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.

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.

Objective To evaluate the clinical efficacy and safety of sulbactam-durlobactam in the treatment of pulmonary infection caused by extensively drug-resistant Acinetobacter baumannii (XDR-AB) after liver transplantation. Methods A retrospective analysis was performed on the data of 3 liver transplant recipients admitted to the First Affiliated Hospital of Xi'an Jiaotong University from May to December 2025, who developed postoperative XDR-AB pulmonary infection and received sulbactam-durlobactam-based anti-infective therapy. Clinical data, clinical efficacy, microbiological response, safety and outcomes were analyzed. Results All isolated strains were XDR-AB producing OXA-23 carbapenemase, and in vitro antimicrobial susceptibility testing showed sensitivity to sulbactam-durlobactam. After treatment with sulbactam-durlobactam, all 3 recipients achieved clinical cure and microbiological eradication, with a treatment course of 6-8 days and pathogen clearance time of 3-6 days. Septic shock was effectively controlled in all recipients, who were successfully weaned from mechanical ventilation, and oxygenation index and organ function scores were significantly improved. No definite nephrotoxicity or other severe adverse reactions related to sulbactam-durlobactam were observed during treatment, and the 30-day all-cause fatality was 0. Two critically ill recipients achieved rapid microbiological clearance after combined nebulized phage therapy. Conclusions Sulbactam-durlobactam-based regimen shows favorable efficacy and safety in liver transplant recipients with postoperative XDR-AB pulmonary infection, and has a promising clinical application prospect.

Osteonecrosis of femoral head （ONFH） is a disease that causes osteocyte death due to interruption of blood supply of the femoral head， which may cause symptoms such as joint movement disorders， pain， and even femoral head collapse. Currently， the commonly used methods for treating ONFH in clinical practice are accompanied by problems such as long-term side effects， inaccurate efficacy， technical limitations， and complication risks. Traditional Chinese medicine （TCM） has shown unique advantages of holistic regulation， mild side effects， and symptom alleviation. A review of the related literature shows that Salviae Miltiorrhizae Radix et Rhizoma， as a representative Chinese herbal medicine for activating blood and resolving stasis， has the effects of activating blood， resolving stasis， dredging meridians， and relieving pain. Its active ingredients （such as salvianolic acid B， tanshinone Ⅱ_A， and tanshinone Ⅰ） interfere with bone metabolism balance， osteogenesis and differentiation， and improve bone microcirculation and bone microstructure. Salviae Miltiorrhizae Radix et Rhizoma is often combined with the herbal medicines with the effects of tonifying the liver and spleen or activing blood to form herb pairs （such as Salviae Miltiorrhizae Radix et Rhizoma-Angelicae Sinensis Radix， Salviae Miltiorrhizae Radix et Rhizoma-Chuanxiong Rhizoma， and Salviae Miltiorrhizae Radix et Rhizoma-Drynariae Rhizoma）， which enhances the efficacy through synergistic effects. In the application of TCM compound formulas， Bushen Huoxue prescription， Bushen Huoxue capsules， Gubi Tongxiao granules， and Shenggu Zaizao pills can regulate signaling pathways such as Wnt/β-catenin， Hedgehog， Notch， transforming growth factor（TGF）-β₁/Smads， and mitogen-activated protein kinase （MAPK） through multiple targets to significantly improve bone metabolism and hip joint function， playing an important role in preventing and treating ONFH. Through a review of available studies， this paper systematically explains the outstanding advantages of the active ingredients， herb pairs， and compound formulas of Salviae miltiorrhizae Radix et Rhizoma in the prevention and treatment of ONFH. The mechanisms may be related to factors such as promoting osteoblast generation and inhibiting osteoclast formation， increasing osteogenic differentiation， promoting angiogenesis， increasing bone density， inhibiting inflammatory response， and regulating signaling pathways. In the future， modern technology can be employed to optimize dosage forms， and high-quality clinical research should be conducted to further clarify its mechanism of action and promote the precise application of TCM. This review aims to provide more thinking directions for the application of Salviae miltiorrhizae Radix et Rhizoma in preventing and treating ONFH.

ObjectiveTo evaluate the effects of Tongnaoyin on the blood-brain barrier status and neurological impairment in acute ischemic stroke （AIS） patients with the syndrome of phlegm-stasis blocking collaterals by dynamic contrast-enhanced magnetic resonance imaging （DCE-MRI）. MethodsA total of 63 patients diagnosed with AIS in the Jiangsu Province Hospital of Chinese Medicine from October 2022 to December 2023 were enrolled in this study. According to random number table method，the patients were assigned into a control group （32 cases） and an observation group （31 cases）. The control group received conventional Western medical treatment，and the observation group took 200 mL Tongnaoyin after meals，twice a day from day 2 of admission on the basis of the treatment in the control group. After 7 days of treatment，the patients were examined by DCE-MRI. The baseline data for two groups of patients before treatment were compared. The National Institute of Health Stroke Scale （NIHSS） score and modified Rankin Scale （mRS） score were recorded before treatment and after 90 days of treatment for both groups. The rKtrans，rKep，and rVe values were obtained from the region of interest （ROI） of the infarct zone/mirror area and compared between the two groups. ResultsThere was no significant difference in the NIHSS or mRS score between the two groups before treatment. After 90 days of treatment，the NIHSS and mRS scores declined in both groups，and the observation group had lower scores than the control group （P<0.05）. After treatment，the rKtrans and rVe in the observation group were lower than those in the control group （P<0.01）. ConclusionCompared with conventional Western medical treatment alone，conventional Western medical treatment combined with Tongnaoyin accelerates the repair of the blood-brain barrier in AIS patients，thereby ameliorating neurological impairment after AIS to improve the prognosis.

Aortic dissection is a life-threatening cardiovascular disease with devastating complications and high mortality. It requires rapid and accurate diagnosis and a focus on prognosis. Many laboratory tests are routinely performed in patients with aortic dissection including D-dimer, brain natriuretic peptide, cardiac troponin I, C-reactive protein, and procalcitonin. D-dimer shows vital performance in the diagnosis of aortic dissection, and brain natriuretic peptide, cardiac troponin I, C-reactive protein, and procalcitonin exhibits important value in risk stratification and prognostic effect in aortic dissection patients. Our review summarized the clinical utility of these laboratory tests in patients with aortic dissection, aiming to provide advanced and comprehensive evidence for clinicians to better understand these laboratory tests and help their clinical practice.

Objective: To analyze the unregistered treatment situation and its influencing factors among pulmonary tuberculosis patients in Quzhou City, Zhejiang Province from 2017 to 2023, so as to provide a basis for promoting the management of tuberculosis patients and optimizing disease prevention and control strategies. Methods: Data of pulmonary tuberculosis patients including demographic information, etiological results, and mortality status were collected through the China Disease Prevention and Control Information System Infectious Disease Reporting and Surveillance System and the Tuberculosis Management Information System. Pulmonary tuberculosis patients not matched in the Tuberculosis Management Information System were defined as unregistered treatment patients, and the unregistered treatment rate was analyzed. Factors affecting unregistered treatment among pulmonary tuberculosis patients were analyzed using a multivariable logistic regression model. Results: A total of 10 779 pulmonary tuberculosis patients were reported in Quzhou City from 2017 to 2023, including 7 700 males (71.44%) and 3 079 females (28.56%). There were 5 484 cases aged <65 years, accounting for 50.88%. Among them, 630 cases were unregistered treatment, with an unregistered treatment rate of 5.84% (95%CI: 5.42%-6.38%). Multivariable logistic regression analysis showed pulmonary tuberculosis patients aged ≥65 years (OR=1.829, 95%CI: 1.512-2.212) had a higher risk of being unregistered treatment than those aged <65 years; patients with non-local household registration (OR=5.710, 95%CI: 4.724-6.901) had a higher risk than local patients; and patients engaged in housework/unemployed (OR=2.001, 95%CI: 1.421-2.818) or other occupations (OR=2.396, 95%CI: 1.789-3.137) had a higher risk than farmers. The mortality of unregistered treatment pulmonary tuberculosis patients was higher than the registered treatment patients (26.67% vs. 5.02%),with a significantly elevated mortality risk (OR=7.147, 95%CI: 5.738-8.902). Conclusions The unregistered treatment rate among pulmonary tuberculosis patients was well controlled in Quzhou City from 2017 to 2023, but the elderly, patients with non-local household registration, and those engaged in housework/unemployed had a higher risk of unregistered treatment. It is recommended to improve medical and social security policies, strengthen health education on tuberculosis prevention, enhance treatment adherence, and reduce mortality risk.

BACKGROUND: Fibrosis of the connective tissue in the vaginal wall predominates in pelvic organ prolapse (POP), which is characterized by excessive fibroblast-to-myofibroblast differentiation and abnormal deposition of the extracellular matrix (ECM). Our study aimed to investigate the effect of ECM stiffness on vaginal fibroblasts and to explore the role of methyltransferase 3 (METTL3) in the development of POP. METHODS: Polyacrylamide hydrogels were applied to create an ECM microenvironment with variable stiffness to evaluate the effects of ECM stiffness on the proliferation, differentiation, and expression of ECM components in vaginal fibroblasts. METTL3 small interfering RNA and an overexpression vector were transfected into vaginal fibroblasts to evaluate the effects of METTL3 silencing and overexpression on matrix stiffness-induced vaginal fibroblast-to-myofibroblast differentiation and abnormal modulation of the ECM. Both procedures were detected by 5-ethynyl-2'-deoxyuridine (EdU) staining, Western blotting (WB), quantitative real-time polymerase chain reaction (RT-qPCR), and immunofluorescence (IF). RESULTS: Vaginal fibroblasts from POP patients exhibited increased proliferation ability, increased expression of α-smooth muscle actin (α-SMA), decreased expression of collagen I/III, and significantly decreased expression of tissue inhibitors of matrix metalloproteinases (TIMPs) in the stiff matrix ( P <0.05). Compared with those from non-POP patients, vaginal wall tissues from POP patients demonstrated a significant increase in METTL3 content ( P <0.05). However, silencing METTL3 expression in vaginal fibroblasts with high ECM stiffness resulted in decreased proliferation ability, decreased α-SMA expression, an increased ratio of collagen I/III, and increased TIMP1 and TIMP2 expression. Conversely, METTL3 overexpression significantly promoted the process of increased proliferation ability, increased α-SMA expression, decreased ratio of collagen I/III and decreased TIMP1 and TIMP2 expression in the soft matrix ( P <0.05). CONCLUSIONS Elevated ECM stiffness can promote excessive proliferation, differentiation, and abnormal ECM modulation, and the expression of METTL3 plays an important role in alleviating or aggravating matrix stiffness-induced vaginal fibroblast-to-myofibroblast differentiation and abnormal ECM modulation.
Humans ; Female ; Extracellular Matrix/metabolism* ; Cell Differentiation/genetics* ; Methyltransferases/metabolism* ; Pelvic Organ Prolapse/pathology* ; Fibroblasts/metabolism* ; Myofibroblasts/metabolism* ; Vagina/metabolism* ; Cell Proliferation/physiology* ; Cells, Cultured ; Middle Aged

In recent years, hybrid brain-computer interfaces (BCIs) have gained significant attention due to their demonstrated advantages in increasing the number of targets and enhancing robustness of the systems. However, Existing studies usually construct BCI systems using intense auditory stimulation and strong central visual stimulation, which lead to poor user experience and indicate a need for improving system comfort. Studies have proved that the use of peripheral visual stimulation and lower intensity of auditory stimulation can effectively boost the user's comfort. Therefore, this study used high-frequency peripheral visual stimulation and 40-dB weak auditory stimulation to elicit steady-state visual evoked potential (SSVEP) and auditory steady-state response (ASSR) signals, building a high-comfort hybrid BCI based on weak audio-visual evoked responses. This system coded 40 targets via 20 high-frequency visual stimulation frequencies and two auditory stimulation frequencies, improving the coding efficiency of BCI systems. Results showed that the hybrid system's averaged classification accuracy was (78.00 ± 12.18) %, and the information transfer rate (ITR) could reached 27.47 bits/min. This study offers new ideas for the design of hybrid BCI paradigm based on imperceptible stimulation.
Brain-Computer Interfaces ; Humans ; Evoked Potentials, Visual/physiology* ; Acoustic Stimulation ; Photic Stimulation ; Electroencephalography ; Evoked Potentials, Auditory/physiology* ; Adult

Objective:To investigate the clinical efficacy of a self-detachable single-J internal stent drainage tube in the laparoscopic primary suture of the common bile duct for hepatolithiasis.Methods:Clinical data of 36 patients with hepatobiliary duct stones who underwent laparoscopic common bile duct primary suture combined with self-detached single J-type internal stent drainage at the First Affiliated Hospital of Xiamen University from April 2022 to April 2025 were retrospectively analyzed, including 17 males and 19 females, aged (54.3±8.7) years. All 36 patients underwent choledochoscopic stone extraction, primary common bile duct suture, and drainage with the self-expelling single-J internal stent. Total bilirubin, aspartate transaminase, and alanine transaminase before and 3 days after operation, as well as operation time, intraoperative blood loss, postoperative hospital stay, postoperative complications (bile leakage, cholangitis, intestinal obstruction, and stent retention), and stent expulsion time were collected.Results:All 36 patients successfully underwent the operation. Total bilirubin, aspartate transaminase, and alanine transaminase 3 days after operation showed significant improvement compared to preoperative levels (all P<0.05). The operation time was (86.5±22.6) min, intraoperative blood loss was 34.2 (13.7, 56.8) ml, and the postoperative hospital stay was (6.6±1.8) days. All single-J internal stents were spontaneously expelled via the anus between 6 and 21 days postoperatively, with the expulsion time of (10.7±2.1) days. No single J-type internal stent drainage tube was displaced into the bile duct in all cases, and there were no complications such as intestinal obstruction, bile leakage, cholangitis, or residual internal stent drainage tube. Conclusion:The self-detachable single-J internal stent drainage tube has been applied in the laparoscopic primary suture of the common bile duct for patients with hepatolithiasis, which demonstrated a good safety and effectiveness.