Proteins responding to drought and high-temperature stress in <i>Pinus armandii</i> Franch
Bibliographic record
Abstract
Proteomic analysis provides a powerful method for studying plant responses to stress at the protein level. To study stress-responsive molecular mechanisms for Pinus armandii Franch, one of the most important forest plantation tree species in subalpine regions of Asia, we analyzed the response of 2-year-old P. armandii seedlings to drought and high temperature using two-dimensional gel electrophoresis. More than 550 reproducible needle proteins were detected in the controls and treatments, and the abundance of 27 proteins were found to change noticeably. We identified five proteins affected by drought stress and eight proteins affected by high temperature. These proteins are functionally quite diverse and are involved in photosynthesis, cell division and elongation, antioxidant metabolism, ammonia assimilation, growth and development, and protein folding. Our results provide fundamental data for future research on responses to drought and high temperature. As drought and high temperature are two major factors limiting the growth of subalpine forests during summer under recent global warming, this research may contribute to an understanding of the development of stress tolerance in trees.
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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".