MétaCan
Menu
← Back to cohort
Record W4240757816 · doi:10.1016/j.jalz.2014.05.536

P1‐296: ALTERNATIVE CEREBRAL GLUCOSE UPTAKE METRICS DETECT EARLY METABOLIC CHANGES IN THE 5XFAD MOUSE MODEL OF ALZHEIMER'S DISEASE

2014· article· en· W4240757816 on OpenAlexaff
Drew R. DeBay, Ian R. Macdonald, G. Andrew Reid, Tim O'Leary, Courtney Jollymore, Meghan K. Cash, George Mawko, Steven Burrell, Earl Martin, Chris V. Bowen, Richard E. Brown, Sultan Darvesh

Bibliographic record

VenueAlzheimer s & Dementia · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolomics and Mass Spectrometry Studies
Canadian institutionsMount Saint Vincent UniversityDalhousie University
Fundersnot available
KeywordsNeocortexAmygdalaThalamusHippocampusCerebellumMedicinePathologyAlzheimer's diseaseNeuroscienceInternal medicineBasal forebrainDiseaseEndocrinologyCentral nervous systemBiology

Abstract

fetched live from OpenAlex

Despite concerted efforts towards identifying brain imaging biomarkers in Alzheimer's Disease (AD), early and definitive diagnosis of AD during life remains elusive. Characteristic neurometabolic dysfunction, as revealed by 18 FDG PET imaging, is profound in later stages of AD. However, altered metabolism at early stages of the disease has been difficult to observe. This may be due, in part, to the variable representation and interpretation of such data using standardized uptake values (SUVs) and relative SUVs (SUVRs). We posit that alternative metrics of 18 FDG uptake may provide new insight into early aberrant metabolic regulation in the AD brain. Male 5XFAD (n=24) and age-matched wild-type (WT) mice (n=13) at 2, 5 and 13 months underwent PET scanning 30 min after 18 FDG administration, and subsequently imaged using CT/MRI. PET/CT/MRI data were co-registered and MR-based ROIs of specific brain regions were generated including amygdala, basal forebrain, cerebellum, hippocampus, hypothalamus, neocortex and thalamus. SUVs were reported and a series of relative SUVs (SUVRs) were iteratively generated to evaluate the sensitivity of each brain region as a candidate reference tissue. 5XFAD animals demonstrated a global decrease in 18 FDG SUVs compared to WT controls at 13 months in each of the brain structures investigated (p ≤ 0.002). 5XFAD mice at 2 and 5 months showed no significant difference in SUVs compared to their control counterparts. Importantly, employing alternative SUVR metrics to express relative 18 F-FDG uptake revealed an early and significant SUVR increase in 5XFAD mice at 2 months when using neocortex as the reference region (p ≤ 0.03) - a feature that could not distinguish 5XFAD and WT mice using SUVs alone, or the frequently employed cerebellar reference SUVR. As in human AD, significant decreases in brain 18 F-FDG uptake are directly observable only in late disease stages in the 5XFAD model. However, determining alternative regional brain glucose metabolism SUVRs in young animals was found to distinguish 5XFAD from WT mice. We conclude 18 FDG uptake could represent a sensitive biomarker for early detection of brain dysfunction in AD mouse models when alternative SUVR metrics are utilized. Further study utilizing the ADNI database will help determine applicability in human AD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.257
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueAlzheimer s & Dementia→Same topicMetabolomics and Mass Spectrometry Studies→French-language works237,207→