The Proteome Response of Salt-Sensitive Rapeseed (Brassica napus L.) Genotype to Salt Stress
Bibliographic record
Abstract
Productivity of rapeseed (Brassica napus L.), the third most important oilseed crop, was reduced more than other crops under the salt stress higher than the threshold. Thus, breeding, especially at seedling stage, seems necessary. Plants under salt stress, by synthesis of essential metabolites, specific structural proteins or enzymes of metabolic pathways deal with the stress. To identify the molecular mechanisms of salt responsiveness in rapeseed, ‘Option500’ a salt-sensitive genotype was exposed to 0, 150, and 300mM NaCl during the seedling stage. An increase in proline and the Na+ content of leaf and a reduction in shoot dry weight, plant height, K+ content and K+/Na+ ratio were observed. Protein expression changes were examined by two-dimensional electrophoresis (2-DE). Out of 110 protein spots identified by 2-DE gels, 37 spots showed significant abundant changes based on induction factor (IF), and 7 spots were recognized significantly at 5% probability level, which 1 and 6 spots were up and down-regulated, respectively. By using LC-MS/MS mass spectrometry analysis, proteins were identified which are involved in energy production and photosynthesis. Activity of enzymes involved in energy production decreased under stress, while the abundance of Phosphoribulokinase (PRK) -an important enzyme in the pentose phosphate pathway- increased.
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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".