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.

Based on WANG Xugao's “thirty methods of treating the liver”， it is believed that the occurrence and development of childhood tic disorders follow the dynamic progression from liver qi disease to liver fire disease and then liver wind disease. The basic pathogenesis of three stages are characterized by binding constraint of liver qi， liver fire hyperactivity， and internal stirring of liver wind. Moreover， liver-blood deficiency and stagnation， and malnutrition of liver yin as the main point in terms of the imbalance of liver qi， blood， yin， and yang should be considered， as well as the imbalance relationship of the five zang organs such as the involvement of other organs and the gradually reach of the other organs. Guided by the principles of “thirty methods of treating the liver”， the treatment of tic disorders in liver qi stage should focus on soothing the liver and rectifying qi， soothing the liver and unblocking the collaterals， using Xiaochaihu Decoction （小柴胡汤） and Sini Powder （四逆散）. The treatment of tic disorders in liver fire stage involves clearing， draining and resolving liver heat， using Longdan Xiegan Decoction （龙胆泻肝汤）， Xieqing Pill （泻青丸）， Danggui Longhui Pill （当归龙荟丸）， and Huagan Decoction （化肝煎）. The treatment of tic disorders in liver wind stage involves extinguishing wind and subduing yang， using Lingjiao Gouteng Decoction （羚角钩藤汤） and Liuwei Dihuang Pill （六味地黄丸）. Throughout the treatment process， attention should be paid to harmonizing the liver's qi， blood， yin， and yang， as well as addressing the pathology of other organs.

italic>Schisandra chinensis is a traditional Chinese medicine with the functions of reinforcing deficiency, strengthening, and inducing astringency, appliable to treat the chronic cough and deficiency in breath, palpitation, and insomnia, etc. A hybrid mass spectrometry scanning strategy (high-definition data-independent/data-dependent acquisition, HDDIDDA), enabling the ion mobility separation and alternating data-independent acquisition/data-dependent acquisition, was established, which, in combination with in-house library-driven automatic peak annotation workflows facilitated by the UNIFI software, was utilized to systematically characterize the multi-classes of chemical components from S. chinensis. The use of an HSS T3 column (100 mm × 2.1 mm, 1.8 μm), 0.1% formic acid in H₂O-acetonitrile as the mobile phase running at the flow rate of 0.3 mL·min^-1, and column temperature at 35 ℃, could enable good separation of the S. chinensis components within 42 min. HDDIDDA scan in both the positive and negative ion modes was employed for data acquisition. Based on the automatic peak annotation, reference standards comparison, MS² data interpretation, and literature analysis, we were able to identify or tentatively characterize 105 compounds in the S. chinensis decoction, involving 56 terpenoids, 42 lignans, five glycosides, one organic acid, and one flavonoid. HDDIDDA scanning can improve the coverage of data acquisition and improve the accuracy of identification, while CCS prediction analysis provides the possibility to distinguish isomers by the ion mobility technology. The results provide reference for the intelligent material basis research of TCM.

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.

Objective To explore the efficacy and safety of recombinant human anti-severe acute respiratory syn-drome coronavirus 2(anti-SARS-CoV-2)monoclonal antibody injection(F61 injection)in the treatment of patients with coronavirus disease 2019(COVID-19)combined with renal damage.Methods Patients with COVID-19 and renal damage who visited the PLA General Hospital from January to February 2023 were selected.Subjects were randomly divided into two groups.Control group was treated with conventional anti-COVID-19 therapy,while trial group was treated with conventional anti-COVID-19 therapy combined with F61 injection.A 15-day follow-up was conducted after drug administration.Clinical symptoms,laboratory tests,electrocardiogram,and chest CT of pa-tients were performed to analyze the efficacy and safety of F61 injection.Results Twelve subjects(7 in trial group and 5 in control group)were included in study.Neither group had any clinical progression or death cases.The ave-rage time for negative conversion of nucleic acid of SARS-CoV-2 in control group and trial group were 3.2 days and 1.57 days(P=0.046),respectively.The scores of COVID-19 related target symptom in the trial group on the 3rd and 5th day after medication were both lower than those of the control group(both P＜0.05).According to the clinical staging and World Health Organization 10-point graded disease progression scale,both groups of subjects improved but didn't show statistical differences(P＞0.05).For safety,trial group didn't present any infusion-re-lated adverse event.Subjects in both groups demonstrated varying degrees of elevated blood glucose,elevated urine glucose,elevated urobilinogen,positive urine casts,and cardiac arrhythmia,but the differences were not statistica-lly significant(all P＞0.05).Conclusion F61 injection has initially demonstrated safety and clinical benefit in trea-ting patients with COVID-19 combined with renal damage.As the domestically produced drug,it has good clinical accessibility and may provide more options for clinical practice.

Objective To explore the diagnostic value of micropure imaging(MI)combined with strain elastography(SE)in correcting artificial intelligence(AI)S-Detect technology for benign and malignant breast complex cystic and solid masses.Methods The S-Detect diagnosis results were corrected based on the manifestations of MI and SE of the 145 breast complex cystic and solid masses.Postoperative pathological results were used as the gold standard to calculate the diagnostic sensitivity,specificity,and accuracy before and after correction.Additionally,receiver operating characteristic(ROC)curves were drawn for both groups,and the areas under the curves were compared.Results There were 80 benign and 65 malignant pathological results.After the correction of S-Detect,the diagnostic sensitivity,specificity,and accuracy,as well as the areas under the ROC curves,were all improved compared to before the correction.Conclusion Combining MI and SE to correct the diagnostic results of S-Detect can help improve the diagnostic efficacy of breast complex cystic and solid masses.

Objective:To investigate the perioperative impact of closure of mesenteric fissure in laparoscopic right hemicolectomy.Methods:The prospective randomized controlled trial was conducted. The clinical data of 320 patients who underwent laparoscopic right hemicolectomy in 11 medical centers, including The First Affiliated Hospital of China Medical University et al, from November 2022 to August 2023 were selected. Based on block randomization, patients were alloca-ted into the mesenteric fissure non-closure group and the mesenteric fissure closure group. Observa-tion indicators: (1) grouping of the enrolled patients; (2) intraoperative conditions; (3) postopera-tive conditions. Measurement data with skewed distribution were represented as M( Q1, Q3) and com-parison between groups was conducted using the Mann-Whitney U test. Count data were represen-ted as absolute numbers or percentages, and comparison between groups was conducted using the chi-square test or Fisher's exact probability. Comparison of ordinal data was conducted using the rank sum test. Comparison of visual analog scores was analyzed using generalized estimating equations. Results:(1) Grouping of the enrolled patients. A total of 320 patients with colon cancer were screened for eligibility, including 156 males and 164 females, aged 68(59,73)years. All the 320 patients were allocated into the mesenteric fissure non-closure group with 164 cases and the mesenteric fissure closure group with 156 cases. There was no significant difference in the age, body mass index, American Society of Anesthesiologist score, maximum tumor diameter, anastomosis location, anastomosis method, surgical approach, range of lymph node dissection, tumor staging between the two groups ( P>0.05) and there was a significant difference in the sex between them ( P<0.05). (2) Intraoperative conditions. There was no significant difference between the mesenteric fissure closure group and the mesenteric fissure non-closure group in the volume of intraoperative blood loss, operation time, conversion to laparotomy, intraoperative complication ( P>0.05). Three patients in the mesenteric fissure non-closure group were converted to laparotomy. One patient in the mesenteric fissure closure group was converted to laparotomy, and 2 cases with intraoperative complication were mesenteric hematoma. (3) Postoperative conditions. There was no significant difference between the mesenteric fissure non-closure group and the mesenteric fissure closure group in the overall postoperative complications ( χ2=0.28, P>0.05). There was no significant difference in the occurrence of postoperative intestinal obstruction, abdominal distension, ascites, pleural effusion, gastric paralysis, anastomotic bleeding, anastomotic leakage, or surgical wound infection between the two groups ( P>0.05). There was no significant difference between the two groups in the reoperation, postoperative gastric tube replacement. There was no significant differ-ence in time to postoperative first flatus, time to postoperative initial liquid food intake, time to post-operative resumption of bowel movements, duration of postoperative hospital stay, total hospital expenses between the two groups ( Z=-0.01, 0.43, 1.04, -0.54, -0.36, P>0.05). One patient in the mesenteric fissure non-closure group received reoperation. No perioperative internal hernia or death occurred in either group. The visual analog score decreased with time in both groups. There was no significant difference in the visual analog score between the mesenteric fissure closure group and the mesenteric fissure non-closure group [ β=-0.20(-0.53,0.13), P>0.05]. Conclusion:Compared with closure of mesenteric fissure, non-closure of mesenteric fissure during laparoscopic right hemi-colectomy dose not increase perioperative complications or postoperative management risk.

Objective To investigate the effect of varying ureteral wall thickness(UWT)at the site of ureteral stones on the clinical efficacy of ureteroscopic lithotripsy(URL).Methods The clinical data of 164 patients with ureteral stones in our hospital were retrospectively analyzed.According to different UWT,the patients were divided into the mild thickening group(84 cases,UWT<3.16 mm),the moderate thickening group(31 cases,UWT 3.16 to 3.49 mm),and the severe thickening group(49 cases,UWT>3.49 mm),and the differences of clinical related indicators among the three groups were compared.Results The incidence of postoperative renal colic and leukocyte disorder in the mild thickening group and the moderate thickening group were lower than those in the severe thickening group,and the differences were statistically significant(P<0.05).The postoperative catheterization time in the mild thickening group and the moderate thickening group were shorter than that in the severe thickening group,and the incidences of secondary lithotripsy,residual stones and stone return to kidney in the mild thickening group and the moderate thickening group were lower than those in the severe thickening group,with statistically significant differences(P<0.05).The length of hospital stay and hospitalization cost in the mild thickening group and the moderate thickening group were shorter/less than those in the severe thickening group,with statistically significant differences(P<0.05).Conclusion With the increase of UWT(especially when UWT>3.49 mm),the incidence of postoperative complications and hospitalization cost of URL increase to varying degrees,and the surgical efficacy decreases.In clinical work,UWT measurement holds potential value in predicting the surgical efficacy and complications of URL.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.