Microglia depletion prior to lipopolysaccharide and paraquat treatment differentially modulates behavioral and neuronal outcomes in wild type and G2019S LRRK2 knock-in mice
Bibliographic record
Abstract
BACKGROUND: Substantial data have implicated microglial-driven neuroinflammation in Parkinson's disease (PD) and environmental toxicants have been long expected as triggers of such inflammatory processes. Of course, these environmental insults act in the context of genetic vulnerability factors and in this regard, leucine rich repeat kinase 2 (LRRK2), may play a prominent role. METHODS: We used a double hit, lipopolysaccharide (LPS; endotoxin) followed by paraquat (pesticide toxicant) model of PD in mice with the most common LRRK2 mutation G2019S, knockin mice and wild type littermates. In order to assess the contribution of microglia, we depleted these cells (through 14 days of the CSF-1 antagonist, PLX-3397) prior to LPS and paraquat exposure. RESULTS: We found that the G2019S mice displayed the greatest signs of behavioral pathology, but that the PLX-3397 induced microglial depletion at the time of LPS exposure diminished toxicity and weight loss and blunted the reduction in home-cage activity with subsequent paraquat exposure. However, neither the PLX-3397 pre-treatment nor the G2019S mutation affected the LPS + paraquat induced loss of substantia nigra pars compacta (SNc) dopamine neurons or elevation of circulating immune (IL-6) or stress (corticosterone) factors. Intriguingly, microglial morphological ratings were basally enhanced in G2019S mice and the PLX-3397 pre-treatment reversed this effect. Moreover, PLX-3397 pre-treatment selectively elevated soluble a-synuclein and SIRT3 levels, while reducing SNc caspase-1 and 3, along with CX3CR1. Hence, the re-populated "new" microglia following cessation of PLX-3397 clearly had an altered phenotype or were immature at the time of sacrifice (i.e. after 11 days). CONCLUSIONS: Collectively, these findings suggest that G2019S knock-in and PLX-3397 microglial depletion at the time of LPS exposure affects behavioral, but not neurodegenerative responses to subsequent environmental toxin exposure.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".