AIM: To investigate the influencing factors of stereoscopic function reconstruction after intermittent exotropia(IXT)surgery and the construction of a nomogram prediction model.METHODS:A total of 204 patients with IXT(all underwent strabismus correction surgery)admitted to our hospital from September 2021 to October 2023 were randomly divided into modeling group(143 cases)and validation group(61 cases). The patients in the modeling group were further divided into reconstructive group and non-reconstructive group according to whether they had stereoscopic function reconstruction after surgery; the general patient information was collected; Multivariate Logistic regression analysis was performed on the influencing factors of stereoscopic visual function reconstruction after IXT surgery. The nomogram model was constructed using R software. The ROC curve was drawn to evaluate the distinction of the nomogram model. The decision curve analysis(DCA)was used to evaluate the clinical application value of the model.RESULTS:Reconstruction occurred in 50.5%(103 cases)of the 204 patients, and reconstruction occurred in 50.3%(72 cases)of the 143 patients in the modeling group. There were differences in age of onset, course of disease and postoperative horizontal strabismus between the reconstructive group and the non-reconstructive group(all P<0.05). Multivariate Logistic regression analysis showed that age of onset and postoperative horizontal strabismus were risk factors for stereoscopic visual function reconstruction after IXT surgery(all P<0.05), and the course of disease was a protective factor(P<0.05). The AUC of the modeling group was 0.892, and the H-L test was χ2=6.654 and P=0.615. The AUC of the validation group was 0.935, and the H-L test was χ2=6.498 and P=0.642. The DCA curve showed that the clinical value of the nomogram model was higher when the probability was 0.09-0.95.CONCLUSION: The age of onset, course of disease and postoperative amount of horizontal strabismus are the influencing factors of stereoscopic visual function reconstruction after IXT surgery, and the nomogram model constructed by this can better predict postoperative stereoscopic function reconstruction.

Organ transplantation is an effective alternative treatment for patients with end-stage organ failure. However, the shortage of donor organs has limited the widespread application of clinical transplantation. In recent years, breakthroughs in CRISPR-Cas9 gene editing technology have overcome the barrier of hyperacute rejection in xenotransplantation, offering a potential solution to the organ shortage crisis. Rejection remains a critical factor affecting graft survival. Antigen-presenting cells play a vital role in the initiation and progression of rejection and immune regulation in xenotransplantation. Therefore, in-depth investigation into the role of antigen-presenting cells in xenotransplantation is of great significance. This article summarizes the roles and therapeutic strategies of professional antigen-presenting cells, including macrophages, dendritic cells and B cells in xenotransplantation, aiming to provide insights for future research on immune regulation mechanisms in this field.

OBJECTIVE To investigate the effects of quercetin （QUE） on intervertebral disc degeneration in rats with lumbar intervertebral disc herniation （LDH） and explore its mechanism based on the forkhead box protein O3/silent information regulator 1 （FOXO3/Sirt1） pathway. METHODS A rat model of LDH was established. The successfully modeled rats were randomly divided into LDH group （gavaged with and intraperitoneally injected with an equal volume of normal saline）， QUE-L group （gavaged with 50 mg/kg QUE+intraperitoneally injected with an equal volume of normal saline）， QUE-H group （gavaged with 100 mg/kg QUE+ intraperitoneally injected with an equal volume of normal saline）， and QUE-H+EX-527 （a Sirt1 inhibitor） group （gavaged with 100 mg/kg QUE+intraperitoneally injected with 1 mg/kg EX-527）， with 12 rats in each group. Additionally， 12 healthy normal rats were selected as the control group （gavaged with and intraperitoneally injected with an equal volume of normal saline）. All rats were administered the corresponding agents once daily for consecutive 8 weeks. After the final administration， the pain threshold and serum levels of inflammatory factors in rats were measured； pathological damage of lumbar intervertebral disc tissue was observed， the apoptosis of nucleus pulposus cells in lumbar intervertebral disc tissue was assessed， and the expression levels of matrix metalloproteinase-3 （MMP-3）， phospholipase A2 （PLA2）， as well as apoptosis-related proteins and FOXO3/Sirt1 pathway- related proteins in intervertebral disc tissue were determined. RESULTS Compared with LDH group， pathological damage of intervertebral disc tissue were improved significantly in QUE-L group and QUE-H group； paw withdrawal mechanical threshold， paw withdrawal thermal latency， the serum levels of transforming growth factor-β1 and interleukin-10 （IL-10） as well as the expression levels of B-cell lymphoma-2 （Bcl-2）， FOXO3 and Sirt1 were significantly increased or prolonged （P＜0.05）. Serum levels of tumor necrosis factor-α and IL-1β， histopathological score of intervertebral disc tissue， apoptotic rate of nucleus pulposus cells， positive expressions of MMP-3 and PLA2 in intervertebral disc tissue and expression levels of Bcl-2 associated X protein were significantly decreased （P＜0.05）. Compared with the QUE-H group， the QUE-H+EX-527 group presented aggravated pathological damage of intervertebral disc tissue， and the trends of all the above indicators were significantly reversed（P＜0.05）. CONCLUSIONS QUE can ameliorate intervertebral disc degeneration in LDH rats， and its mechanism may be related to the activation of the FOXO3/Sirt1 pathway.

Objective: To investigate the current status of benefit finding among young and middle-aged patients with type 2 diabetes mellitus (T2DM) and analyze its influencing factors, so as to provide a reference for improving the level of benefit finding in this population. Methods: From November 2022 to May 2023, young and middle-aged patients with T2DM aged 18-59 years hospitalized in the endocrinology departments of 2 tertiary hospitals in Hengyang City, Hunan Province were selected as survey subjects by a convenience sampling method. Basic demographic information was collected using a general questionnaire survey. Benefit finding, resourcefulness, and stigma were evaluated using the Benefit Finding Scale, the Chinese Version of the Resourcefulness Scale, and the Type 2 Diabetes Stigma Assessment Scale, respectively. A multiple linear regression model was used to analyze the influencing factors of benefit finding among young and middle-aged patients with T2DM. Results: A total of 305 young and middle-aged patients with T2DM were investigated, including 222 males (72.79%) and 83 females (27.21%). There were 231 cases aged 45-59 years, accounting for 75.74%. The scores for benefit finding, resourcefulness, and stigma were (42.86±6.06), (75.12±11.30), and (41.20±10.10), respectively. Multiple linear regression analysis showed that young and middle-aged patients with T2DM who were male (β′=0.088), aged 18-<45 years (β′=0.083), absence of diabetes complications (β′=0.124), and had higher resourcefulness scores (β′=0.679) had higher levels of benefit finding, while patients with higher stigma scores (β′=-0.097) had lower levels of benefit finding. Conclusion The level of benefit finding among young and middle-aged patients with T2DM was moderate, and was related to gender, age, diabetes complications, resourcefulness, and stigma.

Chronic heart failure （CHF） is a complex clinical syndrome caused by ventricular dysfunction， with mitochondrial energy metabolism disorder being a critical factor in disease progression. Heart-Yang deficiency syndrome， as the core pathogenesis of CHF， persists throughout the disease course. Insufficiency of heart-Yang leads to weakened warming and propelling functions， resulting in the accumulation of phlegm-fluid， blood stasis， and dampness. This eventually causes Qi stagnation with phlegm obstruction and blood stasis with water retention， forming a vicious cycle that exacerbates disease progression. According to the theory of reinforcing Yang， the clinical experience of the traditional Chinese medicine （TCM） master Tang Zuxuan in treating CHF with heart-Yang deficiency syndrome， and achievements from molecular biological studies， this study innovatively proposes an integrated research framework of "TCM syndrome differentiation and staging-mitochondrial metabolism mechanisms-intervention with Yang-reinforcing prescriptions" which is characterized by the integration of traditional Chinese and Western medicine. Heart-Yang deficiency syndrome is classified into mild （Stage Ⅰ-Ⅱ）， severe （Stage Ⅲ）， and critical （Stage Ⅳ） stages. The study elucidates the precise correlations between the pathogenesis of each stage and mitochondrial metabolism disorders from theoretical， pathophysiological， and therapeutic perspectives. The mild stage is characterized by impaired biogenesis and substrate-utilization imbalance， corresponding to heart-Yang deficiency and phlegm-fluid aggregation. Linggui Zhugantang and similar prescriptions can significantly improve the expression of peroxisome proliferator-activated receptor gamma co-activator-1α（PGC-1α）/silent information regulator 2 homolog 1 （SIRT1） and ATPase activity. The severe stage centers on oxidative stress and structural damage， reflecting Yang deficiency with water overflow and phlegm-blood stasis intermingling. At this stage， Zhenwu Tang and Qiangxin Tang can effectively mitigate oxidative stress damage， increase adenosine triphosphate （ATP） content， and repair mitochondrial structure. The critical stage arises from calcium overload and mitochondrial disintegration， leading to the collapse of Yin-Yang equilibrium. At this stage， Yang-restoring and crisis-resolving prescriptions such as Fuling Sini Tang and Qili Qiangxin capsules can inhibit abnormal opening of the mitochondrial permeability transition pore （MPTP）， reduce cardiomyocyte apoptosis rate， and protect mitochondrial function. By summarizing the characteristics of mitochondrial energy metabolism disorders at different stages of CHF， this study explores the application of the theory of reinforcing Yang in treating heart-Yang deficiency syndrome and provides new insights for the clinical diagnosis and treatment of CHF.

To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

BackgroundPatients with depressive disorder often exhibit impaired decision-making functions. However， the relationship between decision-making abilities and depressive and anxiety symptoms in these patients remains unclear. ObjectiveTo explore the characteristics of decision-making behavior in patients with depressive disorder， and to analyze its relationship with clinical symptoms. MethodsA total of 48 patients diagnosed with depressive disorder according to the Diagnostic and Statistical Manual of Mental Disorders， fourth edition （DSM-IV） were recruited from the Department of Psychosomatic Medicine of the Affiliated Hospital of Southwest Medical University from October 2020 to May 2023. Concurrently， 52 healthy individuals matched for age and gender were recruited from Luzhou as the control group. Beck Depression Inventory （BDI） and Beck Anxiety Inventory （BAI） were used for assessment， and decision-making behavior was evaluated using Probabilistic Reversal Learning （PRL） task. Indicators assessed included the number of trials to criterion， perseverative errors， win-stay rate and lose-shift rate. Spearman correlation analysis was used to assess the correlation between BDI and BAI scores and PRL task indicators. ResultsThe depression group showed a significantly higher lose-shift rate compared with the control group （t=3.684， P<0.01）. There were no statistically significant differences between two groups in trials to criterion， perseverative errors and win-stay rate （t=0.329， 0.132， 0.609， P>0.05）. In depression group， BDI and BAI scores were positively correlated with the win-stay rate（r=0.450， 0.398， P<0.01）. ConclusionPatients with depressive disorder are more likely to change their decision-making strategies following negative outcomes. Furthermore， the severity of depressive and anxiety symptoms is associated with a greater propensity to maintain existing decisions after receiving positive feedback. ［Funded by 2019 Joint Project of Luzhou Science and Technology Bureau-Southwest Medical University （number， 2019LZXNYDJ39］

Hepatic encephalopathy is a difficult and critical disease with rapid progression and limited treatment methods in the field of liver disease， and it is urgently needed to make breakthroughs in its pathogenesis. Selection of appropriate prevention and treatment strategies is of great importance in delaying disease progression and reducing the incidence and mortality rates. This article reviews the theory of “turbid toxin pathogenesis” and related prevention and treatment strategies for hepatic encephalopathy in traditional Chinese medicine/Zhuang medicine， proposes a new theory of “turbid toxin pathogenesis”， analyzes the scientific connotations of “turbid”， “toxin”， and the theory of “turbid toxin pathogenesis”， and constructs the “four-step” prevention and treatment strategies for hepatic encephalopathy， thereby establishing the new clinical prevention and treatment regimen for hepatic encephalopathy represented by “four prescriptions and two techniques” and clarifying the effect mechanism and biological basis of core prescriptions and techniques in the prevention and treatment of hepatic encephalopathy， in order to provide a reference for the prevention and treatment of hepatic encephalopathy.

Background Construction workers represent a high risk group for occupational injuries. Currently, domestic and international studies examining the factors affecting occupational injuries among construction workers focus on demographic and behavioural characteristics. However, there is limited attention to psychosocial, use of digital technology, and health status of workers. Objective To analyze the occurrence of occupational injuries among workers in the construction industry, explore impacts of psychosocial risk, use of digital technology, health status, and preventive measures at the workplace on occupational injuries, and provide a basis for the development of preventive measures. Methods Publicly available data from the European Union Occupational Safety and Health Administration were retrieved, comprising a sample of 2167 construction workers. The outcome indicator was the presence of occupational injuries among workers. A total of 25 variables in the dimensions of psychosocial risk, use of digital technology, health status, and preventive measures at the workplace were extracted after Chi-square test, and then a combination of Boruta's algorithm and logistic regression was applied to identify the key factors affecting occupational injuries. Results Among the 2167 construction workers surveyed, 182 (8.6%) reported experiencing occupational injuries. The Boruta algorithm identified eight characteristics which in descending order of importance were musculoskeletal disorders, job type, depression and anxiety, level of completed education, use of electronic smart products, timely solution of safety problems, overall fatigue, and age. The logistic regression results indicated that six variables had statistically significant effects on occupational injuries: age, job type, level of completed education, musculoskeletal disorders, overall fatigue, and timely solution of safety problems (P<0.05). Conclusion Occupational injuries in construction workers are influenced by a variety of factors, including age, job type, level of completed education, musculoskeletal disorders, overall fatigue, and timely solution of safety problems. Companies and workers should take targeted measures to reduce the incidence of occupational injuries.

Background Light gradient boosting machine (LightGBM) has become a popular choice in prediction models due to its high efficiency and speed. However, the "black box" issues in machine learning models lead to poor model interpretability. At present, few studies have evaluated the severity of occupational injuries from the perspective of LightGBM model and model interpretability. Objective To evaluate the application value of LightGBM models and model interpretability methods in occupational injury prediction. Methods The Mine Safety and Health Administration (MSHA) occupational injury data set of mining industry workers from 1983 to 2022 was used. Injury severity (death/fatal occupational injury and permanent/partial disability) was used as the outcome variable, and the predictor variables included the month of occurrence, age, sex, time of accident, time since beginning of shift, accident time interval from shift start, total experience, total mining experience, experience at this mine, cause of injury, accident type, activity of injury, source of injury, body part of injury, work environment type, product category, and nature of injury. Feature sets were screened using least absolute shrinkage and selection operator (Lasso) regression. A LightGBM model was then employed to predict occupational injury, with area under curve (AUC) of the model serving as the primary evaluation metric; an AUC closer to 1 indicates better predictive performance of the model. The interpretability of the model was evaluated using Shapley additive explanations (SHAP). Results Through Lasso regression, 7 key influencing factors were identified, including accident time interval from shift start, experience at this mine, cause of injury, accident type, body part of injury, nature of injury, and work environment type. A LightGBM model, constructed based on feature selection via Lasso regression, demonstrated good predictive performance with an AUC value of 0.9941 (95%CI: 0.9917, 0.9966), accuracy of 0.9743, specificity of 0.9781, and sensitivity of 0.9640. The predicted probability of fatal occupational injuries showed high consistency with the actual probability of fatal occupational injuries. In the occupational injury prediction model, the importance of each indicator was analyzed through its SHAP value, and it was found that the body part of injury and the nature of injury were the two main features that affected the prediction results of the model, and the impacts of other features were relatively small. The distribution of SHAP values across body part of injury was broad, with significant impacts on the model's prediction of fatal risk, particularly for injuries to the head and neck, as well as multi-part injuries. The nature of injury also exerted influences on the model in different directions, with suffocation/drowning, crushing, and multi-part injuries having a greater impact on the risk of fatal occupational injuries. Conclusion LightGBM model is capable of efficiently processing large-scale data and providing high-precision prediction results. Research on model interpretability aids in more accurately exploring and analyzing various key risk factors for fatal occupational injuries among mining workers, and further reveals the complex interactions among these factors. This, in turn, enables better preventive intervention and protection measures, as well as optimal resource allocation for labor workers.