Brain age in genetic and idiopathic Parkinson's disease.

The brain-age gap, i.e. the difference between the brain age estimated from structural MRI data and the chronological age of an individual, has been proposed as a summary measure of brain integrity in neurodegenerative diseases.

Differing perspectives on artificial intelligence in mental healthcare among patients: a cross-sectional survey study.

Introduction: Artificial intelligence (AI) is being developed for mental healthcare, but patients' perspectives on its use are unknown. This study examined differences in attitudes towards AI being used in mental healthcare by history of mental illness, current mental health status, demographic characteristics, and social determinants of health.

Methods: We conducted a cross-sectional survey of an online sample of 500 adults asking about general perspectives, comfort with AI, specific concerns, explainability and transparency, responsibility and trust, and the importance of relevant bioethical constructs.

Biological Heterogeneity in Susceptibility to Glucocorticoid-Induced Bone Loss: Short- and Long-Term Hip BMD Trajectories.

Context: Glucocorticoids (GCs) are widely used for their anti-inflammatory and immunosuppressive properties. Their effect on bone health is predominantly negative by decreasing bone formation and increasing risk of fractures.

Objective: This work aimed to quantify the short- and long-term changes in total hip bone mineral density (THBMD) after initiating systemic GC treatment in previously GC treatment-naive adults without bone protective agents.

Phosphatidylethanolamines are the Main Lipid Class Altered in Red Blood Cells from Patients with VPS13A Disease/Chorea-Acanthocytosis.

Background: VPS13A disease is an ultra-rare disorder caused by loss of function mutations in VPS13A characterized by striatal degeneration and by red blood cell (RBC) acanthocytosis. VPS13A is a bridge-like protein mediating lipid transfer at membrane contact sites.

Objectives: To assess the lipid composition of patient-derived RBCs.

Artificial intelligence-based rapid brain volumetry substantially improves differential diagnosis in dementia.

Introduction: This study evaluates the clinical value of a deep learning-based artificial intelligence (AI) system that performs rapid brain volumetry with automatic lobe segmentation and age- and sex-adjusted percentile comparisons.

Methods: Fifty-five patients-17 with Alzheimer's disease (AD), 18 with frontotemporal dementia (FTD), and 20 healthy controls-underwent cranial magnetic resonance imaging scans. Two board-certified neuroradiologists (BCNR), two board-certified radiologists (BCR), and three radiology residents (RR) assessed the scans twice: first without AI support and then with AI assistance.