An imaging-based clinical prediction model to differentiate brucellar spondylitis from pyogenic spondylitis: a multicenter retrospective observational study.

Purpose: Differentiating between pyogenic (PS) and brucellar (BS) spondylitis is clinically challenging due to their similar clinical symptoms, with delayed diagnosis or misdiagnosis common, causing trouble for surgeons in selecting appropriate treatment strategies. Currently, radiology-based diagnostic models for PS and BS are lacking. This study aimed to combine magnetic resonance (MR) and radiographic imaging to elucidate the differences between PS and BS and develop a novel diagnostic model for differential diagnosis.

Residual Al Adatoms Driven Epitaxy of AlGaN QWs for High-Performance UV LEDs.

AlGaN-based ultraviolet (UV) light-emitting diodes (LEDs) experience a notable reduction in efficiency within the 280-330 nm wavelength range, known as the "UVB gap". Given the extensive applications of UV LEDs in this wavelength range, it is imperative to bridge this efficiency gap. In this study, a strategy facilitated by the presence of residual Al adatoms is introduced to simultaneously improve the integration of Ga-adatoms and the migration of Al/Ga-adatoms during the growth of low-Al-composition AlGaN quantum wells (QWs) even at high temperatures comparable to those used for high-Al-composition AlGaN quantum barriers.

Decreased histone H3K9 dimethylation in synergy with DNA demethylation of Spi-1 binding site contributes to ADAMTS-5 expression in articular cartilage of osteoarthritis mice.

Osteoarthritis (OA) is defined by articular cartilage degeneration, synovial membrane inflammation, and abnormal bone remodeling. Recent study has discovered that OA development is linked to an aberrant epigenetic modification of OA-related genes. Our previous research showed that DNA demethylation in ADAMTS-5 promoter region had a substantial impact on ADAMTS-5 expression in the mouse OA model.

Evaluation of targeted sequencing for pathogen identification in bone and joint infections: a cohort study from China.

Purpose: Bone and joint tuberculosis (BJTB) is a distinct variant of tuberculosis in which clinical diagnosis often leads to relative misdiagnosis and missed diagnoses. This study aimed to evaluate the diagnostic accuracy of the targeted nanopore sequencing (TNPseq) assay for BJTB patients in China.

Method: The study enrolled a cohort of 163 patients with suspected BJTB.

DNA demethylation of promoter region orchestrates SPI-1-induced ADAMTS-5 expression in articular cartilage of osteoarthritis mice.

Osteoarthritis (OA) is one of the most prevalent joint diseases in aged people and characterized by articular cartilage degeneration, synovial inflammation, and abnormal bone remodeling. Recent advances in OA research have clearly shown that OA development is associated with aberrant DNA methylation status of many OA-related genes. As one of most important cartilage degrading proteases in OA, a disintegrin and metalloproteinase with thrombospondin motifs subtype 5 (ADAMTS-5) is activated to mediate cartilage degradation in human OA and experimental murine OA models.

Development of a Diagnostic Model for Differentiating Tuberculous Spondylitis and Pyogenic Spondylitis With MRI: A Multicenter Retrospective Observational Study.

Study Design: Multicenter retrospective observational study.

Objective: This study aimed to distinguish tuberculous spondylitis (TS) from pyogenic spondylitis (PS) using magnetic resonance imaging (MRI). Further, a novel diagnostic model for differential diagnosis was developed.

Comprehensive analysis of m6A RNA methylation modification patterns and the immune microenvironment in osteoarthritis.

Background: Osteoarthritis (OA) is the most common joint degenerative disease, and so far, there is no effective therapy to prevent or delay its development. Considerable attention is now being given to the impact of m6A RNA methylation modification on the disease immune regulation. However, much remains unknown about the function of m6A modification in OA.

Evaluation of Biomarkers and Immune Microenvironment of Osteoarthritis: Evidence From Omics Data and Machine Learning.

This study aimed to identify novel biomarkers for osteoarthritis (OA) and explore potential pathological immune cell infiltration. We identified differentially expressed genes (DEGs) between OA and normal synovial tissues using the package in R, and performed enrichment analyses to understand the functions and enriched pathways of DEGs. Weighted gene co-expression network analysis (WGCNA) and distinct machine-learning algorithms were then used to identify hub modules and candidate biomarkers.