Why people tend to make career decisions and What helps them to choose
Bibliographic record
Abstract
Typically fatty acids (FA) exert differential immunomodulatory effects with n-3 [α-linolenic acid (ALA), eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA)] and n-6 [linoleic acid (LA) and arachidonic acid (AA)] exerting anti- and pro-inflammatory effects, respectively. This over-simplified interpretation is confounded by a failure to account for conversion of the parent FA (LA and ALA) to longer-chain bioactive products (AA and EPA/DHA, respectively), thereby precluding discernment of the immunomodulatory potential of specific FA. Therefore, we utilized the Δ6-desaturase model, wherein knockout mice (D6KO) lack the Fads2 gene encoding for the rate-limiting enzyme that initiates FA metabolism, thereby providing a model to determine specific FA immunomodulatory effects. Wild-type (WT) and D6KO mice were fed one of four isocaloric diets differing in FA source (9weeks): corn oil (LA-enriched), arachidonic acid single cell oil (AA-enriched), flaxseed oil (ALA-enriched) or menhaden fish oil (EPA/DHA-enriched). Splenic mononuclear cell cytokine production in response to lipopolysaccharide (LPS), T-cell receptor (TCR) and anti-CD40 stimulation was determined. Following LPS stimulation, AA was more bioactive compared to LA, by increasing inflammatory cytokine production of IL-6 (1.2-fold) and TNFα (1.3-fold). Further, LPS-stimulated IFNγ production in LA-fed D6KO mice was reduced 5-fold compared to LA-fed WT mice, indicating that conversion of LA to AA was necessary for cytokine production. Conversely, ALA exerted an independent immunomodulatory effect from EPA/DHA and all n-3 FA increased LPS-stimulated IL-10 production versus LA and AA. These data definitively identify specific immunomodulatory effects of individual FA and challenge the simplified view of the immunomodulatory effects of n-3 and n-6 FA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".