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.

Circadian rhythm is an endogenous biological clock mechanism that enables organisms to adapt to the earth’s alternation of day and night. It plays a fundamental role in regulating physiological functions and behavioral patterns, such as sleep, feeding, hormone levels and body temperature. By aligning these processes with environmental changes, circadian rhythm plays a pivotal role in maintaining homeostasis and promoting optimal health. However, modern lifestyles, characterized by irregular work schedules and pervasive exposure to artificial light, have disrupted these rhythms for many individuals. Such disruptions have been linked to a variety of health problems, including sleep disorders, metabolic syndromes, cardiovascular diseases, and immune dysfunction, underscoring the critical role of circadian rhythm in human health. Among the numerous systems influenced by circadian rhythm, the skin—a multifunctional organ and the largest by surface area—is particularly noteworthy. As the body’s first line of defense against environmental insults such as UV radiation, pollutants, and pathogens, the skin is highly affected by changes in circadian rhythm. Circadian rhythm regulates multiple skin-related processes, including cyclic changes in cell proliferation, differentiation, and apoptosis, as well as DNA repair mechanisms and antioxidant defenses. For instance, studies have shown that keratinocyte proliferation peaks during the night, coinciding with reduced environmental stress, while DNA repair mechanisms are most active during the day to counteract UV-induced damage. This temporal coordination highlights the critical role of circadian rhythms in preserving skin integrity and function. Beyond maintaining homeostasis, circadian rhythm is also pivotal in the skin’s repair and regeneration processes following injury. Skin regeneration is a complex, multi-stage process involving hemostasis, inflammation, proliferation, and remodeling, all of which are influenced by circadian regulation. Key cellular activities, such as fibroblast migration, keratinocyte activation, and extracellular matrix remodeling, are modulated by the circadian clock, ensuring that repair processes occur with optimal efficiency. Additionally, circadian rhythm regulates the secretion of cytokines and growth factors, which are critical for coordinating cellular communication and orchestrating tissue regeneration. Disruptions to these rhythms can impair the repair process, leading to delayed wound healing, increased scarring, or chronic inflammatory conditions. The aim of this review is to synthesize recent information on the interactions between circadian rhythms and skin physiology, with a particular focus on skin tissue repair and regeneration. Molecular mechanisms of circadian regulation in skin cells, including the role of core clock genes such as Clock, Bmal1, Per and Cry. These genes control the expression of downstream effectors involved in cell cycle regulation, DNA repair, oxidative stress response and inflammatory pathways. By understanding how these mechanisms operate in healthy and diseased states, we can discover new insights into the temporal dynamics of skin regeneration. In addition, by exploring the therapeutic potential of circadian biology in enhancing skin repair and regeneration, strategies such as topical medications that can be applied in a time-limited manner, phototherapy that is synchronized with circadian rhythms, and pharmacological modulation of clock genes are expected to optimize clinical outcomes. Interventions based on the skin’s natural rhythms can provide a personalized and efficient approach to promote skin regeneration and recovery. This review not only introduces the important role of circadian rhythms in skin biology, but also provides a new idea for future innovative therapies and regenerative medicine based on circadian rhythms.

Green prescription is a written prescription aimed at improving health by promoting physical activity and improving diet， with advantages such as high cost-effectiveness， strong feasibility， and minimal harm to patients. The theory of traditional Chinese medicine （TCM） green prescription integrates the health philosophy of "following rule of yin and yang， and adjusting ways to cultivating health"， the exercise philosophy of balancing yin-yang and the five elements， and the dietary philosophy of moderation and balance， which embody core TCM concepts such as treating disease before its onset and harmony between humans and nature. It has also developed traditional exercise practices like Tai Chi， Baduanjin， Wuqinxi， Yi-Gin-Ching， and Qigong， as well as dietary adjustments like medicated diet and herbal wines. However， it is believed that the TCM green prescription currently suffers from insufficient evidence-based research， low patient awareness and acceptance， and weak basic research. Based on this， it is proposed that large-sample clinical trials should be conducted in the future to improve the quality of evidence-based medicine， basic research can be carried out with the help of artificial intelligence and other methods in research design， the hospital information system （HIS） can be used for control at the implementation level， and publicity and patient education can be strengthened through the new media， so as to promote the development and application of the TCM green prescriptions in the field of global health treatment.

Objective To investigate the efficacy of leaflet augmentation technique to repair the recurrent mitral valve (MV) regurgitation after mitral repair in children. Methods A retrospective analysis was conducted on the clinical data of children who underwent redo MV repair for recurrent regurgitation after initial MV repair, using a leaflet augmentation technique combined with a standardized repair strategy at Fuwai Hospital, Chinese Academy of Medical Sciences, from 2018 to 2022. The pathological features of the MV, key intraoperative procedures, and short- to mid-term follow-up outcomes were analyzed. Results A total of 24 patients (12 male, 12 female) were included, with a median age of 37.6 (range, 16.5–120.0) months. The mean interval from the initial surgery was (24.9±17.0) months. All children had severe mitral regurgitation preoperatively. The cardiopulmonary bypass time was (150.1±49.5) min, and the aortic cross-clamp time was (94.0±24.2) min. There were no early postoperative deaths. During a mean follow-up of (20.3±9.1) months, 3 (12.5%) patients developed moderate or severe mitral regurgitation (2 severe, 1 moderate). One (4.2%) patient died during follow-up, and one (4.2%) patient underwent a second MV reoperation. The left ventricular end-diastolic diameter was significantly reduced postoperatively compared to preoperatively [ (43.5±8.6) mm vs. (35.8±7.8)mm, P<0.001]. Conclusion The leaflet augmentation technique combined with a standardized repair strategy can achieve satisfactory short- to mid-term outcomes for the redo mitral repair after previous MV repair. It can be considered a safe and feasible technical option for cases with complex valvular lesions and severe pathological changes.

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 impact of intergenerational parent-child separation (PCS) on allergic diseases among rural preschool children, providing theoretical guidance for developing targeted public health interventions. Methods: From March to June 2024, 10 kindergartens were selected from Nanling, Wuhu City, Anhui Province. A total of 2 279 children aged 3-6 years and their parents/primary caregivers participated in the survey by a combination of convenience sampling and cluster sampling method. Children s fathers and mothers reported the experiences of PCS during their childhood. The children s PCS experiences and allergies were reported by their primary caregivers. The International Study of Asthma and Allergies in Childhood (ISAAC) questionnaire was used to supplement the allergies (allergic asthma, allergic rhinitis and atopic dermatitis). Analysis of variance (ANOVA) and Chi square tests were used to compare differences between children in different PCS groups. Logistic regression models assessed the association between PCS and the risk of allergic diseases in preschool children. Results: Among the preschoolers enrolled, the prevalence of allergic diseases in only parent-child separation group in childhood, only child separation group, and the intergenerational continuity of PCS groups were significantly higher than those of the none separation group (38.0%, 41.8%, 48.1%,30.4%; χ 2=40.45, P < 0.01 ). After adjusting for covariates including child age, sex and body mass index, Logistic regression model revealed that compared to children in the group without PCS, those in the only parent-child separation in childhood( OR =1.43, 95% CI =1.06-1.94), only child separation ( OR =1.82, 95% CI =1.22-2.71), and intergenerational continuity of PCS ( OR =2.33, 95% CI =1.68-3.24) exhibited higher allergic disease risk (all P <0.05). Conclusions Intergenerational continuity of PCS is related to the increased risk of allergies in preschool children. The multigenerational accumulation of adverse effects from PCS underscores the importance of breaking the cycle of disadvantage across generations.

Objective To investigate the significance of intratumoral and peritumoral radiomics models in predicting occult lymph node metastasis in stage T1 non-small cell lung cancer(NSCLC)and to compare the predictive accuracy in different peritumoral radiomics models.Methods The CT images and clinical data of 211 patients without lymph node metastasis on preoperative CT examination and pathologically confirmed NSCLC after surgery were collected.The radiomics features were derived from the three-dimensional volume of interest(VOI)of the intratumoral and peritumoral at 3-,5-,and 10-mm following lesion segmentation on CT images of each patient.The feature data of all nidus were radomly divide into training set and validation set with a ratio of 7︰3.The Pearson or Spearman correlation test was performed to remove redundancy.Dimensionality was reduced by the least absolute shrinkage and selection operator(LASSO)regression analysis.The linear combination of selected features and corresponding coefficients were used to construct the Radiomics score(Radscore).The clinical model and comprehensive model were constructed by logistic regression analysis.The conprehensive model was visualized with the nomogram,and its performance was evaluated.Results Among the peritumoral radiomics models,the peritumoral 5-mm model showed the best predictive efficacy[validation set,area under the curve(AUC)0.771].The comprehensive model containing Radscore,CT image features and CEA exhibited the best performance(validation set,AUC 0.850).Conclusion Intratumoral and peritumoral radiomics models perform efficiently in predicting occult lymph node metastasis in stage T1 NSCLC,and nomogram can effectively and noninvasively predict occult lymph node metastasis in NSCLC.

BACKGROUND:Artificial intelligence planning system can automatically establish a three-dimensional model and generate planning schemes,but its accuracy in predicting the prosthesis size has not been fully verified. OBJECTIVE:To investigate the accuracy of artificial intelligence planning system in predicting prosthesis size before total hip arthroplasty and its influence on clinical prognosis,and further analyze the risk factors affecting the accuracy of planning. METHODS:Clinical data of patients with unilateral initial total hip arthroplasty who were admitted to the Department of Orthopedics of Affiliated Hospital of Xuzhou Medical University from January 2021 to June 2022 were prospectively collected.The patients were randomly divided into the artificial intelligence planning system group(n=80)and the conventional template group(n=79).Intraoperative use of prostheses and preoperative planning of prosthesis matching were compared between the two groups.Postoperative follow-up Harris scores and the occurrence of complications such as leg length discrepancy,dislocation and prosthesis loosening were recorded in both groups.The effects of demographic indicators,preoperative diagnosis,and Dorr typing on the accuracy of femoral stem planning were explored using univariate and multivariate Logistic regression analyses. RESULTS AND CONCLUSION:(1)The prediction of the prosthesis size on the acetabular side and femoral side was 50%(40/80)and 55%(44/80)in the artificial intelligence planning system group,compared to 34%(27/79)and 37%(29/79)in the conventional template group,with statistically significant differences(P＜0.05).(2)The artificial intelligence planning system group had an accuracy rate within one size difference for the acetabular and femoral side prostheses of 91%(73/80)and 86%(69/80),compared to 82%(65/79)and 72%(58/79)in the conventional template group,with differences statistically different only on the femoral side(P＜0.05).(3)No dislocation or prosthesis loosening occurred in the two groups during postoperative follow-up.The difference in lower limb length between the artificial intelligence planning system and conventional template groups was(3.56±2.32)mm and(3.52±2.41)mm.At the last follow-up,the Harris scores of the artificial intelligence planning system and conventional template groups were(92.74±3.08)and(91.81±3.52),respectively;there was no significant difference in the above differences(P＞0.05).(4)Univariate analysis results showed that preoperative diagnosis as developmental dysplasia of the hip and osteonecrosis of the femoral head,and Dorr type B and C femurs had a significant effect on the accuracy of predicted prosthesis size using an artificial intelligence planning system(P＜0.05).(5)Multivariate logistic regression analysis showed that preoperative diagnosis of developmental dysplasia of the hip(OR=18.233,95%CI:2.662-124.888)was an independent risk factor for the prediction of femoral stem size by artificial intelligence planning system.(6)The artificial intelligence planning system has a higher accuracy in predicting prosthetic size than traditional two-dimensional templates,and there is not a significant difference in the risk of postoperative complications or joint function.The accuracy of the artificial intelligence planning system in patients with developmental dysplasia of the hip was low due to anatomical deformities and acetabular anatomical position reconstruction.

Objective To analyze the problems of review of anti-tumor drug prescriptions and medical orders assisted by an information system to improve the review rules,and to provide a reference for improving review quality of anti-tumor drug prescription.Methods The problem with the pre-review of anti-tumor drug prescriptions and medical orders assisted by the information system in Sichuan Cancer Hospital during 2020-2022 were collected.The data came from the MEDICOM PASS system in Sichuan Cancer hospital.Clinical pharmacists made comments on relevant problems and analyzed the results.Results A total of 9 325 antitumor drug pre-approval problems,including 6 279 outpatient prescriptions(67.3%)and 3 046 inpatient orders(32.7%),among which 6 153(66.0%)were unsuitable indications,1 933(20.7%)were drug contraindications,449(4.8%)were problematic routes of administration,345(3.7%)were unsuitable drug compatibility,177(1.9%)were inappropriate drug frequency,133(1.4%)were problematic drug populations,74(0.8%)were unsuitable single doses,39(0.4%)were unacceptable drug interactions,22(0.2%)were unsuitable drug total.The results of clinical pharmacists'comments were 4 459 reasonable cases,with a false positive rate of 47.8%.The false positive problems included 2 264(50.8%)cases of unsuitable indications,1 933(43.3%)cases of drug contraindications,231(5.2%)cases of problematic routes of administration,and 31(0.7%)cases of unsuitable populations.Conclusion The review of anti-tumor drug prescriptions assisted by an information system can effectively intercept irrational drug use and improve the review quality of prescriptions and medical orders.However,the evidence-based medicine date of antitumor drugs is updated quickly.Pharmacists should constantly improve the prescription review rules based on the latest evidence-based medicine data.

Objective To observe the feasibility of cardiac MR tissue tracking(CMR-TT)technique for quantitatively evaluating myocardial strain of patients with myocardial amyloidosis(CA).Methods Cardiac MRI were collected from 20 patients of immunoglobulin amyloid light-chain CA(AL-CA,group A),20 cases of transthyretin CA(ATTR-CA,group B)and 20 healthy subjects(group C),and myocardial strain parameters were obtained using CMR-TT technique.Left ventricular cardiac function parameters were compared among 3 groups,so were strain parameters of each myocardial segment of left ventricle and global myocardium,including 3D longitudinal strain(LS),3D radial strain(RS)and 3D circumferential strain(CS).Results Compared with those in group C,significant differences of left ventricular cardiac function parameters were found in both group A and B(all P＜0.01),while no statistical difference was found between group A and B(all P＞0.05).Except for apical segment RS(P=0.81),strain parameters in group A and B were both lower than those in group C(all P＜0.01),while no significant difference was detected between group A and B(all P＞0.05).Conclusion CMR-TT technique could be used to quantitatively evaluate left ventricular myocardial strain of CA patients.