AtHKT1 gene regulating K+ state in whole plant improves salt tolerance in transgenic tobacco plants
Bibliographic record
Abstract
Abstract The status of K+ is important for plant health. However, little is known about if high-affinity potassium transporter HKTs may help K+ retention under salt stress. Here, we determined the effect of Arabidopsis thaliana transporter gene (AtHKT1) on the K+ status, Na+-induced toxicity, and salt tolerance in tobacco (Nicotiana tabacum L.). Six AtHKT1 transformed tobacco lines (T1, T2, … T6) were contrasted with a non-transgenic plantlet at the whole-plant and molecule levels. AtHKT1 gene was expressed in the xylems of stem, root and leaf vein in the transgenic tobacco, with the line T3 having highest expression. At Day 15, in the 200 mmol L−1 NaCl stress treatment, the transgenic plants remained a healthy K+ status, while the control plants decreased K+ content by 70% and Na+ contents in leaves and stems were 1.7 times that in the transgenic line. The AtHKT1 expression enhanced the activities of SOD, CAT and POD, raised chlorophyll and soluble sugar contents and root activity, and decreased MDA and proline contents and electrolyte leakage destruction. The constitutive over-expression of AtHKT1 that helps maintain a healthy K+ status while reducing Na+ toxicity may serve as a possible mechanism in maximizing productivity of tobacco under salt stress.
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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 | 0.001 |
| 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".