Plasmalogen Augmentation Reverses Striatal Dopamine Loss in MPTP Mice
Bibliographic record
Abstract
Plasmalogens are a class of glycerophospholipids shown to play critical roles in membrane structure and function. Decreased plasmalogens are reported in the brain and blood of Parkinson's disease (PD) patients. The present study investigated the hypothesis that augmenting plasmalogens could protect striatal dopamine neurons that degenerate in response to 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) treatment in mice, a PD model. First, in a pre-treatment experiment male mice were treated for 10 days with the docosahexaenoic acid (DHA)-plasmalogen precursor PPI-1011 (10, 50 and 200 mg/kg). On day 5 mice received MPTP and were killed on day 11. Next, in a post-treatment study, male mice were treated with MPTP and then received daily for 5 days PPI-1011 (5, 10 and 50 mg/kg). MPTP treatment reduced serum plasmalogen levels, striatal contents of dopamine (DA) and its metabolites, serotonin, DA transporter (DAT) and vesicular monoamine transporter 2 (VMAT2). Pre-treatment with PPI-1011 (10 and 50 mg/kg) prevented all MPTP-induced effects. Positive correlations were measured between striatal DA contents and serum plasmalogen levels as well as striatal DAT and VMAT2 specific binding. Post-treatment with PPI-1011 prevented all MPTP-induced effects at 50 mg/kg but not at lower doses. Positive correlations were measured between striatal DA contents and serum plasmalogen levels as well as striatal DAT and VMAT2 specific binding in the post-treatment experiment. PPI-1011 treatment (10 days at 5, 10 and 50 mg/kg) of intact mice left unchanged striatal biogenic amine contents. These data demonstrate that treatment with a plasmalogen precursor is capable of protecting striatal dopamine markers 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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".