Populations of Tau Conformers Drive Prion-like Strain Effects in Alzheimer’s Disease and Related Dementias
Bibliographic record
Abstract
Recent findings of diverse populations of prion-like conformers of misfolded tau protein expand the prion concept to Alzheimer's disease (AD) and monogenic frontotemporal lobar degeneration (FTLD)-MAPT P301L, and suggest that distinct strains of misfolded proteins drive the phenotypes and progression rates in many neurodegenerative diseases. Notable progress in the previous decades has generated many lines of proof arguing that yeast, fungal, and mammalian prions determine heritable as well as infectious traits. The extraordinary phenotypic diversity of human prion diseases arises from structurally distinct prion strains that target, at different progression speeds, variable brain structures and cells. Although human prion research presents beneficial lessons and methods to study the mechanism of strain diversity of protein-only pathogens, the fundamental molecular mechanism by which tau conformers are formed and replicate in diverse tauopathies is still poorly understood. In this review, we summarize up to date advances in identification of diverse tau conformers through biophysical and cellular experimental paradigms, and the impact of heterogeneity of pathological tau strains on personalized structure- and strain-specific therapeutic approaches in major tauopathies.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".