Nitric oxide and hydrogen sulfide crosstalk during heavy metal stress in plants
Bibliographic record
Abstract
Gases such as ethylene, hydrogen peroxide (H2O2), nitric oxide (NO), carbon monoxide (CO) and hydrogen sulfide (H2S) have been recognized as vital signaling molecules in plants and animals. Of these gasotransmitters, NO and H2S have recently gained momentum mainly because of their involvement in numerous cellular processes. It is therefore important to study their various attributes including their biosynthetic and signaling pathways. The present review provides an insight into various routes for the biosynthesis of NO and H2S as well as their signaling role in plant cells under different conditions, more particularly under heavy metal stress. Their beneficial roles in the plant's protection against abiotic and biotic stresses as well as their adverse effects have been addressed. This review describes how H2S and NO, being very small‐sized molecules, can quickly pass through the cell membranes and trigger a multitude of responses to various factors, notably to various stress conditions such as drought, heat, osmotic, heavy metal and multiple biotic stresses. The versatile interactions between H2S and NO involved in the different molecular pathways have been discussed. In addition to the signaling role of H2S and NO, their direct role in posttranslational modifications is also considered. The information provided here will be helpful to better understand the multifaceted roles of H2S and NO in plants, particularly under stress 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".