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.

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.

Objective To evaluate the patient-reported outcome(PRO)of patients with breast cancer who underwent autologous breast reconstruction and implant breast reconstruction.Methods Patients who underwent breast reconstruction in Shanghai Cancer Center,Fudan University from Jan 2020 to Jun 2021 were selected,including 111 patients who underwent autologous breast reconstruction and 108 patients who underwent implant breast reconstruction.Chinese version Breast-Q2.0 scale,breast cancer specificity scale QLQ-BR23 and EORTC quality of life scale QLQ-C30 were used to investigate the PRO of the two groups 18 months after operation.Results The rate of stage Ⅲ breast cancer in the self-weight construction group was higher than that in the implant reconstruction group(64.9%vs.44.4%,P<0.001).The preoperative neoadjuvant therapy and postoperative radiotherapy in the autologous reconstruction group were higher than those in the implant reconstruction group(P<0.001).Postoperative chemotherapy and endocrine therapy in the autologous reconstruction group were lower than those in the implant reconstruction group(P<0.001).The study based on Breast-Q scale showed that the breast satisfaction of autologous reconstruction group was higher than that of implant reconstruction(59.28±17.20 vs.54.94±14.48,P<0.05).The study based on QLQ-BR23 showed that the self-weight construction group was higher than the implant reconstruction group in the field of arm symptoms(20.02±20.80 vs.12.65±16.18,P<0.05).The study based on QLQ-C30 scale showed that there was no significant difference in all functional areas and symptom areas of patients.There was no significant difference in the number and time of social regression between the two groups.Conclusion Breast reconstruction can improve the PRO of breast cancer patients,and oncology factors will affect the choice of breast reconstruction.Patients with autologous breast reconstruction are more satisfied with breast appearance,but upper limb symptoms such as swelling and pain are more obvious than implant reconstruction,which is related to the higher proportion of axillary lymph node dissection in patients with autologous reconstruction.There is no significant difference in quality of life and social regression between the two groups.

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.

Objectives:To evaluate the valvular and cardiac function,cardiac reverse remodeling at 6-month after transcatheter edge-to-edge repair(TEER)for patients with functional and degenerative mitral valve regurgitation,and summarize the experience of echocardiography application. Methods:The clinical data of 93 patients with moderate to severe mitral regurgitation(MR)treated with TEER and completed 6-month follow-up in Yunnan Fuwai Cardiovascular Hospital from July 2022 to February 2023 were retrospectively analyzed.Patients were divided into functional mitral regurgitation(FMR)and degenerative mitral regurgitation(DMR)groups according to MR etiology.The valve characteristic parameters,as well as valvular function,chamber volume and cardiac functional parameters before and at 6 months after operation were compared.The key points of echocardiography application were summarized. Results:Among all patients,71 were FMR and 22 were DMR.There were differences in valve structure between the two groups.Mitral TEER were successfully accomplished and all patients completed 6-month follow-up.The key points of echocardiography application included:valve structure analysis,atrial septal puncture location,device delivery process monitoring and image optimization during clamping process.The mitral regurgitation grade and NYHA grade were significantly improved in all patients at 6 months after TEER(P<0.05),and the mean mitral valve pressure gradient was higher than that before operation(P<0.05).Left ventricular end-diastolic volume(LVEDV),left ventricular end-systolic volume(LVESV)and left atrial volume index in FMR group were significantly decreased(P<0.05),while left ventricular and left atrial volume in DMR group remained unchanged(P>0.05).There were no significant changes in left ventricular ejection fraction and left ventricular global strain in both groups during the observation period(P>0.05).The changes of LVEDV and LVESV before and after operation were more significant in FMR group than those in DMR group(P<0.05). Conclusions:Mitral TEER can reduce the degree of regurgitation and improve cardiac function in the early postoperative period for moderate and severe MR patients with different etiologies.There are differences in preoperative valve structure and postoperative cardiac reverse remodeling between FMR and DMR patients.Echocardiography is an important imaging technique for the evaluation and monitoring process before,during and post mitral TEER.

Band 3 protein is an important channel protein in the erythrocyte membrane which mediates the anion transport process inside and outside the cell membrane,as well as contributes to the maintenance of erythrocyte morphology,and has important physiological functions.However,the distribution state of this protein in the primary cell membrane is not known.Cryo-scanning electron microscopy enables imaging of the surface morphology of biological samples in a near-physiological state.In order to investigate the distribution of band 3 protein on erythrocyte membranes under physiological conditions,the present study utilized 5-nm gold nanoparticles modified with the antibodies to specifically bind to the band 3 protein on human blood erythrocyte membranes and imaged them by cryo-scanning electron microscopy,to obtain distribution of band 3 protein on human blood erythrocyte membranes.The results showed that the membrane proteins on the erythrocyte membranes tended to be clustered and distributed to form ″protein islands″,and band 3 proteins were mainly distributed in these protein islands,which were tightly connected with each other to form several functional microregions to play their respective roles.

Objective To investigate the satisfaction of patients with Crowe Ⅲ-Ⅳ developmental dysplasia of the hip(DDH)after total hip arthroplasty and the related factors.Methods A retrospective study included 169 patients with Crowe type Ⅲ-Ⅳ DDH who underwent total hip arthroplasty between March 2013 and March 2018.Patients were surveyed through WeChat,covering overall satisfaction with the operation,satisfaction with ten daily functions,and the top five questions per-ceived to have a great impact on daily life.Preoperative and postoperative hip function was evaluated by Harris score.Results One hundred and forty-five questionnaires were received,with a follow-up period ranging from 1 to 5 years with an average of(3.23±1.22)years.Among these patients,118 patients were satisfied with the surgical outcomes,while 27 patients were dissat-isfied,with the overall satisfaction rate of 81.38％(118/145).The top five problems affecting patient life were postoperative hip pain,limb length discrepancy,walking,stair climbing,and squatting.There were no statistical differences in age,sex,body mass index,preoperative Harris scores(P＞0.05).However,the dissatisfied group had lower postoperative Harris scores.Post-operative hip pain and limb length discrepancy were identified as direct factors contributing to postoperative surgical dissatis-faction.Conclusion Total hip arthroplasty for patients with Crowe type Ⅲ-Ⅳ DDH is challenging.Postoperative hip pain(mild or severe)and limb length discrepancy(＞2 cm)are independent risk factors for postoperative dissatisfaction.

The relationship between exercise and cardiac health has always been a hotspot in the fields of medicine and exercise science. Recently, with the in-depth study of the biological clock, people have gradually realized the close relationship between cardiac metabolic activity and circadian rhythms. The mammalian circadian system includes the central circadian clock and peripheral circadian clocks, the central circadian clock is the main clock system responsible for regulating the circadian rhythms in organisms, located in the suprachiasmatic nucleus (SCN) of the hypothalamus in mammals, which receives light signals from the retina and translates them into neural signals to regulate peripheral circadian clocks distributed throughout the body. Peripheral circadian clocks exist in various tissues and organs of organisms, coordinating with the central circadian clock to maintain the circadian rhythms of the organism. A series of clock genes regulate downstream clock-controlled genes through the transcriptional-translational feedback loop (TTFL), profoundly affecting the physiological activities of the heart, including cardiac contraction, relaxation, and metabolic processes. Factors such as sleep disorders, shift work, light pollution, and excessive use of electronic devices in modern lifestyles have led to widespread disruption of circadian rhythms, which are significantly correlated with increased cardiovascular disease incidence and mortality. Studies have found that dysregulation of the cardiac circadian clock can not only lead to myocardial lipid degeneration and weakened metabolic rhythms but also decrease myocardial glucose utilization, thereby increasing the risk of adverse cardiac events. Exercise, as a key zeitgeber, has been widely demonstrated to regulate the circadian clocks of peripheral organs such as skeletal muscle, kidneys, and liver. Additionally, exercise, as an important means to improve cardiovascular function, can effectively enhance cardiac metabolic function and resistance to stress stimuli, playing a significant role in promoting heart health. However, the specific mechanisms by which exercise affects the cardiac circadian clock and its related genes are currently unclear. Therefore, this review will focus on the relationship between the cardiac circadian clock and cardiac metabolic activity, summarize previous research to review the possible mechanisms of exercise-mediated regulation of cardiac metabolic activity on the cardiac circadian clock. The cardiac circadian clock plays an important role in maintaining cardiac metabolic activity and physiological functions. The loss of cardiac circadian clock genes Bmal1 and Clock can significantly reduce cardiac fatty acid and glucose utilization rates, increase myocardial lipotoxicity, weaken the circadian rhythm of myocardial triglyceride metabolism, and lead to abnormalities in the circadian clocks of other peripheral organs. Exercise, as a zeitgeber, can independently regulate the cardiac circadian clock apart from the central circadian clock. Additionally, exercise, as an important means to improve cardiovascular function, may regulate cardiac metabolic activity and the transcription of clock genes by activating the hypothalamic-pituitary-adrenal axis (HPA) and sympathetic-adrenal-medullary axis (SAM) and regulating energy metabolism, thereby maintaining the stability of the cardiac circadian clock and promoting heart health. Future research on the molecular mechanisms of exercise regulation of the cardiac circadian clock will help clarify the role and impact of clock genes in cardiac metabolism and physiological activities, providing new preventive and treatment strategies for shift workers, night owls, and patients with cardiovascular diseases. Therefore, future research should focus on (1) the mechanisms by which exercise regulates cardiac metabolic activity and the circadian clock, (2) the effects and mechanisms of exercise on the disruption of cardiac circadian clock induced by light-dark cycle disturbances, and (3) the effects of exercise on the metabolic activity and circadian rhythms of other peripheral organs regulated by the cardiac circadian clock.

As a rapidly developing frontier discipline, structural biology has penetrated into every field of life science research. The course of “Structural Biology” plays an important role in expanding the knowledge system of undergraduate students and promoting students’ scientific spirit and innovation. For the high-quality training of highly skilled talents, we aimed to promote the original innovation of students, the ability of thinking, and the ability of engineering practice. The trinity education concept, including shape of the value, passing on knowledge, and ability cultivation, was applied. During the reform, we explored a step-by-step course content and searched for factors involved in ideological and political education. Based on the problem-based learning (PBL) method, a hybrid teaching model was designed to cultivate the problem-thinking and problem-solving skills of students. Meanwhile, a number of evaluation systems for students and teachers were established, which may be generally adopted for the course of “Structural Biology”. The survey data suggested that the exploration has a good effect on teaching and training and is conducive to the cultivation of research-oriented, comprehensive, innovative talents under the background of “New Engineering”.

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.