Enhanced lanthanum stress tolerance of the transgenic <i>Arabidopsis</i> expressing <i>CnMT2</i> from <i>Chrysanthemum naktongense</i>
Bibliographic record
Abstract
The rare earth element lanthanum (La) as a heavy metal can cause stress damage to plants at high concentrations. Metallothioneins (MTs) are low molecular weight proteins rich in cysteine and play significant roles in detoxification of metal ion stress in plants. In this study, we identified a novel function of CnMT2 from Chrysanthemum naktongense. Two MT homologous genes, namely CnMT2 and CnMT3, were cloned from the wild plant species C. naktongense, which exhibits high resistance to the rare earth element lanthanum (La). qRT-PCR analysis revealed that in C. naktongense, the highest expression level of CnMT2 occurred in roots. Its expression in stems, leaves, or shoot tips was also detected. Low expression levels of CnMT3 occurred in all tissues, with relatively higher expression levels in roots. LaCl3 stress treatment could induce the expression of both CnMT2 and CnMT3, resulting in differential expression patterns between shoots and roots. Transgenic Arabidopsis seeds overexpressing CnMT2 exhibited increased resistance to LaCl3 and H2O2 during germination. Transgenic seedlings also exhibited growth enhancement with prolonged LaCl3 stress, accompanied by significantly elevated enzyme activities of catalase and peroxidase. Our data revealed that CnMT2 from C. naktongense was able to enhance plant resistance to lanthanum and antioxidative capacity. Overall, the study unveiled a new function of CnMT2 in C. naktongense, which can be potentially used for engineering genotypes for phytoremediation.
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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".