Aiding Diagnosis and Classifying of Early Stage Osteonecrosis of the Femoral Head with Convolutional Neural Network Based on Magnetic Resonance Imaging.

Introduction: The Steinberg classification system is commonly used by orthopedic surgeons to stage the severity of patients with osteonecrosis of the femoral head (ONFH), and it includes mild, moderate, and severe grading of each stage based on the area of the femoral head affected. However, clinicians mostly grade approximately by visual assessment or not at all. To accurately distinguish the mild, moderate, or severe grade of early stage ONFH, we propose a convolutional neural network (CNN) based on magnetic resonance imaging (MRI) of the hip joint of patients to accurately grade and aid diagnosis of ONFH.

The updated understanding of advanced maternal age.

The rising rates of pregnancies associated with advanced maternal age (AMA) have created unique challenges for healthcare systems worldwide. The elevated risk of poor maternal outcomes among AMA pregnancies is only partially understood and hotly debated. Specifically, AMA is associated with reduced fertility and an increased incidence of pregnancy complications.

Accuracy of Electronic Health Record Phenotypes to Detect Recognition of Hypertension in Pediatric Primary Care.

Objective: To evaluate the accuracy of extractable electronic health record (EHR) data to define clinician recognition of hypertension in pediatric primary care.

Methods: We used EHR data to perform a cross-sectional study of children aged 3-18 years at well-visits in Connecticut from 2018-2023 (n=50,290) that had either: (1) incident hypertension (hypertensive BP at the well-visit and ≥2 prior hypertensive BPs without prior diagnosis of hypertension); or (2) isolated hypertensive BP at the well-visit without necessarily having prior hypertensive BPs. We tested the accuracy of EHR phenotypes to detect recognition of incident hypertension or hypertensive BP using structured elements, including diagnosis codes, problem list entries, number of BP measurements, orders, and follow-up information.

Three-dimensional digital model of the facial nerve assisted in the excision of benign parotid tumors based on 3D-DESS-WE-MRI.

This study proposes a novel surgical technique for the excision of benign parotid tumors, utilizing a extracapsular dissection guided by a three dimensional digital model of the facial nerve(3DFN-ECD) and compares its clinical efficacy with the extracapsular dissection (ECD) method. This prospective study included 68 patients with benign parotid tumors. The control group (40 patients) received the ECD treatment, while the experimental group (28 patients), underwent the 3DFN-ECD approach proposed in this study.

Light intensity-regulated glycogen synthesis and pollutant removal in microalgal-bacterial granular sludge for wastewater treatment.

As light intensity plays a pivotal role in the microalgal-bacterial granular sludge (MBGS) process, understanding its impact on system performance and energy dynamics is essential. This study investigated the effects of varying light intensities (20, 100, 200, and 300 μ mol/m²/s) on the performance of MBGS in urban wastewater treatment, with a particular focus on glycogen accumulation and pollutant removal. The results demonstrated that light intensity significantly influenced microbial community structure, glycogen accumulation, and pollutant removal efficiency.