Article in npj aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.
0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registry
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Shiva Kazempour Dehkordi *Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, San Antonio, TX, USA.
Sogand Sajedi *Leukemia Department, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Amirreza HeshmatDepartment of Imaging Physics, the University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Miranda E Orr *Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA. orr.m@wustl.edu.
Habil Zare *Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, San Antonio, TX, USA. zare@uthscsa.edu.
Funding
DISCOVERY - Statistics and Analysis CoreU19NS115388 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI Steven M Greenberg, Natalia S Rost · 2019 to 2026
$75.4M
SUPPLEMENT TO RUSH ALZHEIMERS DISEASE CENTER COREP30AG010161 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 1991 to 2020
$49.1M
EPIDEMIOLOGY OF NEURAL RESERVE AND NEUROBIOLOGY IN AGINGR01AG017917 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 2001 to 2023
$43.3M
South Texas Alzheimer's Disease Research CenterP30AG066546 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI Sudha Seshadri · 2021 to 2026
$24.0M
PRECURSORS OF STROKE INCIDENCE AND PROGNOSISR01NS017950 · NINDS · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI Hugo Javier Aparicio, Jose Rafael Romero · 1985 to 2026
$22.9M
RISK FACTORS, PATHOLOGY, AND CLINICAL EXPRESSIONS OF ADR01AG015819 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 1998 to 2024
$21.4M
Multi-omic network-directed proteoform discovery, dissection and functional validation to prioritize novel AD therapeutic targetsU01AG061356 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BENNETT, DAVID ALAN, DE JAGER, PHILIP L · 2018 to 2022
$13.7M
Midwest Murine-Tissue Mapping Center (MM-TMC)U54AG079754 · NIA · UNIVERSITY OF MINNESOTA · PI GR Scott Budinger, Sundeep Khosla · 2022 to 2026
$11.5M
Development of an Innovative Vervet (Chlorocebus aethiops sabaeus) Model of Early Alzheimer's-like Neuropathology and SymptomatologyR24AG073199 · NIA · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI CRAFT, SUZANNE, SHIVELY, CAROL A. · 2021 to 2024
$5.6M
Plasma Proteome and Risk of Alzheimer Dementia and Related Endophenotypes in the Framingham StudyRF1AG063507 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI GERSZTEN, ROBERT E, RAMACHANDRAN, VASAN S · 2019 to 2019
$4.2M
Deconstructing and modeling the single cell architecture of the Alzheimer brainRF1AG057473 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BENNETT, DAVID ALAN, DE JAGER, PHILIP L · 2017 to 2018
$4.0M
Mechanisms of tau- and aging-induced neurological dysfunction: Focus on the nucleusR01AG057896 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI FROST, BESS · 2019 to 2023
Neuronal senescence (i.e., neurescence) is an important hallmark of aging and neurodegeneration, but it remains poorly characterized in the human brain due to the lack of reliable markers. This study aimed to identify neurescence markers based on single-nucleus transcriptome data from postmortem human prefrontal cortex. Using an eigengene approach, we integrated three gene panels: (a) SenMayo, (b) canonical senescence pathway (CSP), and (c) senescence initiating pathway (SIP), to identify neurescence signatures. We found that paired markers outperform single markers; for instance, by combining CDKN2D and ETS2 in a decision tree, a high accuracy of 99% and perfect specificity (100%) were achieved in distinguishing senescent neurons (i.e, neurescent). Differential expression analyses identified 324 genes that are overexpressed in neurescent. These genes showed significant associations with important neurodegeneration-related pathways, including Alzheimer's disease, Parkinson's disease, and Huntington's disease. Interestingly, several of these overexpressed genes are linked to mitochondrial dysfunction and cytoskeletal dysregulation. These findings provide valuable insights into the complexities of neurescence, emphasizing the need for further exploration of histologically viable markers and validation in broader datasets.
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.
Identification of markers for neurescence through transcriptomic profiling of postmortem human brains. · full record | OpenQuestion