Neuronal loss and inflammation preceding fibrillary tau pathology in a rat model with early human-like tauopathy
Bibliographic record
Abstract
In tauopathies such as Alzheimer's disease (AD) and frontotemporal dementia (FTD), the microtubule associated protein tau undergoes conformational and posttranslational modifications in a gradual, staged pathological process. While brain atrophy and cognitive decline are well-established in the advanced stages of tauopathy, it is unclear how the early pathological processes manifest prior to extensive neurodegeneration. For these studies we have applied a transgenic rat model of human-like tauopathy in its heterozygous form, named McGill-R955-hTau. The goal of the present study was to investigate whether lifelong accumulation of mutated human tau could reveal the earliest tau pathological processes in a context of advanced aging, and, at stages before the overt aggregated or fibrillary tau deposition. We characterized the phenotype of heterozygous R955-hTau rats at three endpoints, 10, 18 and 24-26 months of age, focusing on markers of cognitive capabilities, progressive tau pathology, neuronal health, neuroinflammation and brain ultrastructural integrity, using immunohistochemistry and electron microscopy. Heterozygous R955-hTau transgenic rats feature a modest, life-long accumulation of mutated human tau that led to tau hyperphosphorylation and produced deficits in learning and memory tasks after 24 months of age. Such impairments coincided with more extensive tau hyperphosphorylation in the brain at residues pThr231 and with evidence of oligomerization. Importantly, aged R955-hTau rats presented evidence of neuroinflammation, detriments to myelin morphology and detectable hippocampal neuronal loss in the absence of overt neurofibrillary lesions and brain atrophy. The slow-progressing tauopathy of R955-hTau rats should allow to better delineate the temporal progression of tau pathological events and therefore to distinguish early indicators of tauopathy as having the capability to induce degenerative events in the aged CNS.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".