ObjectiveTo elucidate the chemical composition of the reference sample of Jinshui Liujunjian and its distribution characteristics in blood and tissues of rats. MethodsUltra performance liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry（UPLC-Q-TOF-MS/MS） was used to detect the reference sample solution， plasma， and tissue samples of Jinshui Liujunjian under positive and negative ion modes， respectively. Qualitative Analysis 10.0 software and a self-constructed database were employed for primary mass spectrum matching.Compound identification was further validated by comparing retention times， secondary mass spectral fragments， reference standards， and literature data to deduce fragmentation pathways. ResultsA total of 122 compounds were identified in the reference sample of Jinshui Liujunjian， including 47 flavonoids， 5 amino acids， 13 iridoids， 16 triterpenoid saponins， etc.， of which 42 compounds were confirmed by comparison with reference substances. A total of 21 prototype components were identified in blood components； 50 prototype components were identified in different tissues， among which 13， 10， 7， 21， 11， 6， 14， and 40 prototype components were identified in the heart， liver， spleen， lung， kidney， brain， large intestine， and stomach， respectively. Among them， 7 compounds such as ferulic acid， glycyrrhizic acid， and nobiletin were exposed in the target organs of lung and kidney. ConclusionThis study elucidates the material basis of the reference samples of Jinshui Liujunjian， primarily composed of flavonoids and triterpenoid saponins， along with their in vivo distribution characteristics. These findings provide a scientific basis for establishing quality evaluation indicators and offer references for subsequent pharmacodynamic and pharmacokinetic investigations.

ObjectiveTo elucidate the chemical composition of the reference sample of Jinshui Liujunjian and its distribution characteristics in blood and tissues of rats. MethodsUltra performance liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry（UPLC-Q-TOF-MS/MS） was used to detect the reference sample solution， plasma， and tissue samples of Jinshui Liujunjian under positive and negative ion modes， respectively. Qualitative Analysis 10.0 software and a self-constructed database were employed for primary mass spectrum matching.Compound identification was further validated by comparing retention times， secondary mass spectral fragments， reference standards， and literature data to deduce fragmentation pathways. ResultsA total of 122 compounds were identified in the reference sample of Jinshui Liujunjian， including 47 flavonoids， 5 amino acids， 13 iridoids， 16 triterpenoid saponins， etc.， of which 42 compounds were confirmed by comparison with reference substances. A total of 21 prototype components were identified in blood components； 50 prototype components were identified in different tissues， among which 13， 10， 7， 21， 11， 6， 14， and 40 prototype components were identified in the heart， liver， spleen， lung， kidney， brain， large intestine， and stomach， respectively. Among them， 7 compounds such as ferulic acid， glycyrrhizic acid， and nobiletin were exposed in the target organs of lung and kidney. ConclusionThis study elucidates the material basis of the reference samples of Jinshui Liujunjian， primarily composed of flavonoids and triterpenoid saponins， along with their in vivo distribution characteristics. These findings provide a scientific basis for establishing quality evaluation indicators and offer references for subsequent pharmacodynamic and pharmacokinetic 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.

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.

Background Long working hours, as a common risk factor for occupational stress, is closely related to the occurrence of depressive symptoms. Understanding how long working hours affect occupational stress and depressive symptoms will inform occupational health interventions. Objective To quantify the impact of long working hours exposure on occupational stress and depressive symptoms among Internet industry employees, translate black-box outputs into actionable insights, and demonstrate the value of interpretable machine learning for early-warning occupational-health surveillance. Methods A dataset was derived from a cross-sectional survey involving 2866 internet industry employees in China. This survey was part of the project Risk Assessment Of Long Working Hour Exposure And Its Adverse Health Effects, conducted by the National Institute for Occupational Health and Poisoning Control, Chinese Center for Disease Control and Prevention, from 2021 to 2023. Working hours, occupational stress and depressive symptoms were quantified with a set of structured questionnaires including the Core Occupational Stress Scale and the Patient Health Questionnaire. Pairwise associations were screened by Mantel tests and variance-inflation factors. Key predictors identified through feature selection were fed into six machine-learning risk-prediction models. Visual interpretation was provided by feature importance, Shapley additive explanations (SHAP) and local interpretable model-agnostic explanations (LIME), while directed causal effects and intervention impacts of prolonged working hours exposure on occupational stress and depressive symptoms were dissected with causal explanation of features techniques. Results The positive rates of occupational stress and depressive symptoms among internet employees were 12.9% and 77.8% respectively. Twelve core features for occupational stress and nine for depressive symptoms were retained after selection. After these features were supplied to six predictive algorithms and evaluated on five metrics, the Light Gradient Boosting Machine (LGBM) achieved the highest accuracy—0.89 for occupational stress and 0.79 for depressive symptoms on the hold-out test set. The feature-importance rankings converged on fatigue accumulation and life satisfaction as dominant drivers for both outcomes, whereas weekly working hours and daily overtime emerged as the principal exposure-related predictors. The SHAP summary plots revealed that longer weekly hours and daily overtime systematically elevated the probability of occupational stress. The causal feature explanation further quantified that ascending one category in weekly working hours increased the probability of occupational stress by 7.04%. Conclusion Exposure to long working hours is associated with both occupational stress and depressive symptoms among internet industry employees. Interpretable machine-learning frameworks translate these associations into transparent, defensible drivers, enabling precise identification of the pivotal factors and their interplay. This evidence base equips occupational-health practitioners with actionable insights for designing targeted prevention and intervention strategies.

Objective To analyze the infection status and subtype distribution characteristics of human papillomavirus(HPV)patients in Dongguan area from 2017 to 2023,as well as the relationship between the subtype distribution of HPV-positive patients and their cervical histopathology.Methods A total of 21 316 patients who underwent HPV genotyping in Dongguan Maternal and Maternal and Child Health Hospital of Dongguan from 2017 to 2023 were selected as the research subjects.Cervical exfoliated cells were collected from females,and specimens from lesion sites were collected from males.The 23 types of HPV genotyping were performed on the exfoliated cell specimens of the patients by PCR-reverse dot hybridization.Statistically analyze the annual prevalence of HPV subtypes from 2017 to 2023,the viral infection status of patients of dif-ferent genders and age groups,as well as the relationship between the subtype distribution of HPV-positive patients and their cervical histopathology.Results The overall detection rate of HPV was 31.5％(6 719/21 316).The annual prevalence of HPV showed a significant downward trend from 2017 to 2023(P＜0.001),and HPV types 52,16,58,53,and 51 were the most common.Female infections were mainly high-risk HPV types 52,16,58,53 and 51.Male infections were mainly low-risk HPV types 6 and 43 and high-risk HPV types 52,51 and 68.People under the age of 25 and those aged 55-＜65 were high-risk groups for infection,with detection rates of 46.6％(668/1 432)and 42.3％(473/1 117),respectively.There was a statistically significant difference in the overall detection rate among different age groups(P＜0.001).The HPV16 type increased significantly with the progression of cervical lesions from 15.0％(80/545)in patients with cervical intraepi-thelial neoplasia(CIN)Ⅰ to 36.3％(198/545)in patients with CIN Ⅱ-Ⅲ,and the difference was statistically significant(P＜0.001).HPV16 is the main infectious subtype of CIN Ⅱ-Ⅲ.Conclusion The detection rate of HPV in Dongguan area shows a downward trend from 2017 to 2023,and it is age and gender-specific.HPV 16 is closely related to high-grade CIN in HPV genotyping.

BACKGROUND:A large number of studies have confirmed that the therapeutic effectiveness of mesenchymal stem cell secretome is comparable to that of mesenchymal stem cells,but the mechanism of its action is still unclear. OBJECTIVE:To summarize the research progress of mesenchymal stem cell secretome in recent years,to investigate the molecular mechanism of its therapeutic effect,to analyze the current problems and to look forward to the future development. METHODS:The terms"exosomes,mesenchymal stem cells secrete,extracellular vesicles,mesenchymal stem cells,mechanism"were used as English search terms in the PubMed database.Articles that were not related to the research purpose of the article and duplicated articles were excluded.At the same time,we combined the method of literature tracking.Finally,109 articles that met the criteria were incuded for the review. RESULTS AND CONCLUSION:(1)The mesenchymal stem cell secretome promotes tissue repair and regeneration through delivering genetic material,immunomodulatory factors,growth factors,etc.to target cells,by activating anti-apoptotic,regulating angiogenesis,modulating fibrosis and pro-survival pathways in target cells.(2)The potential of mesenchymal stem cell secretome in disease therapy has also been confirmed.Numerous research results have shown that mesenchymal stem cell secretome can be used as a new cell-free treatment for inflammatory and degenerative diseases.(3)Mesenchymal stem cell secretome has been engineered to have more efficient therapeutic effects in recent years.However,due to the heterogeneity of the mesenchymal stem cell secretome and the complexity of its components,the exact mechanism of its therapeutic effect is still unclear.(4)At present,further research is needed to identify the key targets of mesenchymal stem cell secretome,and innovative specific and enhanced mesenchymal stem cell secretome should be developed by combining with engineering and genetic engineering technologies in the future.

Buyang Huanwu Decoction(BYHWD), as one of the classic formulas in traditional Chinese medicine(TCM) for the treatment of cerebral ischemic stroke(CIS), has demonstrated definite effects in clinical practice. However, the material basis and mechanism of treatment have not been systematically elucidated. This study employed network pharmacology and molecular docking to analyze the potential targets and mechanisms of blood-and brain-penetrating active components of BYHWD in reducing cell apoptosis in CIS. Cell experiments were then carried out to validate the prediction results. In the experiments, five active components including hydroxysafflor yellow A( HSYA), tetramethylpyrazine( TMP), astragaloside Ⅳ( AS-Ⅳ), amygdalin( AMY), and paeoniflorin(PF) were selected to explore the pharmacological effects of BYHWD. HT22 cells were treated with BYHWD, and the cell counting kit-8(CCK-8) method was employed to examine the toxic and side effects of BYHWD. A cell model of oxygen-glucose deprivation/reoxygenation( OGD/R) was constructed, with apoptosis and pyroptosis as the main screening indicators. The levels of lactate dehydrogenase(LDH) and glutathione(GSH) were measured to assess the cell membrane integrity. Flow cytometry was employed to detect apoptosis, and the activities of caspase-3 and caspase-1 were measured to clarify the status of apoptosis and pyroptosis. ELISA was employed to determine the levels of interleukin(IL)-1β and IL-18 to confirm pyroptosis. HSYA and AMY were identified in this study as the active components regulating apoptosis and pyroptosis. TUNEL was employed to detect the apoptosis rate, and Western blot was employed to determine the expression levels of apoptosis-related proteins B-cell lymphoma-2(Bcl-2), Bcl-2-associated X protein(Bax), and caspase-3, which confirmed that the anti-apoptotic effect of the combined component group was superior to that of the single component groups. The molecular docking results revealed strong binding affinity of HSYA and AMY with SDF-1α and CXCR4.AMD3100, a selective antagonist of CXCR4, was then used for intervention. The results of Western blot showed alterations in the expression levels of apoptosis-associated proteins, SDF-1α, and CXCR4. In conclusion, HSYA and AMY influence cellular apoptosis by modulating the SDF-1α/CXCR4 signaling cascade.
Drugs, Chinese Herbal/chemistry* ; Apoptosis/drug effects* ; Animals ; Neurons/cytology* ; Mice ; Molecular Docking Simulation ; Cell Line ; Glucose/metabolism* ; Humans ; Neuroprotective Agents/pharmacology*

Premature ovarian insufficiency(POI)is a complex endocrine disorder that significantly affects the physiological and repro-ductive functions of women,and it has become one of the main causes of infertility in women of childbearing age.The clinical features of POI include amenorrhea or oligomenorrhea,low estrogen or estrogen deficiency,and an increase in the level of gonadotropin.The in-cidence rate of POI tends to increase,yet its etiology and pathogenesis remain unclear.At present,the conventional treatment methods for POI have limited efficacy in fundamentally improving ovarian function or addressing the fertility issue.With the development of re-generative medicine,mesenchymal stem cells(MSCs)have become one of the research hotspots in POI therapy,and their exosomes have attracted wide attention as a promising"cell-free therapy".A number of animal experimental studies have shown that MSCs and their exosomes can exert a therapeutic effect on POI by affecting granulosa cell proliferation and apoptosis,promoting ovarian angiogen-esis,reducing oxidative stress and fibrosis,enhancing follicular development,and regulating immunity.In addition,related clinical studies have also made some progress.This article reviews the mechanisms and clinical effect of MSCs and their exosomes in the treatment of POI,in order to provide a reference for further research and bench-to-bedside translation of POI therapies.