Analysis of Amino Acids in the Roots of Tamarix ramosissima by Application of Exogenous Potassium (K+) under NaCl Stress
Bibliographic record
Abstract
Soil salinization is one of the main environmental factors affecting plant growth worldwide. Tamarix ramosissima Ledeb. (T. ramosissima) is a halophyte representative that is widely grown in salinized soils. As an important nutrient element for plant growth, K+ plays an important role in improving the tolerance to salt stress, but the mechanism of reducing the damage caused by NaCl stress to T. ramosissima is less reported. Our results show that the proline content and the Log2 fold-change of proline’s relative quantification in the roots of T. ramosissima increased over time with the application of exogenous potassium (K+) for 48 h and 168 h under NaCl stress. Moreover, 13 amino-acid-related metabolic pathways were involved in the resistance of T. ramosissima to salt stress. Mainly, the aldehyde dehydrogenase family genes and tryptophan-synthase-related genes were found at 48 h and 168 h with exogenous potassium applied to the roots of T. ramosissima under NaCl stress, and they regulated their related metabolic accumulation in the arginine and proline metabolism pathways, increasing the effectiveness of inducing NaCl tolerance of T. ramosissima. It is noteworthy that alpha-ketobutyric was produced in the roots of T. ramosissima under NaCl stress for 48 h with the application of exogenous potassium, which is one of the most effective mechanisms for inducing salt tolerance in plants. Meanwhile, we found three DEGs regulating alpha-ketobutyric acid. This study provides a scientific theoretical basis for further understanding the molecular mechanism of K+ alleviating the salinity damage to T. ramosissima caused by NaCl.
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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 | 0.000 | 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 | 0.001 |
| 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".