Exosome markers of LRRK2 kinase inhibition
Bibliographic record
Abstract
Hyper-activated LRRK2 is linked to Parkinson's disease susceptibility and progression. Quantitative measures of LRRK2 inhibition, especially in the brain, maybe critical in the development of successful LRRK2-targeting therapeutics. In this study, two different brain-penetrant and selective LRRK2 small-molecule kinase inhibitors (PFE-360 and MLi2) were orally administered to groups of cynomolgus macaques. Proposed pharmacodynamic markers in exosomes from urine and cerebrospinal fluid (CSF) were compared to established markers in peripheral blood mononuclear cells (PBMCs). LRRK2 kinase inhibition led to reductions in exosome-LRRK2 protein and the LRRK2-substrate pT73-Rab10 in urine, as well as reduced exosome-LRRK2 and autophosphorylated pS1292-LRRK2 protein in CSF. We propose orthogonal markers for LRRK2 inhibition in urine and CSF can be used in combination with blood markers to non-invasively monitor the potency of LRRK2-targeting therapeutics.
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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) | 0.000 | 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) | 0.001 | 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".