Ethylene Induces Antifreeze Activity in Winter Rye Leaves
Bibliographic record
Abstract
Antifreeze activity is induced by cold temperatures in winter rye (Secale cereale) leaves. The activity arises from six antifreeze proteins that accumulate in the apoplast of winter rye leaves during cold acclimation. The individual antifreeze proteins are similar to pathogenesis-related proteins, including glucanases, chitinases, and thaumatin-like proteins. The objective of this study was to study the regulation of antifreeze activity in response to ethylene and salicyclic acid, which are known regulators of pathogenesis-related proteins induced by pathogens. Nonacclimated plants treated with salicylic acid accumulated apoplastic proteins with no antifreeze activity. In contrast, when nonacclimated plants were exposed to ethylene, both antifreeze activity and the concentration of apoplastic protein increased in rye leaves. Immunoblotting revealed that six of the seven accumulated apoplastic proteins consisted of two glucanases, two chitinases, and two thaumatin-like proteins. The ethylene-releasing agent ethephon and the ethylene precursor 1-aminocyclopropane-1-carboxylate also induced high levels of antifreeze activity at 20 degrees C, and this effect could be blocked by the ethylene inhibitor AgNO(3). When intact rye plants were exposed to 5 degrees C, endogenous ethylene production and antifreeze activity were detected within 12 and 48 h of exposure to cold, respectively. Rye plants exposed to drought produced both ethylene and antifreeze activity within 24 h. We conclude that ethylene is involved in regulating antifreeze activity in winter rye in response to cold and drought.
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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".