Ice-binding proteins that accumulate on different ice crystal planes produce distinct thermal hysteresis dynamics
Bibliographic record
Abstract
Ice-binding proteins that aid the survival of freeze-avoiding, cold-adapted organisms by inhibiting the growth of endogenous ice crystals are called antifreeze proteins (AFPs). The binding of AFPs to ice causes a separation between the melting point and the freezing point of the ice crystal (thermal hysteresis, TH). TH produced by hyperactive AFPs is an order of magnitude higher than that produced by a typical fish AFP. The basis for this difference in activity remains unclear. Here, we have compared the time dependence of TH activity for both hyperactive and moderately active AFPs using a custom-made nanolitre osmometer and a novel microfluidics system. We found that the TH activities of hyperactive AFPs were time-dependent, and that the TH activity of a moderate AFP was almost insensitive to time. Fluorescence microscopy measurement revealed that despite their higher TH activity, hyperactive AFPs from two insects (moth and beetle) took far longer to accumulate on the ice surface than did a moderately active fish AFP. An ice-binding protein from a bacterium that functions as an ice adhesin rather than as an antifreeze had intermediate TH properties. Nevertheless, the accumulation of this ice adhesion protein and the two hyperactive AFPs on the basal plane of ice is distinct and extensive, but not detectable for moderately active AFPs. Basal ice plane binding is the distinguishing feature of antifreeze hyperactivity, which is not strictly needed in fish that require only approximately 1°C of TH. Here, we found a correlation between the accumulation kinetics of the hyperactive AFP at the basal plane and the time sensitivity of the measured TH.
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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) | 0.000 | 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 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".