A machine learning approach identifies cellular senescence on transcriptome data of human cells in vitro.

Although cellular senescence has been recognized as a hallmark of aging, it is challenging to detect senescence cells (SnCs) due to their high level of heterogeneity at the molecular level. Machine learning (ML) is likely an ideal approach to address this challenge because of its ability to recognize complex patterns that cannot be characterized by one or a few features, from high-dimensional data. To test this, we evaluated the performance of four ML algorithms including support vector machines (SVM), random forest (RF), decision tree (DT), and Soft Independent Modelling of Class Analogy (SIMCA), in distinguishing SnCs from controls based on bulk RNA sequencing data.

The Fifth Annual Symposium of the Midwest Aging Consortium.

As the healthcare burden caused by an increasingly aging population rapidly rises, a pressing need exists for innovative geroscience research that can elucidate aging mechanisms and precipitate the development of therapeutic interventions to support healthy aging. The Fifth Annual Midwest Aging Consortium Aging Research symposium, held from April 28-30, 2024, was hosted by The Ohio State University in Columbus, Ohio and featured presentations from investigators across the Midwestern United States. This report summarizes the research presented at the symposium, whose topics included cellular senescence and the aging brain, metabolism and metabolic interventions, nutrition, redox mechanisms and biomarkers, and stress mechanisms.

The Ercc1 mouse model of XFE progeroid syndrome undergoes accelerated retinal degeneration.

Age-related macular degeneration (AMD) is a major cause of vision loss in older adults. AMD is caused by degeneration in the macula of the retina. The retina is the highest oxygen consuming tissue in our body and is prone to oxidative damage.

Quality of life, religion/spirituality, and dementia risk among Black people in the US.

Objectives: Black people in the United States (US) experience an increased risk of being diagnosed with Alzheimer's disease and related dementias (ADRD). More research is needed on psychosocial factors that may contribute to racial disparities in rates of ADRD. Past work has identified a relationship between quality of life (QoL) and ADRD risk and also found that religion/spirituality (R/S) participation protects against ADRD.