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.

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

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.

Objective To explore the effect of rotenone exposure on the metabolic homeostasis of nicotinamide adenine dinucleotide(NAD+)in dopaminergic neurons of the rat mid-brain striatum,and investigate the effect of exogenous NAD+intervention on the cellular damage response of dopaminergic neurons induced by rotenone.Methods Male SD rats(8 weeks old,200～250 g)were divided into a control group using a table of random numbers,a rotenone exposure group,an NAD+-intervention group,and an NAD+group.An intoxication model was established in the rotenone exposure group.NAD+(250 mg/kg)was administered simultaneously with rotenone exposure in the NAD+-intervention group.The NAD+group was only given NAD+,while the control group received no intervention.After modeling,open field test was performed to evaluate behavioral changes.After scarification,serum samples and mid-brain striatal tissues were collected.HE staining was used to observe the morphology of dopaminergic neurons in the striatum.The NAD+content in the tissues was detected with NAD+/NADH kit.Western blotting was employed to determine the contents of tyrosine hydroxylase(TH),nicotinamide phosphoribosyltransferase(NAMPT),nicotinamide mononucleotide adenylyltransferase(NMNAT),and solute carrier family 25 member A51(SLC25A51).ELISA was utilized to measure the content of dopamine in the striatal tissues.Immunohistochemical staining was applied to observe the distribution and contents of TH proteins in the striatal tissues of each group.Results Rotenone exposure significantly affected the vital signs and motor abilities of rats,induced disorderly-arranged,atrophy and deformed neurons in the striatal tissue,decreased the content of TH,rate-limiting enzyme for dopamine synthesis,by approximately 29%(P<0.01),the content of dopamine by about 42%,and that of NAD+by almost 50%(P<0.01),while increased the NADH/NAD+ratio(P<0.01).After exposure,the content of NAMPT,an enzyme related to NAD+synthesis,was decreased by 26%(P<0.05),the contents of NMNAT1-3 and SLC25A51,mitochondrial transporters of NAD+by approximately 21%,38%,43%,and 21%,respectively(P<0.01).Exogenous NAD+intervention improved the motor function of exposure rats and the morphology of dopaminergic neurons in the mid-brain striatal tissue,and restored the content of TH in the striatal tissue significantly by 12.8%(P<0.05),and the content of dopamine by 20.9%(P<0.05).Conclusion Rotenone disrupts the NAD+homeostasis in dopaminergic neurons by inhibiting the NAD+synthesis and transport pathways in the mid-brain striatal tissues,while exogenous NAD+intervention can effectively alleviate the dopaminergic neuron damage induced by rotenone exposure.

Objective:Autoimmune gastritis (AIG) is characterized by the loss of acid-secreting glands, resulting in hypochlorhydria and hypergastrinemia, conditions that significantly increase the risk of developing gastric neuroendocrine tumors (NETs) and gastric adenocarcinoma. In recent years, AIG has garnered increasing attention in both clinical and research settings. However, comprehensive studies on the clinical and endoscopic characteristics of AIG particularly cases complicated by gastric neoplastic lesions remain limited in China. This study aims to comprehensively summarize the clinical and endoscopic features of AIG and its associated gastric neoplastic lesions.Methods:A retrospective analysis was conducted using medical records from patients with AIG diagnosed at Sichuan Provincial People′s Hospital between 2019 and 2024. Data collected included demographic information, medical history, serological test results, imaging findings, and endoscopic observations. The clinical and endoscopic features of AIG patients with gastric NETs or epithelial-derived tumors were compared to those without gastric neoplastic lesions to identify potential risk factors and diagnostic indicators for tumor development in AIG.Results:A total of 72 patients with AIG were included, of whom 62.5% (45/72) were female, with an age range of 30 to 79 years old (mean age: 57±11 years). Parietal cell antibody (PCA) positivity was observed in 93.1% (67/72), intrinsic factor antibody (IFA) positivity in 45.8% (33/72), and Helicobacter pylori ( H. pylori) co-infection in 48.6% (35/72). Endoscopically, 84.7% (61/72) showed prominent corpus-dominant advanced atrophy; 47.2% (34/72) had sticky adherent mucus; and 41.7% (30/72) displayed residual oxyntic mucosa in the gastric body or fundus. Only 23.6% (17/72) had normal antrum mucosa, and just 16.7% (12/72) showed a circular wrinkle-like pattern. Gastric neoplastic lesions were identified in 35 patients (48.6%), including 15 cases (20.8%) with NETs and 20 cases (27.8%) with epithelial-derived tumors (four adenocarcinomas, three adenomas, and 13 cases of intraepithelial neoplasia). No significant differences were found between tumor and non-tumor groups in terms of age, gender, PCA/IFA positivity, gastrin levels, anemia status, folic acid, or serum iron levels. However, patients with NETs had significantly lower vitamin B 12 levels compared to those without tumors (183±111 ng/L vs. 323±159 ng/L, t=2.47, P=0.042). Additionally, AIG patients with NETs were more likely to be H.pylori-negative compared to both the non-tumor group (66.7% vs. 35.1%, χ2=5.26, P=0.072) and the epithelial-derived tumor group (66.7% vs. 30.0%, χ2=5.80, P=0.055). The incidence of reverse atrophy in the epithelial-derived tumor group was significantly lower than that in the non-tumor group (65.0% vs. 91.9%, χ2=6.49, P=0.011) and the NETs group (65.0% vs. 93.3%, χ2=3.90, P=0.048).? Conclusion:In AIG patients with NETs, serum vitamin B 12 levels are significantly reduced, suggesting that vitamin B 12 deficiency may be a key risk factor or clinical indicator for NET development in AIG. Furthermore, NETs are more frequently observed in AIG patients without H.pylori infection, while epithelial-derived tumors are more commonly associated with H.pylori co-infection.

Objective To investigate the changes in the levels of D-dimer(D-D),fibrin degradation product(FDP),thrombomodulin(TM),thrombin-antithrombin complex(TAT),tissue plasminogen activator-plasminogen activator inhibitor-1 complex(t-PAIC),and plasmin-alpha 2 plasmin inhibitor complex(PIC)during the treatment of patients with acute myeloid leukemia(AML)and their predictive value for efficacy and prognosis.Methods Thirty-one AML patients initially diagnosed at Guidong People's Hospital of Guangxi Zhuang Autonomous Region from January 2022 to December 2024 were collected as observation group,and 34 healthy medical checkupers were selected as control group.The changes in the levels of the indicators between two groups as well as before,during and after the treatment of observation group were compared,and observation group was divided into remission group and non-remission group according to the efficacy criteria,and the levels of the indicators between two groups were further compared.Risk factors for the efficacy and prognosis of AML patients were analyzed by using Logistic regression analysis.Results Before treatment,the levels of prothrombin time(PT),activated partial thromboplastin time(APTT),D-D,FDP,t-PAIC,PIC,TM and TAT in observation group were significantly higher than those in control group(P＜0.05),whereas there was no significant difference in fibrinogen(Fib)compared with control group(P＞0.05).During the treatment,the levels of t-PAIC and TM in observation group were higher than those before treatment(P＜0.05);After treatment,the levels of PT,D-D,FDP,PIC and TAT in observation group were significantly lower than those before treatment(P＜0.05).After treatment,the levels of PT,D-D,FDP,t-PAIC,PIC,TM and TAT were all lower than those during treatment(P＜0.05).The D-D,FDP,t-PAIC,PIC,TAT and TM levels in non-remission group were all higher than those in remission group,with the t-PAIC and TM levels showing statistical significance(P＜0.05).Binary Logistic regression analysis showed that t-PAIC was an independent risk factor affecting the efficacy and prognosis of AML patients(P＜0.05,OR=1.205,95％CI:1.015-1.430).Conclusion Regular testing of D-D,FDP,TM,TAT,t-PAIC and PIC levels can help to assess the disease changes and efficacy prognosis of AML patients,and provide an important reference for clinical decision-making.