Abiotic Stress Resistance Analysis of Lilium pumilum Overexpressing the LpMT2 Gene
Bibliographic record
Abstract
Plant metallothioneins (MT) are cysteine-rich proteins present in plants that can improve a plant’s salt tolerance. Therefore, a greater understanding of the MT gene in lily (Lilium pumilum), Liliaceae, is an important factor in the development and cultivation of improved salt-tolerant varieties and enriching plant resources for saline soils. A type 2 MT gene (GenBank access number: MH319787, designated as LpMT2) was isolated from L. pumilum leaves. The response mechanism to stress was then investigated, which provided the basis for molecular breeding of L. pumilum for stress tolerance. The LpMT2 gene amino acid sequence is highly homologous to that of type 2 MT protein. Quantitative real-time PCR (qPCR) determined that different plant tissues expressed the LpMT2 gene differently and these expressions were dependent on the specific stress. Transgenic plants with LpMT2 gene exhibited significantly increased resistance to salt and oxidative stress compared with untransgenic plants. The LpMT2 transgenic plants had better growth, greater chlorophyll and proline content, less malondialdehyde (MDA) content and cell membrane permeability, greater superoxide dismutase (SOD) activity, less Na+ content, greater K+ content and Na+ efflux, and less K+ efflux. These results determined that the transformed LpMT2 gene in L. pumilium plays an important role in enhancing the plant’s salt tolerance and antioxidant capacity.
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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 | 0.000 |
| 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".