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Record W3055948890 · doi:10.1038/s42003-020-01189-5

Thickness of the cerebral cortex shows positive association with blood levels of triacylglycerols carrying 18-carbon fatty acids

2020· article· en· W3055948890 on OpenAlexafffund
Eeva Sliz, Jean Shin, Catriona Syme, Sandra E. Black, Sudha Seshadri, Tomáš Paus, Zdenka Pausová

Bibliographic record

VenueCommunications Biology · 2020
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsHolland Bloorview Kids Rehabilitation HospitalSunnybrook HospitalHealth Sciences CentreSunnybrook Health Science CentreToronto Dementia Research AllianceUniversity of TorontoSickKids FoundationHospital for Sick Children
FundersNational Institute on AgingCanadian Institutes of Health ResearchHospital for Sick ChildrenHeart and Stroke Foundation of Canada
KeywordsDocosahexaenoic acidArachidonic acidMetabolismLinoleic acidCortex (anatomy)Fatty acidCerebral cortexBrain cortexFatty acid metabolismBiochemistryEndocrinologyInternal medicineChemistryBiologyPolyunsaturated fatty acidMedicineNeuroscienceEnzyme

Abstract

fetched live from OpenAlex

Perturbations in fatty acid (FA) metabolism as well as thinning of the cerebral cortex have been associated with cognitive decline in the elderly. Predominant FAs in the brain are docosahexaenoic acid (DHA) and arachidonic acid (ARA). Approximately 2-8% of esterified DHA and 3-5% of esterified ARA in the brain are replaced daily. DHA and ARA are derivatives of 18-carbon essential FAs, α-linolenic acid and linoleic acid, that must be imported into the brain from the circulation. In blood, FAs are primarily transported in triacylglycerols (TAGs) from which they can be released at the blood-brain-barrier and transported inside the brain. We show that circulating levels of TAGs carrying 18-carbon FAs are positively associated with cortical thickness in middle-aged adults. These associations are stronger in cortical regions with higher expression of genes regulating long-chain FA metabolism and cellular membranes, and cortical thickness in the same regions may be related to cognitive performance.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.075
Threshold uncertainty score0.330

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
Research integrity0.0000.001
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 head0.078
GPT teacher head0.342
Teacher spread0.264 · 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

Citations18
Published2020
Admission routes2
Has abstractyes

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