The iFat1 transgene permits conditional endogenous n-3 PUFA enrichment both in vitro and in vivo
Bibliographic record
Abstract
Fat-1 transgenic mice, which endogenously convert n-6 PUFA to n-3 PUFA, are a useful tool in health research; however with this model timing of n-3 PUFA enrichment cannot be directly controlled. To add such capability, the novel Cre-recombinase inducible fat-1 (iFat1) transgenic mouse has been developed. The aim of this study was to characterize the utility of the iFat1 transgene as a model of Cre-inducible endogenous n-3 PUFA enrichment. Functionality of the iFat1 transgene was screened both in vitro and in vivo. In the presence of Cre, the iFat1 transgene resulted in a balancing (p < 0.01) of the n-6/n-3 PUFA ratio within phospholipids in the human embryonic kidney 293T cell line. For in vivo analysis, iFat1 transgenic mice were crossed with the R26-Cre-ER(T2) (Tam-Cre) mouse line, a tamoxifen inducible Cre-expression model. Tam-Cre/iFat1 double hybrids were transiently treated with tamoxifen at 6-7 weeks, then terminated 3 weeks later. Tamoxifen treated mice had increased (p < 0.05) tissue n-3 PUFA and ≥two-fold reduction (p < 0.05) in the n-6/n-3 PUFA ratio of liver, kidney and muscle phospholipids relative to vehicle treated controls. Collectively these findings suggest that the iFat1 transgenic mouse may be a promising tool to help elucidate the temporal effects through which n-3 PUFA impacts health related outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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.
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 source (direct Gemma or distilled Codex), 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".