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.

Objective VATER/VACTERL-like association is associated with adverse pregnancy outcomes.Genetic evidence of this disorder is sporadic.In this study,we aimed to provide genetic insights to improve the diagnosis of VACTERL. Methods We have described a Chinese family in which four members were affected by renal defects or agenesis,anal atresia,and anovaginal fistula,which is consistent with the diagnosis of a VACTERL-like association.Pedigree and genetic analyses were conducted using genome and exome sequencing. Results Segregation analysis revealed the presence of a recessive X-linked microdeletion in two living affected individuals,harboring a 196-380 kb microdeletion on Xq27.1,which was identified by familial exome sequencing.Genome sequencing was performed on the affected male,confirming a-196 kb microdeletion in Xq27.1,which included a 28%loss of the CDR-1 gene.Four family members were included in the co-segregation analysis,and only VACTERL-like cases with microdeletions were reported in X27.1. Conclusion These results suggest that the 196-380 kb microdeletion in Xq27.1 could be a possible cause of the VATER/VACTERL-like association.However,further genetic and functional analyses are required to confirm or rule out genetic background as the definitive cause of the VACTERL association.

Objective:To carry out the policy diffusion analysis of centralized and volume-based drug procurement in China in recent years,and to provide reference for the formulation of centralized and volume-based drug procurement policy.Methods:Through the official websites of the central and provincial governments,the official websites of the Health Commission and the official websites of the Medical Security Bureau,the policy documents related to centralized and volume-based drug procurement from January 1,2009 to December 31,2023 were searched.Based on the policy diffusion theory,the reference network analysis method is used to analyze the intensity,breadth and speed of policy diffusion,and the sequential analysis method of policy keywords is used to analyze the direction of policy diffusion.Results:In the two stages of the development of centralized and volume-based drug procurement policy,the number of policies issued in the medical insurance management stage reached the peak;The top ten policies with the highest diffusion intensity and breadth are all central policies,and most of them are notices and opinions.In addition,the newly promulgated policies have a faster diffusion speed.In the direction of diffusion,top-down and parallel diffusion trends are obvious.Conclusion:The diffusion of centralized and volume-based drug procurement policy in China focuses on the central policy,and the diffusion speed is increasing year by year.It is suggested to strengthen the policy coordination between the central and local governments,establish a unified national information platform for centralized drug procurement,optimize the learning and competition mechanism between governments at all levels,and give play to the advantages of"policy experiment".

Objective:To explore the clinical application of Hisense Computer-Assisted Sur-gery System(CAS)in the perioperative period of hepatectomy for liver cancer.Methods:Clinical data of patients undergoing laparoscopic hepatectomy(LH)for liver cancer from January 2021 to December 2022 were collected.Patients were divided into three groups based on surgical difficulty(low,medium,high)and further stratified into CAS-assisted subgroup and control subgroup ac-cording to whether the CAS system was used.Demographic and perioperative data were com-pared among different groups.Results:A total of 317 patients'clinical data were collected,in-cluding 31 cases in the low difficulty group,132 cases in th medium difficulty group,and 154 cases in the high difficulty group,with 108 cases(34.1％)in the CAS-assisted subgroup and 209 cases(65.9％)in the control group.In the medium difficulty group,the CAS-assisted subgroup had shorter operation time,drainage tube duration,and postoperative hospital stay compared to the control group(P＜0.001),and the AFP levels at 1 month postoperatively in the CAS-assisted sub-group were lower than those in the control group(P＜0.001).In the high difficulty group,the CAS-assisted subgroup showed shorter operation time,drainage tube duration,and postoperative hospi-tal stay,less intraoperative blood loss,and lower AFP levels 1 month post-operation compared to the control group(P＜0.001 for all).Conclusion:Preoperative CAS in medium and high difficulty laparoscopic liver resections improves perioperative outcomes.Hisense CAS effectively assists general surgeons in accurately identifying the anatomical site of liver tumors,providing precise pre-operative simulation and intraoperative navigation,thereby optimizing surgical strategies for pa-tients.

Objective:To investigate the clinical value immature granulocyte percentage(IG％)and other inflammatory indicators in the severity of acute appendicitis.Methods:A total of 201 pediatric patients undergoing appendicitis surgery admitted to Zhoukou Central Hospital from June 2022 to August 2023 were included.Patients with pathologically confirmed actue appendici-tis were divided two subgroups:actue simple appendicitis(ASA)group and actue complicated ap-pendicitis(ACA)group,The variables that included IG％,white blood cell(WBC)count,absolute neutrophil count(ANC),absolute lymphocyte count(ALC),neutrophil to lymphocyte ratio(NLR),pro-calcitonin(PCT),C-reactive protein(CRP),platelet to lymphocyte(PLR)and other indexes were ana-lyzed between ASA and ACA group.The logistic regression model for diagnosis of ACA was es-tablished,and the diagostic value of this model and other inflammtory indicators for ACA was evaluated by receiver operating characteristic(ROC)curve analysis.Results:The levels of IG％,WBC,ANC,ALC,NLR,PCT and PLR were higher and the level of ALC was lower in ACA group than those in ASA group(all P＜0.05).Logistic regression analysis showed that IG％,NLR and CRP were three diagnostic determinants of ACA(all P＜0.05).The AUC of the established logistic model and IG％,NLR,CRP were 0.868,0.821,0.691 and 0.790(all P＜0.001).The logistic model was vali-dated by independent cohorts,and the AUC was 0.872,the sensitivity was 90.0％and the speci-ficity was 75.6％.Conlusions:The IG％value can early indicator for pediatric ACA,and the es-tablished logistic regression model based on biomarkers including IG％,NLR and CRP has clinical value in diagnosing ACA in children.

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.

Aim To explore the effects of sirolimus on the growth and development of motor,vascular,nerv-ous,and immune systems through zebrafish models.Methods After 3 hours of fertilization of zebrafish embryos,different concentrations of sirolimus were add-ed to the growth environment,and the growth and de-velopment of the embryos was recorded.Transgenic ze-brafish models labeled with blood vessels,nerves or im-mune cells were used to compare the drug effects on the growth and development of those systems.Results At the concentration of 0.5 μmol·L-1,the hatching rate and the body length(P＜0.01)were significantly smaller than those of the control group,and movement was also significantly slowed down.Meanwhile,the length of axons of the nervous system,the development of intersegmental vessels,and the growth of immune cells were significantly delayed by drug treatment.But when the concentration was below 0.1 μmol·L-1,there was no statistically difference between the control group and the sirolimus group.Conclusions When the concentration of sirolimus exceeds a certain level,it can significantly slow down the growth and development of movement,blood vessels,nervous system and im-mune system of zebrafish.Therefore,in clinical prac-tice,it is important to monitor the blood concentration of sirolimus in children on time.

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.

Although indigenous malaria has been eliminated in Wuhan since 2013,imported malaria remains a potential threat as an infectious source of local malaria transmission.The epidemiological and clinical characteristics of imported malaria are particularly important in areas where local malaria has been eliminated.This study was aimed at analyzing the epidemiological and clinical characteristics of imported malaria in Wuhan from 2012 to 2019,to provide a basis for further improving the preven-tion and control of imported malaria.Patients in Wuhan diagnosed with imported malaria from January 1,2012,to December 31,2019,were included in this study.A case-control study was con-ducted to analyze the features of patients with severe malaria.Uni-variate and multivariate logistic regression was used to identify risk factors for prolonged hospital length of stay(LOS).Among 229 imported malaria cases,212(92.6％)were in Chinese citizens,and most cases were in men(96.5％).The gender ratio is 28:1,and the age of cases is mainly concertrated between 18 and 50 years old(89.1％).More than 80％of patients were mi-grant workers,and most cases were infections from African countries(92.6％).Plasmodium falciparum(80.8％)was the dominant species.Fifty-three severe malaria cases were identified during the study period.Compared with uncomplicated cases,severe cases tended to occur in patients with no history of malaria(P=0.008),patients infected with Plasmodium falciparum(P=0.009),and patients who were initially misdiagnosed(P＜0.001).The median LOS was 6 days,and the species of infec-tion(Plasmodium falciparum),the use of antimalarial drugs(group B),antipyretic time(longer than 3 days),and the turn-around time of blood smear microscopy(longer than 3 days)were significantly associated with longer LOS(all P＜0.05).Al-though malaria has been eradicated in Wuhan for many years,imported cases continue to pose a threat.Efforts should be made to strengthen malaria knowledge education for outbound personnel.Additionally,medical institutions must enhance diagnosis and treatment capabilities for malaria,and adhere to standardized treatment processes,and the development of drug resistance and occurrence of severe malaria must be prevented.