Background: Ankylosing spondylitis (AS) is a chronic inflammatory and autoimmune disease that primarily affects the sacroiliac joints and axial skeleton. While the exact pathogenetic mechanism of AS remains unclear, previous reports have highlighted the involvement of genetic factors, immune responses, and gut microbiota dysregulation in the development of this condition. Short-chain fatty acids (SCFAs), which are microbial fermentation products derived from sugar, protein, and dietary fibers, play a role in maintaining the intestinal barrier function and reducing inflammatory responses. The aim of this study was to investigate the therapeutic potential of butyric acid (BA), an important SCFA, in the treatment of AS. Methods: To evaluate the anti-inflammatory and anti-bone loss effects of BA, a murine AS model was established using proteoglycan and dimethyl dioctadecyl ammonium (DDA) adjuvants. Various techniques, including an enzyme-linked immunosorbent assay (ELISA), magnetic resonance imaging (MRI), micro-CT, histology, quantitative PCR (qPCR) for intestinal tight junction protein expression, and 16S rDNA sequencing to analyze gut microbiota abundance, were employed to assess the inflammation and bone health in the target tissues. Results: The results indicated that BA demonstrated potential in alleviating the inflammatory response in the peripheral joints and the axial spine affected by AS, as evidenced by the reductions in inflammatory infiltration, synovial hyperplasia, and endplate erosion. Furthermore, BA was found to impact the intestinal barrier function positively. Notably, BA was associated with the downregulation of harmful inflammatory factors and the reversal of bone loss, suggesting its protective effects against AS. Conclusions: These beneficial effects were attributed to the modulation of gut microbiota, anti-inflammatory properties, and the maintenance of skeletal metabolic homeostasis. This study contributes new evidence supporting the relationship between gut microbiota and bone health.

Objective: This study aims to apply different deep learning convolutional neural network algorithms to assess the grading of cervical spinal stenosis and to evaluate their consistency with clinician grading results as well as clinical manifestations of patients. Methods: We retrospectively enrolled 954 patients with cervical spine magnetic resonance imaging (MRI) data and medical records from the Fifth Affiliated Hospital of Sun-Yat Sen University. The Kang grading method for sagittal MR images of the cervical spine and the spinal cord compression ratio for horizontal MR images of the cervical spine were adopted for cervical spinal canal stenosis grading. The collected data were randomly divided into training/validation and test sets. The training/validation sets were processed by various image preprocessing and annotation methods, in which deep learning convolutional networks, including classification, target detection, and key point localization models, were applied. The predictive grading of the test set by the model was finally contrasted with the grading results of the clinicians, and correlation analysis was performed with the clinical manifestations of the patients. Result: The EfficientNet_B5 model achieved a five-fold cross-validated accuracy of 79.45% and near-perfect agreement with clinician grading on the test set (κ= 0.848, 0.822), surpassing resident–clinician consistency (κ = 0.732, 0.702). The model-derived compression ratio (0.45 ± 0.07) did not differ significantly from manual measurements (0.46 ± 0.07). Correlation analysis showed moderate associations between model outputs and clinical symptoms: EfficientNet_B5 grades (r = 0.526) were comparable to clinician assessments (r = 0.517, 0.503) and higher than those of residents (r = 0.457, 0.448). Conclusion: CNN models demonstrate strong performance in the objective, consistent, and efficient grading of cervical spinal stenosis severity, offering potential clinical value in automated diagnostic support.

Background/Objectives: Lumbar disc herniation (LDH) is the most common condition associated with low back pain, and it adversely impacts individuals’ health. The interplay between energy metabolism and apoptosis is critical, as the loss of viable cells in the intervertebral disc (IVD) can lead to a cascade of degenerative changes. Efferocytosis is a key biological process that maintains homeostasis by removing apoptotic cells, resolving inflammation, and promoting tissue repair. Therefore, enhancing mitochondrial energy metabolism and efferocytosis function in IVD cells holds great promise as a potential therapeutic approach for LDH. Methods: In this study, energy metabolism and efferocytosis-related differentially expressed genes (EMERDEGs) were identified from the transcriptomic datasets of LDH. Machine learning approaches were used to identify key genes. Functional enrichment analyses were performed to elucidate the biological roles of these genes. The functions of the hub genes were validated by RT-qPCR. The CIBERSORT algorithm was used to compare immune infiltration between LDH and Control groups. Additionally, we used single-cell RNA sequencing dataset to analyze cell-specific expression of the hub genes. Results: By using bioinformatics methods, we identified six EMERDEGs hub genes (IL6R, TNF, MAPK13, ELANE, PLAUR, ABCA1) and verified them using RT-qPCR. Functional enrichment analysis revealed that these genes were primarily associated with inflammatory response, chemokine production, and cellular energy metabolism. Further, we identified candidate drugs as potential treatments for LDH. Additionally, in immune infiltration analysis, the abundance of activated dendritic cells, neutrophils, and gamma delta T cells varied significantly between the LDH group and Control group. The scRNA-seq analysis showed that these hub genes were mainly expressed in chondrocyte-like cells. Conclusions: The identified EMERDEG hub genes and pathways offer novel insights into the molecular mechanisms underlying LDH and suggest potential therapeutic targets.

There is increasing concern regarding the effects of contemporary lifestyles on spinal health. This study aimed to evaluate recent trends in cervical lordo