ObjectiveThe controllability changes of structural brain network were explored based on the control and brain network theory in young smokers, this may reveal that the controllability indicators can serve as a powerful factor to predict the sleep status in young smokers. MethodsFifty young smokers and 51 healthy controls from Inner Mongolia University of Science and Technology were enrolled. Diffusion tensor imaging (DTI) was used to construct structural brain network based on fractional anisotropy (FA) weight matrix. According to the control and brain network theory, the average controllability and the modal controllability were calculated. Two-sample t-test was used to compare the differences between the groups and Pearson correlation analysis to examine the correlation between significant average controllability and modal controllability with Fagerström Test of Nicotine Dependence (FTND) in young smokers. The nodes with the controllability score in the top 10% were selected as the super-controllers. Finally, we used BP neural network to predict the Pittsburgh Sleep Quality Index (PSQI) in young smokers. ResultsThe average controllability of dorsolateral superior frontal gyrus, supplementary motor area, lenticular nucleus putamen, and lenticular nucleus pallidum, and the modal controllability of orbital inferior frontal gyrus, supplementary motor area, gyrus rectus, and posterior cingulate gyrus in the young smokers’ group, were all significantly different from those of the healthy controls group (P<0.05). The average controllability of the right supplementary motor area (SMA.R) in the young smokers group was positively correlated with FTND (r=0.393 0, P=0.004 8), while modal controllability was negatively correlated with FTND (r=-0.330 1, P=0.019 2). ConclusionThe controllability of structural brain network in young smokers is abnormal. which may serve as an indicator to predict sleep condition. It may provide the imaging evidence for evaluating the cognitive function impairment in young smokers.

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.

Humans ; Adolescent ; Acne Vulgaris/therapy* ; Skin Care ; Surveys and Questionnaires ; Cognition ; China ; Skin

Objective To analyze the medication rules of Professor HUANG Feng for the treatment of low back pain using data mining methods.Methods The information of prescriptions for the effective cases of outpatients with low back pain treated by Professor HUANG Feng were collected and screened.Microsoft Excel 2019 was used to analyze the frequency of medication and the distribution of properties,flavors and meridian tropism of the drugs in the included prescription.IBM SPSS Modeler 18.0 was used for association rule analysis,and IBM Statistics 26.0 was used for cluster analysis.Results A total of 239 prescriptions and 75 Chinese medicines were included.There were 23 high-frequency Chinese medicines with the medication frequency being or over 20 times,and the top 10 Chinese medicines were Glycyrrhizae Radix et Rhizoma,vinegar-processed Corydalis Rhizoma,Cibotii Rhizoma,Atractylodis Macrocephalae Rhizoma,Zanthoxyli Radix,salt-processed Achyranthis Bidentatae Radix,Rehmanniae Radix,Dipsaci Radix,Coicis Semen,and Salviae Miltiorrhizae Radix et Rhizoma.The medicines were mainly warm in nature,and were sweet,bitter and pungent in flavor.Most of the drugs had the meridian tropism of liver,stomach and spleen meridians.Among the drug combinations obtained from association rule analysis with the top 20 highest support,vinegar-processed Corydalis Rhizoma,Cibotii Rhizoma,Atractylodis Macrocephalae Rhizoma and Zanthoxyli Radix were the core drugs.Cluster analysis yielded 6 clustering combinations.Conclusion For the treatment of low back pain,Professor HUANG Feng follows the principle of"treatment adapting to the climate,individuality,and environment"and"treating the root cause of the disease",usually adopts the drugs for activating blood,moving qi and relieving pain,nourishing the liver and kidney,and also uses the medicines for replenishing qi and strengthening the spleen.The ideas of HUANG Feng for the treatment of low back pain can be used as a reference for the clinical treatment.

People frequently struggle to juggle their work, family, and social life in today’s fast-paced environment, which can leave them exhausted and worn out. The development of technologies for detecting fatigue while driving is an important field of research since driving when fatigued poses concerns to road safety. In order to throw light on the most recent advancements in this field of research, this paper provides an extensive review of fatigue driving detection approaches based on electroencephalography (EEG) data. The process of fatigue driving detection based on EEG signals encompasses signal acquisition, preprocessing, feature extraction, and classification. Each step plays a crucial role in accurately identifying driver fatigue. In this review, we delve into the signal acquisition techniques, including the use of portable EEG devices worn on the scalp that capture brain signals in real-time. Preprocessing techniques, such as artifact removal, filtering, and segmentation, are explored to ensure that the extracted EEG signals are of high quality and suitable for subsequent analysis. A crucial stage in the fatigue driving detection process is feature extraction, which entails taking pertinent data out of the EEG signals and using it to distinguish between tired and non-fatigued states. We give a thorough rundown of several feature extraction techniques, such as topology features, frequency-domain analysis, and time-domain analysis. Techniques for frequency-domain analysis, such wavelet transform and power spectral density, allow the identification of particular frequency bands linked to weariness. Temporal patterns in the EEG signals are captured by time-domain features such autoregressive modeling and statistical moments. Furthermore, topological characteristics like brain area connection and synchronization provide light on how the brain’s functional network alters with weariness. Furthermore, the review includes an analysis of different classifiers used in fatigue driving detection, such as support vector machine (SVM), artificial neural network (ANN), and Bayesian classifier. We discuss the advantages and limitations of each classifier, along with their applications in EEG-based fatigue driving detection. Evaluation metrics and performance assessment are crucial aspects of any detection system. We discuss the commonly used evaluation criteria, including accuracy, sensitivity, specificity, and receiver operating characteristic (ROC) curves. Comparative analyses of existing models are conducted, highlighting their strengths and weaknesses. Additionally, we emphasize the need for a standardized data marking protocol and an increased number of test subjects to enhance the robustness and generalizability of fatigue driving detection models. The review also discusses the challenges and potential solutions in EEG-based fatigue driving detection. These challenges include variability in EEG signals across individuals, environmental factors, and the influence of different driving scenarios. To address these challenges, we propose solutions such as personalized models, multi-modal data fusion, and real-time implementation strategies. In conclusion, this comprehensive review provides an extensive overview of the current state of fatigue driving detection based on EEG signals. It covers various aspects, including signal acquisition, preprocessing, feature extraction, classification, performance evaluation, and challenges. The review aims to serve as a valuable resource for researchers, engineers, and practitioners in the field of driving safety, facilitating further advancements in fatigue detection technologies and ultimately enhancing road safety.

Tranexamic acid is widely used in joint orthopedic surgery.At the same time,it has high safety and few adverse drug reactions.It can effectively improve intraoperative bleeding and promote early functional recovery of patients.This article reviews the mode of administration,safe dose,administration time and adverse drug reactions of tranexamic acid in the perioperative period of joint replacement and arthroscopic surgery,in order to provide reference for the clinical application of tranexamic acid.

Objective:To analyze the clinical characteristics and causes of death of patients with pneumoconiosis, and to provide evidence for the prevention and management of pneumoconiosis.Methods:From June 2022 to July 2023, 38 dead patients with pneumoconiosis confirmed by Shandong Academy of Occupational Health and Occupational Medicine were selected as the research objects. The clinical data of patients were collected through hospital information system (HIS) and laboratory information management system (LIS) to analyze the basic situation of patients with pneumoconiosis who died, the distribution of industry types, the course of disease, the nature of work, the type of reimbursement, complications/comorbidities, and the direct causes of death. Univariate analysis of variance was used to compare the course of pneumoconiosis death in patients with different age of exposure to dust.Results:Among the 38 patients with pneumoconiosis, there were 37 males and 1 female. The age of exposure to dust was 5-37 (19.29±8.17) years, the duration of disease was 5-41 (20.26±8.53) years, and the age of death was 27-86 (70.42±12.26) years old. There were 10 cases of stage Ⅰ pneumoconiosis, 18 cases of stage Ⅱ, 10 cases of stage Ⅲ pneumoconiosis and 32 cases (84.21%) of silicosis. There were 30 (78.95%) people aged ≥65 years and 8 (21.05%) people aged <65 years. The industry was mainly metal products (18 workers, 47.37%), and the distribution of work was mainly excavation workers (11 workers, 28.95%). The death course of pneumoconiosis patients with 10-<30 years of exposure to dust accounted for 76.32% (29/38). The average course of pneumoconiosis patients with 20-<30 years of exposure to dust was the longest[ (24.00±9.39) years], and there was no statistically significant difference in the average course of disease among different age of exposure to dust groups ( F=1.81, P=0.165). The working units of the deceased patients were private enterprises or factories, and the hospitalization expenses were borne by individuals for 21 people (55.26%). The working unit was a state-owned enterprise, and 17 people (44.74%) were reimbursed for hospitalization expenses and work-related injuries. The main comorbidities/complications of pneumoconiosis patients were respiratory infection in 18 cases (47.37%) and chronic pulmonary heart disease (47.37%). The top 3 direct causes of death were pneumoconiosis in 13 cases (34.21%), pulmonary infection in 10 cases (26.32%) and lung cancer in 7 cases (18.42%) . Conclusion:Most of 38 cases of pneumoconiosis patients death diseases such as multiple combination of respiratory system, cardiovascular system, respiratory system disease is a major cause of death in pneumoconiosis patients.

Objective To investigate the effects of modified Yupingfeng Powder medicated serum on the inflammatory response of rat lung epithelial type Ⅱ cells RLE-6TN;To explore the mechanism based on nuclear factor(NF)-κB signaling pathway.Methods The inflammatory reaction of RLE-6TN cells was induced by lipopolysaccharide,and the cells were divided into control group,model group,dexamethasone medicated serum group,and 5%,10%and 20%TCM serum group,and the cell model was intervened with different serum.After 24 hours,the content of lactate dehydrogenase(LDH)in cell supernatant was detected by kit,and the content of reactive oxygen species(ROS)in cells were detected by fluorescence staining,Hoechst/PI double staining was used to observe cell apoptosis,and ELISA was used to detect tumor necrosis factor-α(TNF-α),interleukin(IL)-6,and IL-1β contents in cell supernatant,RT-qPCR was used to detect Toll like receptor 4(TLR4),myeloid differentiation factor 88(MyD88),and NF-κB inhibitory protein α(IκBα)mRNA expression,Western blot was used to detect protein expressions of TLR4,MyD88,NF-κBp65 and IκBα.Results Compared with the control group,the contents of LDH,TNF-α,IL-6,IL-1β in RLE-6TN cell supernatant and ROS content in cells of model group significantly increased(P<0.01),the cell apoptosis rate significantly increased(P<0.01),the expressions of TLR4 and MyD88 mRNA and protein significantly increased(P<0.01),the expression of IκBα mRNA significantly decreased(P<0.01),and the ratio of p-NF-κBp65/NF-κBp65 and p-IκBα/IκBα significantly increased(P<0.01).Compared with the model group,the content of LDH,TNF-α,IL-6,IL-1 in RLE-6TN cell supernatant and ROS content in cells significant decreased in the 20%TCM serum group and dexamethasone medicated serum group(P<0.01),the cell apoptosis rate significantly decreased(P<0.01),the expressions of TLR4 and MyD88 mRNA and protein significantly decreased(P<0.05,P<0.01),the expression of IκBα mRNA significantly increased(P<0.01),and the ratio of p-NF-κBp65/NF-κBp65 and p-IκBα/IκBα significantly decreased(P<0.05,P<0.01).Conclusion Modified Yupingfeng Powder medicated serum can reduce RLE-6TN cells inflammatory reaction,and its mechanism may be related to the regulation of NF-κB signaling pathway.

Objective:To investigate the clinical features and prognosis of male with anti-melanoma differentiation-associated gene 5 (MDA5) autoantibody.Methods:The clinical data of 246 patients with DM and anti-MDA5 autoantibodies hospitalized by Jiangsu Myositis Cooperation Group from 2017 to 2020 were collected and retrospectively analyzed. Chi-square test was performed to compared between counting data groups; Quantitative data were expressed by M ( Q1, Q3), and rank sum test was used for comparison between groups; Single factor survival analysis was performed by Kaplan-Meier method and Log rank test; Cox regression analysis were used for multivariate survival analysis. Results:①The male group had a higher proportion of rash at the sun exposure area [67.1%(47/70) vs 52.8%(93/176), χ2=4.18, P=0.041] and V-sign [50.0%(35/70) vs 30.7%(54/176), χ2=8.09, P=0.004] than the female group. The male group had higher levels of creatine kinase [112(18, 981)U/L vs 57 (13.6, 1 433)U/L, Z=-3.50, P<0.001] and ferritin [1 500 (166, 32 716)ng/ml vs 569 (18, 14 839)ng/ml, Z=-5.85, P<0.001] than the female group. The proportion of ILD [40.0%(28/70) vs 59.7%(105/176), χ2=7.82, P=0.020] patients and the red blood cell sedimentation rate[31.0(4.0, 101.5)mm/1 h vs 43.4(5.0, 126.5)mm/1 h, Z=-2.22, P=0.026] in the male group was lower than that of the female group, but the proportion of rapidly progressive interstitial lung disease (PR-ILD) [47.1%(33/70) vs 31.3%(55/176), χ2=5.51, P=0.019] was higher than that of the female group. ②In male patients with positive anti-MDA5 antibodies,the death group had a shorter course of disease[1.0(1.0, 3.0) month vs 2.5(0.5,84) month, Z=-3.07, P=0.002], the incidence of arthritis [16.7%(4/24) vs 42.2%(19/45), χ2=4.60, P=0.032] were low than those in survival group,while aspartate aminotransferase (AST)[64(22.1, 565)U/L vs 51(14,601)U/L, Z=-2.42, P=0.016], lactate dehydrogenase (LDH) [485(24,1 464)U/L vs 352(170, 1 213)U/L, Z=-3.38, P=0.001], C-reactive protein (CRP) [11.6(2.9, 61.7) mg/L vs 4.95(0.6, 86.4) mg/L, Z=-1.96, P=0.050], and ferritin levels [2 000(681, 7 676) vs 1 125 (166, 32 716)ng/ml, Z=-3.18, P=0.001] were higher than those in the survival group, and RP-ILD [95.8%(23/24) vs 22.2%(10/45), χ2=33.99, P<0.001] occurred at a significantly higher rate. ③Cox regression analysis indicated that the course of disease LDH level, and RP-ILD were related factors for the prognosis of male anti-MDA5 antibodies [ HR (95% CI)=0.203(0.077, 0.534), P=0.001; HR (95% CI)=1.002(1.001, 1.004), P=0.003; HR (95% CI)=95.674 (10.872, 841.904), P<0.001]. Conclusion:The clinical manifestations of male anti-MDA5 antibody-positive patients are different from those of female. The incidence of ILD is low, but the proportion of PR-ILD is high. The course of disease, serum LDH level, and RP-ILD are prognostic factors of male anti-MDA5 antibody-positive patients.

Objective:To investigate the current situation of the use of transjugular intrahepatic portosystemic shunt (TIPS) for portal hypertension, which should aid the development of TIPS in China.Methods:The China Portal Hypertension Alliance (CHESS) initiated this study that comprehensively investigated the basic situation of TIPS for portal hypertension in China through network research. The survey included the following: the number of surgical cases, main indications, the development of Early-TIPS, TIPS for portal vein cavernous transformation, collateral circulation embolization, intraoperative portal pressure gradient measurement, commonly used stent types, conventional anticoagulation and time, postoperative follow-up, obstacles, and the application of domestic instruments.Results:According to the survey, a total of 13 527 TIPS operations were carried out in 545 hospitals participating in the survey in 2021, and 94.1% of the hospital had the habit of routine follow-up after TIPS. Most hospitals believed that the main indications of TIPS were the control of acute bleeding (42.6%) and the prevention of rebleeding (40.7%). 48.1% of the teams carried out early or priority TIPS, 53.0% of the teams carried out TIPS for the cavernous transformation of the portal vein, and 81.0% chose routine embolization of collateral circulation during operation. Most of them used coils and biological glue as embolic materials, and 78.5% of the team routinely performed intraoperative portal pressure gradient measurements. In selecting TIPS stents, 57.1% of the hospitals woulel choose Viator-specific stents, 57.2% woulel choose conventional anticoagulation after TIPS, and the duration of anticoagulation was between 3-6 months (55.4%). The limitation of TIPS surgery was mainly due to cost (72.3%) and insufficient understanding of doctors in related departments (77.4%). Most teams accepted the domestic instruments used in TIPS (92.7%).Conclusions:This survey shows that TIPS treatment is an essential part of treating portal hypertension in China. The total number of TIPS cases is far from that of patients with portal hypertension. In the future, it is still necessary to popularize TIPS technology and further standardize surgical indications, routine operations, and instrument application.