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.

BACKGROUND:During bone remodeling,bone formation and bone resorption are spatially and temporally coordinated,involving intricate interactions between osteoclasts and osteoblasts.Isoginkgetin,a flavonoid found in Ginkgo biloba,has a wide range of anticancer activity and anti-reactive oxygen species activity;however,the effect of isoginkgetin on osteoclast differentiation is unknown.OBJECTIVE:To study the effect and mechanism of action of isoginkgetin on osteoclastogenesis.METHODS:In vitro studies were performed on mouse bone marrow-derived macrophages,and cell counting kit-8 cytotoxicity assay was used to detect the effect of isoginkgetin on cell viability of bone marrow-derived macrophages.Macrophage colony-stimulating factor and receptor activator of nuclear factor kappa-B ligand were used to induce the differentiation of bone marrow-derived macrophages to osteoclasts.Network pharmacology and molecular docking and molecular dynamics simulations were used to predict the processes and targets of the effects of isoginkgetin on the differentiation of osteoclasts.Tartrate-resistant acid phosphatase staining and F-actin staining were used to detect the effects of isoginkgetin on the differentiation and function of osteoclasts.Western blot and RT-PCR were used to detect the effects of isoginkgetin on the expression of genes and proteins related to osteoclast differentiation,reactive oxygen species,and PI3K/AKT pathways.Fluorescent probes were used to detect cellular and mitochondrial reactive oxygen species levels.Flow cytometry technology was used to detect reactive oxygen species levels in cells.RESULTS AND CONCLUSION:(1)Network pharmacology results showed that isoginkgetin affected osteoporosis mainly through the PI3K-AKT pathway and cellular response to drugs and hypoxia,and GSK3β,ESR1,MCL1 and CCNA2 were the key targets.(2)Cell counting kit-8 and tartrate-resistant acid phosphatase staining results showed that isoginkgetin at 8 μmol/L had the most significant inhibitory effect on osteoclastogenesis in vitro,and F-actin results showed that isoginkgetin inhibited osteoclast cytoskeletal actin ring formation in a concentration-dependent manner.(3)Molecular dynamics simulations showed that isoginkgetin bound well to osteoclastogenesis marker proteins(NFATc1,c-Fos,CTSK,and MMP9).Western blot and RT-PCR results indicated that isoginkgetin inhibited the expression of osteoclastogenesis marker proteins and genes(NFATc1,c-Fos,CTSK,and MMP9).(4)Western blot results showed that isoginkgetin inhibited the phosphorylation level of PI3K/AKT/GSK3β and suppressed osteoclastogenesis by activating the PI3K-AKT-GSK3β pathway.(5)The results of reactive oxygen species assay showed that isoginkgetin significantly reduced receptor activator of nuclear factor kappa-B ligand-induced cellular and mitochondrial reactive oxygen species production,and inhibited the differentiation of bone marrow-derived macrophages to osteoclasts.

BACKGROUND:β-Caryophyllene has a variety of pharmacological activities such as antioxidant,anti-inflammatory and anti-apoptotic,which may have a better therapeutic effect on osteoarthritis.OBJECTIVE:To investigate the effect and mechanism of β-caryophyllene on mouse osteoarthritis.METHODS:Forty C57BL/6J mice were randomly divided into sham group,model group,low-dose β-caryophyllene group and high-dose β-caryophyllene group,with 10 mice in each group.Hulth method was used to construct an osteoarthritis model in the latter three groups.Four weeks after modeling,70 and 140 mg/kg/d β-caryophyllene was intragastrically given in the low-and high-dose β-caryophyllene groups,respectively,and normal saline was given by gavage in the sham group and the model group,once a day,for 4 weeks.After administration,knee joint morphological changes were observed by hematoxylin-eosin staining,serum levels of inflammatory factors(tumor necrosis factor-α,interleukin-1β,interleukin-6,and interleukin-10)were detected by ELISA,and oxidative stress indexes(glutathione peroxidase,superoxide dismutase,and malondialdehyde)were detected by chemiluminescence.The expression levels of key proteins in the Sonic hedgehog(Shh)/glioma associated oncogene homolog 1(Gli1)signaling pathway were detected by immunohistochemistry and western blot.RESULTS AND CONCLUSION:(1)Compared with the sham group,a large number of inflammatory cells infiltrated in the knee joint of mice in the model group,cartilage tissue was seriously damaged,serum levels of tumor necrosis factor-α,interleukin-1β,interleukin-6,interleukin-10 and malondialdehyde were significantly increased(P＜0.01),the activities of glutathione peroxidase and superoxide dismutase were significantly decreased(P＜0.01),and the relative expression levels of Shh and Gli1 in the knee joint were significantly increased(P＜0.01).(2)Compared with the model group,in the low-and high-dose β-caryophyllene groups,inflammatory cell infiltration in the mouse knee joint was decreased,cartilage tissue injury was alleviated,serum levels of tumor necrosis factor-α,interleukin-1 β,interleukin-6 and malondialdehyde were significantly decreased(P＜0.05),the activities of glutathione peroxidase and superoxide dismutase were significantly increased(P＜0.01),and the expression levels of Shh and Gli1 in the knee joint were significantly decreased(P＜0.01).The above-mentioned improvements were more significant in the high-dose β-caryophyllene group than the low-dose β-caryophyllene group.To conclude,β-caryophyllene can improve osteoarthritis,and its mechanism may be related to reducing inflammation and oxidative stress damage by regulating the Shh/Gli1 signaling pathway.

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 explore whether the long-term and frequent use of citrate anticoagulants negatively affects the bone metabolism balance of female frequent plateletpheresis donors, so as to better protect their health. Methods: A total of 65 female plateletpheresis donors and 55 female whole-blood donors from Guangzhou Blood Center (May to December 2024) were enrolled as experimental and control groups respectively, stratified into age subgroups (18-39 years and 40-60 years). Serum levels of 25-hydroxyvitamin D [25(OH)D], procollagen type I N-terminal propeptide (PINP), osteocalcin (OC), and type I collagen carboxy-terminal telopeptide (CTX) were measured. Differences in bone metabolism markers between experimental and control groups across age subgroups were compared. ANOVA was used to analyze dose-response relationships between donation age, annual apheresis donation frequency, and biochemical indicators. Results: In the 40-60 age subgroup, 25(OH)D levels were significantly lower in the experimental group (P<0.05), exhibiting a linear increase with age and a linear decrease with annual donation frequency. No significant differences in CTX or PINP levels were observed between experimental and control groups in either age subgroup. Conclusion: High-frequency plateletpheresis donation does not disrupt bone metabolic balance in female donors. However, it is associated with reduced vitamin D levels in female donors aged >40 years, potentially increasing the risk of osteoporosis. Vitamin D supplementation is recommended for high-frequency female plateletpheresis donors in this age group.

Objective To investigate the role and regulatory mechanism of LINC00657 in the progression of cervical cancer. Methods Bioinformatics analysis predicted potential binding sites between LINC00657 and miR-30a-5p and between miR-30a-5p and Skp2. These sites were verified by using RNA immunoprecipitation and dual-luciferase reporter experiments. LINC00657, miR-30a-5p, and Skp2 mRNA expression levels in cervical cancer tissues and cell lines were assessed by utilizing RT-qPCR. Western blot analysis was employed to examine the protein levels of Skp2 in cells and subcutaneous xenograft tumor models in nude mice. Immunohistochemistry was applied to analyze Skp2 expression in animal tissues. The cellular processes of cervical cancer cell lines were evaluated through CCK-8, scratch, and Transwell assays. Results LINC00657 and Skp2 presented binding sites for miR-30a-5p. In cervical cancer, LINC00657 and Skp2 showed high expression levels (P<0.05), whereas miR-30a-5p displayed low expression (P<0.05). Functional experiments demonstrated that linc00657 upregulates Skp2 expression, a process that is dependent on its sequestration of miR-30a-5p. Conclusion LINC00657 promoted the malignant progression of cervical cancer by upregulating Skp2 expression through specifically sequestering miR-30a-5p, thereby relieving its inhibitory effect on the target gene Skp2.

BACKGROUND:During bone remodeling,bone formation and bone resorption are spatially and temporally coordinated,involving intricate interactions between osteoclasts and osteoblasts.Isoginkgetin,a flavonoid found in Ginkgo biloba,has a wide range of anticancer activity and anti-reactive oxygen species activity;however,the effect of isoginkgetin on osteoclast differentiation is unknown.OBJECTIVE:To study the effect and mechanism of action of isoginkgetin on osteoclastogenesis.METHODS:In vitro studies were performed on mouse bone marrow-derived macrophages,and cell counting kit-8 cytotoxicity assay was used to detect the effect of isoginkgetin on cell viability of bone marrow-derived macrophages.Macrophage colony-stimulating factor and receptor activator of nuclear factor kappa-B ligand were used to induce the differentiation of bone marrow-derived macrophages to osteoclasts.Network pharmacology and molecular docking and molecular dynamics simulations were used to predict the processes and targets of the effects of isoginkgetin on the differentiation of osteoclasts.Tartrate-resistant acid phosphatase staining and F-actin staining were used to detect the effects of isoginkgetin on the differentiation and function of osteoclasts.Western blot and RT-PCR were used to detect the effects of isoginkgetin on the expression of genes and proteins related to osteoclast differentiation,reactive oxygen species,and PI3K/AKT pathways.Fluorescent probes were used to detect cellular and mitochondrial reactive oxygen species levels.Flow cytometry technology was used to detect reactive oxygen species levels in cells.RESULTS AND CONCLUSION:(1)Network pharmacology results showed that isoginkgetin affected osteoporosis mainly through the PI3K-AKT pathway and cellular response to drugs and hypoxia,and GSK3β,ESR1,MCL1 and CCNA2 were the key targets.(2)Cell counting kit-8 and tartrate-resistant acid phosphatase staining results showed that isoginkgetin at 8 μmol/L had the most significant inhibitory effect on osteoclastogenesis in vitro,and F-actin results showed that isoginkgetin inhibited osteoclast cytoskeletal actin ring formation in a concentration-dependent manner.(3)Molecular dynamics simulations showed that isoginkgetin bound well to osteoclastogenesis marker proteins(NFATc1,c-Fos,CTSK,and MMP9).Western blot and RT-PCR results indicated that isoginkgetin inhibited the expression of osteoclastogenesis marker proteins and genes(NFATc1,c-Fos,CTSK,and MMP9).(4)Western blot results showed that isoginkgetin inhibited the phosphorylation level of PI3K/AKT/GSK3β and suppressed osteoclastogenesis by activating the PI3K-AKT-GSK3β pathway.(5)The results of reactive oxygen species assay showed that isoginkgetin significantly reduced receptor activator of nuclear factor kappa-B ligand-induced cellular and mitochondrial reactive oxygen species production,and inhibited the differentiation of bone marrow-derived macrophages to osteoclasts.

BACKGROUND:β-Caryophyllene has a variety of pharmacological activities such as antioxidant,anti-inflammatory and anti-apoptotic,which may have a better therapeutic effect on osteoarthritis.OBJECTIVE:To investigate the effect and mechanism of β-caryophyllene on mouse osteoarthritis.METHODS:Forty C57BL/6J mice were randomly divided into sham group,model group,low-dose β-caryophyllene group and high-dose β-caryophyllene group,with 10 mice in each group.Hulth method was used to construct an osteoarthritis model in the latter three groups.Four weeks after modeling,70 and 140 mg/kg/d β-caryophyllene was intragastrically given in the low-and high-dose β-caryophyllene groups,respectively,and normal saline was given by gavage in the sham group and the model group,once a day,for 4 weeks.After administration,knee joint morphological changes were observed by hematoxylin-eosin staining,serum levels of inflammatory factors(tumor necrosis factor-α,interleukin-1β,interleukin-6,and interleukin-10)were detected by ELISA,and oxidative stress indexes(glutathione peroxidase,superoxide dismutase,and malondialdehyde)were detected by chemiluminescence.The expression levels of key proteins in the Sonic hedgehog(Shh)/glioma associated oncogene homolog 1(Gli1)signaling pathway were detected by immunohistochemistry and western blot.RESULTS AND CONCLUSION:(1)Compared with the sham group,a large number of inflammatory cells infiltrated in the knee joint of mice in the model group,cartilage tissue was seriously damaged,serum levels of tumor necrosis factor-α,interleukin-1β,interleukin-6,interleukin-10 and malondialdehyde were significantly increased(P＜0.01),the activities of glutathione peroxidase and superoxide dismutase were significantly decreased(P＜0.01),and the relative expression levels of Shh and Gli1 in the knee joint were significantly increased(P＜0.01).(2)Compared with the model group,in the low-and high-dose β-caryophyllene groups,inflammatory cell infiltration in the mouse knee joint was decreased,cartilage tissue injury was alleviated,serum levels of tumor necrosis factor-α,interleukin-1 β,interleukin-6 and malondialdehyde were significantly decreased(P＜0.05),the activities of glutathione peroxidase and superoxide dismutase were significantly increased(P＜0.01),and the expression levels of Shh and Gli1 in the knee joint were significantly decreased(P＜0.01).The above-mentioned improvements were more significant in the high-dose β-caryophyllene group than the low-dose β-caryophyllene group.To conclude,β-caryophyllene can improve osteoarthritis,and its mechanism may be related to reducing inflammation and oxidative stress damage by regulating the Shh/Gli1 signaling pathway.

Rheumatoid arthritis （RA） is a common chronic systemic autoimmune disease with synovitis as the main manifestation， which often causes joint swelling and pain or even deformity. It is considered to be an incurable lifelong disease. Although the current Western medicine treatment can alleviate the progression of the disease， it has the clinical limitations of liver injury， cardiovascular complications， and other adverse reactions， along with easy recurrence. Traditional Chinese medicine （TCM） has a long history and has the advantages of individualized treatment and fewer adverse reactions. It can effectively relieve the symptoms of joint swelling and pain in RA patients and slow down the progression of bone destruction， which has attracted wide concern in the medical community. Janus kinase （JAK）/signal transducer and activator of transcription （STAT） signaling pathway is an important intracellular pathway involved in cell proliferation， differentiation， apoptosis， immune regulation， and other biological behaviors， and plays an important role in the pathophysiological process of RA. In recent years， many studies have confirmed that TCM monomers and compounds can inhibit inflammation and angiogenesis by regulating the JAK/STAT signaling pathway， induce apoptosis and inhibit proliferation of fibroblast-like synoviocytes （FLS）， regulate immune response， and thus exert an effect in the treatment of RA. However， there is still a lack of comprehensive and systematic induction and overview. Therefore， by searching the relevant literature in China National Knowledge Infrastructure （CNKI） and PubMed databases from 2009 to 2024， this study described the mechanism of the JAK/STAT signaling pathway in the occurrence and development of RA and summarized the research progress of TCM monomers and compounds in regulating the JAK/STAT signaling pathway in RA intervention. The study aims to provide new ideas and strategies for the clinical treatment of RA with TCM and the research and development of new drugs.

AIM: To explore the factors associated with significant corneal astigmatism during the perioperative period in patients with pterygium. METHODS: Patients with primary pterygium presenting at Shanxi Eye Hospital between February and June 2025 were enrolled. All patients underwent medical history collection. Pre- and postoperative data were obtained using Pentacam, anterior segment photography, Image J software, and anterior segment optical coherence tomography(AS-OCT). All patients underwent pterygium excision combined with autologous bulbar conjunctival flap transplantation under local infiltration anesthesia. RESULTS: A total of 76 patients(76 eyes)with pterygium were finally enrolled(30 males, 46 females)with a mean age of 62.2±8.2 y. The mean length of corneal invasion by pterygium was 3.61±0.89 mm, the mean depth of invasion into the anterior corneal surface was 0.15±0.09 mm, and the median area of corneal invasion was 10.25(6.90, 18.75)mm2. The median preoperative corneal astigmatism was 1.50(0.70, 5.45)D. Median astigmatism was 0.8(0.40, 1.28)D at 2 wk postoperatively and 0.60(0.30, 1.15)D at 1 mo postoperatively. Patient age showed a positive correlation with preoperative astigmatism, and with residual astigmatism at 2 wk and 1 mo postoperatively(all P<0.05). The length of corneal invasion was positively correlated with preoperative astigmatism and residual astigmatism at both postoperative timepoints(P<0.01). The depth of invasion showed no significant linear correlation with astigmatism at any stage(P=0.250, 0.761, 0.686). The area of corneal invasion was positively correlated with astigmatism at all stages(P<0.01). Patients were grouped based on significant astigmatism(≥1.0 D)and non-significant astigmatism(<1.0 D), after adjusting for other variables, age(P=0.031)and the area of corneal invasion(P=0.004)were identified as risk factors for significant astigmatism. Pterygium invasion length was not significant factors(P>0.05). Receiver operating characteristic(ROC)analysis showed the highest area under the curve(AUC)for the invasion area(AUC=0.915). CONCLUSION: Significant preoperative corneal astigmatism in pterygium patients is correlated with patient age, the length of corneal invasion, and the area of invasion. The area of pterygium invasion into the cornea is the strongest predictor of significant preoperative corneal astigmatism.