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 sensitive scalp is a complex syndrome characterised by abnormal nerve sensations, such as stinging, itching, burning, and tightness, and diminished tolerance to physical or chemical stimuli that would not typically cause such unpleasant responses, with its pathology involving physical barrier destruction at the stratum corneum level, neural hyperreactivity and sensory nerve sensitization, and local immunological dysregulation and chronic low‑grade inflammation. The homeostasis of the scalp microenvironment plays a crucial regulatory role in maintaining the hair follicle growth cycle, yet this “soil” factor has long been underappreciated in hair loss research, which has traditionally centered on intrinsic follicular defects, such as genetic predisposition or androgen-driven mechanisms. In this review, we summarized the potential mechanisms underlying the imbalance in the “barrier-neural-immune” network in sensitive scalps. Sensitive scalp is further manifested as impaired skin barrier, including increased transepidermal water loss and abnormal lipid secretion. These alterations are accompanied by increased surface pH, excessive secretion of sebum rich in free fatty acids, reduced microbial diversity, and dysbiosis characterized by a reduction in Cutibacterium and an increase in Staphylococcus colonization. Mechanistically, we also analyzed how neurogenic inflammation, mediated by substances such as substance P (SP) and calcitonin gene-related peptide (CGRP), along with persistent low-grade inflammation, disrupts the microenvironment of the hair follicle stem cell niche through mechanisms involving mechanosensitive ion channels (e.g., Piezo1), oxidative stress, and cytokine cascades. When the barrier is compromised, the weakened stratum corneum may facilitate the penetration of external stimuli, sensitizing cutaneous nerve endings. Those hyperresponsive nerves then fire off neuropeptides like substance P and CGRP. These peptides activate mast cells and other immune cells via the MrgprB2 receptor, prompting degranulation and a wave of pro-inflammatory mediators that kick off neurogenic inflammation. At the same time, oxidative stress and inflammatory cytokines drive a persistent low-grade inflammation that directly damages the hair follicle stem cell niche. Physical compression from shrinking hair shafts activates Piezo1 channels, setting off calcium influx and Caspase‑3‑dependent apoptotic signaling. We primarily considered the interactions between inflammatory signaling and the sensitization of the androgen receptor (AR) pathway, as well as the inhibition of the Wnt/β‑catenin pathway, which may subsequently contribute to hair follicle miniaturization and disruption of the growth cycle. The inflammatory microenvironment appears to boost AR expression in dermal papilla cells, making them more sensitive to dihydrotestosterone (DHT). This heightened sensitivity may promote the expression of transforming growth factor-β1 (TGF-β1), TGF-β2, and Dickkopf-1 (DKK1), which suppress the Wnt/β‑catenin pathway—essential for follicle growth and regeneration—potentially accelerating follicular miniaturization and stalling the growth cycle. Coupled with direct inflammatory apoptosis, oxidative stress, and circadian disruption, these routes may collectively speed up hair follicle stem cell depletion and diffuse hair thinning. These findings point to the need for more mechanistic and translational research to test the proposed pathways and explore therapies that target the microenvironment in sensitive scalp-related hair loss. Ultimately, we hope to provide theoretical support for the intervention of hair loss by restoring the steady state of the scalp microenvironment and combining with new precision delivery technologies such as microneedles.

Objective To analyze the literature on artificial intelligence in forensic research from 2012 to 2022 in the Web of Science Core Collection Database,to explore research hotspots and developmen-tal trends.Methods A total of 736 articles on artificial intelligence in forensic medicine in the Web of Science Core Collection Database from 2012 to 2022 were visualized and analyzed through the litera-ture measuring tool CiteSpace.The authors,institution,country(region),title,journal,keywords,cited references and other information of relevant literatures were analyzed.Results A total of 736 articles published in 220 journals by 355 authors from 289 institutions in 69 countries(regions)were identi-fied,with the number of articles published showing an increasing trend year by year.Among them,the United States had the highest number of publications and China ranked the second.Academy of Forensic Science had the highest number of publications among the institutions.Forensic Science Inter-national,Journal of Forensic Sciences,International Journal of Legal Medicine ranked high in publica-tion and citation frequency.Through the analysis of keywords,it was found that the research hotspots of artificial intelligence in the forensic field mainly focused on the use of artificial intelligence technol-ogy for sex and age estimation,cause of death analysis,postmortem interval estimation,individual identification and so on.Conclusion It is necessary to pay attention to international and institutional cooperation and to strengthen the cross-disciplinary research.Exploring the combination of advanced ar-tificial intelligence technologies with forensic research will be a hotspot and direction for future re-search.

The air at high altitude is thin and belongs to the environment of low temperature, low oxygen and low pressure. The human brain is the most sensitive to hypoxia. Hypoxia will cause dysfunction of the central nervous system, resulting in high-altitude hypoxic brain injury, including mild high altitude headache and more destructive high altitude cerebral edema (HACE). Recently, with more and more people work and live in high altitude areas, the development of high-altitude hypoxic brain injury drugs would produce great economic value and social significance. Non clinical pharmacodynamic evaluation is the basic of drug development, which plays a key role in improving the success rate of clinical transformation and reducing the risk of clinical research. This review summarizes the cell models and animal models, and the evaluation indicators usually used to explore the candidates of high-altitude hypoxic brain injury. We aim at establishing a standardized non clinical efficacy evaluation system for high altitude hypoxic encephalopathy, and provide a standardized reference for drug development in hypoxic encephalopathy at high altitude at nonclinical stage.

Aim To explore the mechanism of process¬ing and increasing efficiency of Arisaematis rhizomz preparatum. Methods UPLC-Q-TOF-MS/MS tech¬nology was used to detect the chemical components be¬fore and after processing of Arisaematis rhizomz prepara¬tum, and its mechanism of action was analysed in the treatment of 44 asthma and phlegm " by using network pharmacology. A rat model of allergic asthma was es- tablished to compare the efficacy of Arisaematis rliizoma before and after processing. Results A total of 27 chemical components were identified, among which cur- cumin ,6-gingerol and other components increased after processing. Combined with the database prediction, the action mechanism of the 36 chemical components in the treatment of 44 asthma and phlegm" diseases was dis¬cussed and predicted through network pharmacology. The results of animal experiments showed that the effect of processed Arisaematis rhizoma on allergic asth¬ma was better than that of Arisaematis rhizoma, but there was no significant difference. Conclusions The addition of curcumin, 6-gingerol, camphor, demethyl- curcumin and other components after the processed Ari¬saematis rhizomz preparatum may be the reason for the synergistic effect of Arisaematis rhizomz preparatum in the treatment of allergic asthma.

OBJECTIVE: We aimed to assess the feasibility and superiority of machine learning (ML) methods to predict the risk of Major Adverse Cardiovascular Events (MACEs) in chest pain patients with NSTE-ACS. METHODS: Enrolled chest pain patients were from two centers, Beijing Anzhen Emergency Chest Pain Center Beijing Bo'ai Hospital, China Rehabilitation Research Center. Five classifiers were used to develop ML models. Accuracy, Precision, Recall, F-Measure and AUC were used to assess the model performance and prediction effect compared with HEART risk scoring system. Ultimately, ML model constructed by Naïve Bayes was employed to predict the occurrence of MACEs. RESULTS: According to learning metrics, ML models constructed by different classifiers were superior over HEART (History, ECG, Age, Risk factors, & Troponin) scoring system when predicting acute myocardial infarction (AMI) and all-cause death. However, according to ROC curves and AUC, ML model constructed by different classifiers performed better than HEART scoring system only in prediction for AMI. Among the five ML algorithms, Linear support vector machine (SVC), Naïve Bayes and Logistic regression classifiers stood out with all Accuracy, Precision, Recall and F-Measure from 0.8 to 1.0 for predicting any event, AMI, revascularization and all-cause death ( vs. HEART ≤ 0.78), with AUC from 0.88 to 0.98 for predicting any event, AMI and revascularization ( vs. HEART ≤ 0.85). ML model developed by Naïve Bayes predicted that suspected acute coronary syndrome (ACS), abnormal electrocardiogram (ECG), elevated hs-cTn I, sex and smoking were risk factors of MACEs. CONCLUSION Compared with HEART risk scoring system, the superiority of ML method was demonstrated when employing Linear SVC classifier, Naïve Bayes and Logistic. ML method could be a promising method to predict MACEs in chest pain patients with NSTE-ACS.
Humans ; Acute Coronary Syndrome/epidemiology* ; Bayes Theorem ; Feasibility Studies ; Risk Assessment/methods* ; Chest Pain/etiology* ; Myocardial Infarction/diagnosis*

Objective: To study the impact of regional positive lymph node ratio (LNR) on prognosis of patients with gallbladder carcinoma. Methods: The clinicopathological and survival data of 53 patients with gallbladder carcinoma who underwent radical resection with regional lymph node metastasis in Ningbo University Affiliated Lihuili Hospital from May 2012 to December 2020 were collected, and receiver operating characteristic curve (ROC) was used to determine the optimal cut-off value of LNR for predicting postoperative survival status in patients with gallbladder carcinoma. According to the critical value, the patients were divided into low LNR group and high LNR group. The clinicopathological features and prognosis of the two groups were compared. Log rank test was used for univariate analysis of prognostic factors in patients with gallbladder carcinoma, and Cox proportional hazards model was used for multivariate analysis. Results: A total of 417 regional lymph nodes were dissected in 53 patients, of which 144 lymph nodes were positive, with a positive rate of 34.5%. The optimal cut-off value of LNR for predicting postoperative survival status of patients with gallbladder carcinoma was 0.33. According to this cut-off value, patients were divided into low LNR group (LNR≤0.33, 28 cases) and high LNR group (LNR>0.33, 25 cases). The recurrence rates were 64.3% (18/28) and 88.0 % (22/25) in low LNR group and high LNR group, respectively. The median recurrence-free survival (RFS) was 8 and 7 months, respectively (P=0.032). In the low LNR group, the 1-, 3-, and 5-year survival rates were 56.2%, 38.4%, and 32.0%, respectively, and the median overall survival (OS) was 16 months. In the high LNR group, the 1-, 3-, and 5-year survival rates were 37.9%, 5.4%, and 0, respectively, and the median OS was 9 months. The postoperative survival rate of patients in the low LNR group was better than that in the high LNR group (P=0.008). Univariate analysis showed that LNR was even associated with RFS and OS in patients with gallbladder carcinoma (P<0.05). Multivariate analysis showed that LNR>0.33 was an independent risk factor for postoperative RFS (HR=1.977, 95% CI: 1.045-3.740), but not for OS (HR=1.561, 95% CI: 0.685-3.553). Conclusion: On the basis of clearing a sufficient number of regional lymph nodes, patients with gallbladder carcinoma with regional LNR>0.33 are more likely to relapse after operation, but the predictive value of LNR>0.33 OS is insufficient.
Humans ; Lymph Node Ratio ; Gallbladder Neoplasms/pathology* ; Lymph Node Excision ; Lymphatic Metastasis/pathology* ; Neoplasm Staging ; Retrospective Studies ; Lymph Nodes/pathology* ; Prognosis

Objective: To evaluate the feasibility and effectiveness of the application of internet-based HIV testing in men who have sex with men (MSM) in practical application and provide evidence for its application in the future. Methods: MSM who visited the internet-based intervention platform for at least one time from June to December 2020 were selected for the study. The information about platform visit, the number of self-test kits provided, the basic characteristics of the MSM and their satisfactory level were collected. And multivariable logistic regression analyses were conducted to identify the potential factors associated with the reporting of self-test results. Results: By the end of December 31^th, 2020, a total of 132 267 platform visits had been recorded, and 3 511 HIV self-test kits had been provided upon the MSM's requests, and 3 237 MSM (92.2%) reported self-test results. The HIV positive rate was 2.4% (69/2 855) and the confirmation rate of positive HIV test results was 86.7% (52/60). The MSM who asked for self-test kits online were mainly aged ≤30 years, had education level of college or above, and found their sexual partners through internet or dating software. Multivariable logistic regression analyses showed that repeat of online HIV self-test kits application (OR=3.50,95%CI:2.10-5.83), guarantee deposit of 50 yuan at application (OR=2.55,95%CI:1.33-4.89), monthly economic income 1-3 000 yuan (OR=1.54,95%CI:1.05-2.28) or no income (OR=1.71,95%CI:1.20-2.42) and online sexual partners finding (OR=1.49,95%CI:1.13-1.95) were associated with higher reporting rate of self-test results. The satisfactory rate the MSM to the service of platform was 99.5% (217/218). Conclusions: The study confirmed the feasibility and effectiveness of internet-based intervention for HIV tests in MSM, which could promote the self-test of HIV in MSM and facilitate the early detection of HIV infection through social media platforms and multi-channel promotion.
Male ; Humans ; Homosexuality, Male ; HIV Infections/prevention & control* ; Feasibility Studies ; Sexual and Gender Minorities ; HIV Testing ; Internet

OBJECTIVES: To study the serum levels of insulin-like growth factor-1 (IGF-1) and insulin-like growth factor binding protein-3 (IGFBP-3) in children with autism spectrum disorder (ASD) and their association with the core symptoms of ASD. METHODS: A total of 150 ASD children aged 2-7 years (ASD group) and 165 healthy children matched for age and sex (control group) who were recruited at the outpatient service of Chongqing Health Center for Women and Children were enrolled as subjects. Autism Behavior Checklist (ABC) and Childhood Autism Rating Scale (CARS) were used to evaluate the core symptoms of the ASD children. Chemiluminescence was used to measure the serum levels of IGF-1 and IGFBP-3 in both groups. RESULTS: The ASD group had a significantly lower serum level of IGF-1 than the control group (P<0.05). The children with severe ASD had significantly lower serum levels of IGF-1 and IGFBP-3 than those with mild-to-moderate ASD (P<0.001). For the children aged 2-3 years, the ASD group had a significantly lower serum level of IGF-1 than the control group (P<0.05). Boys had a significantly lower serum level of IGF-1 than girls in both ASD and control groups (P<0.05). The serum levels of IGF-1 and IGFBP-3 were negatively correlated with the total score of CARS (r=-0.32 and -0.40 respectively, P<0.001). CONCLUSIONS The reduction in serum IGF-1 level in early childhood may be associated with the development of ASD, and the serum levels of IGF-1 and IGFBP-3 are associated with the core symptoms of ASD children.
Autism Spectrum Disorder ; Autistic Disorder ; Child ; Child, Preschool ; Female ; Humans ; Insulin-Like Growth Factor Binding Protein 3 ; Insulin-Like Growth Factor I ; Male