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Record W4390199136 · doi:10.1002/alz.080440

The relationship between [<sup>18</sup>F]FDG‐PET signal and key‐players of brain glucose metabolism

2023· article· en· W4390199136 on OpenAlexaff
Christian Limberger, Luiza Santos Machado, João Pedro Ferrari‐Souza, Guilherme Povala, Giovanna Carello‐Collar, Tharick A. Pascoal, Anne‐Karine Bouzier‐Sore, Luc Pellerin, Débora Guerini de Souza, Eduardo R. Zimmer

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsMcGill University
Fundersnot available
KeywordsGLUT3NeurodegenerationGLUT1Positron emission tomographyNeuroscienceGlutamate receptorInternal medicinePrecuneusHuman brainEndocrinologyGlucose uptakePsychologyBiologyMedicineDiseaseFunctional magnetic resonance imaging

Abstract

fetched live from OpenAlex

Abstract Background Neuronal activity is supported by activity‐dependent lactate production from astrocytes, as postulated by the astrocyte–neuron lactate shuttle (ANLS) hypothesis. Indeed, astrocytic glutamate uptake is a main trigger for brain glucose consumption. [18F]fluorodeoxyglucose (FDG)‐PET showing a hypometabolic signature has been used as an index of neurodegeneration in Alzheimer’s disease (AD). In the early stages of the disease, soluble amyloid‐beta (Aβ) has been associated with neuronal hyperactivity due to decreased astrocytic glutamate uptake. It is hypothesized that this phenomenon occurs especially in regions with high ongoing baseline activity. Over time, neurodegeneration and hypometabolism in such regions may contribute to the progress of the AD continuum. Thus, we investigated whether the [18F]FDG‐PET signal in typical hypometabolic regions in AD is associated with the expression of ANLS transporters and enzymes in the healthy brain. Method Gene expression of GLUT1, GLUT3, MCT1, MCT2, MCT4, LDHA, and LDHB (ANLS genes) from postmortem brain tissue of healthy individuals were obtained from the Allen Human Brain Atlas. [18F]FDG‐PET data from cognitively unimpaired individuals were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Pearson correlations were performed between the mean gene expression and the mean [18F]FDG‐PET SUVr across typically hypometabolic brain regions in AD (precuneus, angular and temporal gyri, and parietal and cingulate regions) and non‐vulnerable regions (uncorrected p‐value < 0.05). Results The expression of ANLS genes had a stronger positive correlation with [18F]FDG‐PET SUVr across the AD hypometabolic regions than the non‐vulnerable regions (p < 0.05). Of note, the astrocytic glucose transporter GLUT1 presented a stronger correlation with [18F]FDG‐PET than the neuronal transporter GLUT3 in AD‐vulnerable regions. Figure 1 presents all correlations. Conclusion Our results show that the physiological expression of transporters and enzymes responsible for the brain glucose metabolism correlate more with the [18F]FDG‐PET signal in typical brain regions of the AD hypometabolic signature. This suggests these regions present a higher baseline activity and may be more susceptible to Aβ‐induced hyperactivation in early AD, which could lead to a bioenergetic collapse in later disease stages, as shown in the [18F]FDG‐PET of AD individuals.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.065
GPT teacher head0.335
Teacher spread0.269 · 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 designObservational
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
Published2023
Admission routes1
Has abstractyes

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