Evidence map›Paper›PMID 43019186›Full record

ArticleScientific reports2026

Full-compartmental modeling of [

Mattia De Francisci, Edoardo Faggionato, Chiara Dalla Man, John J Lee, Nicholas Metcalf, Marcus E Raichle, John C Morris, Tammie L S Benzinger, Andrei G Vlassenko, Alessandra Bertoldo and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Mattia De FrancisciDepartment of Information Engineering, University of Padova, Padua, Italy.
Edoardo FaggionatoDepartment of Information Engineering, University of Padova, Padua, Italy.
Chiara Dalla ManDepartment of Information Engineering, University of Padova, Padua, Italy.
John J LeeNeuroimaging Laboratories Research Center, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO USA.
Nicholas MetcalfNeuroimaging Laboratories Research Center, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO USA.
Marcus E RaichleNeuroimaging Laboratories Research Center, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO USA.
John C MorrisKnight ADRC, Department of Neurology, Washington University School of Medicine, St. Louis, USA.
Tammie L S BenzingerNeuroimaging Laboratories Research Center, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO USA.
Andrei G VlassenkoNeuroimaging Laboratories Research Center, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO USA.
Alessandra BertoldoDepartment of Information Engineering, University of Padova, Padua, Italy.
Manu S GoyalNeuroimaging Laboratories Research Center, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO USA.ORCID 0000-0003-1970-4270

Funding

Aerobic Glycolysis in the Development ofAlzheimer's DiseaseR01AG053503 · NIA · WASHINGTON UNIVERSITY · PI RAICHLE, MARCUS E, VLASSENKO, ANDREI G. · 2017 to 2021
$4.1M
Aerobic Glycolysis: A Marker of BrainResilience to Aging and Alzheimer's DiseaseR01AG057536 · NIA · WASHINGTON UNIVERSITY · PI GOYAL, MANU S, VLASSENKO, ANDREI G. · 2017 to 2021
$3.7M
Brain metabolism during task-evoked and spontaneous activity in aging and Alzheimer's diseaseRF1AG074992 · NIA · WASHINGTON UNIVERSITY · PI GOYAL, MANU S, VLASSENKO, ANDREI G. · 2023 to 2023
$2.3M
White Matter Metabolism in the Context of Aging, White Matter Hyperintensities and Alzheimer's DiseaseRF1AG073210 · NIA · WASHINGTON UNIVERSITY · PI GOYAL, MANU S, VLASSENKO, ANDREI G. · 2022 to 2022
$2.3M
NIA NIH HHS R01 AG053503NIA NIH HHS R01 AG057536NIA NIH HHS RF1 AG073210NIA NIH HHS RF1 AG074992
6 · The paper itself

Abstract

Within the Alzheimer disease (AD) spectrum, metabolic alterations occur in addition to proteinopathies. While hypometabolism is frequently observed in the late symptomatic stages, characterizing the metabolic changes during early AD stages might aid in both understanding its pathophysiology and in patient selection for future treatments. In this study, we conduct an exploratory, data-driven analysis aimed at better understanding the timing and specificity of the metabolic changes in early AD. Using kinetic analysis of [ Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1038/s41598-026-64573-x.

Indexed as

AgingAlzheimer DiseaseBrainFluorodeoxyglucose F18Positron-Emission TomographyAgedAged, 80 and overFemaleGlucoseHumansMaleRadiopharmaceuticalsFluorodeoxyglucose F18GlucoseRadiopharmaceuticalsBiomarkersDiseasesNeurologyNeuroscience

Identifiers

PMID43019186
PMCPMC13722582

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.