Substoichiometric inhibition of transthyretin misfolding by immune-targeting sparsely populated misfolding intermediates: a potential diagnostic and therapeutic for TTR amyloidoses
Bibliographic record
Abstract
Wild-type and mutant transthyretin (TTR) can misfold and deposit in the heart, peripheral nerves, and other sites causing amyloid disease. Pharmacological chaperones, Tafamidis(®) and diflunisal, inhibit TTR misfolding by stabilizing native tetrameric TTR; however, their minimal effective concentration is in the micromolar range. By immune-targeting sparsely populated TTR misfolding intermediates (i.e. monomers), we achieved fibril inhibition at substoichiometric concentrations. We developed an antibody (misTTR) that targets TTR residues 89-97, an epitope buried in the tetramer but exposed in the monomer. Nanomolar misTTR inhibits fibrillogenesis of misfolded TTR under micromolar concentrations. Pan-specific TTR antibodies do not possess such fibril inhibiting properties. We show that selective targeting of misfolding intermediates is an alternative to native state stabilization and requires substoichiometric concentrations. MisTTR or its derivative may have both diagnostic and therapeutic potential.
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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".