Expression of progerin enhances disease-related endpoints in a tau seeding reporter cell system
Bibliographic record
Abstract
Sporadic Alzheimer's disease and some forms of frontotemporal lobar degeneration (FTLD-tau) are neurological disorders of later life where cognitive deficits follow from the progressive accumulation of microtubule-associated tau protein. Disease-related tau accumulation is marked by altered subcellular distribution and rearrangement of this natively unstructured protein into alternative conformational forms, including highly organized fibrillar assemblies. With a partial analogy to effects seen in prion diseases, pathological tau conformers have a templating activity called seeding that may be measured in cellular and cell-free systems. Moreover, cellular systems and disease models can recapitulate "strain effects" wherein the same tau amino acid sequence can adopt markedly different conformations. Here we analyzed FTLD-tau conformers in cellular reporter systems expressing a pro-aging mutant form of the lamin A protein termed "progerin." Measured versus the baseline performance of a reporter system based on HEK293 cells, the addition of tau burden or progerin expression produced only mild changes in proteomic analyses or morphology, whereas application of both stressors produced a notable shift in ER stress and homeostasis, including increased levels of DNAJC10 and DNAJA2. The phenotypic effects scored here appear unrelated to the generation of new tau strains or to the type of strain input, insofar as progerin-expressing cells were more responsive to tau seeding by diverse brain samples containing different populations of tau conformers. Thus, premature aging and disease-associated tau conformers can exhibit an additive relationship in a model system.
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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".