Nrf2 pathways in neuroprotection: Alleviating mitochondrial dysfunction and cognitive impairment in aging

AA Bhat, E Moglad, A Goyal, M Afzal, R Thapa… - Life Sciences, 2024 - Elsevier
Mitochondrial dysfunction and cognitive impairment are widespread phenomena among the
elderly, being crucial factors that contribute to neurodegenerative diseases. Nuclear factor …

[HTML][HTML] Nanotechnology and nucleic acid nanoparticles for treatment of metabolic disorders

DT Chu, HV Thi, TT Nguyen, TD Vu, YVN Thi, I Mani… - OpenNano, 2023 - Elsevier
Metabolic disorders result from inborn and acquired dysfunction of organs and tissues that
are responsible for producing energy in the body. These diseases are now among the most …

Why is iron deficiency/anemia linked to Alzheimer's disease and its comorbidities, and how is it prevented?

K Fehsel - Biomedicines, 2023 - mdpi.com
Impaired iron metabolism has been increasingly observed in many diseases, but a deeper,
mechanistic understanding of the cellular impact of altered iron metabolism is still lacking. In …

Integrating chemical analysis with in vitro, in silico, and network pharmacology to discover potential functional compounds from Marrubium astracanicum subsp …

ÖK Avşar, S Kasbolat, G Ak, G Caprioli… - Journal of Molecular …, 2024 - Elsevier
The members of the genus Marrubium are of great interest because they contain biologically
active compounds. With in this mind, we aimed to examine the chemical profiles and …

Saponin components in Polygala tenuifolia as potential candidate drugs for treating dementia

S Li, Z Hou, T Ye, X Song, X Hu, J Chen - Frontiers in Pharmacology, 2024 - frontiersin.org
Objective This study aims to elucidate the intervention effects of saponin components from
Polygala tenuifolia Willd (Polygalaceae) on dementia, providing experimental evidence and …

A Scalable High Throughput Fully Automated Pipeline for the Quantification of Amyloid Pathology in Alzheimer's Disease using Deep Learning Algorithms

V Gopal Ramaswamy, M Ahirwar, G Ryan… - bioRxiv, 2023 - biorxiv.org
The most common approach to characterize neuropathology in Alzheimer's disease (AD)
involves a manual survey and inspection by an expert neuropathologist of postmortem …

Machine Learning and Deep Learning Techniques for Alzheimer's Disease Prediction Using CSF and Plasma Biomarkers

AR Zouaoui, H Bentahar, M Djeriuoi… - … on Networking and …, 2023 - ieeexplore.ieee.org
Alzheimer's disease (AD) is a progressive neurodegenerative disease with vast worldwide
consequences. Timely and accurate diagnosis is crucial but present methods are costly and …

Convolutional Neural Networks for Alzheimer's Disease

J Hu - 2023 - preprints.org
Alzheimer's disease (AD) is a progressive and evolving neurodegenerative disease with an
insidious onset that can lead to memory loss and cognitive impairment. There is no effective …

Alzheimer's Disease Investigated via Gene-Environment Interactions, Biochemical Pathways, Cellular Processes, and Disease Phenotype Variability

V Shafi, I Siddiqui - 2024 - researchsquare.com
Background: Alzheimer's disease (AD) is a neurodegenerative disorder influenced by
genetic and environmental factors. APOE, APP, PSEN1, PSEN2, CLU, SORL1, BIN1, CR1 …