Phosphatidylcholine 36:1 concentration decreases along with demyelination in the cuprizone animal model and in post‐mortem multiple sclerosis brain tissue
Bibliographic record
Abstract
Multiple sclerosis is a demyelinating and inflammatory disease. Myelin is enriched in lipids, and more specifically, oleic acid. The goal of this study was to evaluate the concentration of oleic acid following demyelination and remyelination in the cuprizone model, test if these changes occurred in specific lipid species, and whether differences in the cuprizone model correlate with changes observed in post-mortem human brains. Eight-week-old C57Bl/6 mice were fed a 0.2% cuprizone diet for 5 weeks and some animals allowed to recover for 11 days. Demyelination, inflammation, and lipid concentrations were measured in the corpus callosum. Standard fatty acid techniques and liquid chromatography combined with tandem mass spectrometry were performed to measure concentrations of fatty acids in total brain lipids and a panel of lipid species within the phosphatidylcholine (PC). Similar measurements were conducted in post-mortem brain tissues of multiple sclerosis patients and were compared to healthy controls. Five weeks of cuprizone administration resulted in demyelination followed by significant remyelination after 11 days of recovery. Compared to control, oleic acid was decreased after 5 weeks of cuprizone treatment and increased during the recovery phase. This decrease in oleic acid was associated with a specific decrease in the PC 36:1 pool. Similar results were observed in human post-mortem brains. Decreases in myelin content in the cuprizone model were accompanied by decreases in oleic acid concentration and is associated with PC 36:1 suggesting that specific lipids could be a potential biomarker for myelin degeneration. The biological relevance of oleic acid for disease progression remains to be verified.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".