Bioluminescence Imaging of Neuroinflammation in Transgenic Mice After Peripheral Inoculation of Alpha-Synuclein Fibrils
Bibliographic record
Abstract
To study the prion-like behavior of misfolded alpha-synuclein, mouse models are needed that allow fast and simple transmission of alpha-synuclein prionoids, which cause neuropathology within the central nervous system (CNS). Here we describe that intraglossal or intraperitoneal injection of alpha-synuclein fibrils into bigenic Tg(M83+/-:Gfap-luc+/-) mice, which overexpress human alpha-synuclein with the A53T mutation from the prion protein promoter and firefly luciferase from the promoter for glial fibrillary acidic protein (Gfap), is sufficient to induce neuropathologic disease. In comparison to homozygous Tg(M83+/+) mice that develop severe neurologic symptoms beginning at an age of 8 months, heterozygous Tg(M83+/-:Gfap-luc+/-) animals remain free of spontaneous disease until they reach an age of 22 months. Interestingly, injection of alpha-synuclein fibrils via the intraperitoneal route induced neurologic disease with paralysis in four of five Tg(M83+/-:Gfap-luc+/-) mice with a median incubation time of 229 ±17 days. Diseased animals showed severe deposits of phosphorylated alpha-synuclein in their brains and spinal cords. Accumulations of alpha-synuclein were sarkosyl-insoluble and colocalized with ubiquitin and p62, and were accompanied by an inflammatory response resulting in astrocytic gliosis and microgliosis. Surprisingly, inoculation of alpha-synuclein fibrils into the tongue was less effective in causing disease with only one of five injected animals showing alpha-synuclein pathology after 285 days. Our findings show that inoculation via the intraglossal route and more so via the intraperitoneal route is suitable to induce neurologic illness with relevant hallmarks of synucleinopathies in Tg(M83+/-:Gfap-luc+/-) mice. This provides a new model for studying prion-like pathogenesis induced by alpha-synuclein prionoids in greater detail.
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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 | 0.001 |
| 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".