Protection of cortical neurons from excitotoxicity by conjugated linoleic acid
Bibliographic record
Abstract
Conjugated linoleic acid (CLA) is an isomeric mixture of 18-carbon polyunsaturated fatty acids with conjugated double bonds derived from linoleic acid. CLA is sourced nutritionally from dairy products and ruminant animal meat and is associated with beneficial heath effects in several disorders, including cancer, atherosclerosis, diabetes, obesity, and inflammation. We investigated the potential for CLA to protect neurons from death in stroke simulated by exposing cultured mouse embryonic cortical neurons to glutamate. CLA (10 30 μM) significantly protected neuronal survival in response to glutamate (3 μM) excitotoxicity when given concurrently with glutamate. CLA (30 μM) also reduced neuron death when given up to 5 h after glutamate exposure (73.1 ± 13.3% protection, p < 0.01), suggesting potential utility as a post-injury therapeutic tool. The cis-9, trans-11 CLA isomer, which comprises about 40% of the commercial CLA mixture used, was identified as the active neuroprotective species. The other major species, trans-10, cis-12 CLA (40%) was without significant neuroprotective effect. CLA significantly increased neuronal Bcl-2 levels when given with glutamate and attenuated glutamate-induced dissipation of mitochondrial membrane potential, suggesting a stabilizing influence on mitochondrial function. These results show that CLA is capable of strong neuroprotective effects in glutamate excitotoxicity at concentrations likely achieved by consumption of CLA as a dietary supplement.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 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".