Role of domain interactions in the aggregation of full-length immunoglobulin light chains
Bibliographic record
Abstract
Significance The misfolding and/or aggregation of proteins can give rise to amyloid diseases, including immunoglobulin light-chain (LC) amyloidosis, leading to large proteinaceous deposits in organs throughout the body. A third of patients die within a year of diagnosis. The LC structure–proteotoxicity relationships and how protein aggregation causes degeneration are not understood. Using solution NMR we characterized the strengths of interactions between different domains in the dimeric 2-domain immunoglobulin LC structure to dissect their relative importance in protecting against aggregation. The constant domain (C L ) is particularly important in conferring protection, as are the stabilities of the individual domains. Our studies establish a threshold of stability, below which aggregation occurs rapidly, suggesting that stabilizing the C L –C L domain interface could prevent aggregation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".