Melatonin-mediated ionic homeostasis in plants: mitigating nutrient deficiency and salinity stress
Bibliographic record
Abstract
Melatonin promotes plant tolerance to abiotic stresses by stimulating the expression of many stress-related genes and protecting plants from oxidative stress, which has been reviewed extensively. Salinity forces plants to uptake excessive amounts of sodium (Na + ) and chloride ions, resulting in the alteration of essential minerals such as potassium (K + ), calcium, magnesium, and iron homeostasis. Moreover, exposure to essential nutrient deficiencies, such as nitrogen, iron, sulfur, and potassium changes ionic homeostasis in plants. This review highlighted the effects of melatonin on the improvement of plant Na + -K + balance and micronutrient homeostasis under salinity conditions and on the improvement of ionic homeostasis in plants under nutrient-deficit conditions. Melatonin inhibits Na + loading in roots and increases Na + retrieval from shoots resulting in increased K + accumulation. Melatonin mainly maintains Na + -K + homeostasis by upregulating the Na + /H + antiporter 1 and AKT serine/threonine kinase 1 transporter genes. Moreover, melatonin improves calcium, magnesium, copper, and iron contents in plants under stress conditions. Under nutrient-deficient stress, melatonin modulates numerous transporter genes and regulates the uptake and translocation of different essential nutrients. In-depth ionomics studies should be performed in plants exposed to salinity and nutrient deficiency stress to better understand the potential mechanism of melatonin-assisted ionic homeostasis under these conditions.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".