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.

Objective To compare the long-term survival outcomes of patients with T_1-2N₀M₀ duodenal neuroendocrine tumor (DNET) after endoscopic resection (ER) or surgical resection (SR). Methods Patients diagnosed with T_1-2N₀M₀ DNET between January 1, 2004, and December 31, 2015, were extracted from the SEER database. Kaplan-Meier survival curve and log-rank test were used to compare overall survival (OS) rate and cancer-specific survival (CSS) rate between patients undergoing ER or SR. Propensity score matching (PSM) was used to reduce grouping differences, and multivariate Cox regression was used to analyze factors affecting OS and CSS before and after PSM. Results A total of 656 patients were included, with 457 in ER group and 199 in SR group. Before PSM, there was no significant difference in the 5-year OS rate between the ER and SR groups (88.9% vs 89.6%), but there was a significant difference in the 5-year CSS rate (99.3% vs 96.9%, P＝0.017). Before PSM, multivariate Cox regression analysis showed advanced age was an independent risk factor for decreased OS (P＜0.001). After PSM, there was no significant difference between the ER group (n＝187) and SR group (n＝187) in 5-year OS rate (90.2% vs 88.9%) or CSS rate (98.9% vs 96.7%). After PSM, multivariate Cox regression also showed advanced age was an independent risk factor for decreased OS, while resection method was not an independent factor for OS or CSS. Conclusions There is no significant difference in OS or CSS after endoscopic treatment and surgical treatments for patients with T_1-2N₀M₀ DNET, and advanced age is an independent factor for OS.

Based on ultra-high performance liquid chromatography-quadrupole-Exactive Orbitrap mass spectrometry(UPLC-Q-Exactive Orbitrap-MS) technology and network pharmacology, this study explored the pharmacodynamic substances and potential mechanisms of Huazhuo Sanjie Chubi Decoction in the treatment of gouty arthritis(GA). UPLC-Q-Exactive Orbitrap-MS technology was used to identify the components in Huazhuo Sanjie Chubi Decoction, and the qualitative analysis of its active ingredients was carried out, with a total of 184 active ingredients identified. A total of 897 active ingredient targets were screened through the PharmMapper database, and 491 GA-related disease targets were obtained from the OMIM, GeneCards, CTD databases. After Venn analysis, 60 intersecting targets were obtained. The component target-GA target network was constructed through the Cytoscape platform, and the STRING database was used to construct a protein-protein interaction network, with 16 core targets screened. The core targets were subjected to Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses, and the component-target-pathway network was constructed. It was found that the main active ingredients of the formula for the treatment of GA were phenols, flavonoids, alkaloids, and terpenoids, and the key targets were SRC, MMP3, MMP9, REN, ALB, IGF1R, PPARG, MAPK1, HPRT1, and CASP1. Through GO analysis, it was found that the treatment of GA mainly involved biological processes such as lipid response, bacterial response, and biostimulus response. KEGG analysis showed that the pathways related to the treatment of GA included lipids and atherosclerosis, neutrophil extracellular traps(NETs), IL-17, and so on. In summary, phenols, flavonoids, alkaloids, and terpenoids may be the core pharmacodynamic substances of Huazhuo Sanjie Chubi Decoction in the treatment of GA, and the pharmacodynamic mechanism may be related to SRC, MMP3, MMP9, and other targets, as well as lipids and atherosclerosis, NETs, IL-17, and other pathways.
Drugs, Chinese Herbal/therapeutic use* ; Network Pharmacology ; Arthritis, Gouty/metabolism* ; Chromatography, High Pressure Liquid/methods* ; Humans ; Mass Spectrometry/methods* ; Protein Interaction Maps/drug effects*

This study aims to comprehensively analyze the material basis of toad visceral oil(hereafter referred to as toad oil), and explore the pharmacological effect of toad oil on atopic dermatitis(AD). Ultra-high performance liquid chromatography-linear ion trap/orbitrap high-resolution mass spectrometry(UHPLC-LTQ-Orbitrap-MS) and gas chromatography-mass spectrometry(GC-MS) were employed to comprehensively identify the chemical components in toad oil. The animal model of AD was prepared by the hapten stimulation method. The modeled animals were respectively administrated with positive drug(0.1% hydrocortisone butyrate cream) and low-and high-doses(1%, 10%) of toad oil by gavage. The effect of toad oil on AD was evaluated with the AD score, ear swelling rate, spleen index, and pathological section results as indicators. A total of 99 components were identified by UHPLC-LTQ-Orbitrap-MS, including 14 bufadienolides, 7 fatty acids, 6 alkaloids, 10 ketones, 18 amides, and other compounds. After methylation of toad oil samples, a total of 20 compounds were identified by GC-MS. Compared with the model group, the low-and high-dose toad oil groups showed declined AD score, ear swelling rate, and spleen index, alleviated skin lesions, and reduced infiltrating mast cells. This study comprehensively analyzes the chemical composition and clarifies the material basis of toad oil. Meanwhile, this study proves that toad oil has a good therapeutic effect on AD and is a reserve resource of traditional Chinese medicine for external use in the treatment of AD.
Animals ; Dermatitis, Atopic/immunology* ; Disease Models, Animal ; Mice ; Male ; Gas Chromatography-Mass Spectrometry ; Humans ; Bufonidae ; Oils/administration & dosage* ; Chromatography, High Pressure Liquid ; Female ; Mice, Inbred BALB C

Descurainiae Semen Lepidii Semen, also known as Tinglizi, originates from Brassicaceae plants Descurainia sophia or Lepidium apetalum. The former is commonly referred to as "Southern Tinglizi(Descurainiae Semen)", while the latter is known as "Northern Tinglizi(Lepidii Semen)". To scientifically and accurately identify the origin of Tinglizi medicinal materials and traditional Chinese medicine products, this study developed a specific DNA mini-barcode based on chloroplast genome sequences. By combining the DNA mini-barcode with DNA metabarcoding technology, a method for the qualitative and quantitative identification of Tinglizi medicinal materials and Chinese patent medicines was established. In this study, chloroplast genomes of Southern Tinglizi and Northern Tinglizi and seven commonly encountered counterfeit products were downloaded from the GenBank database. Suitable polymorphic regions were identified to differentiate these species, enabling the development of the DNA mini-barcode. Using DNA metabarcoding technology, medicinal material mixtures of Southern and Northern Tinglizi, as well as the most common counterfeit product, Capsella bursa-pastoris seeds, were analyzed to validate the qualitative and quantitative capabilities of the mini-barcode and determine its minimum detection limit. Additionally, the mini-barcode was applied to Chinese patent medicines containing Tinglizi to authenticate their botanical origin. The results showed that the developed mini-barcode(psbB) exhibited high accuracy and specificity, effectively distinguishing between the two authentic origins of Tinglizi and commonly encountered counterfeit products. The analysis of mixtures demonstrated that the mini-barcode had excellent qualitative and quantitative capabilities, accurately identifying the composition of Chinese medicinal materials in mixed samples with varying proportions. Furthermore, the analysis of Chinese patent medicines revealed the presence of the adulterant species(Capsella bursa-pastoris) in addition to the authentic species(Southern and Northern Tinglizi), indicating the occurrence of adulteration in commercially available Tinglizi-containing products. This study developed a method for the qualitative and quantitative identification of multi-origin Chinese medicinal materials and related products, providing a model for research on other multi-origin Chinese medicinal materials.
DNA Barcoding, Taxonomic/methods* ; Drugs, Chinese Herbal/chemistry* ; Drug Contamination ; Genome, Chloroplast ; Medicine, Chinese Traditional

The holistic view is the key in the study of traditional Chinese medicine(TCM). The component structure theory is based on the holistic view to investigate the correlation between material basis and efficiency, which enriches the holistic "component-effect" research of TCM. Gintonin is a newly isolated non-saponin component of ginseng. Compared to ginsenosides, gintonin has many different pharmacological activities, and it provides new knowledge for the holistic research of ginseng. Thus, taking the discovery of gintonin from ginseng as an example, this paper explored the linkage between ginsenosides and gintonin from the perspective of "component-effect" correlations and systematically sorted out the similarities and differences between them in terms of structural characteristics, modes of action, and pharmacological activities. Starting from the collaborative interaction of TCM compounds, the study discussed the application and value of the holistic view in TCM "component-effect" research in the light of the component structure theory to provide new thoughts for the development of modern TCM research.
Panax/chemistry* ; Drugs, Chinese Herbal/pharmacology* ; Medicine, Chinese Traditional ; Humans ; Ginsenosides/pharmacology* ; Animals

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 explore the application value of fractional anisotropy(FA)analysis of RGB component transformation in different directions of fibers in substantia nigra in Parkinson's disease(PD).Methods There were 35 cases of PD and 37 cases of normal control group.After being performed by brain diffusion tensor imaging(DTI)scanning,the sequence was imported into 3DSlicense 5.6.0,and the diffusion module was used to implement pseudo color mapping based on FA,locate and segment substantia nigra,and use the substantia nigra mask as the tracking starting point.After forming tracing,fibers were imported into DTIANALYSIS 1.51,converting the RGB components into FA values for analysis,and visualized the analysis result.At the same time,fiber length,fiber density,and segmented FA point cloud percentage were compared.Results Compared with the normal group,the length of substantia nigra fibers in the PD group was shorter[(95.14±19.85)mm vs(115.99±21.39)mm,P＜0.01],and there was a statistical difference between the two groups.There was no statistical difference in fiber density[(0.07±0.05)/mm3 vs(0.10±0.12)/mm3,P＞0.05]between control group and PD group.The percentage of FA segment point clouds in the PD group was lower than that in the normal group at 0.9-1,but the principal component characteristics of the point cloud ratios in each FA segment were not significant.Conclusion Based on the transformation of RGB components into FA analysis,the length,density,and FA values of substantia nigra nerve fibers in PD patients can be quantified and visualized,providing a basis for the study of PD neural pathways.

OBJECTIVE: To investigate chronic hepatitis C virus (HCV) infection's effect on gestational liver function, pregnancy and delivery complications, and neonatal development. METHODS: A total of 157 HCV antibody-positive (anti-HCV[+]) and HCV RNA(+) patients (Group C) and 121 anti-HCV(+) and HCV RNA(-) patients (Group B) were included as study participants, while 142 anti-HCV(-) and HCV RNA(-) patients (Group A) were the control group. Data on biochemical indices during pregnancy, pregnancy complications, delivery-related information, and neonatal complications were also collected. RESULTS: Elevated alanine aminotransferase (ALT) rates in Group C during early, middle, and late pregnancy were 59.87%, 43.95%, and 42.04%, respectively-significantly higher than Groups B (26.45%, 15.70%, 10.74%) and A (23.94%, 19.01%, 6.34%) ( P < 0.05). Median ALT levels in Group C were significantly higher than in Groups A and B at all pregnancy stages ( P < 0.05). No significant differences were found in neonatal malformation rates across groups ( P > 0.05). However, neonatal jaundice incidence was significantly greater in Group C (75.16%) compared to Groups A (42.25%) and B (57.02%) ( χ ² = 33.552, P < 0.001). HCV RNA positivity during pregnancy was an independent risk factor for neonatal jaundice ( OR = 2.111, 95% CI 1.242-3.588, P = 0.006). CONCLUSIONS Chronic HCV infection can affect the liver function of pregnant women, but does not increase the pregnancy or delivery complication risks. HCV RNA(+) is an independent risk factor for neonatal jaundice.
Humans ; Female ; Pregnancy ; Adult ; Pregnancy Complications, Infectious/epidemiology* ; Retrospective Studies ; Pregnancy Outcome ; Infant, Newborn ; Viremia/virology* ; Hepatitis C ; Hepacivirus/physiology* ; Hepatitis C, Chronic/virology* ; Young Adult ; Alanine Transaminase/blood*