Evolutionary conservation of systemic and reversible amyloid aggregation
Bibliographic record
Abstract
In response to environmental stress, human cells have been shown to form reversible amyloid aggregates within the nucleus, termed amyloid bodies (A-bodies). These protective physiological structures share many of the biophysical characteristics associated with the pathological amyloids found in Alzheimer's and Parkinson's disease. Here, we show that A-bodies are evolutionarily conserved across the eukaryotic domain, with their detection in Drosophila melanogaster and Saccharomyces cerevisiae marking the first examples of these functional amyloids being induced outside of a cultured cell setting. The conditions triggering amyloidogenesis varied significantly among the species tested, with results indicating that A-body formation is a severe, but sublethal, stress response pathway that is tailored to the environmental norms of an organism. RNA-sequencing analyses demonstrate that the regulatory low-complexity long non-coding RNAs that drive A-body aggregation are both conserved and essential in human, mouse and chicken cells. Thus, the identification of these natural and reversible functional amyloids in a variety of evolutionarily diverse species highlights the physiological significance of this protein conformation, and will be informative in advancing our understanding of both functional and pathological amyloid aggregation events. This article has an associated First Person interview with the first author of the paper.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".