Seed structure and phosphorylation in the fuzzy coat impact tau seeding competency
Bibliographic record
Abstract
Tau misfolding into β-sheet-rich filaments and subsequent recruitment of monomeric tau are central to Alzheimer's disease (AD) pathogenesis. While cryo-EM has resolved the conformation of the AD tau core, the structural features conferring biological activity remain unclear. Here, we investigated how tau filament core structure and post-translational modifications influence seeding capacity in neurons and mice. Our findings show that although filament structure impacts seeding, the AD tau core alone is insufficient to fully replicate AD tau's biological activity. The unstructured fuzzy coat, particularly phosphorylation within this region, is essential for full seeding competence. Importantly, recombinant tau filaments bearing twelve phospho-mimetic residues (PAD12 tau) and adopting the AD fold recapitulate the seeding activity of native AD tau. These results demonstrate that tau filament pathogenicity arises from the combined contributions of both the ordered core structure and post-translational modifications within the fuzzy coat, providing critical insights into mechanisms underlying tau-driven neurodegeneration.
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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 | 0.000 |
| 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".