Objective To explore the differences in heartbeat-evoked response (HER) under drug-related cues and neutral cues in individuals with heroin use disorder (HUD), and analyze the correlation between HER potentials and immediate cue-induced craving scores. Methods Fifty HUD participants were recruited from the Chang’an Compulsory Isolation Drug Rehabilitation Center in Shaanxi Province from June to September 2024. Simultaneous acquisition of 64-channel electroencephalography (EEG) and electrocardiogram signals was performed. Twenty alternating segments of drug-related and neutral cue videos were presented, and participants rated their subjective craving after each segment using visual analogue scale (VAS) scores. Scalp EEG data were source analyzed to obtain cortical EEG signals and corresponding HER. Short-time Fourier transform was used to calculate the power spectral density (PSD) of EEG within a time window from 100 ms before the R-peak to 500 ms after it, using the R-peak as the time zero point. Cluster-based permutation testing was used to analyze PSD differences between drug-related and neutral cues in the HUD individuals. Pearson correlation analysis was performed to evaluate the correlation between HER potentials and VAS scores. Results In the 350–420 ms time window, HER potentials in the left posterior parietal, temporal, and posterior cingulate cortices were significantly lower under drug-related cues compared to neutral cues (P＜0.01); in the 140–210 ms time window, HER potentials in the right prefrontal cortex were significantly higher under drug-related cues compared to neutral cues (P＜0.01). Correlation analysis showed that HER potentials in the left temporal and left posterior cingulate cortices were significantly negatively correlated with VAS scores (P＜0.05). Drug-related cues enhanced PSD of γ power (30–100 Hz) in salience network (fronto-insular), parietal and occipital regions (P＜0.05). PSD integrations of low-γ power (40–60 Hz) in parietal region (350–400 ms) and high-γ power (70–100 Hz) in left salience network (fronto-parietal) and occipital regions (300–350 ms) were positively correlated with VAS scores (P＜0.05). Conclusions Drug-related cues may modulate cortical activity related to heartbeat perception in HUD individuals, and such dynamic changes in both time and frequency domains are stably associated with subjective craving.

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.

ObjectiveThis paper proposes a novel real-time bedside pulmonary ventilation monitoring method for the diagnosis of chronic obstructive pulmonary disease (COPD), based on electrical impedance tomography (EIT). Four indicators—center of ventilation (CoV), global inhomogeneity index (GI), regional ventilation delay inhomogeneity (RVDI), and the ratio of forced expiratory volume in one second to forced vital capacity (FEV₁/FVC)—are calculated to enable the spatiotemporal assessment of COPD. MethodsA simulation of the respiratory cycles of COPD patients was first conducted, revealing significant differences in certain indicators compared to healthy individuals. The effectiveness of these indicators was then validated through experiments. A total of 93 subjects underwent multiple pulmonary function tests (PFTs) alongside simultaneous EIT measurements. Ventilation heterogeneity under different breathing patterns—including forced exhalation, forced inhalation, and quiet tidal breathing—was compared. EIT images and related indicators were analyzed to distinguish healthy individuals across different age groups from COPD patients. ResultsSimulation results demonstrated significant differences in CoV, GI, FEV₁/FVC, and RVDI between COPD patients and healthy individuals. Experimental findings indicated that, in terms of spatial heterogeneity, the GI values of COPD patients were significantly higher than those of the other two groups, while no significant differences were observed among healthy individuals. Regarding temporal heterogeneity, COPD patients exhibited significantly higher RVDI values than the other groups during both quiet breathing and forced inhalation. Moreover, during forced exhalation, the distribution of FEV₁/FVC values further highlighted the temporal delay heterogeneity of regional lung function in COPD patients, distinguishing them from healthy individuals of various ages. ConclusionEIT technology effectively reveals the spatiotemporal heterogeneity of regional lung function, which holds great promise for the diagnosis and management of COPD.

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 investigate the characteristics of allele frequencies for 9 red blood cell (RBC) blood group systems in the Hui ethnic voluntary blood donor population of Suzhou using real-time fluorescence PCR technology, so as to provide technical support for establishing a RBC blood group genetic database. Methods: PCR-TaqMan technology was employed to perform genotyping detection for 9 RBC blood group systems using 144 samples from Hui voluntary blood donors in Suzhou, collected between October 2023 and August 2024. Results: Blood group allele frequencies among Suzhou Hui voluntary blood donors were distributed as follows: MNS system (M=0.566 0, N=0.434 0; S=0.079 9, s=0.920 1); Lutheran system (Lu =0.003 5, Lu =0.996 5; Au =0.895 8, Au =0.104 2); Kell system (K=0.000 0, k=1.000 0; Kp =0.003 5, Kp =0.996 5; JS =0.000 0, JS =1.000 0); Duffy system (Fy =0.899 3, Fy =0.100 7); Kidd system (JK =0.451 4, JK =0.548 6); Diego system (Di =0.041 7, Di =0.958 3); Yt system (Yt =0.996 5, Yt =0.003 5); Dombrock system (Do =0.128 5, Do =0.871 5); Colton system (Co =1.000 0, Co =0.000 0). The PCR-TaqMan-based RBC blood group genotyping technology successfully completed testing for all samples. Conclusion: The MNS, Lutheran, Duffy, Kidd, Diego, and Dombrock blood group systems in the Suzhou Hui population exhibited polymorphic distribution patterns, whereas the Colton system was monomorphic. Standardized application of PCR-TaqMan technology facilitates the establishment of an RBC blood group genetic database.

Mental state is an important part of the normal life activities of the human body, and it is also the most external expression and the most easily obtained information of the physical condition. The normal activities of the mind depend on the normal operation of the viscera, qi, and blood, and are a unified whole that prospers together and suffers together. The theory of the five-spirit-viscera in the Yellow Emperor’s Inner Classic revealed that the normal mental activities of the human body were dominated by the five internal organs, that is, the five internal organs were the body and the five spirits were the function. And it highlighted the viewpoint that the five internal organs store the spirits and are actually one. The heart governs the spirit and belongs to the four internal organs. On this basis, Synopsis of Golden Chamber used the internal organs to diagnose and treat mental diseases, integrating the theory of the five spirits into it, forming a unique method of diagnosis and treatment with the heart as the leading factor and regulating the qi and blood of the four internal organs. It identified the pathogenesis of diseases such as pathogenic crying, lily disease, and hysteria from five levels: heart deficiency and weak qi, heart-lung disharmony, heart-liver disharmony, the heart of the loss of the spleen nourishment, and disharmony between heart and kidney. The treatment was mainly to replenish the deficiency of the viscera and eliminate the pathogens, reflecting the characteristics of regulating the mind and calming the four internal organs. This unique view on diagnosis and treatment has profoundly influenced the diagnosis and treatment theories of mental illnesses by later doctors, and is of great significance to the current clinical treatment of such illnesses.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

ObjectiveTo identify the active components in Maimendong decoction (MMDD) against pulmonary fibrosis (PF) and validate their molecular effects in vitro, while focusing on the role of methylophiopogonanone B in regulating fibrosis.MethodsData on MMDD components and targets were gathered from databases including BATMAN-TCM and PubMed, whereas the PF gene data were sourced from GeneCards, OMIM, and TTD. Shared targets were determined using the STRING database, and molecular docking was used to analyze the essential molecules associated with fibrosis. To simulate PF conditions, human embryonic lung fibroblasts (HPF) and A549 cells were exposed to transforming growth factor-β1 (TGF-β1). Various assays were used to determine the effects of MMDD and methylophiopogonanone B on signaling pathways, apoptosis, and epithelial–mesenchymal transition.ResultsWe identified 11 active components from MMDD extracts that targeted 511 shared proteins associated with PF, revealing 10 key targets in network analysis. Gene ontology analysis indicated that processes and pathways such as apoptosis regulation and PI3K/Akt signaling were involved. In vitro experiments revealed that MMDD downregulated the expression of α-smooth muscle actin (α-SMA), collagen type I (COL-I), and collagen type III and regulated Bcl-2/Bax signaling pathways to promote apoptosis. The flow cytometry apoptosis assay revealed that MMDD promoted the TGF-β1-induced apoptosis of myofibroblasts. The primary active ingredient in MMDD, methylophiopogonanone B, reduced α-SMA, COL-I, and PI3K/Akt/mTOR-related protein levels in TGF-β1-treated HPF cells, decreased Bcl-2 and cleaved caspase 3, and increased Bax. Moreover, methylophiopogonanone B increased E-cadherin levels and reduced α-SMA, fibronectin, N-cadherin, vimentin, and snail in TGF-β1-treated A549 cells.ConclusionMethylophiopogonanone B demonstrated the potential to treat PF by inducing myofibroblast apoptosis and inhibiting EMT. However, despite encouraging initial results, further clinical research is warranted to verify the safety and efficacy of methylophiopogonanone B in the management of PF

Background: and Purpose Although amyloid positron emission tomography (PET) might provide a molecular diagnosis for cerebral amyloid angiopathy (CAA), it does not have sufficient specificity for this condition relative to incipient Alzheimer’s disease (AD). To identify a regional amyloid uptake pattern specific to CAA, we attempted to reduce this overlap by selecting “pure CAA” (i.e., fulfilling the criteria for probable CAA but without tau PET AD signature) and “pure AD” (i.e., positive amyloid PET and presence of tau PET AD signature, but without lobar hemorrhagic lesions). We hypothesized that occipital tracer uptake relative to the whole cortex (WC) would be higher in patients with pure CAA and may serve as a specific diagnostic marker. Methods: Patients who fulfilled these criteria were identified. In addition to the occipital region of interest (ROI), we assessed the frontal and posterior cingulate cortex (PCC) ROIs that are sensitive to AD. Amyloid PET uptake was expressed as the absolute standardized uptake value ratio (SUVR) and ROI/WC ratio. The diagnostic utility of amyloid PET was assessed using the Youden index cutoff. Results: Eighteen patients with AD and 42 patients with CAAs of comparable age were eligible. The occipital/WC was significantly higher in CAA than AD (1.02 [0.97–1.06] vs. 0.95 [0.87–1.01], P=0.001), with an area under curve of 0.762 (95% confidence interval [CI] 0.635–0.889) and a specificity of 72.2% (95% CI 46.5–90.3) at Youden cutoff (0.98). The occipital lobe, frontal lobe, PCC and WC SUVRs were significantly lower in CAA than in AD. The frontal/WC and PCC/WC ratios did not differ significantly between the groups. Conclusion Using stringent patient selection to minimize between-condition overlap, this study demonstrated the specificity of higher relative occipital amyloid uptake in CAA than in AD.

Background and Objectives: There is no dedicated occlusive device for closing coronary artery fistulas (CAFs), and specific efficacy and safety data of various off-label occlusive devices for CAFs closure are scarce. Methods: Patients undergoing transcatheter closure of CAFs from January 2011 to December 2022 were included in the single-center retrospective study. The study population was divided into 2 groups: coils group (n=35) and patent ductus arteriosus (PDA) occluders group (n=66). Results: No significant intergroup differences were observed in demographic characteristics except age. The presence of multiple CAF origins (54.3% vs. 4.5%, p<0.001) and multiple draining sites (51.4% vs. 3.0%, p<0.001) were more common in the coils group. In contrast, the presence of aneurysm (72.7% vs. 14.3%, p<0.001), and large fistula (75.8% vs. 37.1%, p<0.001) were more prevalent in the PDA occluders group. The acute procedural success rate of the PDA occluders group was higher compared to that of the coils group (87.9% vs.62.9%, adjusted odds ratio [OR], 7.20; 95% confidence interval, 1.59–32.64; p=0.01).In addition, no significant intergroup differences were noted in both the recanalization rate (7.8% vs. 20%, p=0.107) and the reintervention rate (3.1% vs. 8.6%, p=0.342). Conclusions Transcatheter closure of CAFs using PDA occluders was associated with significantly higher acute procedural success rates compared to coil embolization with comparable late outcomes.