Osteoporosis (OP), a prevalent public health concern primarily caused by osteoclast-induced bone resorption, requires potential therapeutic interventions. Natural compounds show potential as therapeutics for postmenopausal OP. Emerging evidence from in vitro osteoclastogenesis assay suggests that aconine (AC) serves as an osteoclast differentiation regulator without causing cytotoxicity. However, the in vivo functions of AC in various OP models need clarification. To address this, we administered intraperitoneal injections of AC to ovariectomy (OVX)-induced OP mice for 8 weeks and found that AC effectively reversed the OP phenotype of OVX mice, leading to a reduction in vertebral bone loss and restoration of high bone turnover markers. Specifically, AC significantly suppressed osteoclastogenesis in vivo and in vitro by decreasing the expression of osteoclast-specific genes such as NFATc1, c-Fos, Cathepsin K, and Mmp9. Importantly, AC can regulate osteoclast ferroptosis by suppressing Gpx4 and upregulating Acsl4, which is achieved through inhibition of the phosphorylation of I-κB and p65 in the NF-κB signaling pathway. These findings suggest that AC is a potential therapeutic option for managing OP by suppressing NF-κB signaling-mediated osteoclast ferroptosis and formation.

Osteoporosis (OP) is a common skeletal disease, characterized by decreased bone formation and increased bone resorption. As a novel Chinese medicine formula, Zhuanggu Busui formula (ZGBSF) has been proved to be an effective prescription for treating OP in clinic, however, the pharmacological mechanisms underlying the beneficial effects remain obscure. In this study, we explored the pharmacological mechanisms of ZGBSF against OP via network pharmacology analysis coupled with in vivo experimental validation. The results of the network pharmacology analysis showed that a total of 86 active ingredients and 164 targets of ZGBSF associated with OP were retrieved from the corresponding databases, forming an ingredient-target-disease network. The protein-protein interaction (PPI) network manifested that 22 core targets, including Caspase-3, BCL2L1, TP53, Akt1, etc, were hub targets. Moreover, functional enrichment analyses revealed that PI3K-Akt and apoptosis signalings were significantly enriched by multiple targets and served as the targets for in vivo experimental study validation. The results of animal experiments revealed that ZGBSF not only reversed the high expression of Caspase-3, Bax, Prap, and low expression of Bcl-2 in osteoblasts of the OP mouse model but also contributed to the phosphorylation of Akt1 and expression of PI3K, thereby promoting osteogenesis and ameliorating the progression of OP. In conclusion, this study systematically and intuitively illustrated that the possible pharmacological mechanisms of ZGBSF against OP through multiple ingredients, targets, and signalings, and especially the inhibition of the apoptosis and the activation of PI3K-Akt signaling.

Study Design.: A retrospective, cross-sectional cohort study. Objective.: This study aimed to investigate the association between paraspinal muscle parameters and single-segment degenerative lumbar spondylolisthesis (DLS). Summary of Background Data.: The relationship between lumbar paraspinal muscle morphology and single-segment DLS remains unclear. Methods.: A retrospective review was conducted on 115 patients with L4/5 single-segment DLS and 105 subjects without DLS. Two independent investigators assessed the relative cross-sectional area and fat infiltration rate of the multifidus, erector spinae, and psoas major at L3/4, L4/5, and L5/S1 levels, comparing these measurements between the 2 groups. In addition, binary logistic regression analysis was performed with DLS as the dependent variable to analyze the relative cross-sectional area and fat infiltration rate of different paraspinal muscles. Within the DLS group, the correlation between paraspinal muscle characteristics and the anteroposterior diameter of the spinal canal was examined. Results.: The fat infiltration rate of multifidus, erector spinae, and psoas major was higher in the DLS group than in the control group, whereas the relative cross-sectional area of multifidus and psoas major was lower in the DLS group. Binary logistic regression analysis revealed a significant correlation between the fat infiltration rate of multifidus and psoas major and DLS. The relative cross-sectional area of multifidus and erector spinae was significantly smaller below the affected segment in the DLS group compared with the control group. A significant positive correlation was observed between the relative cross-sectional area of multifidus and erector spinae and the anteroposterior diameter of the spinal canal. Conclusion.: There is a close association between paraspinal muscle degeneration and single-segment DLS, with an increased relative cross-sectional area of the multifidus and psoas major possibly being risk factors for single-segment DLS. The restoration or enhancement of paraspinal muscle function could potentially serve as a pivotal target for the prevention and treatment of single-segment DLS. Level of Evidence.: Level III.

The paraspinal muscles play a critical role in maintaining lumbar spine stability, and different muscles may have varying impacts on lumbar disc degeneration (LDD). However, studies exploring these relationships remain relatively limited. This study aimed to investigate the relationship between various paravertebral muscles and LDD and to develop and validate a predictive model for LDD using machine learning (ML). Retrospective cohort study PATIENT SAMPLE: A retrospective analysis was performed on hospitalized patients who underwent computed tomography (CT) and magnetic resonance imaging (MRI) examinations for chronic low back pain from February 2018 to January 2023. The primary outcome measures included model performance metrics such as receiver operating characteristic (ROC) curves, accuracy, sensitivity, specificity, F1 score, positive predictive value (PPV), negative predictive value (NPV), and calibration curves. Clinical decision-making benefits were assessed using decision curve analysis (DCA). Secondary outcome measures focused on model interpretability, evaluated through SHapley Additive exPlanations (SHAP), which identified key predictors and quantified their contributions to LDD prediction. This study enrolled 518 patients as the internal cohort, who were randomly assigned to a training set (70%) and a test set (30%). The Synthetic Minority Oversampling Technique (SMOTE) was applied to mitigate class imbalance in the training set. Model parameters were optimized using grid search and 10-fold cross-validation to develop four machine learning models: Extreme Gradient Boosting (XGBoost), Random Forest (RF), Logistic Regression (LR), and Decision Tree (DT). External validation was performed using data from 343 patients from different tertiary medical centers. Paraspinal muscle parameters on lumbar spine CT and MRI images were measured using ImageJ, and LDD was evaluated based on the Pfirrmann grading system. Spearman correlation analysis and logistic regression were performed to assess factors associated with LDD. Model performance was evaluated using metrics such as ROC curves, accuracy, sensitivity, F1 score, PPV, NPV, calibration curves, and DCA. The SHAP method was employed to interpret the ML models. This study included a total of 861 patients for analysis. In the external validation cohort, the XGBoost model demonstrated the best performance, achieving an AUC of 0.880 (95% CI: 0.826-0.935). Its accuracy (0.819), specificity (0.841), and positive predictive value (PPV =0.958) outperformed other models. Notably, it also exhibited superior sensitivity (0.814) and F1-score (0.880).. SHAP analysis further revealed that age, the psoas muscle index (PMI), and the functional cross-sectional area (fCSA) of the multifidus muscle were critical predictors of LDD. In this study, an LDD prediction model was developed using paravertebral muscle quantitative data and ML algorithms, with SHAP analysis incorporated to enhance model interpretability. The XGBoost model demonstrated the best predictive performance and holds potential to guide early clinical prevention and treatment.

Lumbar disc herniation (LDH) is a common, disabling musculoskeletal disorder. Magnetic resonance imaging has clarified the natural history of lumbar disc lesions and has documented that disc lesions can become smaller and can even be completely resorbed. Previous studies have confirmed that some traditional Chinese medicine (TCM) therapies can promote resorption of the protrusion. However, high-quality research evidence is needed to support the effectiveness of the protocol. Objective: This clinical trial aims to establish whether TCM can promote the resorption of LDH and to assess the efficacy of such therapy for LDH, thereby evaluating its clinical effect. Methods: The present study design is for a single-center, 2-arm, open-label randomized controlled trial. A total of 150 eligible LDH patients will be randomly assigned to either a TCM treatment group or a control group in a 1:1 ratio. Patients in the TCM group will be administered a TCM decoction for 4 weeks. Patients in the conventional drug control group will be instructed to take a specific daily dose of celecoxib. The primary outcome measure is the change from baseline in the volume of the protrusion, as assessed using MR images. Secondary outcome measures include visual analog scale pain scores and Japanese Orthopaedic Association scores assessed at 3 and 6 months. Discussion: The design and methodological rigor of this trial will allow evaluation of the basic clinical efficacy and safety data for TCM in the treatment of patients with LDH. The trial will also assess whether TCM can promote the resorption of LDH. This research will therefore help provide a solid foundation for the clinical treatment of LDH and for future research in TCM therapy. Trial registration: ChiCTR1900022377.

Purpose: Non-specific chronic neck pain (NSCNP) is an increasingly common musculoskeletal disease and an important issue in the global healthcare system. Some studies have shown that the combination of manual therapy and exercise is effective in treating NSCNP but still with several limitations. Traditional Chinese manual therapy (tuina) is a Chinese manual therapy that consists of soft tissue manipulation and spinal manipulation. This study aims to design a randomized controlled trial to assess the effect of a tuina combined with specific therapeutic neck exercise modified protocol for NSCNP patients. Patients and Methods: This is a study protocol for a randomized, participant-, assessor- and analyst-blinded controlled trial. Eighty-eight eligible NSCNP patients will be randomly allocated into tuina combined with specific therapeutic neck exercise group (TSTE group) and tuina combined with sham therapeutic neck exercise group (TS group) in a ratio of 1:1. All participants will receive 8 treatment sessions applied in 4 weeks and then be followed up for another 12 weeks. Clinical data will be collected at baseline, during treatment phase (at the 2- and 4-week) and at the 8-, 12-, 16-week follow-ups. The primary outcome is the changes in neck pain intensity (visual analogue scale). The secondary outcomes include neck disability (Neck Disability Index), cervical range of motion (ROM), neck muscle endurance, cervical muscle cross-sectional area, cervical curvature and analgesic consumption. Adverse events will be collected and recorded throughout the study. Conclusion: We will discuss whether our tuina combined with specific therapeutic neck exercise modified protocol is more effective at improving pericervical muscle endurance, ROM, cervical muscle cross-sectional area and cervical curvature than tuina alone, thereby decreases neck pain and disability in individuals with NSCNP more effectively. Trial Registration: Chinese Clinical Trials Registry, ChiCTR2300067903. Registered on 31 January 2023.