The aim of this study was to identify risk factors for progressive local kyphosis (PLK) following percutaneous vertebroplasty/kyphoplasty (PVP/PKP) in patients with osteoporotic vertebral fracture (OVF) and to develop a predictive model based on the osteoporotic fracture (OF) classification, integrating baseline characteristics, imaging parameters, and surgical factors. This model aims to preoperatively identify high-risk patients for PLK and to optimize perioperative surgical decision-making. This retrospective cohort study included 374 OVF patients who underwent single-level PVP/PKP with a ≥ 2-year follow-up. Patients were randomly divided into a derivation cohort (n = 267) and a validation cohort (n = 107). Multidimensional data, including demographics, bone mineral density, comorbidities, imaging parameters (local kyphotic angle [LKA], vertebral compression ratio, OF classification, and endplate integrity), surgical details (cement volume/distribution), and clinical outcomes (visual analog scale [VAS]/Oswestry Disability Index [ODI]), were collected. PLK was defined as a ≥ 10° increase in the LKA at the final follow-up compared with that on postoperative Day 1. Predictors were identified using random forest, least absolute shrinkage and selection operator (LASSO) regression, and decision tree analyses. A risk scoring system was developed via logistic regression and validated using receiver operating characteristic (ROC) curves, Hosmer-Lemeshow tests, calibration curves, and decision curve analysis (DCA). Among 267 patients in the derivation cohort, 43 (16.1

Excessive mechanical stress is a major cause of intervertebral disc degeneration (IVDD). Macrophages can sense physical signals, but their role in responding to mechanical stress within the disc to maintain homeostasis is unclear. This study investigates the function of macrophage-derived legumain (LGMN) in IVDD. Single-cell RNA sequencing data of human disc samples were analyzed. Macrophage-specific Lgmn knockout (LgmnF/F;LysMCre) and nucleus pulposus cell (NPC)-specific Yap1 knockin (Yap1LSL/LSL; Col2a1Cre) mice were generated to study IVDD progression in vivo using a lumbar spine instability model. In vitro, NPCs and macrophages were cultured under mechanical compression. Molecular interactions were predicted with AlphaFold3 and validated by coimmunoprecipitation and mass spectrometry. Signaling pathways were analyzed via RNA sequencing, western blot, and chromatin immunoprecipitation. Engineered LGMN-overexpressing small extracellular vesicles (sEVs) were tested therapeutically in a rat compression model. LGMN was significantly upregulated in human and animal degenerate discs, primarily in macrophages. Conditional knockout in macrophages accelerated IVDD in mice. Mechanistically, macrophage-derived LGMN bound to integrin αvβ3 on NPCs, inhibiting RhoA activity and activating the Hippo pathway. This led to phosphorylation and cytoplasmic retention of YAP1, which suppressed mechanical stress-induced ferroptosis in NPCs. Mechanical stress promoted STAT3 nuclear translocation in macrophages, directly enhancing LGMN transcription. Intradiscal delivery of LGMN-enriched sEVs alleviated IVDD in rats. Macrophage-derived LGMN is a key mechanosensitive regulator that ameliorates IVDD by inhibiting NPC ferroptosis via the integrin αvβ3–Hippo pathway, revealing a novel endogenous protective mechanism and a potential therapeutic strategy.

Intervertebral disc degeneration (IDD) is the main cause of low back pain, which is closely related to an imbalance in extracellular matrix decomposition–anabolism mediated by immune inflammation. Duhuo Jisheng decoction (DHJSD) is effective in treating IDD, but its specific mechanism of action remains unclear and warrants further study. This study aimed to investigate the role of DHJSD in IDD treatment and its underlying mechanisms of action, providing potential therapeutic targets for IDD. High-performance liquid chromatography‒mass spectrometry (HPLC‒MS/MS) was employed to characterize the chemical composition of DHJSD. A Cell Counting Kit-8 (CCK-8) was used to detect the effects of DHJSD on the viability of pressure-treated nucleus pulposus (NP) cells. NP cells were randomly divided into three groups: control, pressure, and DHJSD groups. Western blotting was used to detect the expression of NLRP3, ASC, caspase-1, IL-1β, collagen II, aggrecan, Sox-9, MMP-3, MMP-13, and Adamts-4 in the aforementioned three groups of cells. An immunofluorescence assay was used to detect NLRP3 expression. Additional groups included the DHJSD + dimethyl sulfoxide (DMSO) and DHJSD + cyclosporine A groups. The expression of mitophagy-related factors, the NLRP3 inflammasome, and subsequent inflammatory reactions were detected by Western blotting and immunofluorescence. Network pharmacology and molecular docking were used to explore the key components and key genes of DHJSD involved in treating IDD. Finally, we verified the bioinformatics results using a rat tail acupuncture model of IDD. DHJSD-containing serum improved NP cell viability; the optimal intervention concentration was 20

STUDY DESIGN:Retrospective cohort study. OBJECTIVE:To investigate risk factors for progressive kyphosis (PK) following percutaneous kyphoplasty (PKP) and develop a validated nomogram for individualized risk prediction. SUMMARY OF BACKGROUND DATA:PK after PKP significantly impacts patient outcomes, yet its pathogenesis remains incompletely understood. While paravertebral muscle (PVM) degeneration has been implicated in spinal pathology, its independent contribution to PK after PKP has not been systematically quantified, and no clinical prediction model incorporating muscle quality exists. METHODS:This study enrolled 330 elderly patients (aged ≥60 y) who underwent single-level PKP for acute or subacute osteoporotic vertebral compression fractures (2013-2022), with a minimum follow-up of 24 months (median 39 mo). PK was defined as an increase in local Cobb angle >10° from immediate postoperative to final follow-up. Patients were randomly divided into training (n=231, 70%) and validation (n=99, 30%) sets. LASSO regression was used for variable selection, followed by multivariable logistic regression to identify independent risk factors and construct a nomogram. PVM fat infiltration (FI) was quantified on axial T2-weighted MRI at the L4/5 level using ImageJ. Model performance was assessed by AUC, calibration plots, and decision curve analysis. RESULTS:Four independent predictors were identified: age (OR=1.107, P=0.012), preoperative paravertebral muscle fat infiltration (OR=1.116, P<0.001), preoperative Cobb angle (OR=1.227, P=0.001), and black line signal on MRI (OR=3.251, P=0.015). The nomogram showed excellent discrimination in training (AUC=0.885) and validation (AUC=0.881) sets, with good calibration and net benefit. An online dynamic nomogram was developed for clinical use (https://dynamicnomogramlee.shinyapps.io/DynNomApp/). CONCLUSION:The nomogram incorporating age, paravertebral muscle fat infiltration, preoperative Cobb angle, and black line signal provides accurate, individualized prediction of progressive kyphosis after kyphoplasty, enabling early identification of high-risk patients for targeted preventive strategies.

This study aimed to investigate the association between the dietary index for gut microbiota (DI-GM) and the risk of osteoporosis in postmenopausal women aged 50 years and older in the United States. A total of 3520 postmenopausal women aged 50 years and older were selected from the National Health and Nutrition Examination Survey conducted from 2007 to 2018. Participants' DI-GM scores were obtained via a dietary questionnaire, and femoral bone mineral density was measured using dual-energy x-ray absorptiometry (DXA). Weighted logistic regression was used to analyze the association between DI-GM and osteoporosis risk. Subgroup analyses were performed to examine the association between DI-GM and osteoporosis risk in different subgroups. Participants were categorized into 4 groups based on DI-GM quartiles, with the lowest quartile (0-4) serving as the reference. After adjusting for covariates, compared with the reference group, participants in the second highest (DI-GM score of 6) and highest (DI-GM score ≥ 7) quartiles exhibited a 41% (OR: 0.59, 95% CI: 0.42-0.84) and 44% (OR: 0.56, 95% CI: 0.38-0.84), respectively, reduced risk of osteoporosis. Subgroup analysis revealed that this association was consistent across different age groups of postmenopausal women but was statistically significant only among White women. This study of postmenopausal women aged 50 and older in the United States demonstrated that those with higher DI-GM scores had a lower risk of osteoporosis compared to those with lower scores. This finding suggests that dietary intake increasing beneficial components of the gut microbiota may have a positive role in the prevention of postmenopausal osteoporosis.

Intervertebral disc degeneration (IDD) is a common musculoskeletal system disease, which is one of the most important causes of low back pain. Despite the high prevalence of IDD, current treatments are limited to relieving symptoms, and there are no effective therapeutic agents that can block or reverse the progression of IDD. Oxidative stress, the result of an imbalance between the production of reactive oxygen species (ROS) and clearance by the antioxidant defense system, plays an important role in the progression of IDD. Polyphenols are antioxidant compounds that can inhibit ROS production, which can scavenge free radicals, reduce hydrogen peroxide production, and inhibit lipid oxidation in nucleus pulposus (NP) cells and IDD animal models. In this review, we discussed the antioxidant effects of polyphenols and their regulatory role in different molecular pathways associated with the pathogenesis of IDD, as well as the limitations and future prospects of polyphenols as a potential treatment of IDD.

Suppressing bone mesenchymal stem cell (BMSC) ferroptosis is expected to optimize BMSCs-based therapy for intervertebral disc degeneration (IVDD). Our previous study revealed that Prominin-2 could protect against ferroptosis by decreasing cellular Fe2+ content and inhibiting transcription regulator protein BACH1 (BACH1) expression. In this study we probed the molecular mechanisms underlying the Prominin-2/BACH1 pathway in BMSC ferroptosis. Using an array of in vitro and in vivo experiments we found that heat shock factor protein 1 (HSF1) activates PROM2 (encoding protein Prominin-2) transcription and elevated Prominin-2 expression. Furthermore, we showed that Prominin-2 attenuates ferroptosis induced by tert-butyl hydroperoxide (TBHP) through promoting BACH1 ubiquitination and degradation. Inhibition of BACH1 expression reversed TBHP-stimulated down expression of glutaminase kidney isoform, mitochondrial (GLS), which plays a crucial role in protecting BMSCs against ferroptosis. Targeting the Prominin-2/BACH1 axis has also been shown to improve BMSC survival post-transplantation and mitigate IVDD progression by inhibiting ferroptosis. Our results support a new mechanistic insight into the regulation of the Prominin-2/BACH1/GLS pathway in BMSC ferroptosis. These finding could lead to potential therapeutic targets to improve the survival of engrafted BMSCs under oxidative stress circumstances.

Targeting cellular senescence and senescence associated secretory phenotype (SASP) through autophagy has emerged as a promising intervertebral disc (IVD) degeneration (IDD) treatment strategy in recent years. This study aimed to clarify the role and mechanism of autophagy in preventing IVD SASP. Methods involved in vitro experiments with nucleus pulposus (NP) tissues from normal and IDD patients, as well as an in vivo IDD animal model. GATA4's regulatory role in SASP was validated both in vitro and in vivo, while autophagy modulators were employed to assess their impact on GATA4 and SASP. Transcriptomic sequencing identified oxidized low-density lipoprotein receptor 1 (OLR1) as a key regulator of autophagy and GATA4. A series of experiments manipulated OLR1 expression to investigate associated effects. Results demonstrated significantly increased senescent NP cells (NPCs) and compromised autophagy in IDD patients and animal models, with SASP closely linked to IDD progression. The aged disc milieu impeded autophagic GATA4 degradation, leading to elevated SASP expression in senescent NPCs. Restoring autophagy reversed senescence by degrading GATA4, hence disrupting the SASP cascade. Moreover, OLR1 was identified for its regulation of autophagy and GATA4 in senescent NPCs. Silencing OLR1 enhanced autophagic activity, suppressing GATA4-induced senescence, and SASP expression in senescent NPCs. In conclusion, OLR1 was found to control autophagy-GATA4 and SASP, with targeted OLR1 inhibition holding promise in alleviating GATA4-induced senescence and SASP expression while delaying extracellular matrix degradation, offering a novel therapeutic approach for IDD management.

Degenerative scoliosis (DS) is a significant health concern, affecting approximately 32-68% of the Chinese population aged 65 and above. This study aims to investigate the correlation between multifidus muscle atrophy and the severity of spinal curvature in DS patients, thereby providing evidence-based recommendations for the clinical prevention and management of DS. After applying the inclusion and exclusion criteria, 231 patients with chronic low back pain admitted to the Department of Spinal Surgery, Zhongda Hospital affiliated with Southeast University between January 2023 and January 2024 were ultimately selected as the study population. Based on imaging diagnosis, chronic low back pain patients without DS were assigned to the control group (non-DS, n = 81), while patients with scoliosis were assigned to the observation group (DS, n = 150). The observation group was further subdivided into mild scoliosis (n = 72), moderate scoliosis (n = 56), and severe scoliosis (n = 22) groups based on the degree of curvature. ImageJ software was used to measure the cross-sectional area (CSA) of the multifidus muscle at the mid-level of L4 and L5 on T2-weighted magnetic resonance imaging (MRI) scans and calculate the degree of atrophy. The proportion of males and bone mineral density (BMD) were significantly higher in the non-DS group compared to the DS group (P < 0.05). The multifidus cross-sectional area (CSA) and functional cross-sectional area ratio (LCSA/GCSA) were significantly higher in the non-DS group than in the DS group (P < 0.05). Patients in the severe scoliosis group were significantly older than those in the mild and moderate groups, and had significantly lower BMD than the mild group (P < 0.05). The LCSA/GCSA was highest in the mild scoliosis group, lowest in the severe scoliosis group, and intermediate in the moderate group (P < 0.05). CSA was significantly higher in the mild scoliosis group than in the severe group (P < 0.05). In the mild and moderate scoliosis groups, the convex-side CSA and LCSA/GCSA were significantly greater than those on the concave side (P < 0.001). In the severe scoliosis group, no significant difference was found in convex-side versus concave-side CSA (P = 0.307), but convex-side LCSA/GCSA remained significantly greater than concave-side (P = 0.007). Pearson correlation and linear regression analysis showed no correlation between multifidus LCSA/GCSA and Cobb angle in non-DS patients (P > 0.05), but a significant negative correlation existed in DS patients (P < 0.05). The absolute value of the correlation coefficient increased with worsening scoliosis severity (severe group > moderate group > mild group). Multifidus muscle atrophy is closely associated with degenerative scoliosis. Multifidus LCSA/GCSA negatively correlates with scoliosis severity in DS patients, but not in non-DS patients. The convex side exhibits less atrophy compared to the concave side in DS patients. The difference in concave-convex sides is more pronounced in patients with mild to moderate conditions. Increasing age and reduced BMD may be associated with worsening scoliosis severity. When BMD < - 0.900 T-Score, LCSA/GCSA < 0.805, and the patient is female, the likelihood of developing DS is high.

BackgroundThe objective of this study was to develop machine learning (ML) algorithms utilizing natural language processing (NLP) techniques for the automated detection of cervical spondylotic myelopathy (CSM) through the analysis of positive symptoms in free-text admission notes. This approach enables the timely identification and management of CSM, leading to optimal outcomes.MethodsThe dataset consisted of 1,214 patients diagnosed with cervical diseases as their primary condition between June 2013 and June 2020. A random ratio of 7:3 was employed to partition the dataset into training and testing subsets. Two machine learning models, Extreme Gradient Boosting (XGBoost) and Bidirectional Long Short Term Memory Network (LSTM), were developed. The performance of these models was assessed using various metrics, including the Receiver Operating Characteristic (ROC) curve, Area Under the Curve (AUC), accuracy, precision, recall, and F1 score.ResultsIn the testing set, the LSTM achieved an AUC of 0.9025, an accuracy of 0.8740, a recall of 0.9560, an F1 score of 0.9122, and a precision of 0.8723. The LSTM model demonstrated superior clinical applicability compared to the XGBoost model, as evidenced by calibration curves and decision curve analysis.ConclusionsThe timely identification of suspected CSM allows for prompt confirmation of diagnosis and treatment. The utilization of NLP algorithm demonstrated excellent discriminatory capabilities in identifying CSM based on positive symptoms in free-text admission notes complaint data. This study showcases the potential of a pre-diagnosis system in the field of spine.

Osteoporotic bone defect and fracture healing remain significant challenges in clinical practice. While traditional therapeutic approaches provide some regulation of bone homeostasis, they often present limitations and adverse effects. In orthopedic procedures, bone cement serves as a crucial material for stabilizing osteoporotic bone and securing implants. However, with the exception of magnesium phosphate cement, most cement variants lack substantial bone regenerative properties. Recent developments in biomaterial science have opened new avenues for enhancing bone cement functionality through innovative modifications. These advanced materials demonstrate promising capabilities in modulating the bone microenvironment through their distinct physicochemical properties. This review provides a systematic analysis of contemporary biomaterial-based modifications of bone cement, focusing on their influence on the bone healing microenvironment. The discussion begins with an examination of bone microenvironment pathology, followed by an evaluation of various biomaterial modifications and their effects on cement properties. The review then explores regulatory strategies targeting specific microenvironmental elements, including inflammatory response, oxidative stress, osteoblast-osteoclast homeostasis, vascular network formation, and osteocyte-mediated processes. The concluding section addresses current technical challenges and emerging research directions, providing insights for the development of next-generation biomaterials with enhanced functionality and therapeutic potential.

Cell-free therapy is an emerging approach for treating intervertebral disc (IVD) degeneration (IDD). Recently, small extracellular vesicles (sEVs) from M2 macrophages have shown considerable promise in mitigating disc degeneration. The primary aim of our study was to assess whether sEVs isolated from M2 are beneficial in protecting against IDD and to further explore the underlying mechanisms. Cellular models simulating intradiscal fibrosis were developed in vitro, and an animal model of intervertebral disc fibrosis was created by needling the caudal spines of rats. The results indicate that sEVs alleviate IDD by reducing abnormal expression of fibrosis and restore the normal extracellular matrix (ECM) composition within the intervertebral disc, both in vivo and in vitro. Transcriptome sequencing revealed that PAI-1 was the gene most significantly downregulated following treatment with M2-sEVs, while the PI3K/AKT signaling pathway was activated. Based on the prediction that FOXO1 targets and inhibits PAI-1, we found that M2-sEVs suppressed PAI-1 expression by enhancing FOXO1 phosphorylation, thereby reducing fibrosis progression within the IVD and delaying IDD. M2-sEVs alleviate IDD via inhibiting nucleus pulposus cell fibrosis through the Akt/FOXO1/PAI-1 axis, providing promising therapeutic targets for IDD.

OBJECTIVE:This study aims to develop machine learning (ML) models combined with an explainable method for the prediction of surgical site infection (SSI) after posterior lumbar fusion surgery. METHODS:In this retrospective, single-center study, a total of 1016 consecutive patients who underwent posterior lumbar fusion surgery were included. A comprehensive dataset was established, encompassing demographic variables, comorbidities, preoperative evaluation, details related to diagnosed lumbar disease, preoperative laboratory tests, surgical specifics, and postoperative factors. Utilizing this dataset, 6nullML models were developed to predict the occurrence of SSI. Performance evaluation of the models on the testing set involved several metrics, including the receiver operating characteristic curve, the area under the receiver operating characteristic curve, accuracy, recall, F1 score, and precision. The Shapley Additive Explanations (SHAP) method was employed to generate interpretable predictions, enabling a comprehensive assessment of SSI risk and providing individualized interpretations of the model results. RESULTS:Among the 1016 retrospective cases included in the study, 36 (3.54%) experienced SSI. Out of the six models examined, the Extreme Gradient Boost model demonstrated the highest discriminatory performance on the testing set, achieving the following metrics: precision (0.9000), recall (0.8182), accuracy (0.9902), F1 score (0.8571), and area under the receiver operating characteristic curve (0.9447). By utilizing the SHAP method, several important predictors of SSI were identified, including the duration of indwelling jugular vein catheter, blood urea nitrogen levels, total protein levels, sustained fever, creatinine levels, triglycerides levels, monocyte count, diabetes mellitus, drainage time, white blood cell count, cerebral infarction, estimated blood loss, prealbumin levels, Prognostic Nutritional Index, low back pain, posterior fusion score, and osteoporosis. CONCLUSIONS:ML-based prediction tools can accurately assess the risk of SSI after posterior lumbar fusion surgery. Additionally, ML combined with SHAP could provide a clear interpretation of individualized risk prediction and give physicians an intuitive comprehension of the effects of the model's essential features.

Through analyzing the data of the NHANES 2007–2020 cycle, this study concluded that high-intensity exercise 1–2 sessions a week can help maintain bone mass, and there is no significant difference from regular exercise more than 3 times a week. This study aims to explore the relationship between the various physical activity(PA) patterns and the risk of low bone mineral density(BMD) in Americans of working age. A total of 6482 participants aged 20–60 were selected from the National Health and Nutrition Survey (NHANES) conducted from 2007 to 2020. The PA data of the participants were obtained through individual interviews, and the participants were divided into four groups (inactive, insufficiently active, less frequent but sufficiently active(1–2 sessions a week and PA ≥ 150 min), and regularly active). Weighted logistic regression was used to analyze the correlation between PA patterns and the risk of low BMD. Subgroup analyses were applied to display the correlation between PA patterns and low BMD in different subgroups. After adjusting for confounding factors, the multiple logistic regression model showed that compared with inactive individuals, sufficiently active and regularly active individuals had a 35

Nucleus pulposus (NP) cell senescence is a critical factor in the progression of intervertebral disc degeneration (IVDD). Our analysis demonstrates that FTO and YAP1 expression levels are significantly diminished in degenerative NP tissues from both human and rat models, which correlates with increased m6A modification of YAP1 transcripts. To investigate the underlying mechanisms, we utilized IL-1β to induce senescence in cultured NP cells. Our findings reveal that FTO knockdown leads to a decrease in YAP1 levels while simultaneously increasing senescence markers. In contrast, the overexpression of YAP1 alleviates the senescence phenotype in FTO-deficient cells, underscoring the protective role of YAP1 in NP cells. This study proposes a novel regulatory pathway in which FTO modulates YAP1 through m6A demethylation, suggesting potential therapeutic targets for mitigating NP cell senescence and IVDD.

PURPOSE:Current research suggests that oxidative stress may decrease bone mineral density (BMD) by disrupting bone metabolism balance. However, no study investigated the relationship between systemic oxidative stress status and adult BMD. This study aims to investigate whether oxidative balance score (OBS) is associated with BMD in adults under 40. METHODS:3963 participants were selected from the National Health and Nutrition Survey (NHANES) from 2011 to 2018. OBS is scored based on 20 dietary and lifestyle factors. Weighted multiple logistic regression and restricted cubic splines were used to assess the correlation between OBS and osteopenia. RESULTS:After adjusting for confounding factors, the weighted logistic regression results showed that compared with the first tertile of OBS, the highest tertile had a 38% (OR: 0.62, 95% CI: 0.47-0.82) lower risk of osteopenia. The restrictive cubic spline curve indicates a significant nonlinear correlation between OBS and the risk of osteopenia. CONCLUSION:The research findings emphasize the relationship between OBS and the risk of osteopenia in young adults. Adopting an antioxidant diet and lifestyle may help young adults to maintain bone mass.

Degeneration of intervertebral discs is considered one of the most important causes of low back pain and disability. The intervertebral disc (IVD) is characterized by its susceptibility to various stressors that accelerate the senescence and apoptosis of nucleus pulposus cells, resulting in the loss of these cells and dysfunction of the intervertebral disc. Therefore, how to reduce the loss of nucleus pulposus cells under stress environment is the main problem in treating intervertebral disc degeneration. Autophagy is a kind of programmed cell death, which can provide energy by recycling substances in cells. It is considered to be an effective method to reduce the senescence and apoptosis of nucleus pulposus cells under stress. However, further research is needed on the mechanisms by which autophagy of nucleus pulposus cells is regulated under stress environments. M6A methylation, as the most extensive RNA modification in eukaryotic cells, participates in various cellular biological functions and is believed to be related to the regulation of autophagy under stress environments, may play a significant role in nucleus pulposus responding to stress. This article first summarizes the effects of various stressors on the death and autophagy of nucleus pulposus cells. Then, it summarizes the regulatory mechanism of m6A methylation on autophagy-related genes under stress and the role of these autophagy genes in nucleus pulposus cells. Finally, it proposes that the methylation modification of autophagy-related genes regulated by m6A may become a new treatment approach for intervertebral disc degeneration, providing new insights and ideas for the clinical treatment of intervertebral disc degeneration.

Objective To investigate the risk factors relating to the need for mechanical ventilation (MV) in isolated patients with cervical spinal cord injury (cSCI) and to construct a nomogram prediction model. Design Retrospective analysis study. Setting National Spinal Cord Injury Model System Database (NSCID) observation data were initially collected during rehabilitation hospitalization. Participants A total of 5784 patients (N=5784) who had a cSCI were admitted to the NSCID between 2006 and 2021. Interventions Not applicable. Main Outcome Measure(s) A univariate and multivariate logistic regression analysis was used to identify the independent factors affecting the use of MV in patients with cSCI, and these independent influencing factors were used to develop a nomogram prediction model. The area under the receiver operating characteristic curve (AUROC), calibration curve, and decision curve analysis (DCA) were used to evaluate the efficiency and the clinical application value of the model, respectively. Results In a series of 5784 included patients, 926 cases (16.0%) were admitted to spinal cord model system inpatient rehabilitation with the need for MV. Logistic regression analysis demonstrated that associated injury, American Spinal Cord Injury Association Impairment Scale (AIS), the sum of unilateral optimal motor scores for each muscle segment of upper extremities (sUEM), and neurologic level of injury (NLI) were independent predictors for the use of MV (P<.05). The prediction nomogram of MV usage in patients with cSCI was established based on the above independent predictors. The AUROC of the training set, internal verification set, and external verification set were 0.871 (0.857-0.886), 0.867 (0.843-0.891), and 0.850 (0.824-0.875), respectively. The calibration curve and DCA results showed that the model had good calibration and clinical practicability. Conclusions The nomograph prediction model based on sUEM, NLI, associated injury, and AIS can accurately and effectively predict the risk of MV in patients with cSCI, to help clinicians screen high-risk patients and formulate targeted intervention measures.

OBJECTIVE: To develop and validate natural language METHODS: EHRs of patients undergoing single-level percutaneous endoscopic lumbar discectomy for the treatment of LDH at the L4/5 or L5/S1 level between June 1, 2013, and December 31, 2021, were collected. The primary outcome was LDH with L5 and S1 radiculopathy, which was defined as nerve root compression recorded in the operative notes. Datasets were created using the history of present illness text and positive symptom text with radiculopathy (L5 or S1), respectively. The datasets were randomly split into a training set and a testing set in a 7:3 ratio. Two machine learning models, the long short-term memory network and Extreme Gradient Boosting, were developed using the training set. Performance evaluation of the models on the testing set was done using measures such as the receiver operating characteristic curve, area under the curve, accuracy, recall, F1-score, and precision. RESULTS: The study included a total of 1681 patients, having S1 radiculopathy. Among the 4 models developed, the long short-term memory model based on positive symptom text showed the best discrimination in the testing set, with precision (0.9054), recall (0.9405), accuracy (0.8950), F1 -score (0.9226), and area under the curve (0.9485). CONCLUSIONS: This study provides preliminary valida- tion of the concept that natural language processing -driven AI models can be used for the diagnosis of lumbar disease using EHRs. This study could pave the way for future research that may develop more comprehensive and clin- ically impactful AI -driven diagnostic systems.

Background Intervertebral disc degeneration(IVDD) is the primary etiology of low back pain and radicular pain. Recent studies have found that chemokines play a role in IVDD, but the underlying mechanism is largely unclear. Methods Bioinformatics analysis was employed to screen CXCL8 as the target gene. The expression levels of CXCL8 and CXCR2 were quantified using RT-qPCR, western blot(WB), immunohistochemistry(IHC), and enzyme-linked immuno-sorbent assay(ELISA). In the IVDD mouse model, X-ray images, Safranin O-fast green staining(SO-FG), IHC, and WB were conducted to assess the therapeutic effects of CXCL8 on IVDD. Reactive oxygen species (ROS) production, apoptosis of nucleus pulposus cells (NPCs), and the involvement of the NF-κB pathway were evaluated through WB, flow cytometry, immunofluorescence(IF), and Tunnel assay. Results In our study, we observed that CXCL8 emerged as one of the chemokines that were up-regulated in IVDD. The mitigation of extracellular matrix degradation (ECM) and the severity of IVDD were significantly achieved by neutralizing CXCL8 or its receptor CXCR2(SB225002, CXCR2 antagonist). The release of CXCL8 from infiltrated macrophages within intervertebral discs (IVDs) was predominantly observed upon stimulation. CXCL8 exerted its effects on NPCs by inducing apoptosis and ECM degradation through the activation of CXCR2. Specifically, the formation of the CXCL8/CXCR2 complex triggered the NF-κB signaling pathway, resulting in an abnormal increase in intracellular ROS levels and ultimately contributing to the development of IVDD. Conclusion Our findings suggest that macrophage-derived CXCL8 and subsequent CXCR2 signaling play crucial roles in mediating inflammation, oxidative stress, and apoptosis in IVDD. Targeting the CXCL8/CXCR2 axis may offer promising therapeutic strategies to ameliorate IVDD. The translational potential of this article This study indicates that CXCL8 can effectively exacerbate the excessive apoptosis and oxidative stress of NPCs through activating the NF-κB pathway. This study may provide new potential targets for preventing and reversing IVDD.