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Record W2111741044 · doi:10.2217/clp.14.61

Challenges to determining whether DHA can protect against age-related cognitive decline

2015· article· en· W2111741044 on OpenAlexaff
Marie Hennebelle, Emilie Harbeby, Sébastien Tremblay, Raphaël Chouinard‐Watkins, Fabien Pifferi, Mélanie Plourde, Philippe Guesnet, Stephen C. Cunnane

Bibliographic record

VenueClinical Lipidology · 2015
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsCognitive declineNeuroprotectionDiseaseDocosahexaenoic acidBrain functionNeuroscienceAging brainAnimal studiesBrain agingCognitionMedicineAlzheimer's diseaseHomeostasisGerontologyBioinformaticsBiologyPsychologyPolyunsaturated fatty acidDementiaFatty acidEndocrinologyBiochemistryInternal medicine

Abstract

fetched live from OpenAlex

DHA, an omega-3 fatty acid, is an important constituent of brain membranes and has a key role in brain development and function. This review aims to highlight recent research on DHA’s role during age-related cognitive decline and Alzheimer’s disease. Animal and in vitro studies have provided some interesting mechanistic leads, especially on brain glucose metabolism, that may be involved in neuroprotection by DHA. However, results from human studies are more mitigated, perhaps due to changing DHA metabolism during aging. Recent innovative tools such as 13C-DHA for metabolic studies and 11C-DHA for PET provide interesting opportunities to study factors that affect DHA homeostasis during aging and to better understand whether and how to use DHA to delay or treat Alzheimer’s disease.

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)0.024
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.044
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0040.007
Open science0.0020.003
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0080.003

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 head0.274
GPT teacher head0.465
Teacher spread0.191 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations16
Published2015
Admission routes1
Has abstractyes

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