Molecular Mechanisms of Phosphorus Metabolism and Transport during Leaf Senescence
Bibliographic record
Abstract
Leaf senescence, being the final developmental stage of the leaf, signifies the transition from a mature, photosynthetically active organ to the attenuation of said function and eventual death of the leaf. During senescence, essential nutrients sequestered in the leaf, such as phosphorus (P), are mobilized and transported to sink tissues, particularly expanding leaves and developing seeds. Phosphorus recycling is crucial, as it helps to ensure that previously acquired P is not lost to the environment, particularly under the naturally occurring condition where most unfertilized soils contain low levels of soluble orthophosphate (Pi), the only form of P that roots can directly assimilate from the soil. Piecing together the molecular mechanisms that underpin the highly variable efficiencies of P remobilization from senescing leaves by different plant species may be critical for devising effective strategies for improving overall crop P-use efficiency. Maximizing Pi remobilization from senescing leaves using selective breeding and/or biotechnological strategies will help to generate P-efficient crops that would minimize the use of unsustainable and polluting Pi-containing fertilizers in agriculture. This review focuses on the molecular mechanisms whereby P is remobilized from senescing leaves and transported to sink tissues, which encompasses the action of hormones, transcription factors, Pi-scavenging enzymes, and Pi transporters.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".