Femoral head translation in borderline and definite dysplastic hips during weight-bearing: 2D/3D image registration analysis.

Purpose: The aims of this study were to 1) assess femoral head translation during weight-bearing in symptomatic developmental dysplasia of the hip (DDH) and 2) compare it between borderline DDH and definite DDH.

Methods: The study included four individuals with borderline DDH and nine with definite DDH, scheduled for periacetabular osteotomy. Anteroposterior X-ray images of the hip joint were obtained in the standing position, and computed tomography images of the pelvis were obtained in the supine position.

Feasibility of Bone Mineral Density and Bone Microarchitecture Assessment Using Deep Learning With a Convolutional Neural Network.

Objectives: We evaluated the feasibility of using deep learning with a convolutional neural network for predicting bone mineral density (BMD) and bone microarchitecture from conventional computed tomography (CT) images acquired by multivendor scanners.

Methods: We enrolled 402 patients who underwent noncontrast CT examinations, including L1-L4 vertebrae, and dual-energy x-ray absorptiometry (DXA) examination. Among these, 280 patients (3360 sagittal vertebral images), 70 patients (280 sagittal vertebral images), and 52 patients (208 sagittal vertebral images) were assigned to the training data set for deep learning model development, the validation, and the test data set, respectively.

Study protocol and baseline characteristics of newly induced dialysis patients: a prospective multi-center cohort study with a biological sample bank, the Ibaraki Dialysis Initiation Cohort (iDIC) study.

Background: Patients with end-stage kidney disease (ESKD) face higher risks of life-threatening events including cardiovascular disease. Various risk factors are identified as agents influencing the life prognosis of ESKD patients. Herein, we evaluated the risk factors related to the outcomes of Japanese patients with dialysis induction.

A new likelihood approach to autonomous multiple model estimation.

This paper presents an autonomous multiple model (AMM) estimation algorithm for hybrid systems with sudden changes in their parameters. Estimates of Kalman filters (KFs) that are tuned and employed for different system modes are merged based on a newly defined likelihood function without any necessity for filter interaction. The proposed likelihood function is composed of two measures, the filter agility measure and the steady-state error measure.

Effect of mitragynine, derived from Thai folk medicine, on gastric acid secretion through opioid receptor in anesthetized rats.

Mitragynine, an indole alkaloid from Thai folk medicine Mitragyna speciosa, exerts agonistic effects on opioid receptors. Gastric acid secretion is proposed to be regulated by opioid receptors in the central nervous system (CNS). Previously, we reported the dual roles (inhibition via micro-opioid receptors and stimulation via kappa-opioid receptors) of the opioid system in the central control of gastric acid secretion.