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Record W2761877473 · doi:10.1111/febs.14291

Deuterium‐reinforced polyunsaturated fatty acids improve cognition in a mouse model of sporadic Alzheimer's disease

2017· article· en· W2761877473 on OpenAlexafffund
Ahmed Elharram, Nicole M. Czegledy, Michael Golod, Ginger L. Milne, Erik D. Pollock, Brian M. Bennett, Mikhail S. Shchepinov

Bibliographic record

VenueFEBS Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsQueen's University
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesCanadian Institutes of Health ResearchNational Institute on AgingNational Institutes of Health
KeywordsPolyunsaturated fatty acidDiseaseCognitionAlzheimer's diseaseBiochemistryChemistryMedicineBiologyFatty acidNeuroscienceInternal medicine

Abstract

fetched live from OpenAlex

Oxidative damage resulting from increased lipid peroxidation ( LPO ) is considered an important factor in the development of late onset/age‐related Alzheimer's disease ( AD ). Deuterium‐reinforced polyunsaturated fatty acids (D‐ PUFA s) are more resistant to the reactive oxygen species‐initiated chain reaction of LPO than regular hydrogenated (H‐) PUFA s. We investigated the effect of D‐ PUFA treatment on LPO and cognitive performance in aldehyde dehydrogenase 2 ( Aldh2 ) null mice, an established model of oxidative stress‐related cognitive impairment that exhibits AD ‐like pathologies. Mice were fed a Western‐type diet containing either D‐ or H‐ PUFA s for 18 weeks. D‐ PUFA treatment markedly decreased cortex and hippocampus F 2 ‐isoprostanes by approximately 55% and prostaglandin F 2α by 20–25% as compared to H‐ PUFA treatment. D‐ PUFA s consistently improved performance in cognitive/memory tests, essentially resetting performance of the D‐ PUFA ‐fed Aldh2 − / − mice to that of wild‐type mice fed a typical laboratory diet. D‐ PUFA s therefore represent a promising new strategy to broadly reduce rates of LPO , and combat cognitive decline in 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.743
Threshold uncertainty score0.518

Codex and Gemma teacher scores by category

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

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 head0.038
GPT teacher head0.296
Teacher spread0.258 · 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 teacher head, 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

Citations58
Published2017
Admission routes2
Has abstractyes

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