Online ISSN: 1945-4589
www.aging-us.com
About Aging
Launched in 2009, Aging publishes papers of general interest and biological significance in all fields of aging research and age-related diseases, including cancer—and now, with a special focus on COVID-19 vulnerability as an age-dependent syndrome. Topics in Aging go beyond traditional gerontology, including, but not limited to, cellular and molecular biology, human age-related diseases, pathology in model organisms, signal transduction pathways (e.g., p53, sirtuins, and PI-3K/AKT/mTOR, among others), and approaches to modulating these signaling pathways.

LEARN MORE ABOUT AGING

Inhibiting NLRP3 Signaling in Aging Podocytes Improves Longevity

Aging

August 8, 2023
PRESS RELEASE: A new research paper was published in Aging's Volume 15, Issue 14, entitled, “Inhibiting NLRP3 signaling in aging podocytes improves their life- and health-span.” continue reading »

Navigating the Frailty Factor in Atrial Fibrillation Management

Aging

August 3, 2023
In a new editorial, researchers discuss the impact of frailty on clinical decision-making in managing patients with atrial fibrillation and the prescription of oral anticoagulants. continue reading »

Towards Disease-Oriented Dosing of Rapamycin for Longevity

Aging

August 2, 2023
PRESS RELEASE: A new research perspective was published in Aging's Volume 15, Issue 14, entitled, “Towards disease-oriented dosing of rapamycin for longevity: does aging exist or only age-related diseases?” continue reading »

Human Senescent Fibroblasts Cause Lung Fibrosis in Mice

Aging

July 31, 2023
PRESS RELEASE: A new research paper was published on the cover of Aging's Volume 15, Issue 14, entitled, “Human senescent fibroblasts trigger progressive lung fibrosis in mice.” continue reading »

Predicting Lifespan-Extending Chemical Compounds for C. Elegans With Machine Learning

News

July 26, 2023
PRESS RELEASE: A new research paper was published in Aging's Volume 15, Issue 13, entitled, “Predicting lifespan-extending chemical compounds for C. elegans with machine learning and biologically interpretable features.” continue reading »