Objective: To explore the influencing factors of recurrence in postoperative patients with renal cell carcinoma，construct machine learning prediction models and evaluate their performance. Methods: Clinical data of 915 patients with renal cell carcinoma treated in our hospital during 2013 and 2021 were retrospectively collected.The data were randomly divided into a training set (n=510) and a validation set (n=218) in a 7∶3 ratio.In the training set，LASSO regression algorithm was used to screen important variables，and machine learning prediction models were constructed to predict the recurrence risk.In the validation set，the effectiveness of the models was compared combined with the area under receiver operating characteristic curve (AUC)，accuracy rate，F1 value and other indicators. Results: LASSO regression screened out the risk factors，including smoking history，tumor size，N stage，Fuhrman grade，thrombin time and fibrinogen，based on which，the logistic model，decision tree model，random forest model，and Bayes model were constructed.In the validation set，the AUC of the above 4 models was 0.862，0.792，0.843 and 0.861，respectively; the accuracy was 0.917，0.908，0.904 and 0.927，respectively; F1 value was 0.357，0.286，0.323 and 0.600，respectively.The Bayes model had the most stable performance and best differentiation. Conclusion: In this data set，the prediction model based on Bayes algorithm has a good performance and can provide reference for clinical decision making.

Objective:To propose a deep learning（DL）-based ultrasound imaging auxiliary tool for automatic segmentation and recognition of the brachial plexus（BP），and to enhance the accuracy and safety of clinical procedures.Methods:It was a multicenter study that collected 773 healthy subjects from Peking University Third Hospital and its branch campuses，the Third Medical Center of the Chinese PLA General Hospital，and Shanghai Eighth People's Hospital between August 2024 and February 2025. Brachial plexus（BP）images in the interscalene groove were captured used high-frequency ultrasound by senior sonographers，a dataset comprising 1 289 standardized images were constructed and the improved model（CHA-TransUNet）was trained. The test set was input into 6 different models（CHA-TransUNet，R50-Unet，TransUnet，SegFormer，SwinUnet，MISSFormer）for segmentation. Segmentation accuracy was evaluated using metrics including the Dice similarity coefficient（DSC），95% Hausdorff distance（HD95）and mean intersection over union（mIoU），and was compared with the segmentation results of 3 ultrasound physicians with varying experience levels（junior physicians and senior physicians）to validate the model's segmentation efficacy.Results:The CHA-TransUNet model established based on a dataset of 1 289 standardized images achieved segmentation results for the BP with a DSC of 90.15%，mIoU of 91.02%，and HD95 of 8.08. Its accuracy was higher than other mainstream models（DSC：90.15% vs. 87.60%，87.77%，81.35%，84.78%，84.55%），significantly better than junior physicians（DSC：90.15% vs. 68.73%， Z=-127.76， P<0.001），and approached the level of senior physician（DSC：90.15% vs. 86.15%， Z=-31.33， P=0.549）. The model demonstrated superior boundary recognition in complex anatomical structures（e.g.，C6/C7 nerve roots）compared to ultrasound physicians（junior and senior）（HD95：8.08 vs. 26.34，17.44，56.80）. Conclusions:This study proposes an analysis model for BP ultrasound images，CHA-TransUNet. This model achieves segmentation and recognition of the BP with relatively complex pathways and structures. The model exhibits high accuracy and stability，outperforming current mainstream network models and junior physicians while approaching the performance level of senior physicians. It assists junior physicians or trainees in more accurately identifying and localizing the BP.

BACKGROUND:Compared with conventional repetitive transcranial magnetic stimulation,Theta burst transcranial magnetic stimulation(TBS)has attracted extensive attention from scholars in various fields due to its advantages of short stimulation time,high efficiency,good safety and long-lasting effect,and the research popularity continues to rise.OBJECTIVE:Through the visual bibliometrics analysis of international TBS research in the past 20 years,to sort out the development context of TBS research,summarize the research status,reveal research hotspots and development trends,and provide reference for subsequent research.METHODS:Relevant studies on TBS from January 2005 to June 2024 were searched in the Web of Science Core Collection database.CiteSpace software was used to perform annual publication volume analysis,co-occurrence analysis of countries,institutions and authors,and co-citation analysis of references,journals and authors,keywords co-occurrence,clustering,time evolution and emergence analysis,and so on,and draw the visual knowledge map.RESULTS AND CONCLUSION:(1)After screening,a total of 1914 papers were included in the study,and the amount of TBS research has shown an overall increasing trend over the past 20 years,and it is expected to continue to be a hot topic of research in the future.(2)The top three countries in terms of number of publications are the United States,China and Italy,and the top three institutions are the University of Toronto,the University of London and Harvard Medical School.Pascual-leone Alvaro from Harvard Medical School has the most research achievements,and HUANG YZ from Chang Gung University has the most citations.NEURON is the most influential core journal.(3)Analyses of high-frequency keywords,highly cited references and clustering topics showed that the research hotspots of TBS in the past 20 years mainly focus on the mechanism of TBS on synaptic plasticity and neurophysiological activity,the effect of TBS on stimulating targets in different brain regions(including the motor cortex,dorsolateral prefrontal cortex,anterior cingulate cortex and cerebellum,etc.),and the therapeutic effect of TBS on neurological and psychiatric diseases(including depression,Parkinson's disease movement disorder,post-stroke movement disorder and cognitive impairment,and Alzheimer's disease memory disorders).(4)Keyword burst,literature emergence and keyword temporal evolution analyses showed that"major depression,application guidelines,rating scale,efficacy,disorder,refractory depression,meta-analysis,etc."are not only current research hotspots,but also future research trends.(5)In the future,TBS research should strengthen the regional cooperation of core authors and institutions,explore the clinical application in the treatment of refractory diseases,and realize the precision,personalization and optimization of TBS application by combining cutting-edge technologies and optimizing stimulus parameters,so as to solve more clinical problems.

BACKGROUND:Compared with conventional repetitive transcranial magnetic stimulation,Theta burst transcranial magnetic stimulation(TBS)has attracted extensive attention from scholars in various fields due to its advantages of short stimulation time,high efficiency,good safety and long-lasting effect,and the research popularity continues to rise.OBJECTIVE:Through the visual bibliometrics analysis of international TBS research in the past 20 years,to sort out the development context of TBS research,summarize the research status,reveal research hotspots and development trends,and provide reference for subsequent research.METHODS:Relevant studies on TBS from January 2005 to June 2024 were searched in the Web of Science Core Collection database.CiteSpace software was used to perform annual publication volume analysis,co-occurrence analysis of countries,institutions and authors,and co-citation analysis of references,journals and authors,keywords co-occurrence,clustering,time evolution and emergence analysis,and so on,and draw the visual knowledge map.RESULTS AND CONCLUSION:(1)After screening,a total of 1914 papers were included in the study,and the amount of TBS research has shown an overall increasing trend over the past 20 years,and it is expected to continue to be a hot topic of research in the future.(2)The top three countries in terms of number of publications are the United States,China and Italy,and the top three institutions are the University of Toronto,the University of London and Harvard Medical School.Pascual-leone Alvaro from Harvard Medical School has the most research achievements,and HUANG YZ from Chang Gung University has the most citations.NEURON is the most influential core journal.(3)Analyses of high-frequency keywords,highly cited references and clustering topics showed that the research hotspots of TBS in the past 20 years mainly focus on the mechanism of TBS on synaptic plasticity and neurophysiological activity,the effect of TBS on stimulating targets in different brain regions(including the motor cortex,dorsolateral prefrontal cortex,anterior cingulate cortex and cerebellum,etc.),and the therapeutic effect of TBS on neurological and psychiatric diseases(including depression,Parkinson's disease movement disorder,post-stroke movement disorder and cognitive impairment,and Alzheimer's disease memory disorders).(4)Keyword burst,literature emergence and keyword temporal evolution analyses showed that"major depression,application guidelines,rating scale,efficacy,disorder,refractory depression,meta-analysis,etc."are not only current research hotspots,but also future research trends.(5)In the future,TBS research should strengthen the regional cooperation of core authors and institutions,explore the clinical application in the treatment of refractory diseases,and realize the precision,personalization and optimization of TBS application by combining cutting-edge technologies and optimizing stimulus parameters,so as to solve more clinical problems.

Objective:To propose a deep learning（DL）-based ultrasound imaging auxiliary tool for automatic segmentation and recognition of the brachial plexus（BP），and to enhance the accuracy and safety of clinical procedures.Methods:It was a multicenter study that collected 773 healthy subjects from Peking University Third Hospital and its branch campuses，the Third Medical Center of the Chinese PLA General Hospital，and Shanghai Eighth People's Hospital between August 2024 and February 2025. Brachial plexus（BP）images in the interscalene groove were captured used high-frequency ultrasound by senior sonographers，a dataset comprising 1 289 standardized images were constructed and the improved model（CHA-TransUNet）was trained. The test set was input into 6 different models（CHA-TransUNet，R50-Unet，TransUnet，SegFormer，SwinUnet，MISSFormer）for segmentation. Segmentation accuracy was evaluated using metrics including the Dice similarity coefficient（DSC），95% Hausdorff distance（HD95）and mean intersection over union（mIoU），and was compared with the segmentation results of 3 ultrasound physicians with varying experience levels（junior physicians and senior physicians）to validate the model's segmentation efficacy.Results:The CHA-TransUNet model established based on a dataset of 1 289 standardized images achieved segmentation results for the BP with a DSC of 90.15%，mIoU of 91.02%，and HD95 of 8.08. Its accuracy was higher than other mainstream models（DSC：90.15% vs. 87.60%，87.77%，81.35%，84.78%，84.55%），significantly better than junior physicians（DSC：90.15% vs. 68.73%， Z=-127.76， P<0.001），and approached the level of senior physician（DSC：90.15% vs. 86.15%， Z=-31.33， P=0.549）. The model demonstrated superior boundary recognition in complex anatomical structures（e.g.，C6/C7 nerve roots）compared to ultrasound physicians（junior and senior）（HD95：8.08 vs. 26.34，17.44，56.80）. Conclusions:This study proposes an analysis model for BP ultrasound images，CHA-TransUNet. This model achieves segmentation and recognition of the BP with relatively complex pathways and structures. The model exhibits high accuracy and stability，outperforming current mainstream network models and junior physicians while approaching the performance level of senior physicians. It assists junior physicians or trainees in more accurately identifying and localizing the BP.

Under the backdrop of the "Healthy China 2030" strategy, running has become the most common form of exercise. Fitness running is a kind of endurance aerobic exercise. Compared with swimming, aerobics, and other sports with high activity and intensity, the risk of lower limb fatigue injury during fitness running is higher. In this review paper, the risk factors for running-related injuries were summarized by consulting and analyzing the database and focuses on discussing and analyzing the impact of running on joints. The results showed that hip adduction, knee bending, and ankle joint abnormalities are the three joint-related factors that cause the main injuries during running. Four rehabilitation intervention methods for running-related injuries were proposed, that can guide patients to generate personalized rehabilitation treatment plans through training.

Acute high altitude disease (AHAD) is a general term for a series of clinical reactions that occur when the body fails to adapt to the low-pressure hypoxic environment of high altitudes. Mild cases can cause symptoms such as headache, nausea and vomiting, while more severe cases can lead to life-threatening conditions such as pulmonary edema, cerebral edema and other critical conditions that can be fatal. With the increasing demand for high altitudes deployment, understanding the common preventive measures of AHAD can reduce its morbidity or mortality to a certain extent, which is of great benefit to those who reside temporarily at high altitudes. In recent years, as people's health awareness has improved, there has been a growing attention towards non-pharmacological methods of disease prevention. At the same time, non-pharmacological therapy has significant therapeutic effects in preventing and treating high-altitude diseases, which has attracted the attention of researchers in this field. This review summarizes the major non-pharmacological preventive components of modern medicine and outlines the current non-pharmacological approaches to AHAD from the perspective of traditional Chinese medicine, intending to serve clinical purposes and improve the onset and prognosis of AHAD.

Objective:To explore the effects of life events, family environment and coping style on self-injury behavior in adolescents with first-episode depression.Methods:From July 2019 to December 2022, a total of 110 adolescent patients with first-episode depression were selected in the Psychiatry Department of the First Affiliated Hospital of Zhengzhou University. According to whether the patients had self-injury behavior, the patients were divided into group without self-injury( n=54)and group with self-injury( n=56).Patients in the two groups were evaluated by a general clinical data questionnaire, adolescent self-rating life events checklist (ASLEC), family environment scale-Chinese version(FES-CV), simplified coping style questionnaire (SCSQ), 24 items Hamilton depression scale (HAMD-24), Hamilton anxiety scale (HAMA) and 90 symptom checklist-90 (SCL-90). Statistical analysis including t-test, χ2 test and binary Logistic regression analysis were performed on the enrolled data by SPSS 25.0 statistical software. Results:Among 110 patients, there were 56 patients(50.9%) exhibited self-injury behavior.The scores of ASLEC(51.04±5.99, 48.02±6.86), intimacy(3.70±1.85, 4.59±1.60), emotional expression(3.84±1.80, 4.69±1.96), positive coping styles(15.84±5.85, 18.22±4.84), negative coping styles(12.50±3.23, 11.06±3.64), and HAMA(20.63±2.86, 19.48±2.55) showed statistically significant differences between the group with and without self-injury ( t=-2.46, 2.72, 2.36, 2.32, -2.20, -2.21, all P<0.05). Binary Logistic regression analysis showed that life events ( B=0.079, OR=1.083, 95% CI=1.008-1.163, P=0.030), negative coping style ( B=0.173, OR=1.188, 95% CI=1.033-1.367, P=0.016), HAMA ( B=0.225, OR=1.252, 95% CI=1.057-1.482, P=0.009) were risk factors for self-injury, while intimacy ( B=-0.264, OR=0.768, 95% CI=0.593-0.995, P=0.046) and positive coping styles ( B=-0.092, OR=0.912, 95% CI=0.834-0.997, P=0.044) were protective factors for self-injury. Conclusion:The self-injury behavior of adolescents with first-episode depression may be related to negative life events, early adverse family environment and coping style.

Objective:To explore the effects of depressive symptoms on sleep quality in adolescents with depressive disorder, and the mediating roles of cognitive fusion and sleep belief.Methods:A sample of 210 adolescents with first episode depressive disorder aged 12-18 years were recruited to complete 17-item Hamilton depression scale (HAMD-17), Pittsburgh sleep quality index (PSQI), cognitive fusion questionnaire (CFQ), and dysfunctional beliefs and attitudes about sleep scale (DBAS-16) from November 2021 to July 2022. SPSS 26.0 software was used to perform descriptive analysis and correlation analysis. The mediating effect was tested by Bootstrap analysis using PROCESS V 3.4 Macro program.Results:The incidence of low sleep quality in adolescents with depressive disorder was 69.0%(145/210). HAMD-17 score was (22.4±7.9), PSQI score was (9.7±3.7), CFQ score was (51.6±7.8), DBAS-16 score was (43.5±8.4).PSQI was positively correlated with the scores of HAMD-17 and CFQ( r=0.613, 0.463, both P<0.001).HAMD-17 was positively correlated with CFQ score ( r=0.488, P<0.001).DBAS-16 was negatively correlated with scores of PSQI, HAMD-17 and CFQ( r=-0.326, -0.284, -0.354, all P<0.001). The direct effect of depression on sleep quality was 0.230(95% CI=0.169-0.293). The indirect effect of depression on sleep quality through two pathways, the separate mediating effect value of cognitive fusion was 0.041 (95% CI=0.011-0.074), and the chain mediating effect value of cognitive fusion and sleep beliefs was 0.008(95% CI=0.001-0.020). Conclusion:Depressive symptoms can directly affect sleep quality of depressive disorder adolescents and indirectly through cognitive fusion and sleep beliefs.

Objective To explore the risk factors of 1-year readmission in patients after percutaneous coronary intervention(PCI)treated with Bayaspirin combined with Clopidogrel and to construct a risk prediction model.Methods The clinical data of patients with myocardial infarction(MI)who underwent primary PCI in the Department of Cardiovascular Medicine of Lishui People's Hospital from January 2020 to June 2023 were retrospectively analyzed.The patients were divided into the readmission group(RG)and the non-readmission group(NRG)according to whether they were readmitted due to myocardial reinfarction or complications of MI within 1 year.Univariate analysis was used to explore the differential variables between the RG and NRG groups.Multivariate Logistic regression(Stepwise)was used to explore the risk factors of 1-year readmission in patients after PCI and the"optimal model".The"optimal model"was visualized using R software and transformed into a nomogram risk prediction model.The predictive ability of the Nomogram risk prediction model was evaluated using the receiver operating characteristic(ROC)curve.The calibration of the Nomogram risk prediction model was evaluated using the calibration curve(resampling,Bootstrap n=1 000).The net benefit of the nomogram risk prediction model was evaluated using the decision curve.Results A total of 100 patients were included in the study and the readmission rate within 1 year was 34.00％.Age(≥63 years old),diabetes,the number of diseased vessels(≥2),monocyte-high-density lipoprotein ratio(≥0.36),and prognosis nutrition(＜39.39)were independent risk factors for readmission in patients with MI after PCI(all P＜0.05).ROC analysis showed that the readmission risk prediction model had a good predictive efficiency for readmission in patients with MI after PCI,with an area under ROC curve of 0.903(95％CI:0.836-0.970).The calibration curve showed that the"predicted readmission probability"was approximately consistent with the"actual readmission probability";the decision curve showed that the net benefit of the readmission risk prediction model nomogram was higher than that of the"all"clinical net benefit.Conclusion The readmission prediction model of patients with MI after PCI constructed in this study can accurately identify high-risk groups of readmission and may be beneficial for the standardized management of patients after PCI in clinical practice,improve the long-term prognosis of patients.