OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

The c-Jun N-terminal kinase （JNK） signaling pathway， a key member of the mitogen-activated protein kinase （MAPK） family， plays a central role in the pathogenesis and progression of central nervous system （CNS） diseases by regulating core biological processes such as apoptosis， inflammatory responses， synaptic plasticity， and autophagy. This article sorts out and analyzes relevant literature published domestically and internationally in recent years， summarizing the mechanisms of action of the JNK signaling pathway in common CNS diseases and the research progress in traditional Chinese medicine （TCM） interventions in CNS diseases through the regulation of the JNK signaling pathway. Studies have shown that active components of TCM， such as berberine， paeoniflorin， and astragaloside Ⅳ， as well as compound formulations like Heixiaoyao san， Ditan tang， and Buyang huanwu tang， can exert neuroprotective effects in various CNS disorders， including Alzheimer’s disease， Parkinson’s disease， cerebral ischemia-reperfusion injury， and epilepsy， by inhibiting the aberrant activation of the JNK signaling pathway， thereby alleviating neuroinflammation， oxidative stress， and neuronal apoptosis， while improving synaptic function and cognitive behavioral deficits， regulating autophagy， and maintaining blood-brain barrier integrity.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

Alzheimer’s disease （AD） is an age-related neurodegenerative disorder. Marrow-sea insufficiency serves as the fundamental basis for the onset of AD. Early syndrome differentiation-based intervention helps to delay disease progression， and improve patients’ cognitive function. Qifu yin is a representative specialized prescription for AD with marrow-sea insufficiency syndrome. Studies demonstrate that Qifu yin exerts neuroprotective effects through multiple pathways， including inhibiting the abnormal deposition of amyloid β -protein and hyperphosphorylation of tau protein， alleviating neuroinflammation， regulating oxidative stress and mitochondrial dysfunction， modulating the cholinergic system， and improving synaptic plasticity. Qifu yin combined with Western medicine such as donepezil， memantine， and butylphthalide， or combined with external therapies such as acupuncture， can effectively improve cognitive function and activities of daily living in AD patients with favorable safety. Future research should focus on the core pathogenesis and key targets of AD with marrow-sea insufficiency syndrome， provide in-depth elucidation of the scientific connotation of Qifu yin’s “tonifying the kidney to produce marrow”， and further conduct high-quality clinical studies to provide scientific evidence for the prevention and treatment of AD with marrow-sea insufficiency syndrome.

ObjectiveTo develop an exercise intervention program for patients undergoing total knee arthroplasty based on the daily goal management pathway, and preliminarily verify its clinical feasibility and effectiveness. MethodsThe intervention program was formulated based on the daily goal management pathway and hope theory, combined with literature analysis, qualitative interviews and expert consultation. Feasibility evaluation was conducted among orthopedic nurses and patients in Beijing Bo'ai Hospital from September to November, 2025. A controlled pilot study was performed with 15 patients in each group: the control group received routine rehabilitation care, while the experimental group received the developed intervention program. The Hospital for Special Surgery Knee Score (HSS), range of motion (ROM) of knee, functional exercise compliance score, Visual Analogue Scale (VAS) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) were compared between two groups. ResultsThe program covered three themes from admission to three weeks postoperatively, including seven training methods and 32 specific recommendations. Feasibility results showed 100% patient recruitment rate, 93.75% retention rate and 96.94% program acceptance rate. A total of 21 orthopedic nurses scored ≥ 4.5 on all four dimensions of the program. After intervention, HSS score and knee ROM significantly increased (|t| > 6.205, P < 0.001), while WOMAC and VAS score decreased (t = 9.127, Z = -3.415, P < 0.01) in the experimental group; in the control group, VAS score decreased (Z = -3.122, P = 0.002), and knee ROM reduced (t = -2.622, P = 0.015), with no significant improvement in other indicators (P > 0.05); all the indexes were better in the experimental group than in the control group (|t| > 7.949, |Z| > 2.990, P < 0.01), including the functional exercise compliance (t = -8.565, P < 0.001). ConclusionThe exercise intervention program based on the daily goal management pathway is scientific, feasible and preliminarily effective, which can provide a new structured and humanized nursing for early exercise training of patients during hospitalization for total knee arthroplasty.

OBJECTIVE To investigate the current status of informatization tools applied to antimicrobial stewardship in county hospitals in China， and to provide a reference for promoting the informatization development of antimicrobial stewardship in county hospitals.METHODS From August to September 2025， an online questionnaire survey was conducted among 1 007 county hospitals across 31 provinces（autonomous regions， and municipalities） in China. The survey focused on the application of four types of informatization tools：the real-time monitoring system for antimicrobial use， the pre-prescription review system， the irrational use warning system， and the electronic prescription evaluation system（hereinafter referred to as the “monitoring system”“review system”“warning system”“evaluation system”，respectively）. Correlation analysis and binary Logistic regression analysis were employed to explore the influencing factors.RESULTS Of the county hospitals， 80.83% were equipped with at least one type of informatization tool for antimicrobial stewardship， while 19.17% had no relevant tool. Only 18.87% of the hospitals were equipped with all four types of tools. The monitoring system exhibited the highest equipped rate （70.80%）， whereas the warning system was equipped in only 33.96% of the hospitals. Four types of tools are evenly and adequately deployed in the eastern region， the central and western regions have far lower deployment rates of intervention tools including review system and warning system， accompanied by prominent intra-provincial gaps. The total number of the health technicians， hospital grade， and prescription review rate of outpatient antibacterial drug were significantly and positively correlated with the deployment rates of the four informatization tools （ P ＜0.05）. The results of the Logistic regression model fitting indicated that the model of the review system was rated “excellent” [area under the receiver operating characteristic curve （AUC）＝0.81]， and the model of the warning system was rated “further improvement” （AUC＝0.67）. The total number of health technicians was significantly positively correlated with the deployment rates of all four types of informatization tools （all P ＜0.05）.CONCLUSIONS The informatization of antimicrobial stewardship in county hospitals in China remains in the initial stage of transitioning from “passive statistics” to “active prevention and control”， with challenges such as structural imbalance and regional disparities. In the future， differentiated support strategies should be implemented， the allocation of resources should be optimized， to enhance the level of refined antimicrobial stewardship.

Objective To investigate the general characteristics and treatment processes of patients with advanced esophageal cancer (EC) treated in county- or prefecture-level hospitals in high-incidence areas of EC in China. Methods In this retrospective observational study, electronic medical records of patients with advanced EC were collected from six medical centers in high-incidence areas. Eligible patients had advanced EC and whose first medical contact was documented between January 1, 2022, and June 1, 2024. Descriptive statistical analyses were conducted to evaluate patient characteristics and treatment plans. Results A total of 322 EC patients were included, of whom 230 were male (71.4%). The median age was 69 years. Among the 270 patients with available tumor diagnosis information, 264 patients (97.8%) presented with EC-specific symptoms. Of the 281 patients with pathological data, esophageal squamous cell carcinoma was the predominant type, accounting for 254 cases (90.4%). Among 235 patients with information on the initial diagnostic method, 220 (93.6%) were diagnosed through endoscopy. A total of 216 patients (67.1%) with advanced disease progressed from early or locally advanced stages. Surgical treatment was performed in 126 patients (39.1%), of whom 123 (97.6%) achieved R0 resection, and 71 (56.3%) of them received perioperative treatment. Definitive chemoradiotherapy was administered to 116 patients (36.0%). The median disease-free survival for patients undergoing radical surgery was 13.9 months, while that for patients treated with definitive chemoradiotherapy was 10.6 months. At the advanced stage, lymph node metastasis was observed in 250 patients (77.6%), with mediastinal lymph node metastasis being the most common type. Organ metastasis occurred in 176 patients (54.7%), most frequently involving the lungs, liver, and bones. Most patients (79.8%, 229/287) were from the county or city where the hospoital was loacted, 77.9% (232/298) were covered by resident basic medical insurance, and 88.7% (274/309) of patients initiated advanced treatment at the participating hospitals. Conclusion This study reveals the unique epidemiological, clinical, and pathological characteristics of patients with EC in high-incidence areas of China. The results provide an important reference for further exploration of this disease and its management.

Objective This study aims to evaluate the safety and efficacy of internal carotid artery(ICA)embolization for the resection of head and neck tumors invading the ICA.Methods A retrospective analysis was conducted on eight patients with ICA-invading head and neck tumors treated between August 2022 and June 2024 in Beijing Tongren Hospital,Capital Medical University.All patients underwent a preoperative balloon occlusion test(BOT),which yielded negative results before undergoing ICA embolization.Parameters from BOT,technical success rates of embolization procedures,perioperative complications,and follow-up outcomes were recorded.Results During BOT assessments,the mean reflux pressure was found to be 75.4％±10.3％of the pre-occlusion pressure.Patency of both anterior and posterior communicating arteries was observed in three cases;four cases exhibited patency solely in the anterior communicating artery,while one case showed patency only in the posterior communicating artery.The technical success rate of embolization was 100％.One patient experienced acute cerebral infarction following embolization treatment,while two patients had migraine attacks post-procedure.All patients achieved complete tumor resection without new-onset neurological deficits.Conclusion For patients with head and neck tumors invading the ICA who are negative on BOT,preoperative ICA embolization is a safe and feasible approach that enhances surgical safety during tumor resection.

Objective To use imaging features of pulmonary nodules to predict the risk of lymph node metastasis in patients with cT1-stage non-small cell lung cancer (NSCLC), providing a reference for clinical decision-making. Methods A retrospective analysis was conducted on the imaging features and postoperative pathological results of cT1 NSCLC patients who underwent surgical treatment at Linyi People’s Hospital from July 2019 to July 2022. Patients were grouped and analyzed according to lymph node metastasis status. Results A total of 1 123 patients were included, comprising 471 males and 652 females, with a median age of 59 (52, 66) years. Comparative analysis revealed that sex, age, nodule location, nodule size on imaging, solid component size, consolidation tumor ratio (CTR), average CT value, and tumor proximity to the pleura all influenced lymph node metastasis. A nomogram was constructed, indicating that the probability of lymph node metastasis in cT1 NSCLC was positively correlated with solid component size, CTR, and average CT value of the pulmonary nodule, and negatively correlated with patient age. The area under the receiver operating characteristic curve was 0.929. Conclusion For cT1 NSCLC patients, the probability of lymph node metastasis can be predicted by measuring the solid component size, CTR, and average CT value of the pulmonary nodule, in conjunction with patient age. However, relying solely on pulmonary nodule imaging characteristics is insufficient to determine a specific lymph node dissection strategy.

Objective To explore the application value of simple drawing line puncture combined with visual articular process arthroplasty in lateral foraminoscopy.Methods A retrospective analysis was performed on 89 patients with single-segment lumbar disc herniation treated with lateral foraminoscopy from May 2019 to December 2022,including traditional transforaminal endoscopic spine system(TESSYS)technology(conventional group,35 cases)and simple drawing line puncture combined with visual articular process arthroplasty(modified group,54 cases).The fluoroscopy times,puncture time,and operation time of the two groups were compared.The Visual Analogue Score(VAS),Oswestry Disability Index(ODI),and MacNab criteria were used to evaluate the surgical effect at 3 d after surgery and at the last follow-up.Results All the operations were successfully completed without conversion to open surgery.In the conventional group,there was 1 case of L4 nerve root injury,who was considered intraoperative nerve root compression injury.There was no abnormality in lower limb muscle strength after surgery,but hyperalgesia and numbness in the innervated cutaneous area accompanied by nocturnal cramps.The patient was given treatment with pregabalin,mecobalamin,vitamin B1 and B6 for 2 months,and returned to normal at 1 year of follow-up.The other cases had no complications such as dural injury,abdominal organ injury,or incision infection.Recurrence occurred in 1 case in the conventional group and 2 cases in the modified group,and all the 3 cases occurred within 3 months after operation.Among them,2 patients had severe symptoms and underwent endoscopic revision again,and the other patient improved after conservative treatment.Compared with the conventional group,the puncture times[(1.8±0.7)times vs.(7.5±1.1)times,t=27.543,P=0.000].fluoroscopy times[(5.7±1.8)times vs.(23.2±2.2)times,t=41.235,P=0.000]and operation time[(72.7±7.2)min vs.(92.7±7.7)min,t=12.317,P=0.000]in the modified group were significantly reduced or shortened,and there was no significant difference in postoperative hospital stay[(3.2±0.6)d vs.(3.3±0.6)d,t=0.062,P=0.951]between the two groups.The conventional group was followed up for(14.0±1.3)months and the modified group was followed up for(13.6±1.2)months.There were no significant differences in VAS scores[(1.5±0.6)points vs.(1.6±0.7)points,t=0.751,P=0.455].ODI[(10.8±3.4)％vs.(11.8±3.9)％,t=1.284,P=0.202].and excellent and good rate of MacNab criteria[100％(54/54)vs.100％(35/35),Z=-0.981,P=0.327]between the two groups at the last follow-up.Conclusions Simple drawing line puncture combined with visual articular process arthroplasty can significantly improve the accuracy of intervertebral foramen aspiration,with simple operation,reduced X-ray exposure for doctors and patients,shortened operation time,and improved surgical safety.It is worthy of promotion and application in percutaneous foraminoscopy.