ObjectiveThe present study aimed to investigate alterations in white matter microstructure and spontaneous neural activity in male college smokers, and to further explore their associations with nicotine dependence. Given that adolescence and early adulthood represent critical periods for brain maturation, particularly for white matter development, understanding the neural correlates of smoking behavior during this stage is of substantial importance for both neuroscience and public health. MethodsA total of 115 male undergraduate students were initially recruited for this study. After quality control and exclusion procedures, 52 male college smokers and 42 demographically matched healthy non-smokers were included in the final analysis. All participants underwent multimodal magnetic resonance imaging (MRI), including diffusion tensor imaging (DTI) and resting-state functional MRI (rs-fMRI). White matter fiber tracts were reconstructed using the automated fiber quantification (AFQ) method, which enables precise identification and quantification of major fiber bundles. Eighteen major white matter tracts were segmented for each participant. Along the core trajectory of each tract, 100 equidistant nodes were sampled. Fractional anisotropy (FA) was calculated at each node to assess white matter microstructural integrity, while amplitude of low-frequency fluctuation (ALFF) was computed to evaluate spontaneous neural activity within white matter tracts. Between-group differences in FA and ALFF were assessed using two-sample t-tests, with appropriate corrections applied for multiple comparisons. Furthermore, Pearson correlation analyses were conducted to examine the relationships between imaging-derived metrics (FA and ALFF values in regions showing significant group differences) and nicotine dependence severity, as measured by the Fagerström test for nicotine dependence (FTND). ResultsCompared with healthy non-smokers, male college smokers exhibited significantly increased FA values in several white matter tracts, including the left thalamic radiation, right corticospinal tract, forceps major of the corpus callosum, left uncinate fasciculus, and right arcuate fasciculus. These findings suggest altered microstructural organization or increased directional coherence within these pathways. In addition, smokers demonstrated significantly elevated ALFF values in the forceps major, right uncinate fasciculus, and left arcuate fasciculus, indicating enhanced spontaneous neural activity in these white matter regions. Correlation analyses revealed that FA values in the left thalamic radiation and right corticospinal tract were negatively correlated with FTND scores, suggesting that higher levels of nicotine dependence were associated with reduced microstructural integrity or altered fiber organization in these regions. In contrast, ALFF values in the forceps major and right uncinate fasciculus were positively correlated with FTND scores, indicating that greater nicotine dependence was associated with increased spontaneous neural activity in specific white matter pathways. ConclusionThe present study provides evidence that male college smokers exhibit distinct alterations in both white matter microstructure and functional activity. These abnormalities are not uniformly distributed but rather localized to specific fiber tracts implicated in sensorimotor processing, interhemispheric communication, and higher-order cognitive and emotional regulation. Importantly, the observed associations between imaging metrics and nicotine dependence severity suggest that these structural and functional alterations may reflect neurobiological mechanisms underlying addiction. The combination of AFQ-based tract profiling and multimodal MRI offers a sensitive approach for detecting subtle changes along white matter pathways, highlighting its potential utility in identifying neuroimaging biomarkers of nicotine dependence. Overall, these findings indicate that smoking during early adulthood may disrupt ongoing white matter maturation, potentially leading to long-term consequences for brain function. This study provides novel insights into the neural basis of nicotine dependence and underscores the importance of early intervention and prevention strategies targeting young smokers.

[摘 要] 目的：探讨间充质基质细胞来源细胞外囊泡（MSC-EV）对小鼠免疫检查点抑制剂相关肺炎（CIP）模型的改善作用及分子机制。方法：选取Foxp3DTR小鼠，皮下接种MC38小鼠结肠癌细胞，待肿瘤生长至可触及后，随机分为3组（每组n = 6）：①对照组；②CIP模型组[接种MC38细胞后腹腔注射白喉毒素（DT）及anti-PD-1抗体，构建Treg细胞耗竭联合anti-PD-1抗体诱导的小鼠CIP模型]；③MSC-EV干预组（CIP模型基础上，经鼻滴注MSC-EV干预，剂量109个/只，每3天1次，共2次）。体内实验采用H-E染色观察肺组织病理损伤，测定肺干湿比评估肺水肿程度，ELISA检测支气管肺泡灌洗液（BALF）中IL-1β、IL-6及TNF-α水平，流式细胞术检测BALF中Ly6G⁺粒细胞浸润比例，监测肿瘤体积评价抗肿瘤疗效。体外实验采用DiO荧光标记观察细胞外囊泡（EV）被骨髓来源巨噬细胞摄取的情况，WB法检测NOD样受体家族含Pyrin域蛋白3（NLRP3）炎症小体关键蛋白（剪切型GSDMD、成熟型IL-1β）的表达水平。结合GEO数据库miRNA测序数据（GSE69909）、Dicer敲低及miR-21/miR-125抑制剂干预揭示潜在机制。结果：MSC-EV经鼻滴注可减轻CIP模型小鼠肺部炎症损伤，降低BALF中IL-1β、IL-6、TNF-α水平及Ly6G⁺粒细胞浸润比例（P < 0.05），且不削弱anti-PD-1抗体的抗肿瘤疗效。体外DiO标记示踪显示MSC-EV可被巨噬细胞摄取，WB法检测结果显示，MSC-EV可降低NLRP3炎症小体关键活化蛋白（剪切型GSDMD、成熟型IL-1β）水平（P < 0.05）。体外实验中，Dicer敲低后制备的MSC-EV 对巨噬细胞IL-1β的下调作用减弱（P < 0.05）。miRNA测序显示miR-21、miR-125在MSC-EV中高表达，抑制miR-21或miR-125后，相应MSC-EV对巨噬细胞IL-1β剪切的抑制作用降低（P < 0.05）。结论：MSC-EV通过其携带的miR-21和miR-125等miRNA发挥抗炎效应，其机制可能与抑制巨噬细胞NLRP3炎症小体活化有关，可有效改善CIP且不影响免疫检查点抑制剂的抗肿瘤疗效。

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Objective To develop dynamic prediction models based on multiple postnatal time points to support early diagnosis and individualized intervention for bronchopulmonary dysplasia(BPD)in preterm infants with gestational age<32 weeks.Methods Clinical data of 472 preterm infants with gestational age<32 weeks admitted to the Second Xiangya Hospital of Central South University between January 2016 and November 2020 were retrospectively analyzed.Multivariable logistic regression was applied to develop five independent prediction models at postnatal days 1,7,14,21,and 28.The performance of the models was assessed using the area under the receiver operating characteristic curve(AUC)and the Hosmer-Lemeshow test.Results Baseline characteristics such as gestational age and birth weight differed significantly between the BPD group(n=147)and the non-BPD group(n=325)(P<0.05).Predictors of BPD evolved across time points:on day 1,key predictors included gestational age,birth weight,Score for Neonatal Acute Physiology II(SNAP-II),invasive mechanical ventilation,and fraction of inspired oxygen>30%;by day 7,additional variables emerged,including fasting duration>2 days,mean feeding advancement rate<8.5 mL/(kg·d),neonatal respiratory distress syndrome,apnea of prematurity,and positive sputum culture;from day 14 onward,nutrition-and treatment-related indicators were incorporated additionally.The models demonstrated good discrimination at postnatal days 1,7,14,21,and 28,with AUCs of 0.917,0.927,0.939,0.944,and 0.968,respectively,and good calibration(Hosmer-Lemeshow P>0.05).Internal validation showed AUCs ranging from 0.899 to 0.958,indicating robust performance.Conclusions Dynamic postnatal prediction models incorporating indicators spanning perinatal factors,respiratory support,nutritional management,and therapeutic interventions demonstrate high predictive performance and facilitate dynamic risk assessment for BPD in preterm infants with gestational age<32 weeks.

Aim To explore the mechanism of action of Guizhi Jia Gegen decoction(GGD)in treating pneu-monia-enteritis induced by H1N1 influenza virus infec-tion in a mouse model,using network pharmacology and molecular docking techniques,followed by in vivo verification.Methods A pneumonia-enteritis mouse model was established,and the intervention effects of GGD on the model mice were evaluated using indica-tors such as body weight,rectal temperature,lung in-dex,colon length,H1N1 M gene expression,relative mRNA expression levels of inflammatory cytokines,and pathological sections of the lung and intestine.The targets of the blood-absorbed components of GGD were identified using the Swiss Target Prediction platform,and the disease targets were retrieved from the Gene-Cards platform.The intersecting targets were analyzed through PPI network analysis using the STRING data-base to identify core targets.GO analysis and KEGG pathway enrichment analysis were performed using the Metascape database.RT-qPCR was employed to vali-date the core targets and pathways.Molecular docking was conducted using AutoDock Tools software to verify the interactions between blood-absorbed components and key targets.Results GGD demonstrated signifi-cant therapeutic effects on the pneumonia-enteritis mouse model.The results of network pharmacology in-dicated that the therapeutic effects of GGD were strong-ly associated with targets such as TNF,ALB,PTGS2,MMP9,EGFR,ESR1,SRC,HSP90AA1,PPARG and MMP2.RT-qPCR results indicated that GGD could intervene in pneumonia-enteritis by regulating the targets TNF,ALB,EGFR and the related targets of the NF-κB pathway.Molecular docking results re-vealed that blood-absorbed components such as puerar-in and liquiritin could stably bind to TNF,ALB and EGFR.Conclusion Components such as puerarin and liquiritin in GGD may exert therapeutic effects on pneumonia-enteritis induced by H1N1 influenza virus infection by acting on targets such as TNF,ALB and EGFR.

Objective To develop dynamic prediction models based on multiple postnatal time points to support early diagnosis and individualized intervention for bronchopulmonary dysplasia(BPD)in preterm infants with gestational age<32 weeks.Methods Clinical data of 472 preterm infants with gestational age<32 weeks admitted to the Second Xiangya Hospital of Central South University between January 2016 and November 2020 were retrospectively analyzed.Multivariable logistic regression was applied to develop five independent prediction models at postnatal days 1,7,14,21,and 28.The performance of the models was assessed using the area under the receiver operating characteristic curve(AUC)and the Hosmer-Lemeshow test.Results Baseline characteristics such as gestational age and birth weight differed significantly between the BPD group(n=147)and the non-BPD group(n=325)(P<0.05).Predictors of BPD evolved across time points:on day 1,key predictors included gestational age,birth weight,Score for Neonatal Acute Physiology II(SNAP-II),invasive mechanical ventilation,and fraction of inspired oxygen>30%;by day 7,additional variables emerged,including fasting duration>2 days,mean feeding advancement rate<8.5 mL/(kg·d),neonatal respiratory distress syndrome,apnea of prematurity,and positive sputum culture;from day 14 onward,nutrition-and treatment-related indicators were incorporated additionally.The models demonstrated good discrimination at postnatal days 1,7,14,21,and 28,with AUCs of 0.917,0.927,0.939,0.944,and 0.968,respectively,and good calibration(Hosmer-Lemeshow P>0.05).Internal validation showed AUCs ranging from 0.899 to 0.958,indicating robust performance.Conclusions Dynamic postnatal prediction models incorporating indicators spanning perinatal factors,respiratory support,nutritional management,and therapeutic interventions demonstrate high predictive performance and facilitate dynamic risk assessment for BPD in preterm infants with gestational age<32 weeks.

Objective To investigate the clinical efficacy of dual-layer artificial dermis combined with vacuum sealing drainage and autologous split-thickness skin graft in the treatment of chronic refractory wounds.Methods A total of 60 patients with chronic refractory wounds were prospectively selected and divided into the control group(30 cases)and the observation group(30 cases)according to random number table method.In the control group,patients were treated with simple vacuum sealing drainage in the first phase and autologous split-thickness skin graft in the second phase.In the observation group,patients received dual-layer artificial dermis combined with vacuum sealing drainage in the first phase and autologous split-thickness skin graft in the second phase.The survival of autologous split-thickness skin,the incidence of adverse reactions,and the degree of scarring[Vancouver scar scale(VSS)score]of patients in the two groups were observed.The degree of pain before and after treatment[visual analogue scale(VAS)score],serum matrix metalloproteinase 13(MMP-13)level,serum tissue inhibitor of metalloproteinase 1(TIMP-1)level,and MMP-13/TIMP-1 ratio of patients in the two groups were compared before and after treatment.Results After treatment,the survival rate of autologous split-thickness skin in the observation group was better than that in the control group,the incidence of adverse reactions,the VSS score of the graft site and the donor site,and the pain degree in the observation group was lower/lighter than those in the control group,and the above differences were statistically significant(P<0.05).After treatment,the serum MMP-13 level and MMP-13/TIMP-1 ratio of patients in the two groups were lower than those before treatment,and the serum TIMP-1 level was higher than that before treatment,and the changes in the observation group were greater than that in the control group,and the differences were statistically significant(P<0.05).Conclusion Dual-layer artificial dermis combined with vacuum sealing drainage and autologous split-thickness skin graft have significant effects in the treatment of chronic refractory wounds,which can increase the survival rate of autologous split-thickness skin,reduce adverse reactions,alleviate scar conditions and pain degree,and regulate serum MMP-13 and TIMP-1 levels.

Aim To perform high-throughput screen-ing of immunomodulatory traditional Chinese medicine(TCMs)based on an in vitro B cell differentiation-antibody secretion model,identifying active herbal candidates with immune-enhancing properties to pro-vide novel therapeutic options and theoretical support for influenza virus treatment in immunocompromised in-dividuals.Methods B cells were stimulated with dif-ferent concentrations of cytosine-phosphate-guanine oli-godeoxynucleotide 2006(CpG)and nterleukin-2(IL-2)to promote proliferation,differentiation,and anti-body secretion,and the effects of varying concentra-tions of the solvent DMSO were also evaluated.The op-timal conditions for the B cell differentiation-anti-body secretion model were determined based on the se-cretion levels of three antibody isotypes.The feasibility of the model was further validated using rapamycin,a known B cell function inhibitor.On this basis,a high-throughput screening platform for immunomodulatory a-gents was optimized and established.Subsequently,the immune-enhancing activity of 465 polarity extract from TCMs was evaluated.Results The optimal con-ditions for the model were determined as 2 mg·L-1 CpG,1.67 × 106 nkat·L-1 IL-2,and DMSO with a volume fraction of 0.1％.Rapamycin effectively inhib-ited B cell differentiation into plasmablast and signifi-cantly reduced antibody production,indicating the reli-ability of the model.Multiple rounds of screening re-vealed that the dichloromethane extract of licorice,the dichloromethane extract of Vinegar-processed Curcumae Rhizoma,the cyclohexane extract of Honey-prepared Radix Asteris,and the aqueous extract of Siphonostegia chinensis Benth were identified to significantly promote both B cell proliferation and differentiation and anti-body secretion at a concentration of 600 μg·L-1.Conclusion This study successfully optimizes an in vitro B cell differentiation-antibody secretion model and identifies several TCM extracts,including licorice,with potential immune-enhancing activity.

Aim To explore the mechanism of baicalin combined with heat stimulation in treating acute lym-phoblastic leukemia(ALL)based on network pharma-cology and in vitro experiments.Methods The CCK-8 assay was used to screen the suitable conditions for heat stimulation to interfere ALL cell lines Jurkat,CCRF-CEM,Hut-78 and a normal lymphocyte HMy2.CIR,and the effects of baicalin combined with heat stimulation on the proliferation of three ALL cell lines and a normal lymphocyte were tested.The key targets of baicalin combined with fever stimulation for the treatment of ALL were obtained based on network phar-macological analysis,and the potential mechanisms were predicted by gene ontology(GO)annotation and kyoto encyclopedia of genes and genomes(KEGG)en-richment.The expression levels of TNF-α,AKT1,TYMS and CASP3 mRNA in ALL cell lines Jurkat and CCRF-CEM were examined by RT-qPCR with baicalin alone and baicalin combined with heat stimulation.Results The optimal conditions for heat stimulation to intervene ALL cells were 41 ℃ for 24 h,and heat stimulation combined with baicalin synergistically inhibited the growth of ALL cell lines and effectively reduced the cy-totoxicity of baicalin.Based on the network pharmaco-logical analysis,55 intersecting targets of baicalin with ALL diseases and 77 intersecting targets of baicalin with fever were obtained.The results of GO annotation and KEGG enrichment suggested that baicalin com-bined with fever stimulation to intervene ALL might be associated with influencing intracellular reactive oxygen species metabolism,DNA transcription and apoptotic processes involved in cysteine enzymes.Apoptosis,TNF and IL-17 signaling pathways were the key pathways for baicalin combined with heat stimulation in treating ALL.Under heat stimulation at 41 ℃ using SDHA gene as housekeeping gene,in vitro experiments showed that baicalin significantly up-regulated the expression of TNF-α and CASP3,and down-regulated the expression of TYMS in ALL cells.Conclusions Based on net-work pharmacologic analyses and in vitro experiments,baicalin combined with heat stimulation can regulate TNF-α and CASP3 gene levels in ALL cells and de-stroy cellular structure to promote cell apoptosis,thus synergistically treating ALL.

Aim To explore the mechanism of action of Guizhi Jia Gegen decoction(GGD)in treating pneu-monia-enteritis induced by H1N1 influenza virus infec-tion in a mouse model,using network pharmacology and molecular docking techniques,followed by in vivo verification.Methods A pneumonia-enteritis mouse model was established,and the intervention effects of GGD on the model mice were evaluated using indica-tors such as body weight,rectal temperature,lung in-dex,colon length,H1N1 M gene expression,relative mRNA expression levels of inflammatory cytokines,and pathological sections of the lung and intestine.The targets of the blood-absorbed components of GGD were identified using the Swiss Target Prediction platform,and the disease targets were retrieved from the Gene-Cards platform.The intersecting targets were analyzed through PPI network analysis using the STRING data-base to identify core targets.GO analysis and KEGG pathway enrichment analysis were performed using the Metascape database.RT-qPCR was employed to vali-date the core targets and pathways.Molecular docking was conducted using AutoDock Tools software to verify the interactions between blood-absorbed components and key targets.Results GGD demonstrated signifi-cant therapeutic effects on the pneumonia-enteritis mouse model.The results of network pharmacology in-dicated that the therapeutic effects of GGD were strong-ly associated with targets such as TNF,ALB,PTGS2,MMP9,EGFR,ESR1,SRC,HSP90AA1,PPARG and MMP2.RT-qPCR results indicated that GGD could intervene in pneumonia-enteritis by regulating the targets TNF,ALB,EGFR and the related targets of the NF-κB pathway.Molecular docking results re-vealed that blood-absorbed components such as puerar-in and liquiritin could stably bind to TNF,ALB and EGFR.Conclusion Components such as puerarin and liquiritin in GGD may exert therapeutic effects on pneumonia-enteritis induced by H1N1 influenza virus infection by acting on targets such as TNF,ALB and EGFR.