Bibliographic record
Abstract
Abstract Tardigrades, also known as water bears, make up a phylum of small but extremely hardy animals, renowned for their ability to survive extreme stresses, including desiccation. How tardigrades survive desiccation is one of the enduring mysteries of animal physiology. Here we show that CAHS D, an intrinsically disordered protein belonging to a unique family of proteins possessed only by tardigrades, undergoes a liquid-to-gel phase transition in a concentration dependent manner. Unlike other gelling proteins, such as gelatin, our data support a mechanism in which gel formation of CAHS D is driven by intermolecular β-β interactions. We find that gel formation corresponds with strong coordination of water and slowing of water diffusion. The degree of water coordination correlates with the ability of CAHS D to protect lactate dehydrogenase from unfolding when dried. This implies that the mechanism for unfolding protection can be attributed to a combination of hydration and slowed molecular motion. Conversely, rapid diffusion leading to efficient molecular shielding appears to be the predominant mechanism preventing protein aggregation. Our study demonstrates that distinct mechanisms are required for holistic protection during desiccation, and that protectants, such as CAHS D, can act as molecular ‘Swiss Army Knives’ capable of providing protection through several different mechanisms simultaneously.
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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 | 0.014 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.046 | 0.036 |
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".