Osteoporosis

Repeatability of AI-quantified incidental findings on lung cancer screening CT scans in the NELSON trial.

OBJECTIVES: Computed tomography (CT) scans for lung cancer screening provide the opportunity of quantifying incidental findings. We evaluated the repeatability of AI-based measurements of incidental findings using short-term repeat CT scan pairs. MATERIALS AND METHODS: AI-Rad Companion Chest CT software was applied to low-dose non-contrast CT scans from the NELSON lung cancer screening trial to me...

Computer-aided diagnosis system for thoracic computed tomography of rib fractures in older emergency patients: A preliminary study.

The peculiarities of older individuals related to osteoporosis and hyperostosis may lead to a higher rate of misdiagnosis of rib fractures on computed tomography (CT) images in older than in middle-aged/young people when using radiologist-only reading. However, none of these studies on rib fracture computer-aided diagnostic (CAD) systems grouped patients by age or evaluated the value of using CAD ...

Double electron-electron resonance (DEER) structural study of the holo and apo states of calmodulin.

PURPOSE: Human calmodulin-1 (CaM) undergoes calcium-dependent conformational changes that are difficult to capture owing to substantial structural fle...

AI-driven discovery of synergistic combinations from Psoralea corylifolia fruit for treating osteoporosis.

BACKGROUND: Estrogen-deficient osteoporosis demands safe and effective therapies. Psoralea corylifolia fruit (PCF), a phytoestrogenic herbal medicine ...

Exploring the ROS-Related Therapeutic Mechanism of Bushen Huoxue Decoction in Postmenopausal Osteoporosis through Transcriptomics and Network Pharmacology.

INTRODUCTION: Postmenopausal osteoporosis (PMOP) involves bone loss and fracture risk, driven by estrogen deficiency, oxidative stress, immune dysregu...

TRPV1, Endocannabinoid, and Opioid Systems in Analgesia: Molecular Mechanisms and Drug Development Strategies.

Pain modulation relies on complex molecular interactions among ion channels, G protein-coupled receptors, and intracellular signaling cascades. The Tr...

AI-assisted extraction of opportunistic findings from oncologic CT reports using large language models.

Opportunistic findings at imaging (iOFs), such as osteoporosis, liver steatosis, or coronary artery calcifications, are clinically relevant abnormalit...

Influence of gravity variations on the activity of neuronal spheroids in an acoustic trap.

Among biological models, cell culture constitutes an important paradigm that allows rapid examination of cell phenotype and behavior. While cell cultu...

Identification of Chronic Stress-Related Biomarkers for Potential Diagnosis and Treatment of Osteoporosis: An Integrated Multi-omic and Clinical Data Analysis.

OBJECTIVE: The mechanisms through which chronic stress-related genes influence the diagnosis of osteoporosis (OP), where chronic stress serves as a ri...

MedADL: High-Throughput Information Extraction of Functional Status from Electronic Health Records to Advance Frailty Assessment in Older Adults.

BACKGROUND: Functional status is essential for assessing frailty and planning care in older adults but is often under-documented in the structured fie...

Development of a machine learning-based prediction model for hypothyroidism-associated delirium in elderly hypothyroid patients in the intensive care unit.

BACKGROUND: Patients with hypothyroidism admitted to the intensive care unit (ICU) frequently develop hypothyroidism-associated delirium (HAD), a cond...

Heat shock protein-mediated remodeling of the bone immune microenvironment: mechanisms and precision therapeutic strategies for osteoporosis.

BACKGROUND: Osteoporosis is a systemic bone disorder marked by reduced bone mass and deteriorating bone microstructure, commonly associated with infla...

The emerging role of coronary computed tomography for prevention of cardiovascular disease in asymptomatic individuals.

The persistent global rise in atherosclerotic cardiovascular disease (ASCVD) challenges the effectiveness of current risk factor-based algorithms in p...

A body roundness index (BRI)-based predictive model for metabolic syndrome in perimenopausal and postmenopausal women-from a cross-sectional machine learning study to a longitudinal dynamic assessment.

BACKGROUND AND AIMS: Metabolic syndrome (MetS) is highly prevalent among perimenopausal and postmenopausal women and poses a major public health chall...

Comment on "Integrating machine learning into fracture liaison services: Toward precision risk stratification in osteoporosis care: A prospective cohort study".

Predicting drilling fluid lost circulation volume and radius using petrophysical well logs and machine learning approaches.

Lost circulation, which refers to the unintended loss of drilling fluid into underground formations, presents a significant challenge in drilling oper...

Virtual photon-counting micro-CT platform for simulation of head and neck cancer imaging in mice.

OBJECTIVE: Our goal was to develop a simulation platform for photon-counting CT (PCCT) imaging in mouse models of head and neck squamous cell carcinom...

Decoding neuron-specific lineage to identify diagnostic biomarkers and therapeutic targets for ischemic stroke.

Ischemic stroke (IS) imposes a major global health burden. To uncover new diagnostic and therapeutic targets, we profiled neuronal heterogeneity durin...

VAV3 is associated with atherosclerosis and ox-LDL-induced endothelial dysfunctional remodeling.

BACKGROUND: Atherosclerosis is a major cause of ischemic stroke and is characterized by complex immune-metabolic dysregulation. VAV3, a Rho guanine nu...

Histopathological Assessment of Myocardial Ischemia-Reperfusion Injury Using Transformer-Based Artificial Intelligence: Model Comparison Study.

BACKGROUND: Myocardial ischemia-reperfusion injury (MIRI) poses diagnostic challenges due to complex histopathological changes. OBJECTIVE: This study ...