The aim of this study was to create artificial intelligence (AI) software with the purpose of providing a second opinion to physicians to support distal radius fracture (DRF) detection, and to compare the accuracy of fracture detection of physicians with and without software support. The dataset consisted of 26,121 anonymized anterior-posterior (AP) and lateral standard view radiographs of the wrist, with and without DRF. The convolutional neural network (CNN) model was trained to detect the presence of a DRF by comparing the radiographs containing a fracture to the inconspicuous ones. A total of 11 physicians (six surgeons in training and five hand surgeons) assessed 200 pairs of randomly selected digital radiographs of the wrist (AP and lateral) for the presence of a DRF. The same images were first evaluated without, and then with, the support of the CNN model, and the diagnostic accuracy of the two methods was compared.Aims
Methods
Osteoporosis (OP) is a metabolic bone disease, characterized by a decrease in bone mineral density (BMD). However, the research of regulatory variants has been limited for BMD. In this study, we aimed to explore novel regulatory genetic variants associated with BMD. We conducted an integrative analysis of BMD genome-wide association study (GWAS) and regulatory single nucleotide polymorphism (rSNP) annotation information. Firstly, the discovery GWAS dataset and replication GWAS dataset were integrated with rSNP annotation database to obtain BMD associated SNP regulatory elements and SNP regulatory element-target gene (E-G) pairs, respectively. Then, the common genes were further subjected to HumanNet v2 to explore the biological effects.Aims
Methods
This study examined the relationship between obesity (OB) and osteoporosis (OP), aiming to identify shared genetic markers and molecular mechanisms to facilitate the development of therapies that target both conditions simultaneously. Using weighted gene co-expression network analysis (WGCNA), we analyzed datasets from the Gene Expression Omnibus (GEO) database to identify co-expressed gene modules in OB and OP. These modules underwent Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and protein-protein interaction analysis to discover Hub genes. Machine learning refined the gene selection, with further validation using additional datasets. Single-cell analysis emphasized specific cell subpopulations, and enzyme-linked immunosorbent assay (ELISA), protein blotting, and cellular staining were used to investigate key genes.Aims
Methods
The aim of this study was to review the current evidence and future application for the role of diagnostic and therapeutic ultrasound in fracture management. A review of relevant literature was undertaken, including articles indexed in PubMed with keywords “ultrasound” or “sonography” combined with “diagnosis”, “fracture healing”, “impaired fracture healing”, “nonunion”, “microbiology”, and “fracture-related infection”.Objectives
Methods
Heterotopic ossification (HO) is perhaps the
single most significant obstacle to independence, functional mobility, and
return to duty for combat-injured veterans of Operation Enduring
Freedom and Operation Iraqi Freedom. Recent research into the cause(s)
of HO has been driven by a markedly higher prevalence seen in these
wounded warriors than encountered in previous wars or following
civilian trauma. To that end, research in both civilian and military
laboratories continues to shed light onto the complex mechanisms
behind HO formation, including systemic and wound specific factors,
cell lineage, and neurogenic inflammation. Of particular interest,
non-invasive
Small animal models of fracture repair primarily investigate
indirect fracture healing via external callus formation. We present
the first described rat model of direct fracture healing. A rat tibial osteotomy was created and fixed with compression
plating similar to that used in patients. The procedure was evaluated
in 15 cadaver rats and then Objectives
Methods
