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

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

Objective: To examine the prevalence of e-cigarette use and associated factors among primary and secondary school students in Pudong New Area, Shanghai, and to explore the pathways linking harm perception of e-cigarettes, interpersonal social influence, and attitudes toward e-cigarette use with experimentation behavior, in order to provide scientific basis for further optimizing the prevention and control strategies of e-cigarette among adolescents. Methods: From September to October 2025, a multi stage cluster random sampling method was used to select 5 144 primary and secondary school students aged 8-19 years from 47 primary and secondary schools in Pudong New Area, Shanghai, to conduct an anonymous questionnaire survey. The questionnaire collected information on e-cigarette use, harm perception of e-cigarette, interpersonal social influence, and attitudes toward e-cigarette use. The Chi-square test was applied to analyze the differences in cigarette and e-cigarette use behavior among primary and secondary school students with different demographic characteristics. Structural equation modeling (SEM) was constructed using Mplus 8.3 software, and the bootstrap method was utilized to test the mediating effects. Results: The reported rates of cigarette experimentation, e-cigarette experimentation, and current e-cigarette use among primary and secondary school students were 1.85%, 2.10%, and 0.70%, respectively. Higher reporting rates of e-cigarette experimentation were observed among boys (2.82%), secondary school students aged 16-19 (3.39%), senior high school students (3.05%), and those with weekly pocket money >100 yuan ( 6.11% ) ( χ 2=11.67, 8.61, 8.00, 54.18, all P <0.05). Structural pathway analysis results demonstrated that e-cigarette harm perception positively predicted interpersonal social influence ( β =0.61) and e-cigarette use attitude ( β = 0.53 ), and interpersonal social influence ( β =0.65) and e-cigarette use attitude ( β =0.25) further promoted e-cigarette experimentation behavior among primary and secondary school students (all P <0.01), with interpersonal social influence playing a major mediating role (indirect effect=0.40). Conclusions E-cigarette experimentation behavior among primary and secondary school students in Pudong New Area is jointly influenced by multiple psychosocial factors. Intervention strategies should strengthen interpersonal social factors such as family and peers on the basis of health education, thereby constructing a comprehensive prevention and control strategy for e-cigarette use among primary and secondary school students.

Objective This study conducted molecular biological identification of the viruses carried by Culex pipiens pallens specimens collected in Shunyi District, Beijing in 2023, and observed the changes in the infection rate of the viruses carried by Cx. pipiens pallens at different collection times. Methods Cx. pipiens pallens were collected using carbon dioxide mosquito traps. The mosquito samples were ground in batches and analyzed by molecular biology technologies. The virus infection rate at different collection times was analyzed statistically. Results 17 strains of Culex pipiens pallens densovirus(CppDNV)were identified from Cx. pipiens pallens samples collected in Shunyi District, Beijing, in 2023. The nucleotide sequence analysis of the virus genome coding region showed that CppDNV was a single-stranded DNA virus with a total length of 3 335 nt, encoding 2 non-structural proteins(NS1, NS2)and 1 capsid protein(VP). The nucleotide(amino acid)sequence lengths of the three proteins were 2 376 nt(791 aa),1 092 nt(363 aa)and 1 071 nt(356 aa), respectively. Phylogenetic analysis showed that CppDNV was located in genus Brevihamaparvovirus. Statistical analysis showed no significant difference in infection rates across collection times(χ2=4.429, P=0.194). Conclusions CppDNV was identified in Cx. pipiens pallens in Beijing, and it was stably maintained in this natural population.

Regulated cell death (RCD) has long been conceptualized as an elaborate program orchestrated by the nucleus and mitochondria in eukaryotic cells. However, this paradigm was fundamentally changed in 2025 by two independent studies published in Cell. One revealed that mature, enucleated erythrocytes execute a cytoskeletal disintegration-driven lysis via a miniNLRP3-ASC-caspase-8‑β‑spectrin axis, termed spectrin-dependent death (spectosis), wherein caspase-8 undergoes a functional switch from an initiator to an executioner, reflecting an evolutionary adaptation in protein economy. The other uncovered mitoxypterilysis, a modality in which metabolic distress and innate immune signals converge to trigger mTORC2-mediated aberrant mitochondrial-plasma membrane contacts, culminating in localized lipid peroxidation and membrane rupture. Mitoxypterilysis shows a logic defined by dual metabolic-immune regulation. This paper systematically dissects the molecular architectures of both modalities, and through comparative analysis, delineates their distinctions from classical RCD pathways as well as their divergent dependencies on organellar integrity, triggering contexts, and executional programs. In parallel, we integrate the recent discovery of reductive death, which underscores a central metabolic checkpoint to contextualize these findings within an emerging framework. Finally, we evaluate their therapeutic implications in hemolytic diseases, oncology, and inflammatory pathologies, while critically reflecting on current limitations and future directions, with the aim of providing a renewed conceptual foundation for targeted intervention strategies.

ObjectiveTo explore the effects of "dryness pathogen" on a bronchial asthma rat model from the perspective of the prostaglandin D₂ （PGD₂）/eosinophil （EOS） axis. MethodsForty SD rats were randomly divided into five groups， blank group， asthma group， mild dryness asthma group， moderate dryness asthma group， and severe dryness asthma group， with 8 rats in each group. The asthma model was induced in the asthma group using ovalbumin （OVA）， while the asthma-dryness syndrome groups were modeled using a climate chamber combined with OVA to establish animal models of bronchial asthma with Northwest dryness syndrome. During modeling， general behavioral performance of the rats in each group was observed and recorded， and body weight， water intake， and asthma symptom scores were compared. On day 21 of the modeling， small animal respiratory system testing was used to measure respiratory rate and intermittent respiratory contraction index. Pathological changes in rat lung tissues were observed using HE staining. Giemsa staining was used to observe eosinophil （EOS） infiltration in lung tissues and calculate EOS counts. ELISA was used to detect serum levels of prostaglandin D₂ （PGD₂）， interleukin-5 （IL-5）， and interleukin-4 （IL-4）. Western Blot was used to detect eosinophil peroxidase （EPX） and prostaglandin D₂ receptor （CRTH2） protein levels in rat lung tissues. ResultsCompared to the blank group， the average water intake of rats in all asthma-dryness groups increased （P＜0.01）. The body weight of rats decreased in the moderate and severe asthma-dryness groups on day 14， and in all modelling groups on day 21 （P＜0.05 or P＜0.01）. Across all model groups， the asthma symptom score， respiratory rate， intermittent respiratory contraction index， EOS count in lung tissue， serum levels of PGD₂， IL-5， and IL-4， as well as the relative protein expression levels of EPX and CRTH2 in lung tissue all significantly increased （P＜0.01）. Compared to the asthma group， the water intake of rats in the mild， moderate， and severe asthma-dryness groups increased （P＜0.01）. On day 21 of the experiment， the body weight of rats in the moderate and severe asthma-dryness groups decreased （P＜0.05）， and the respiratory rate of rats in all asthma-dryness groups increased， as well as the serum levels of PGD₂， IL-5， and IL-4， and the relative protein expression levels of EPX and CRTH2 in lung tissues （P＜0.05 or P＜0.01）. Furthermore， in the moderate and severe asthma-dryness groups， the asthma symptom scores and intermittent respiratory contraction indices were elevated， and the EOS counts in lung tissue increased （P＜0.05 or P＜0.01）. Compared to the mild asthma-dryness group， serum levels of PGD₂， IL-5， and IL-4 in the severe asthma-dryness group increased， as well as the relative protein expression levels of EPX and CRTH2 in lung tissue （P＜0.05 or P＜0.01）. Pathological observation showed that rats in all asthma-dryness syndrome groups exhibited increased inflammatory infiltration in the lung tissue， alveolar wall thickening， luminal narrowing， pulmonary interstitial congestion， and aggravated viscous secretions. These pathological manifestations worsened as the degree of dryness increased. ConclusionThe "dryness pathogenic factor" can exacerbate bronchial asthma symptoms and lung tissue pathological damage through the PGD₂/EOS axis， and the damage progressively worsens with the increasing severity of the dryness pathogen.

During habitation on low-Earth-orbit (LEO) space stations, astronauts are exposed to a combination of orbital microgravity, space radiation, an enclosed and artificially controlled cabin environment, altered sleep-wake rhythms, and sustained operational and psychosocial demands. These factors can modify sensorimotor inputs, body-fluid distribution, arousal state, and task-related neural processing, thereby affecting brain function and behavior. Because evidence from real spaceflight remains limited by small samples, heterogeneous mission durations, and different measurement time points, this review integrates findings from real human spaceflight with relevant ground-based analog studies while treating real orbital studies as the primary source of evidence. We focus on electroencephalography (EEG) and event-related potentials (ERPs), structural and functional neuroimaging, and sensorimotor and cognitive outcomes, with particular attention to the direction, anatomical distribution, temporal course, and possible physiological significance of the reported changes. EEG studies indicate that long-duration spaceflight is associated with increased resting-state beta activity, particularly in sensorimotor and frontotemporal regions, together with state-dependent alterations in beta-band functional connectivity. In contrast, alpha source power and functional connectivity associated with the default mode network are reduced during long-duration missions, and some of these effects may persist into the early postflight period. Task-related electrophysiological findings further suggest that sustained mental workload can weaken frontocentral theta-temporoparietal gamma phase-amplitude coupling, whereas in-flight decision-making is accompanied by reduced P300 amplitude and reorganization of feedback-related potentials. Short-duration missions, however, have shown relative preservation of posterior dominant rhythms and some ERP measures, indicating that mission duration, recording state, and task demands substantially influence the observed electrophysiological phenotype. Neuroimaging provides complementary evidence at structural and network levels. Long-duration spaceflight has been associated with upward brain displacement, ventricular and cerebrospinal fluid expansion, regional gray- and white-matter remodeling, and alterations in white-matter structural connectivity. Functional magnetic resonance imaging (fMRI) studies further indicate reorganization of vestibular-sensorimotor, visual, and default mode networks. Some network changes recover after return to Earth, whereas others may remain detectable for months. Importantly, most MRI measurements are obtained after landing rather than in orbit; therefore, postflight findings may reflect a mixture of in-flight adaptation, the rapid transition back to 1 g, and subsequent readaptation rather than a single spaceflight effect. Behavioral evidence is most consistent for sensorimotor function. Early after return, astronauts frequently show impaired postural control, gait, spatial orientation, and coordination, consistent with reweighting among vestibular, visual, and proprioceptive information. By comparison, simple cognition and some critical operational tasks are often preserved. More subtle or high-load processes-including sustained attention, feedback evaluation, temporal processing, error monitoring, and metacognitive calibration may be more sensitive than global cognitive performance. This dissociation between neural change and preserved behavior suggests that altered brain activity should not automatically be interpreted as functional deterioration. Integrating the available modalities, we propose that LEO space-station habitation is better characterized by system-specific and stage-dependent neural adaptation than by a generalized increase or decline in brain function. The most coherent cross-modal pattern involves sensorimotor reorganization: reduced gravitational reference and weight-bearing feedback under microgravity may drive reweighting of vestibular, visual, and proprioceptive inputs, accompanied by changes in beta activity and vestibular-sensorimotor networks and followed by transient postflight sensorimotor deficits. A second major process involves fluid-related structural remodeling, in which cephalad fluid shifts and altered hydrostatic gradients may contribute to changes in cerebrospinal fluid spaces, ventricular volume, and brain tissue configuration. Resting-state and cognitive electrophysiological changes likely represent additional adjustments in network regulation and resource allocation, but their functional interpretation remains more dependent on sleep, workload, recording conditions, and individual differences. Future studies should move beyond isolated pre-post comparisons and group averages toward standardized longitudinal designs spanning preflight, multiple in-flight time points, and postflight recovery. Synchronized assessment of brain function, behavior, sleep, and key environmental parameters should be used to characterize individual adaptation trajectories and determine which neural changes reflect successful compensation, which predict delayed recovery, and which have genuine value for brain-health risk prediction and individualized countermeasures.

This study was aimed at understanding the antimicrobial resistance patterns,virulence characteristics,and phyloge-netic relationships of foodborne Listeria monocytogenes in Weifang.A total of 67 strains of Listeria monocytogenes were isolated from livestock,poultry meat,and clinical samples in Weifang between 2020 and 2023.The susceptibility of these isolates was determined through broth microdilution.Whole-genome sequencing and genetic characterization of these isolates were conducted.The 67 strains were divided into 12 STs,among which ST121,ST8,ST9,and ST87 predominated(76.12%).Eight groups of closely related strains were identified through cgMLST typing.Three Listeria pathogenicity islands and two genomic islands were identified in all strains:100%of the strains carried LIPI-1,5.97%carried LIPI-3,14.93%carried LIPI-4,2.99%carried LGI-2,and 4.48%of the strains carried LGI-3.No antibiotic resistance genes were found in any strains.All isolates were susceptible to ampicillin,penicillin,merope-nem,trimethoprim-sulfamethoxazole,and vancomycin.Five isolates were resistant to tetracycline,and three strains of ST87,one strain of ST8,one strain of ST224,and two strains of ST87 were simultaneously resistant to erythromycin.The tet(M)tetracycline re-sistance genes and msr(D)and mef(A)erythromycin resistance genes from three strains of ST87 and one strain of ST8 were carried by a phage similar to phi1605 in Erysipelothrix,with>95%identity.The tet(M)gene from the ST224 isolates was carried by a transposon similar to Tn5801_B15 in Enterococcus faecalis,with>95%identity.Drug-resistant strains of Listeria monocytogenes were found in livestock and poultry meat on sale in Weifang,particularly strains of type ST87 and ST224 simultaneously carrying highly pathogenic virulence islands,thus posing a threat to food safety and public health.These findings therefore warrant attention from relevant depart-ments and strengthened monitoring efforts.

Metabolomics covers a wide range of applications in life sciences,biomedicine,and phytology.Data acquisition(to achieve high coverage and efficiency)and analysis(to pursue good classification)are two key segments involved in metabolomics workflows.Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups.However,insufficient feature extraction,inappropriate feature selection,overfitting,or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused.Using two ginseng varieties,namely Panax japonicus(PJ)and Panax japonicus var.major(PJvm),containing the similar ginsenosides,we integrated pseudo-targeted metabolomics and deep neural network(DNN)modeling to achieve accurate species differentiation.A pseudo-targeted metabolomics approach was optimized through data acquisition mode,ion pairs generation,comparison between multiple reaction monitoring(MRM)and scheduled MRM(sMRM),and chromatographic elution gradient.In total,1980 ion pairs were monitored within 23 min,allowing for the most comprehensive ginseng metabolome analysis.The established DNN model demonstrated excellent classification performance(in terms of accuracy,precision,recall,F1 score,area under the curve,and receiver operating characteristic(ROC))using the entire metabolome data and feature-selection dataset,exhibiting superior advantages over random forest(RF),support vector ma-chine(SVM),extreme gradient boosting(XGBoost),and multilayer perceptron(MLP).Moreover,DNNs were advantageous for automated feature learning,nonlinear modeling,adaptability,and generalization.This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples.This established approach holds promise for plant metabolomics and is not limited to ginseng.

This study employed ultrahigh-performance liquid chromatograph-hybrid quadrupole orbitrap high resolution mass spectrometry (UHPLC-Q-Orbitrap HRMS) to detect the chemical constituents of traditional Chinese medicine in Sizi Dingchuan granules. Network pharmacology and molecular docking techniques were then utilized to predict the effects of Sizi Dingchuan granules on bronchial asthma, along with its target molecules and signaling pathways. UHPLC analysis identified 172 compounds, including 84 flavonoids, 38 organic acids and their derivatives, 22 phenylpropanoids, 16 organic oxygen compounds, 3 phenolic compounds, 2 terpenoids, 2 sugars and glycosides, and 5 other compounds. Typical compound fragmentation patterns were documented. Using network pharmacology methods, 117 compounds were ultimately selected for target prediction, establishing a “drug-component-target-disease” network, which revealed that quercetin, schisandrin A, baicalin, gomisin H, and baicalin exhibit multiple targets related to bronchial asthma, suggesting that they may be the active components responsible for the compound’s efficacy in treating this condition. Protein-protein interaction analysis identified core targets including TNF, IL-6, JAK2, STAT3, BCL2, CASP3, and EGFR, primarily clustered within the JAK-STAT signaling pathway. This suggests that the main components of Sizi Dingchuan granules may regulate the balance between Th17 and Treg cells, as well as Th1 and Th2 cell differentiation, by modulating the JAK-STAT signaling pathway, thereby exerting a positive therapeutic effect on bronchial asthma.