Enhancement of salt-stressed cucumber tolerance by application of glucose for regulating antioxidant capacity and nitrogen metabolism
Bibliographic record
Abstract
The current study was carried out to assess the potential functions of exogenous glucose (Glu) on plant growth, nitrogen metabolism, and antioxidant defense system in cucumber seedings under salt stress. Our results revealed that the cucumber seedlings exposed to salinity for 7 d exhibited a significant reduction of plant height, and fresh and dry weight. The salt-induced growth inhibition was effectively alleviated by foliar application of 100 mmol L−1 Glu. Exogenous Glu supplementation strikingly reduced the malondialdehyde content and controlled overaccumulation of superoxide anion ([Formula: see text]) generation rate in the salt-stressed cucumber leaves. In addition, Glu significantly increased the antioxidant enzymes activities such as super oxidase dismutase, peroxidase, catalase and ascorbate peroxidase, and regulated gene expressions of encoding these enzymes, which decreased oxidative damage induced by salt stress. The [Formula: see text] content significantly decreased, but the [Formula: see text] level significantly increased due to salt treatment. However, Glu significantly increased the activities of nitrate reductase and nitrite reductase in salt-stressed cucumber leaves, which coincided with modulating the gene expressions of key enzymes of nitrogen metabolism, and thus, promoted the conversion of ammonium nitrogen to amino acids and proteins. These results suggest that exogenous Glu could alleviate salt-induced growth inhibition through regulating antioxidant capacity and nitrogen metabolism, which is associated with an improvement of cucumber growth and salt tolerance.
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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".