Winter rye antifreeze activity increases in response to cold and drought, but not abscisic acid
Bibliographic record
Abstract
Antifreeze activity increases in winter rye (Secale cereale L.) during cold acclimation as the plants accumulate antifreeze proteins (AFPs) that are similar to glucanases, chitinases and thaumatin-like proteins (TLPs) in the leaf apoplast. In the present work, experiments were conducted to assess the role of drought and abscisic acid (ABA) in the regulation of antifreeze activity and accumulation of AFPs. Antifreeze activity was detected as early as 24 h of drought treatment at 20 degrees C and increased as the level of apoplastic proteins increased. Apoplastic proteins accumulated rapidly under water stress and reached a level within 8 days that was equivalent to the level of apoplastic proteins accumulated when plants were acclimated to cold temperature for 7 weeks. These drought-induced apoplastic proteins had molecular masses ranging from 11 to 35 kDa and were identified as two glucanases, two chitinases, and two TLPs, by using antisera raised against cold-induced rye glucanase, chitinase, and TLP, respectively. Apoplastic extracts obtained from plants treated with ABA lacked the ability to modify the growth of ice crystals, even though ABA induced the accumulation of apoplastic proteins within 4 days to a level similar to that obtained when plants were either drought-stressed for 8 days or cold-acclimated for 7 weeks. These ABA-induced apoplastic proteins were identified immunologically as two glucanases and two TLPs. Moreover, the ABA biosynthesis inhibitor fluridone did not prevent the accumulation of AFPs in the leaves of cold-acclimated rye plants. Our results show that cold acclimation and drought both induce antifreeze activity in winter rye plants and that the pathway regulating AFP production is independent of ABA.
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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) | 0.001 | 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".