Background: Tuberculosis (TB) represents a bacterial infection affecting many individuals each year and potentially leading to death. Overexpression of transforming growth factor (TGF)-β1 has a primary immunomodulatory function in human tuberculosis. This work aimed to develop nanoliposomes to facilitate the delivery of anti-tubercular products to THP-1-derived human macrophages as Mycobacterium host cells and to evaluate drug efficiencies as well as the effects of a TGF-β1-specific short interfering RNA (siRNA) delivery system employing nanoliposomes. Methods: In the current study, siTGF-β1 nanoliposomes loaded with the anti-TB drugs HRZ (isoniazid, rifampicin, and pyrazinamide) were prepared and characterized in vitro, determining the size, zeta potential, morphology, drug encapsulation efficiency (EE), cytotoxicity, and gene silencing efficiency of TGF-β1 siRNA. Results: HRZ/siTGF-β1 nanoliposomes appeared as smooth spheres showing the size and positive zeta potential of 168.135 ± 0.5444 nm and + 4.03 ± 1.32 mV, respectively. Drug EEs were 90%, 88%, and 37% for INH, RIF, and PZA, respectively. Meanwhile, the nanoliposomes were weakly cytotoxic towards human macrophages as assessed by the MTT assay. Nanoliposomal siTGF-β1 could significantly downregulate TGF-β1 in THP-1-derived human macrophages in vitro. Conclusion: These findings suggested that HRZ-loaded nanoliposomes with siTGF-β1 have the potential for improving spinal tuberculosis chemotherapy via nano-encapsulation of anti-TB drugs.

Traditional diagnostic tools for scoliosis screening necessitate a substantial number of specialized personnel and equipment, leading to inconvenience that can result in missed opportunities for early diagnosis and optimal treatment. We have developed a deep learning-based image segmentation model to enhance the efficiency of scoliosis screening. A total of 350 patients with scoliosis and 108 healthy subjects were included in this study. The dataset was created using their bare back images and standing full-length anteroposterior spinal X-rays. An attention mechanism was incorporated into the original U-Net architecture to build a Dual AttentionUNet model for image segmentation. The entire dataset was divided into the training (321 cases), validation (46 cases), and test (91 cases) sets in a 7:1:2 ratio. The training set was used to train the Dual AttentionUNet model, and the validation set was used to fine-tune hyperparameters and prevent overfitting during training. The performance of the model was evaluated in the test set. After automatic segmentation of the back contour, a back asymmetry index was calculated via computer vision algorithms to classify scoliosis into different severities. The accuracy of classifications was statistically compared to those of three clinical experts. Following the segmentation of bare back images and the application of computer vision algorithms, the Dual AttentionUNet model achieved an accuracy, precision, and recall rate of over 90% in predicting severe scoliosis. Notably, the model achieved an AUC value of 0.93 in identifying whether the subjects had scoliosis, which was higher than the 0.92 achieved by the deputy chief physician. In identifying severe scoliosis, their AUC values were 0.95 and 0.96, respectively. The Dual AttentionUNet model, based on only bare back images, achieved accuracy and precision comparable to clinical physicians in determining scoliosis severity. Radiation-free, cost-saving, easy-to-operate and noninvasive, this model provides a novel option for large-scale scoliosis screening.

Objective: To investigate the correlation between the expression of lipopolysaccharide-binding protein (LBP) in peripheral blood of spinal tuberculosis and clinical diagnosis and to evaluate its value as a diagnostic marker of spinal tuberculosis. Methods: In the experimental group, clinical history data and peripheral blood were collected from 100 patients with spinal tuberculosis who were admitted to the Department of Spine Surgery, General Hospital of Ningxia Medical University from May 2017 to May 2020, and peripheral blood was collected from 30 healthy volunteers in the control group. Screening of differential LBP expression by proteomics and ELISA to verify its expression in peripheral blood of spinal tuberculosis patients. t-test, Spearman analysis, linear regression and ROC curve were used to evaluate the diagnostic value of LBP in peripheral blood for spinal tuberculosis. Results: The expression of LBP protein in peripheral blood is significantly higher in patients with spinal tuberculosis than in the normal population; LBP assay values were significantly and positively correlated with CRP and ESR values (P < 0.01); the AUC of LBP in the diagnosis of spinal tuberculosis for pathological examination, bacteriological culture, T-cell spot test for tuberculosis infection (T-SPOT), imaging diagnosis, and acid fast bacillus were, respectively, 0.677 (P < 0.01), 0.707 (P < 0.01), 0.751 (P < 0.01), 0.714 (P < 0.01), and 0.656 (P < 0.05), and there was a correlation between LBP and the diagnostic evaluation of spinal tuberculosis. Conclusion: LBP could be a new candidate biomarker for the diagnosis of spinal tuberculosis.

Objective: To evaluate the diagnostic performance and clinical utility of targeted next-generation sequencing (tNGS) in primary osteoarticular infections (POI).Methods: Eighty-seven patients diagnosed with POI at the Bone Infection Ward of Ningxia Medical University General Hospital between September 2023 and September 2024 were enrolled, including cases of tuberculous osteoarticular infection (35 cases), Brucella-related osteoarticular infection (21 cases), and pyogenic osteoarticular infection (31 cases). Using bacterial culture, Xpert MTB/RIF assay, Brucella agglutination test, and histopathological examination as reference standards, the diagnostic value of tNGS in pathogen identification and resistance gene analysis was systematically evaluated.Results: All patients had complete follow-up data. The cohort comprised 87 POI patients (mean age: 55.36 ± 17.24 years; male-to-female ratio: 1.35:1). tNGS demonstrated significantly higher overall sensitivity than conventional bacterial culture (85.0% vs. 31.0%, P < 0.001). For resistance profiling, tNGS identified Mycobacterium tuberculosis complex mutations associated with resistance to isoniazid (2 cases), rifampicin (2 cases), ethambutol (1 case), pyrazinamide (5 cases), and streptomycin (1 case). Additionally, one fluoroquinolone resistance gene and one extended-spectrum β-lactamase (ESBL)-producing pathogen were detected. Notably, one multidrug-resistant (MDR) case harbored mutations conferring resistance to five anti-tuberculosis agents. Receiver operating characteristic (ROC) curve analysis revealed that tNGS exhibited superior diagnostic accuracy for tuberculous osteoarticular infections (AUC = 0.926), Brucella-related osteoarticular infections (AUC = 0.891), and pyogenic osteoarticular infections (AUC = 0.912), outperforming Xpert MTB/RIF (0.814), Brucella agglutination test (0.832), bacterial culture (0.652), and histopathology (0.704) (all P < 0.05).Conclusion: tNGS enables simultaneous pathogen identification and resistance gene detection with high efficiency, broad coverage, and accuracy, demonstrating significant advantages in POI diagnosis. This technology holds critical value in guiding optimized antimicrobial therapy and is recommended as a first-line molecular diagnostic tool for POI.

BACKGROUND: Spinal Tuberculosis (STB) is a common cause of spinal malformation caused by extrapulmonary tuberculosis in developing countries, which seriously affects the quality of life of patients. It was found that the expression of miRNAs in macrophages was stable, specific and readily available after Mycobacterium tuberculosis (MTB) infection. Our research group determined the differential expression of miR-29a-3p in the vertebra of spinal tuberculosis and intervertebral disc lesions through RNAs chip screening and bioinformatics analysis. However, the specific molecular mechanism of miR-29a-3p in the inflammatory response of spinal tuberculosis remains unclear. OBJECTIVE: In this study, we mainly discussed the expression of miR-29a-3p in the focal tissue of spinal tuberculosis and the role and molecular mechanism of miR-29a-3p mediated by METTL3 in the inflammatory response of spinal tuberculosis. METHODS: The tissues of 15 cases of lumbar degenerative diseases and vertebral lesions of spinal tuberculosis were collected, and the THP-1 macrophage model infected by Mycobacterium tuberculosis was constructed, and verified by qRT-PCR, Western blot, fluorescence in situ hybridization, immunohistochemistry, Cell fluorescence and ELISA. RESULTS AND CONCLUSION We found that the expression of miR-29a-3p was significantly down-regulated in the vertebral body and disc lesion tissues of patients with spinal tuberculosis. Overexpression of miR-29a-3p inhibited the levels of inflammatory factors including tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β) and interleukin-6 (IL-6), and inhibition of miR-29a-3p expression promoted the release of the levels of TNF-α, IL-1β and IL-6 inflammatory factors. Our study also shows that knockout of methyltransferase 3 (METTL3) can significantly reduce the expression of miR-29a-3p and promote the release of pro-inflammatory cytokines in macrophages.