OBJECTIVE:Postoperative recurrence is a common complication of percutaneous endoscopic lumbar discectomy for lumbar disc herniation,which can significantly increase the risk of reoperation.A well-performing risk prediction model can help identify high-risk groups early and prevent postoperative recurrence.This study systematically evaluated the risk prediction model for postoperative recurrence after percutaneous endoscopic lumbar discectomy to provide a reference for surgical decision-making.METHODS:The PubMed,Embase,Web of Science,CNKI,WanFang Data,VIP,and CBM were electronically searched to collect studies on the recurrence risk prediction models after percutaneous endoscopic lumbar discectomy from inception to July 1,2024.Two reviewers independently screened the literature and extracted data.The models' risk of bias,applicability,and report quality were assessed using prediction model risk of bias assessment tool(PROBAST)and Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis(TRIPOD)tools,respectively.Meta-analysis of postoperative recurrence rate of percutaneous endoscopic lumbar discectomy and related predictors was performed using Revman 5.4 software.RESULTS:(1)A total of 15 studies were included,all of which were retrospective studies,including 24 models for predicting the risk of recurrence after percutaneous endoscopic lumbar discectomy.(2)The PROBAST evaluation results indicated that all 15 studies exhibited a high risk of bias.Regarding applicability,two studies demonstrated a low risk,while 13 presented a high risk.(3)Regarding the TRIPOD reporting quality,the overall quality across the 15 studies was low.The primary reasons for this low compliance included the failure to report blinding,a lack of explanation for the sample size calculation method,lack of detailed description of missing data processing methods,and lack of information such as introduction to the model used.(4)Furthermore,the area under the receiver operating characteristic curve for the model ranged from 0.684 to 0.972,with the number of potential predictor variables varying from 15 to 28.(5)The results of meta-analysis showed that the postoperative recurrence rate of lumbar disc herniation patients treated with percutaneous endoscopic lumbar discectomy was 12％(95％CI=9.0％-15.0％),Modic changes(OR=6.72,95％CI=3.90-11.59),body mass index(OR=1.28,95％CI=1.10-1.49),work intensity(OR=3.22,95％CI=1.85-5.59),age(OR=2.28,95％CI=1.50-3.48),and smoking history(OR=2.65,95％CI=1.75-4.00)were independent influencing factors for postoperative recurrence of percutaneous endoscopic lumbar discectomy(all P＜0.05).CONCLUSION:The overall predictive performance of the recurrence risk prediction models after percutaneous endoscopic lumbar discectomy is satisfactory;however,the model exhibits a high overall risk of bias and applicability,coupled with low reporting quality.Additionally,there is a lack of prospective research and external validation.Future,risk prediction models should consider factors such as Modic changes,body mass index,work intensity,age,and smoking history as potential predictors.

OBJECTIVE:Postoperative recurrence is a common complication of percutaneous endoscopic lumbar discectomy for lumbar disc herniation,which can significantly increase the risk of reoperation.A well-performing risk prediction model can help identify high-risk groups early and prevent postoperative recurrence.This study systematically evaluated the risk prediction model for postoperative recurrence after percutaneous endoscopic lumbar discectomy to provide a reference for surgical decision-making.METHODS:The PubMed,Embase,Web of Science,CNKI,WanFang Data,VIP,and CBM were electronically searched to collect studies on the recurrence risk prediction models after percutaneous endoscopic lumbar discectomy from inception to July 1,2024.Two reviewers independently screened the literature and extracted data.The models' risk of bias,applicability,and report quality were assessed using prediction model risk of bias assessment tool(PROBAST)and Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis(TRIPOD)tools,respectively.Meta-analysis of postoperative recurrence rate of percutaneous endoscopic lumbar discectomy and related predictors was performed using Revman 5.4 software.RESULTS:(1)A total of 15 studies were included,all of which were retrospective studies,including 24 models for predicting the risk of recurrence after percutaneous endoscopic lumbar discectomy.(2)The PROBAST evaluation results indicated that all 15 studies exhibited a high risk of bias.Regarding applicability,two studies demonstrated a low risk,while 13 presented a high risk.(3)Regarding the TRIPOD reporting quality,the overall quality across the 15 studies was low.The primary reasons for this low compliance included the failure to report blinding,a lack of explanation for the sample size calculation method,lack of detailed description of missing data processing methods,and lack of information such as introduction to the model used.(4)Furthermore,the area under the receiver operating characteristic curve for the model ranged from 0.684 to 0.972,with the number of potential predictor variables varying from 15 to 28.(5)The results of meta-analysis showed that the postoperative recurrence rate of lumbar disc herniation patients treated with percutaneous endoscopic lumbar discectomy was 12％(95％CI=9.0％-15.0％),Modic changes(OR=6.72,95％CI=3.90-11.59),body mass index(OR=1.28,95％CI=1.10-1.49),work intensity(OR=3.22,95％CI=1.85-5.59),age(OR=2.28,95％CI=1.50-3.48),and smoking history(OR=2.65,95％CI=1.75-4.00)were independent influencing factors for postoperative recurrence of percutaneous endoscopic lumbar discectomy(all P＜0.05).CONCLUSION:The overall predictive performance of the recurrence risk prediction models after percutaneous endoscopic lumbar discectomy is satisfactory;however,the model exhibits a high overall risk of bias and applicability,coupled with low reporting quality.Additionally,there is a lack of prospective research and external validation.Future,risk prediction models should consider factors such as Modic changes,body mass index,work intensity,age,and smoking history as potential predictors.

Colorectal cancer is a common tumor of the digestive system and is the third leading cause of cancer-related death worldwide. The global incidence of colorectal cancer is currently increasing. In some patients, the tumor has already spread to nearby organs at the time of diagnosis, with the small intestine and bladder being common sites of invasion.[1,2] The diagnosis of colorectal cancer that has spread to the bladder can be challenging. Aside from a few patients who experience urinary symptoms due to invasion of the bladder trigone or the entire bladder wall, there are no distinct clinical signs, which often leads to misdiagnosis. The following case report details one such instance.

OBJECTIVE To develop the quality evaluation standard indicator system for hospital cough and wheeze pharmaceutical care clinic （CWPC） pharmacist training within the layered learning practice model （LLPM）， and apply it in clinical practice. METHODS Our teaching team established an LLPM model to train cough and wheeze pharmacists， according to the actual conditions of our college. Using qualitative interview methods， expert questionnaires were compiled with literature research； the expert correspondence methods were employed to conduct two rounds of consultation with 10 domestic respiratory medicine experts， thus constructing an evaluation index system for the teaching quality of cough and wheeze pharmacists. The experts’ positive coefficient， authority coefficient， Kendall’s harmony coefficient， and the degree of concentration of opinions were calculated. The analytic hierarchy process （AHP） was used to determine the weight of each indicator within the index system. From June 2023 to June 2024， the teaching team enrolled 21 pharmacists in the training program. The teaching team assessed and scored the trial group （LLPM） and control group （traditional teaching model） based on the benefit indicators for pharmacists and patients in the evaluation index system， and compared the results. RESULTS This study explored the establishment of a training system for cough and wheeze pharmacists under the LLPM model， and initially established an evaluation index system using the Delphi method. In two rounds of Delphi method questionnaires， the recovery rate was 100%， with an authority coefficient exceeding 0.8， Kendall’s harmony coefficient ranging from 0.235 to 0.459， and all P-values being less than 0.05. Four primary （comprising trainee feedback， learning gains， behavioral improvements， and training performance）， 12 secondary and 33 tertiary indicators were finalized. In the empirical evaluation， the results of the two groups showed a significant benefit to the pharmacists in the trial group. Specifically， the percentage of patients receiving corticosteroids for COPD or wheeze service patients per month （80.5%）， an average increase in the number of cough and wheeze team service outpatient visits per month （compared to the same period of the previous year） of 14.8 visits per month， and the patient satisfaction score （4.9） were all significantly higher than those in the control group （P＜0.05）. CONCLUSIONS The application of the LLPM in competency training for pharmacists specializing in cough and wheeze care yields multiple benefits and holds significant guiding value. The constructed training quality evaluation index system under this model is scientific and reliable.

Liver fibrosis is a vital cause of morbidity in patients with liver diseases and developing novel anti-fibrotic drugs is imperative. Isovalerylspiramycin I (ISP I) as a major component of carrimycin applied to upper respiratory infections, was first found to possess anti-fibrotic potential. The present study aims to evaluate the functions and mechanisms of ISP I in protecting against liver fibrosis. According to our results, ISP I not only reduced the expressions of fibrogenic markers in LX-2 cells but also appeared great protective effects on liver injury and liver fibrosis in bile duct ligation (BDL) rats and carbon tetrachloride (CCl₄) mice. We proved that nucleotide-binding protein 2 (NUBP2) was the direct target of ISP I. ISP I through targeting NUBP2, increased the amount of vascular non-inflammatory molecule-1 (VNN1) on the cell membrane, which will inhibit oxidative stress and fibrosis. Simultaneously, the original carrimycin's protective effect on liver damage and fibrosis was verified. Therefore, our study provides potential agents for patients with liver fibrosis-related diseases, and the clear mechanism supports wide application in the clinic.

Objective To understand the overall development of county-level Maternal and Child Healthcare(MCH)institutions in China in 2023,and to provide a basis for strengthening the standardisation and normative management of county-level MCH institutions in China.Methods Data from the National Monitoring Information System for MCH institutions were used to conduct descriptive analyses of the establishment of all county-level MCH institutions in China,the provision of outpatient and inpatient services,and statistical analyses of the rate of compliance with the construction of county-level MCH institutions throughout the country in accordance with the relevant standards.Results In 2023,there were 2 830 county-level administrative districts nationwide,with 2 683 county-level MCH institutions actually established,an establishment rate of 94.8%.The proportion of county-level MCH institutions that provide outpatient and inpatient services is 90.1%and 60.5%respectively,and the construction rate that meets the standards is 56.4%.Among them,the construction rate of county-level MCH institutions with a population of≥300 000 was 60.5%,with the highest rate(72.3%)in the western region and the lowest rate(26.3%)in the northeastern region.The construction rate of county-level MCH institutions for counties with populations of＜300 000 was 49.7%,with the highest rate in the eastern region(61.7%)and the lowest in the northeastern region(23.6%).Conclusion The overall development of MCH institutions at the county level in China is uneven,and the construction of institutions to meet the standards is unsatisfactory,especially in counties and districts with a population of＜300 000,where the construction and development of MCH institutions need to be continuously strengthened.

Fetal malformation of cortical development(MCD)is a group of structural neurological disorders caused by abnormalities in development of cortical layer during embryogenesis,characterized by significant heterogeneity and diversity,which may lead to adverse clinical outcomes such as epilepsy and intellectual disabilities.The progresses in prenatal evaluation on fetal MCD were reviewed in this article.

Liver fibrosis is a vital cause of morbidity in patients with liver diseases and developing novel anti-fibrotic drugs is imperative.Isovalerylspiramycin Ⅰ(ISP Ⅰ)as a major component of carrimycin applied to upper respiratory infections,was first found to possess anti-fibrotic potential.The present study aims to evaluate the functions and mechanisms of ISP Ⅰ in protecting against liver fibrosis.According to our results,ISP Ⅰ not only reduced the expressions of fibrogenic markers in LX-2 cells but also appeared great protective effects on liver injury and liver fibrosis in bile duct ligation(BDL)rats and carbon tetrachloride(CCl4)mice.We proved that nucleotide-binding protein 2(NUBP2)was the direct target of ISP Ⅰ.ISP Ⅰ through targeting NUBP2,increased the amount of vascular non-inflammatory molecule-1(VNN1)on the cell membrane,which will inhibit oxidative stress and fibrosis.Simultaneously,the original carri-mycin's protective effect on liver damage and fibrosis was verified.Therefore,our study provides po-tential agents for patients with liver fibrosis-related diseases,and the clear mechanism supports wide application in the clinic.

Objective To identify potential drug target genes associated with idiopathic pulmonary fibrosis(IPF)and predict therapeutic candidates using a two-sample Mendelian randomization(MR)approach across the druggable genome.Methods Druggable genome data from the DGIdb database and Finan were integrated to identify overlapping genes.A two-sample MR analysis was performed to infer causal relationships between genes and IPF.Functional enrichment analyses,including Gene Ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG),were conducted to explore biological pathways.Drug-target interactions were predicted via DSigDB database screening,followed by molecular docking simulations to evaluate binding affinities.Results Among the 2588 overlapping druggable genes,thirty exhibited significant causal associations with IPF(P＜0.05).Four hub genes(NOD2,LATS2,LTA,and TCF7L2)were enriched in IPF-related pathways,notably Hippo and TNF signaling.Six potential therapeutics were identified:oxyphenbutazone,moexipril,α-galactosylceramide,GSK429286A,CGP74514A,and JW-7-24-1.Molecular docking confirmed strong binding affinities between these drugs and their targets.Conclusion This study has identified thirty druggable gene targets and six candidate drugs for IPF.The enrichment of hub genes in key pathways and validated drug-target interactions provide insights into IPF therapies.

BACKGROUND:Cervical spondylosis is a chronic degenerative disease that has become one of the most common and frequent diseases threatening human health.At present,the initial diagnosis of the cervical spine and its surrounding structures mainly relies on the interpretation of medical images by radiologists,which not only requires a high level of technical requirements for operators,but also has the disadvantages of strong subjectivity,high labor intensity,and low efficiency.With the rapid development of artificial intelligence technology,its powerful data processing and image recognition capabilities have shown broad application prospects in the medical field.Deep learning has also made certain progress in the research of spinal diseases.OBJECTIVE:To summarize the current status and research progress in the application of artificial intelligence technology in cervical spine imaging images in recent years,evaluating the performance of artificial intelligence models as well as future trends and challenges to be overcome.METHODS:The first author searched the relevant articles in WanFang,CNKI,and PubMed in June 2024.The Chinese search terms were"artificial intelligence,deep learning,cervical spine."English serach terms were"artificial intelligence,Al,cervical vertebrae,cervical."Finally,101 articles were included and analyzed.RESULTS AND CONCLUSION:(1)Artificial intelligence technology can realize automatic segmentation of cervical vertebrae and measurement of curvature change by segmentation,classification,landmarks recognition of medical image parts,detect cervical vertebral fracture,nerve root,and spinal cord type cervical spondylosis,identify cervical spine ossification of posterior longitudinal ligament,and predict post-surgery related risk factors and cervical vertebra maturation classification.(2)Although artificial intelligence technology has shown great potential in the field of cervical spine research,it is still in the early stages of exploration and rapid development,with unlimited room for development and innovation.