Physiological, Structural, and Functional Insights Into the Cryoprotection of Membranes by the Dehydrins
Bibliographic record
Abstract
Plants can be exposed to cold temperatures and have therefore evolved several mechanisms to prevent damage caused by freezing. One of the most important targets are membranes, which are particularly susceptible to cold damage. To protect against such abiotic stresses, plants express a family of proteins known as late embryogenesis abundant (LEA) proteins. Many LEA proteins are intrinsically disordered, that is, they do not contain stable secondary or tertiary structures alone in solution. These proteins have been shown in a number of studies to protect plants from damage caused by cold, drought, salinity, and osmotic stress. In this family, the most studied proteins are the type II LEA proteins, better known as dehydrins (dehydration-induced proteins). Many physiological studies have shown that dehydrins are often located near the membrane during abiotic stress and that the expression of dehydrins helps to prevent the formation of oxidation-modified lipids and reduce the amount of electrolyte leakage, two hallmarks of damaged membranes. One of the earliest biophysical clues that dehydrins are involved in membrane cryoprotection came from in vitro studies that demonstrated a binding interaction between the protein and membranes. Subsequent work has shown that one conserved motif, known as K-segments, is involved in binding, while recent studies have used NMR to explore the residue specific structure of dehydrins when bound to membranes. The biophysical techniques also provide insight into the mechanism by which dehydrins protect the membrane from cold stress, which appears to mainly involve the lowering of the transition temperature.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".