Unaltered Striatal Dopamine Release Levels in Young Parkin Knockout, Pink1 Knockout, DJ-1 Knockout and LRRK2 R1441G Transgenic Mice
Bibliographic record
Abstract
Parkinson's disease (PD) is one of the most prevalent neurodegenerative brain diseases; it is accompanied by extensive loss of dopamine (DA) neurons of the substantia nigra that project to the putamen, leading to impaired motor functions. Several genes have been associated with hereditary forms of the disease and transgenic mice have been developed by a number of groups to produce animal models of PD and to explore the basic functions of these genes. Surprisingly, most of the various mouse lines generated such as Parkin KO, Pink1 KO, DJ-1 KO and LRRK2 transgenic have been reported to lack degeneration of nigral DA neuron, one of the hallmarks of PD. However, modest impairments of motor behavior have been reported, suggesting the possibility that the models recapitulate at least some of the early stages of PD, including early dysfunction of DA axon terminals. To further evaluate this possibility, here we provide for the first time a systematic comparison of DA release in four different mouse lines, examined at a young age range, prior to potential age-dependent compensations. Using fast scan cyclic voltammetry in striatal sections prepared from young, 6-8 weeks old mice, we examined sub-second DA overflow evoked by single pulses and action potential trains. Unexpectedly, none of the models displayed any dysfunction of DA overflow or reuptake. These results, compatible with the lack of DA neuron loss in these models, suggest that molecular dysfunctions caused by the absence or mutation of these individual genes are not sufficient to perturb the function and survival of mouse DA neurons.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".