Results 241 to 250 of about 2,022,626 (303)

Robust Metabolomic Age Prediction Based on a Wide Selection of Metabolites. [PDF]

J Gerontol A Biol Sci Med Sci
Faquih TO, van Hylckama Vlieg A, Surendran P, Butterworth AS, Li-Gao R, de Mutsert R, Rosendaal FR, Noordam R, van Heemst D, Willems van Dijk K, Mook-Kanamori DO.   +10 more
europepmc   +1 more source

Value of MRI Outcomes for Preventive and Early‐Stage Trials in Spinocerebellar Ataxias 1 and 3

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To examine the value of MRI outcomes as endpoints for preventive and early‐stage trials of two polyglutamine spinocerebellar ataxias (SCAs). Methods A cohort of 100 participants (23 SCA1, 63 SCA3, median Scale for the Assessment and Rating of Ataxia (SARA) score = 5, 42% preataxic, and 14 gene‐negative controls) was scanned at 3T up ...
Thiago J. R. Rezende, Emilien Petit, Young Woo Park, Sophie Tezenas du Montcel, James M. Joers, Jonathan M. DuBois, H. Moore Arnold, Michal Povazan, Ipek Özdemir, Guita Banan, Romain Valabregue, Philipp Ehses, Jennifer Faber, Chiadi U. Onyike, Peter B. Barker, Jeremy D. Schmahmann, Eva‐Maria Ratai, Sub H. Subramony, Thomas H. Mareci, Khalaf O. Bushara, Henry Paulson, Thomas Klockgether, Alexandra Durr, Tetsuo Ashizawa, Christophe Lenglet, Gülin Öz, READISCA Investigators   +26 more
wiley   +1 more source

Biological age prediction using a DNN model based on pathways of steroidogenesis. [PDF]

Sci Adv
Wang Q, Wang Z, Mizuguchi K, Takao T.
europepmc   +1 more source

Fluid Biomarkers of Disease Burden and Cognitive Dysfunction in Progressive Supranuclear Palsy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Identifying objective biomarkers for progressive supranuclear palsy (PSP) is crucial to improving diagnosis and establishing clinical trial and treatment endpoints. This study evaluated fluid biomarkers in PSP versus controls and their associations with regional 18F‐PI‐2620 tau‐PET, clinical, and cognitive outcomes.
Roxane Dilcher, Charles B. Malpas, Stuart J. McDonald, William T. O’Brien, Craig Despott, Kelly L. Bertram, Matthew P. Pase, Lukas Frontzkowski, Meng Law, Terence J. O’Brien, Lucy Vivash   +10 more
wiley   +1 more source

[Research progress in electroencephalogram-based brain age prediction]. [PDF]

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi
Zu H, Zhan P, Yu H, Wang W, Liu H.
europepmc   +1 more source

Brain age prediction model based on electroencephalogram signal and its application in children with autism spectrum disorders. [PDF]

Front Neurol
Ju Y, Zhao T, Gao Z, Hu W, Luo J, Cheng N, Liu C, Jiang Y, Hong B, Ji T, Yan Y.   +10 more
europepmc   +1 more source

Deep Learning-based Brain Age Prediction Using MRI to Identify Fetuses with Cerebral Ventriculomegaly. [PDF]

Radiol Artif Intell
Yun HJ, Lee HJ, You S, Lee JY, Aguirre-Chavez J, Vasung L, Lee HJ, Tarui T, Feldman HA, Grant PE, Im K.   +10 more
europepmc   +1 more source

Association between shift work and brain age gap: a neuroimaging study using MRI-based brain age prediction algorithms. [PDF]

Front Aging Neurosci
Kim Y, Choi JY, Petrovskiy E, Lee W.
europepmc   +1 more source

The immunological age prediction of monocytes indicates that gestational diabetes mellitus accelerates the aging of monocytes in offspring. [PDF]

Immun Ageing
Zhang Y, Guo R, Yin M, Shi M, Zhong T, Liu S, Li X.   +6 more
europepmc   +1 more source

Potential vulnerability and resilience to accelerated brain aging in women exposed to stressful life events: insights from the brain age prediction model. [PDF]

Neurobiol Stress
Jeong H, Joo Y, Shim Y, Kim Y, Lee H, Jin Y, Kim SJ, Yoon S, Lyoo IK.   +8 more
europepmc   +1 more source