Root developmental adaptation to Fe toxicity: Mechanisms and management
Bibliographic record
Abstract
Iron (Fe) is an essential microelement but is highly toxic when in excess. To cope with Fe excess, plants have evolved complex adaptive responses that include morphological and physiological modifications. The highly dynamic adjustments in overall root system architecture (RSA) determine root plasticity and allow plants to efficiently adapt to environmental constraints. However, the effects of Fe excess on RSA are poorly understood. Recently, we showed that excess Fe treatment in Arabidopsis not only directly impairs primary root (PR) growth but also arrests lateral root (LR) formation by acting at the tip of the growing primary root. Such a change is believed to help RSA adjust and restrict excessive Fe absorption in the part of the rhizosphere subject to acute toxicity while maintaining the absorption of other nutrients in the less stressed components of the root system. We further showed that the suppression of PR growth and LR formation under excess Fe is alleviated by K(+) addition, providing useful insight into the effectiveness of nutrient management to improve RSA and alleviate Fe toxicity symptoms in the field.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".