Genetic engineering of improved nitrogen use efficiency in rice by the tissue‐specific expression of <i>alanine aminotransferase</i>
Why this work is in the frame
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Bibliographic record
Abstract
Summary Nitrogen is quantitatively the most essential nutrient for plants and a major factor limiting crop productivity. One of the critical steps limiting the efficient use of nitrogen is the ability of plants to acquire it from applied fertilizer. Therefore, the development of crop plants that absorb and use nitrogen more efficiently has been a long-term goal of agricultural research. In an attempt to develop nitrogen-efficient plants, rice (Oryza sativa L.) was genetically engineered by introducing a barley AlaAT (alanine aminotransferase) cDNA driven by a rice tissue-specific promoter (OsAnt1). This modification increased the biomass and grain yield significantly in comparison with control plants when plants were well supplied with nitrogen. Compared with controls, transgenic rice plants also demonstrated significant changes in key metabolites and total nitrogen content, indicating increased nitrogen uptake efficiency. The development of crop plants that take up and assimilate nitrogen more efficiently would not only improve the use of nitrogen fertilizers, resulting in lower production costs, but would also have significant environmental benefits. These results are discussed in terms of their relevance to the development of strategies to engineer enhanced nitrogen use efficiency in crop plants.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it