Tandem Mass Spectrometry Multiplex Analysis of Glucosylceramide and Galactosylceramide Isoforms in Brain Tissues at Different Stages of Parkinson Disease
Bibliographic record
Abstract
Previous studies demonstrated that Parkinson disease (PD) is associated with a decreased activity of the glucocerebrosidase (GCase) enzyme in brain tissues. The objective of this study was to determine if GCase deficiency is associated with the accumulation of its glucosylceramide (GluCer) substrate in PD brain tissues. An ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was developed, optimized, and validated for the multiplex analysis of GluCer isoforms (C18:0, C20:0, C22:0, C24:1, and C24:0) in brain tissue samples. These molecules were chromatographically separated from their isobaric galactosylceramide (GalCer) counterparts using normal phase chromatography. The analysis was performed by tandem mass spectrometry in the multiple reaction monitoring (MRM) acquisition mode. Limits of detection ranging from 0.4 to 1.1 nmol/g brain tissue were established for the different GluCer isoforms analyzed. For the first time, GluCer isoform levels were analyzed in temporal cortex brain tissue samples from 26 PD patients who were divided into three PD disease stages (IIa, III, and IV) according to the Unified Staging System for Lewy Body Disorders. These specimens were compared with brain tissue samples from 12 controls and 6 patients with Incidental Lewy Body Disease. No significant GluCer concentration differences were observed between the 5 sample groups. The GluCer isoform levels were also normalized with their matching GalCer isoforms. The normalized results showed a trend for GluCer levels which increased with PD severity. However, the differences observed between the groups were not significant, owing likely to the high standard deviations measured.
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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 | 0.000 | 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 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".