Artificial intelligence-based computer-aided system for knee osteoarthritis assessment increases experienced orthopaedic surgeons' agreement rate and accuracy.

Purpose: The aims of this study were to (1) analyze the impact of an artificial intelligence (AI)-based computer system on the accuracy and agreement rate of board-certified orthopaedic surgeons (= senior readers) to detect X-ray features indicative of knee OA in comparison to unaided assessment and (2) compare the results to those of senior residents (= junior readers).

Methods: One hundred and twenty-four unilateral knee X-rays from the OAI study were analyzed regarding Kellgren-Lawrence grade, joint space narrowing (JSN), sclerosis and osteophyte OARSI grade by computerized methods. Images were rated for these parameters by three senior readers using two modalities: plain X-ray (unaided) and X-ray presented alongside reports from a computer-assisted detection system (aided).

Automated Knee Osteoarthritis Assessment Increases Physicians' Agreement Rate and Accuracy: Data from the Osteoarthritis Initiative.

. To assess the impact of a computerized system on physicians' accuracy and agreement rate, as compared with unaided diagnosis. .

An exclusive α/β code directs allostery in TetR-peptide complexes.

The allosteric mechanism of one of the best characterized bacterial transcription regulators, tetracycline repressor (TetR), has recently been questioned. Tetracycline binding induces cooperative folding of TetR, as suggested by recent unfolding studies, rather than switching between two defined conformational states, namely a DNA-binding-competent conformation and a non-DNA-binding conformation. Upon ligand binding, a host of near-native multiconformational structures collapse into a single, highly stabilized protein conformation that is no longer able to bind DNA.