Antifreeze Proteins Modify the Freezing Process In Planta
Bibliographic record
Abstract
During cold acclimation, winter rye (Secale cereale L. cv Musketeer) plants accumulate antifreeze proteins (AFPs) in the apoplast of leaves and crowns. The goal of this study was to determine whether these AFPs influence survival at subzero temperatures by modifying the freezing process or by acting as cryoprotectants. In order to inhibit the growth of ice, AFPs must be mobile so that they can bind to specific sites on the ice crystal lattice. Guttate obtained from cold-acclimated winter rye leaves exhibited antifreeze activity, indicating that the AFPs are free in solution. Infrared video thermography was used to observe freezing in winter rye leaves. In the absence of an ice nucleator, AFPs had no effect on the supercooling temperature of the leaves. However, in the presence of an ice nucleator, AFPs lowered the temperature at which the leaves froze by 0.3 degrees C to 1.2 degrees C. In vitro studies showed that apoplastic proteins extracted from cold-acclimated winter rye leaves inhibited the recrystallization of ice and also slowed the rate of migration of ice through solution-saturated filter paper. When we examined the possible role of winter rye AFPs in cryoprotection, we found that lactate dehydrogenase activity was higher after freezing in the presence of AFPs compared with buffer, but the same effect was obtained by adding bovine serum albumin. AFPs had no effect on unstacked thylakoid volume after freezing, but did inhibit stacking of the thylakoids, thus indicating a loss of thylakoid function. We conclude that rye AFPs have no specific cryoprotective activity; rather, they interact directly with ice in planta and reduce freezing injury by slowing the growth and recrystallization of ice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 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".