LRRK2 mouse models: dissecting the behavior, striatal neurochemistry and neurophysiology of PD pathogenesis
Bibliographic record
Abstract
Mutations in leucine-rich repeat kinase 2 (LRRK2) are the most common genetic cause of familial Parkinson's disease (PD), resembling the sporadic disorder. Intensive effort has been directed toward LRRK2 mouse modeling and investigation, aimed at reproducing the human disease to inform mechanistic studies of pathogenesis and design of neuroprotective therapies. The physiological function of LRRK2 is still under exploration, but a clear role in striatal neurophysiology and animal behavior has emerged. Alterations in LRRK2 impair dopamine (DA) transmission, regulation and signaling, in addition to corticostriatal synaptic plasticity. Consistently, several subtle abnormalities in motor and nonmotor abilities have been demonstrated in LRRK2 genetic mouse models, generally paralleling preclinical symptoms of early DA dysfunction. However, the variability in model design and phenotypes observed requires a critical approach in interpreting the results, adapting the model used to the specific research question. Etiologically appropriate knockin mice might represent the ultimate animal model in which to study early disease mechanisms and therapies as well as to investigate drug effectiveness and off-target consequences.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".