Objectives: In this study, artificial intelligence techniques were used to achieve automated diagnosis and classification of temporomandibular joint (TMJ) degenerative joint disease (DJD) on cone beam computed tomography (CBCT) images.
Methods: An AI model utilizing the YOLOv10 algorithm was trained, validated and tested on 7357 annotated and corrected oblique sagittal TMJ images (3010 images of normal condyles and 4347 images of condyles with DJD) from 1018 patients who visited Peking University School and Hospital of Stomatology for temporomandibular disorders and underwent TMJ CBCT examinations. This model could identify DJD as well as the radiographic signs of DJD, namely, erosion, osteophytes, sclerosis and subchondral cysts.
Photodiagnosis Photodyn Ther
January 2025
Purpose: To evaluate the differences in fundus tessellation among various severities using multifocal visual electrophysiology (MfERG) and optical coherence tomography angiography (OCTA) for clinical grading and treatment.
Methods: This study included 52 patients totaling 87 eyes. The Early Treatment Diabetic Retinopathy Study (ETDRS) grid division method was utilized to assess Grade of fundus tessellation.
De novo design of antimicrobial peptides is a pivotal strategy for developing new antibacterial agents, leveraging its rapid and efficient nature. (XXYY), where X represents cationic residues, Y denotes hydrophobic residues, and n varies from 2 to 4, is a classical α-helix template. Based on which, numerous antimicrobial peptides have been synthesized.
View Article and Find Full Text PDFBiology (Basel)
January 2025
Almost all organisms, from the simplest bacteria to advanced mammals, havea near 24 h circadian rhythm. Circadian rhythms are highly conserved across different life forms and are regulated by circadian genes as well as by related transcription factors. Transcription factors are fundamental to circadian rhythms, influencing gene expression, behavior in plants and animals, and human diseases.
View Article and Find Full Text PDFBeijing Da Xue Xue Bao Yi Xue Ban
February 2025
Objective: To develop a clinical automated diagnostic system for temporomandibular disorders (TMD) based on the diagnostic criteria for TMD (DC/TMD) to assist dentists in making rapid and accurate clinical diagnosis of TMD.
Methods: Clinical and imaging data of 354 patients, who visited the Center for TMD & Orofacial Pain at Peking University Hospital of Stomatology from September 2023 to January 2024, were retrospectively collected. The study developed a clinical automated diagnostic system for TMD using the DC/TMD, built on the.