Applying Machine Learning Approach to Explore Childhood Circumstances and Self-Rated Health in Old Age - China and the US, 2020-2021.

Introduction: Childhood circumstances impact senior health, prompting the introduction of machine learning methods to assess their individual and collective contributions to senior health.

Methods: Using health and retirement study (HRS) and China Health and Retirement Longitudinal Study (CHARLS), we analyzed 2,434 American and 5,612 Chinese participants aged 60 and above. Conditional inference trees and forests were employed to estimate the influence of childhood circumstances on self-rated health (SRH).

"Taste typicality" is a foundational and multi-modal dimension of ordinary aesthetic experience.

Aesthetic experience seems both regular and idiosyncratic. On one hand, there are powerful regularities in what we tend to find attractive versus unattractive (e.g.

Diffuse large B-cell lymphoma with concurrent high MYC and BCL2 expression shows evidence of active B-cell receptor signaling by quantitative immunofluorescence.

B-cell receptor (BCR)-mediated signaling plays an important role in the pathogenesis of a subset of diffuse large B-cell lymphoma (DLBCL), and novel agents targeting this pathway are now in clinical use. We have previously identified a signature of active BCR signaling on formalin-fixed paraffin-embedded specimens using quantitative immunofluorescence, allowing for identification of patients who might benefit from anti-BCR therapies. We sought to characterize the clinicopathologic significance of active BCR signaling in DLBCL by correlating measures of signaling intensity with clinical features and various tumor cell characteristics.