Transgenic conversion of omega-6 into omega-3 fatty acids in a mouse model of Parkinson's disease
Bibliographic record
Abstract
We have recently identified a neuroprotective role for omega-3 polyunsaturated fatty acids (n-3 PUFAs) in a toxin-induced mouse model of Parkinson's disease (PD). Combined with epidemiological data, these observations suggest that low n-3 PUFA intake is a modifiable environmental risk factor for PD. In order to strengthen these preclinical findings as prerequisite to clinical trials, we further investigated the neuroprotective role of n-3 PUFAs in Fat-1 mice, a transgenic model expressing an n-3 fatty acid desaturase converting n-6 PUFAs into n-3 PUFAs. Here, we report that the expression of the fat-1 transgene increased cortical n-3:n-6 PUFA ratio (+28%), but to a lesser extent than dietary supplementation (92%). Such a limited endogenous production of n-3 PUFAs in the Fat-1 mouse was insufficient to confer neuroprotection against 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine neurotoxicity as assessed by dopamine levels, tyrosine hydroxylase (TH)-positive neurons and fibers, as well as nigral Nurr1 and dopamine transporter (DAT) mRNA expression. Nevertheless, higher cortical docosahexaenoic acid (DHA) concentrations were positively correlated with markers of nigral dopaminergic neurons such as the number of TH-positive cells, in addition to Nurr1 and DAT mRNA levels. These associations are consistent with the protective role of DHA in a mouse model of PD. Taken together, these data suggest that dietary intake of a preformed DHA supplement is more effective in reaching the brain and achieving neuroprotection in an animal model of PD.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".