Endometrial receptivity in women of advanced age: an underrated factor in infertility

ADS Pathare, M Loid, M Saare, SB Gidlöf… - Human reproduction …, 2023 - academic.oup.com
BACKGROUND Modern lifestyle has led to an increase in the age at conception. Advanced
age is one of the critical risk factors for female-related infertility. It is well known that maternal …

Epigenetic clocks provide clues to the mystery of uterine ageing

PI Deryabin, AV Borodkina - Human Reproduction Update, 2023 - academic.oup.com
BACKGROUND Rising maternal ages and age-related fertility decline are a global
challenge for modern reproductive medicine. Clinicians and researchers pay specific …

[HTML][HTML] Refining epigenetic prediction of chronological and biological age

E Bernabeu, DL McCartney, DA Gadd, RF Hillary… - Genome Medicine, 2023 - Springer
Background Epigenetic clocks can track both chronological age (cAge) and biological age
(bAge). The latter is typically defined by physiological biomarkers and risk of adverse health …

[HTML][HTML] Biologically informed deep learning for explainable epigenetic clocks

A Prosz, O Pipek, J Börcsök, G Palla, Z Szallasi… - Scientific Reports, 2024 - nature.com
Ageing is often characterised by progressive accumulation of damage, and it is one of the
most important risk factors for chronic disease development. Epigenetic mechanisms …

[HTML][HTML] Precious1GPT: multimodal transformer-based transfer learning for aging clock development and feature importance analysis for aging and age-related …

A Urban, D Sidorenko, D Zagirova, E Kozlova… - Aging (Albany …, 2023 - ncbi.nlm.nih.gov
Aging is a complex and multifactorial process that increases the risk of various age-related
diseases and there are many aging clocks that can accurately predict chronological age …

eXplainable Artificial Intelligence (XAI) in aging clock models

A Kalyakulina, I Yusipov, A Moskalev… - Ageing Research …, 2023 - Elsevier
XAI is a rapidly progressing field of machine learning, aiming to unravel the predictions of
complex models. XAI is especially required in sensitive applications, eg in health care, when …

[HTML][HTML] Examining the biological mechanisms of human mental disorders resulting from gene-environment interdependence using novel functional genomic …

PP Silveira, MJ Meaney - Neurobiology of Disease, 2023 - Elsevier
We explore how functional genomics approaches that integrate datasets from human and
non-human model systems can improve our understanding of the effect of gene …

[HTML][HTML] Yearning for machine learning: applications for the classification and characterisation of senescence

BK Hughes, R Wallis, CL Bishop - Cell and Tissue Research, 2023 - Springer
Senescence is a widely appreciated tumour suppressive mechanism, which acts as a barrier
to cancer development by arresting cell cycle progression in response to harmful stimuli …

[HTML][HTML] CellBiAge: Improved single-cell age classification using data binarization

D Yu, M Li, G Linghu, Y Hu, KH Hajdarovic, A Wang… - Cell reports, 2023 - cell.com
Aging is a major risk factor for many diseases. Accurate methods for predicting age in
specific cell types are essential to understand the heterogeneity of aging and to assess …

[HTML][HTML] Accurate age prediction from blood using a small set of DNA methylation sites and a cohort-based machine learning algorithm

M Varshavsky, G Harari, B Glaser, Y Dor, R Shemer… - Cell Reports …, 2023 - cell.com
Chronological age prediction from DNA methylation sheds light on human aging, health,
and lifespan. Current clocks are mostly based on linear models and rely upon hundreds of …