(BG)and blood lipids(BL)at multiple time points in pediatric patients undergoing liver transplantation(LT)and to analyze the influencing factors.Methods·An observational study was conducted,including pediatric LT patients from the Hepatic Surgery Department of Renji Hospital,Shanghai Jiao Tong University School of Medicine.Blood samples were collected one day before surgery and on days 1,7,and 14 after surgery.Basic patient information and laboratory indicators were recorded,including complete blood count(CBC),cytochrome P450(CYP)genotyping,tacrolimus dosage(TD),tacrolimus serum drug level(TSDL),fasting blood glucose(FBG),2-hour postprandial blood glucose(PBG),and biochemical testing for liver transplantation(BTLT).BTLT included the following indicators:total protein(TP),albumin(ALB),alanine aminotransferase(ALT),aspartate aminotransferase(AST),alkaline phosphatase(AKP),transglutaminase(GGT),direct bilirubin(DBil),total bilirubin(TBil),creatinine(Cr),triglyceride(TAG),total cholesterol(TC),prothrombin time(PT),and international normalized ratio(INR).The t-test or Mann-Whitney U test was used to analyze factors influencing PBG,Cox regression analysis was used to analyze factors influencing FBG,and logistic regression analysis was used to analyze factors influencing TC.Results·A total of 82 pediatric LT patients were included,with 45 males(54.9%)and 37 females(45.1%).The average age was 7 months,average height was 65 cm,and average body weight was 7.15 kg.FBG[(6.54±1.71)mmol/L]and PBG[(7.42±2.19)mmol/L]reached their highest values on the first postoperative day and gradually decreased to normal levels.There were 59 patients in the normal FBG and PBG groups and 23 in the abnormal groups.TAG[(0.93±0.63)mmol/L]and TC[(1.91±1.08)mmol/L]reached their lowest values on the first postoperative day and then slowly increased.The t-test indicated that TP(P=0.050),AKP(P=0.020),GGT(P=0.002),TC(P=0.017),and TD(P=0.028)showed statistically significant differences between the normal and abnormal PBG groups.Cox regression analysis showed that gender(HR=0.501,95%CI 0.184?1.361),age(HR=0.972,95%CI 0.876?1.079),height(HR=1.012,95%CI 0.903?1.135),body weight(HR=1.067,95%CI 0.720?1.579),and blood type(A type HR=1.294,95%CI 0.464?3.612;B type HR=1.303,95%CI 0.456?3.723;AB type HR=1.520,95%CI 0.310?7.441)did not significantly affect the BG's time change process.Logistic regression analysis showed that the patient's CYP(1×3 OR=9.332,95%CI 0.960?90.719;3×3 OR=18.083,95%CI 1.414?231.219)was a factor influencing TC.Conclusion·TD is a factor influencing PBG on the first postoperative day,and the patient's CYP is a factor influencing TC on the same day.

Aim To investigate the antidepressant mechanism of hyperforin via the utilization of single-cell sequencing technology.Methods C57BL/6 mice were randomly divided into the control group,depres-sion model group,and hyperforin intervention group.The chronic unpredictable mild stress(CUMS)model was induced and drug interventions were administered for 28 d.Behavioral experiments were conducted to as-sess depressive symptoms,and hippocampal tissue was collected for single-cell RNA sequencing.Key cell populations and differentially expressed genes across groups were identified,followed by PPI network,GO,and KEGG enrichment analysis.Results Behavioral experiments indicated that CUMS successfully induced depressive symptoms in mice,while hyperforin im-proved depressive behavior.In the depression model group,the proportion of brain perivascular macrophages(PVM)increased,and this proportion decreased after hyperforin intervention,approaching the level seen in the control group.The top 20 common differentially ex-pressed genes in the PVM subpopulation were Saa3,Hbb-bs and Ccl24.PPI network analysis identified core targets,including Ccl2,Dhx9,C3,Msr1,Cxcl2 and Cx3cr1.KEGG enrichment analysis revealed pathways related to chemokines,phagosome formation,and inosi-tol phosphate metabolism.Conclusion The antide-pressant mechanism of hyperforin may be related to the regulation of Ccl24 and its related chemokine signaling pathway by PVM.