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Record W3122555749 · doi:10.3390/nu13020284

Consumption of Oleic Acid on the Preservation of Cognitive Functions in Japanese Elderly Individuals

2021· article· en· W3122555749 on OpenAlexaboutno aff
Keisuke Sakurai, Chutong Shen, Izumi Shiraishi, Noriko Inamura, Tatsuhiro Hisatsune

Bibliographic record

VenueNutrients · 2021
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsnot available
FundersMinistry of Agriculture, Forestry and Fisheries
KeywordsMontreal Cognitive AssessmentCognitionOleic acidMedicineNutrientGerontologyWechsler Adult Intelligence ScaleCohortInternal medicineBiologyBiochemistryCognitive impairmentEcology

Abstract

fetched live from OpenAlex

We recruited 154 community-dwelling elderly individuals and conducted a cohort study to find out the nutrient intake that is suitable for maintaining cognitive function in Japanese elders. Cognitive function was evaluated by the two functional tests, the Montreal Cognitive Assessment (MoCA) and Wechsler Memory Scale-Delayed Recall (WMS-DR), and daily nutrient intake was estimated from a Brief-type Self-administered Diet History Questionnaire (BDHQ). By a multiple regression analysis, among the four major nutrients (protein, fat, carbohydrate and ash), we detected a significant correlation between the score of cognitive functions assessed by both MoCA and WMS-DR and daily consumption of fat (p = 0.0317 and p = 0.0111, respectively). Among categories of fatty acid, we found a significant correlation between the score of both MoCA and WMS-DR and consumption of monounsaturated fatty acid (MUFA) (p = 0.0157 and p = 0.0136, respectively). Finally, among MUFAs, we observed a significant correlation between the score of both MoCA and WMS-DR and consumption of oleic acid (p = 0.0405 and p = 0.0165, respectively). From these observations, we can propose that daily consumption of fat, especially in oleic acid, has a beneficial effect against cognitive decline in community-dwelling Japanese elderly 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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.187

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 head0.050
GPT teacher head0.303
Teacher spread0.253 · 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 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

Citations44
Published2021
Admission routes1
Has abstractyes

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