# Biological Age

Ibáñez and colleagues report in Science Advances a 'speech clock': they recorded 2,928 Spanish speakers from Argentina, Chile, Colombia, Mexico and Peru across various speech tasks, used machine learning to extract more than 700 speech features that change with ageing and dementia (such as pitch and vocabulary range), trained a model to predict age and compute a 'speech age gap', and found the clock could distinguish healthy individuals from those with some form of cognitive impairment, rating the speech of people with cognitive issues as older than expected for their chronological age while healthy people's speech generally matched their age.

Ibáñez and colleagues report in Science Advances a 'speech clock': they recorded 2,928 Spanish speakers from Argentina, Chile, Colombia, Mexico and Peru across various speech tasks, used machine learning to extract more than 700 speech features that change with ageing and dementia (such as pitch and vocabulary range), trained a model to predict age and compute a 'speech age gap', and found the clock could distinguish healthy individuals from those with some form of cognitive impairment, rating the speech of people with cognitive issues as older than expected for their chronological age while healthy people's speech generally matched their age.

Jesse Poganik's team at Harvard grafted hearts from young, middle-aged and old mice into mice of all three age groups and measured DNA methylation across roughly 320,000 genomic regions, finding that grafted hearts shifted their biological age toward the recipient; the same effect appeared in biopsy samples from 11 historical heart transplants at Brigham and Women's Hospital with large donor-recipient age gaps, while some functional measures such as heart rate, posterior wall thickness and exercise capacity tracked recipient age rather than donor age.

Jesse Poganik's team at Harvard grafted hearts from young, middle-aged and old mice into mice of all three age groups and measured DNA methylation across roughly 320,000 genomic regions, finding that grafted hearts shifted their biological age toward the recipient; the same effect appeared in biopsy samples from 11 historical heart transplants at Brigham and Women's Hospital with large donor-recipient age gaps, while some functional measures such as heart rate, posterior wall thickness and exercise capacity tracked recipient age rather than donor age.

A report in Cell describes an artificial-intelligence system for ageing biology that introduces large language models trained on ageing data, a suite of 17 benchmark tasks for evaluating these and other LLMs on ageing-related projects, and an interface that brings the models and other ageing research tools together with AI agents; using these benchmarks, the authors compared their specialist LLMs with much larger commercial models from companies including OpenAI and DeepSeek, finding that the ageing-tailored LLMs outperformed the large LLMs in many, though not all, tests.

A report in Cell describes an artificial-intelligence system for ageing biology that introduces large language models trained on ageing data, a suite of 17 benchmark tasks for evaluating these and other LLMs on ageing-related projects, and an interface that brings the models and other ageing research tools together with AI agents; using these benchmarks, the authors compared their specialist LLMs with much larger commercial models from companies including OpenAI and DeepSeek, finding that the ageing-tailored LLMs outperformed the large LLMs in many, though not all, tests.