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Record W2770733176 · doi:10.3390/nu9121289

Integrated Immunomodulatory Mechanisms through which Long-Chain n-3 Polyunsaturated Fatty Acids Attenuate Obese Adipose Tissue Dysfunction

2017· review· en· W2770733176 on OpenAlexafffund
Danyelle M. Liddle, Amber L. Hutchinson, Hannah R. Wellings, Krista A. Power, Lindsay E. Robinson, Jennifer M. Monk

Bibliographic record

VenueNutrients · 2017
Typereview
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsUniversity of OttawaUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAdipokineAdipose tissueDocosahexaenoic acidPolyunsaturated fatty acidEicosapentaenoic acidInflammationMedicineObesityFish oilEndocrinologyImmune systemInternal medicineImmunologyBiologyInsulin resistanceFatty acidBiochemistryFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Obesity is a global health concern with rising prevalence that increases the risk of developing other chronic diseases. A causal link connecting overnutrition, the development of obesity and obesity-associated co-morbidities is visceral adipose tissue (AT) dysfunction, characterized by changes in the cellularity of various immune cell populations, altered production of inflammatory adipokines that sustain a chronic state of low-grade inflammation and, ultimately, dysregulated AT metabolic function. Therefore, dietary intervention strategies aimed to halt the progression of obese AT dysfunction through any of the aforementioned processes represent an important active area of research. In this connection, fish oil-derived dietary long-chain n-3 polyunsaturated fatty acids (PUFA) in the form of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) have been demonstrated to attenuate obese AT dysfunction through multiple mechanisms, ultimately affecting AT immune cellularity and function, adipokine production, and metabolic signaling pathways, all of which will be discussed herein.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.048
GPT teacher head0.332
Teacher spread0.284 · 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

Citations40
Published2017
Admission routes2
Has abstractyes

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