A roadmap to build a phenotypic metric of ageing: insights from the Baltimore Longitudinal Study of Aging

PL Kuo, JA Schrack, MD Shardell… - Journal of Internal …, 2020 - Wiley Online Library
Over the past three decades, considerable effort has been dedicated to quantifying the pace
of ageing yet identifying the most essential metrics of ageing remains challenging due to …

Senolytic therapy in mild Alzheimer's disease: a phase 1 feasibility trial

MM Gonzales, VR Garbarino, TF Kautz, JP Palavicini… - Nature medicine, 2023 - nature.com
Cellular senescence contributes to Alzheimer's disease (AD) pathogenesis. An open-label,
proof-of-concept, phase I clinical trial of orally delivered senolytic therapy, dasatinib (D) and …

Why experimental variation in neuroimaging should be embraced

G Kiar, JA Mumford, T Xu, JT Vogelstein… - Nature …, 2024 - nature.com
In a perfect world, scientists would develop analyses that are guaranteed to reveal the
ground truth of a research question. In reality, there are countless viable workflows that …

Brain aging patterns in a large and diverse cohort of 49,482 individuals

Z Yang, J Wen, G Erus, ST Govindarajan, R Melhem… - Nature medicine, 2024 - nature.com
Brain aging process is influenced by various lifestyle, environmental and genetic factors, as
well as by age-related and often coexisting pathologies. Magnetic resonance imaging and …

OASIS-3: longitudinal neuroimaging, clinical, and cognitive dataset for normal aging and Alzheimer disease

PJ LaMontagne, TLS Benzinger, JC Morris, S Keefe… - medrxiv, 2019 - medrxiv.org
ABSTRACT OASIS-3 is a compilation of MRI and PET imaging and related clinical data for
1098 participants who were collected across several ongoing studies in the Washington …

[HTML][HTML] Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan

R Pomponio, G Erus, M Habes, J Doshi, D Srinivasan… - NeuroImage, 2020 - Elsevier
As medical imaging enters its information era and presents rapidly increasing needs for big
data analytics, robust pooling and harmonization of imaging data across diverse cohorts …

Advancing the cancer genome atlas glioma MRI collections with expert segmentation labels and radiomic features

S Bakas, H Akbari, A Sotiras, M Bilello, M Rozycki… - Scientific data, 2017 - nature.com
Gliomas belong to a group of central nervous system tumors, and consist of various sub-
regions. Gold standard labeling of these sub-regions in radiographic imaging is essential for …

Bias in machine learning models can be significantly mitigated by careful training: Evidence from neuroimaging studies

R Wang, P Chaudhari… - Proceedings of the …, 2023 - National Acad Sciences
Despite the great promise that machine learning has offered in many fields of medicine, it
has also raised concerns about potential biases and poor generalization across genders …

Two distinct neuroanatomical subtypes of schizophrenia revealed using machine learning

GB Chand, DB Dwyer, G Erus, A Sotiras, E Varol… - Brain, 2020 - academic.oup.com
Neurobiological heterogeneity in schizophrenia is poorly understood and confounds current
analyses. We investigated neuroanatomical subtypes in a multi-institutional multi-ethnic …

Association of intensive vs standard blood pressure control with cerebral white matter lesions

IM Nasrallah, NM Pajewski, AP Auchus, G Chelune… - Jama, 2019 - jamanetwork.com
Importance The effect of intensive blood pressure lowering on brain health remains
uncertain. Objective To evaluate the association of intensive blood pressure treatment with …