Major Alterations of Phosphatidylcholine and Lysophosphotidylcholine Lipids in the Substantia Nigra Using an Early Stage Model of Parkinson’s Disease
Bibliographic record
Abstract
Parkinson's disease (PD) is a progressive neurodegenerative disease affecting the nigrostriatal pathway, where patients do not manifest motor symptoms until >50% of neurons are lost. Thus, it is of great importance to determine early neuronal changes that may contribute to disease progression. Recent attention has focused on lipids and their role in pro- and anti-apoptotic processes. However, information regarding the lipid alterations in animal models of PD is lacking. In this study, we utilized high performance liquid chromatography electrospray ionization tandem mass spectrometry (HPLC-ESI-MS/MS) and novel HPLC solvent methodology to profile phosphatidylcholines and sphingolipids within the substantia nigra. The ipsilateral substantia nigra pars compacta was collected from rats 21 days after an infusion of 6-hydroxydopamine (6-OHDA), or vehicle into the anterior dorsal striatum. We identified 115 lipid species from their mass/charge ratio using the LMAPS Lipid MS Predict Database. Of these, 19 lipid species (from phosphatidylcholine and lysophosphotidylcholine lipid classes) were significantly altered by 6-OHDA, with most being down-regulated. The two lipid species that were up-regulated were LPC (16:0) and LPC (18:1), which are important for neuroinflammatory signalling. These findings provide a first step in the characterization of lipid changes in early stages of PD-like pathology and could provide novel targets for early interventions in PD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.000 | 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 teacher head, 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".