Ferric reduction oxidase 2 gene from Pyrus betulifolia is regulated by iron deficiency and auxin
Bibliographic record
Abstract
Pyrus betulifolia Bunge belongs to the woody plant family and is an ideal model for studying molecular strategies of iron acquisition and metabolism in strategy I plants. Using polymerase chain reaction amplification technology, a gene encoding a putative ferric chelate reductase (FCR) protein was isolated from P. betulifolia and designated as PbFRO2. This gene was 2166 bp in length with an open reading frame encoding a protein of 721 amino acids. A hidden Markov model for topology prediction of PbFRO2 suggested that there were 10 transmembrane regions (I–X) connected by nine loops. Phylogenetic analyses demonstrated that PbFRO2 had the highest homology with Malus xiaojinensis Cheng & Jiang. Iron starvation induced significant increase in root FCR activity and PbFRO2 expression. The split-root experiment demonstrated that Fe limitation in one portion of the root system triggered significant up-regulation of the PbFRO2 expression in the Fe-sufficient part, suggesting that the PbFRO2 expression was induced by systemic signals. Furthermore, the addition of α-naphthaleneacetic acid was found to strengthen the Fe deficiency-caused up-regulation of the PbFRO2 expression in the roots. By contrast, 1-naphthylphthalamic acid application blocked up-regulation of the PbFRO2 expression. The results indicated that Fe deficiency-induced alterations of the PbFRO2 expression were mediated by auxin.
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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".