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Record W4368355085 · doi:10.21203/rs.3.rs-2890683/v1

Microglial depletion does not impact alpha-synuclein aggregation or nigrostriatal degeneration in the rat preformed fibril model

2023· preprint· en· W4368355085 on OpenAlexfundno aff
Anna C. Stoll, Christopher J. Kemp, Joseph R. Patterson, Michael Kubik, Nathan C. Kuhn, Matthew J. Benskey, Megan F. Duffy, Kelvin C. Luk, Caryl E. Sortwell

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
FundersNational Institutes of HealthWeston Brain Institute
KeywordsPars compactaSubstantia nigraMicrogliaNeurodegenerationNeuroinflammationAlpha-synucleinParkinson's diseaseChemistryCell biologyNeuroscienceDopamineBiologyPathologyMedicineDopaminergicImmunologyInflammation

Abstract

fetched live from OpenAlex

Background: Parkinson's disease (PD) is a neurodegenerative disorder that is characterized by the presence of proteinaceous alpha-synuclein (α-syn) inclusions (Lewy bodies), markers of neuroinflammation and the progressive loss of nigrostriatal dopamine (DA) neurons. These pathological features can be recapitulated in vivo using the α-syn preformed fibril (PFF) model of synucleinopathy. We have previously described the time course of microglial major-histocompatibility complex-II (MHC-II) expression and alterations in microglia morphology in the PFF model in rats. Specifically, the peaks of α-syn inclusion formation, MHC-II expression, and reactive morphology in the substantia nigra pars compacta (SNpc) all occur two months post PFF injection, months before neurodegeneration occurs. These results suggest that activated microglia may contribute to neurodegeneration and could represent a potential target for novel therapeutics. The goal of this study was to determine whether microglial depletion could impact the magnitude of α-syn aggregation, nigrostriatal degeneration, or related microglial activation during the α-syn PFF model. Methods: Male Fischer 344 rats were injected intrastriatally with either α-syn PFFs or saline. Rats were continuously administered Pexidartinib (PLX3397B, 600mg/kg), a colony stimulating factor-1 receptor (CSF1R) inhibitor, to deplete microglia for a period of either two or six months. Results: PLX3397B administration resulted in significant depletion (45-53%) of ionized calcium-binding adapter molecule 1 immunoreactive (Iba-1ir) microglia within the SNpc. Microglial depletion did not impact accumulation of phosphorylated α-syn (pSyn) within SNpc neurons and did not alter pSyn associated microglial reactivity or expression of MHC-II. Further, microglial depletion did not impact SNpc neuron degeneration. Paradoxically, long term microglial depletion resulted in increased soma size of remaining microglia in both control and PFF rats, as well as expression of MHC-II in extranigral regions. Conclusions: Collectively, our results suggest that microglial depletion is not a viable disease-modifying strategy for PD and that partial microglial depletion can induce a heightened proinflammatory state in remaining microglia.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.129
GPT teacher head0.418
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2023
Admission routes1
Has abstractyes

Explore more

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