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Record W7132964874

The Role of Omega-3 Polyunsaturated Fatty Acids in Adipose Tissue Inflammation: a Longitudinal Analysis in the PROMISE Cohort

2023· dissertation· W7132964874 on OpenAlexaboutno aff
Ji-Eun Chon

Bibliographic record

VenueTSpace · 2023
Typedissertation
Language
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsnot available
Fundersnot available
KeywordsAdipose tissueCohortInflammationPolyunsaturated fatty acidDiseaseCohort studyAdipokineHuman studies
DOInot available

Abstract

fetched live from OpenAlex

The role of adipose tissue (AT) as the initiating organ of the sub-clinical inflammation phenotype characterizing obesity-associated chronic disease is being actively investigated. Pre-clinical evidence suggests that n-3 PUFAs modulate AT inflammation, although human data are limited and inconclusive. This thesis aimed to (1) map existing literature on n-3 PUFAs and AT inflammation in healthy humans in a scoping review; and (2) investigate longitudinal associations of circulating levels and dietary intake of n-3 PUFAs with AT-specific biomarkers using data from a cohort study of Canadian adults at high risk for type 2 diabetes. The scoping review documented inconsistent findings in published studies (n=25), as well as considerable heterogeneity in important methodological features. Cohort analysis indicated significant inverse associations of circulating n-3 PUFAs, more specifically EPA, DPA, and DHA, with AT-specific biomarkers. Collectively, these results suggest n-3 PUFAs may have a beneficial effect on modulating AT inflammation in humans, although additional well-designed studies are needed.

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)0.007
metaresearch head score (Gemma)0.009
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 score0.051
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.023
GPT teacher head0.367
Teacher spread0.344 · 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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