AI-Assisted Tailored Intervention for Nurse Burnout: A Three-Group Randomized Controlled Trial.

Background: High-stress environments, heavy workloads, and the emotional demands of patient care, which are common challenges faced by nurses, are factors that can lead to burnout. Shift work can make traditional burnout interventions costly and difficult to implement. Artificial intelligence (AI) could offer solutions that are less constrained by time, resources, and labor.

A national estimate of mental disorders and mortality outcomes in cancer survivors.

Background: This study evaluated the prevalence of various mental disorders and their influence on mortality outcomes in individuals with cancer.

Methods: The authors' institutional database included patients with cancer diagnosed between 2011 and 2015 who had mental disorders and death information up to 2021. Mental disorders included nonaffective psychotic disorders, affective psychotic disorders, anxiety-related and stress-related disorders, alcohol or drug misuse, and mood disorders without psychotic symptoms.

A disintegrin and metallopeptidase domain (ADAM) 12, ADAM 17 mRNA and ADAM10 protein hold potential as biomarkers for detection of early gastric cancer.

No biomarker can effectively screen for early gastric cancer (EGC). Players in the A disintegrin and metalloproteinase (ADAM)-natural killer group 2 member D (NKG2D) receptor axis may have a role for that. As a proof-of-concept pilot study, the expression of ADAM8, ADAM9, ADAM10, ADAM12, ADAM17, and major histocompatibility complex (MHC) class I chain-related sequence A (MICA), a ligand for NKG2D, in gastric cancer was investigated in silico using The Cancer Genome Atlas (TCGA) database.