Identification of Genes Expressed in Vascular Tissues Using NPA-Induced Vascular Overgrowth in Arabidopsis
Bibliographic record
Abstract
The genetic basis of vascular differentiation and function is relatively poorly understood, partly due to the difficulty of screening for mutants defective in internal vascular tissues. Here we present an approach based on a predicted increase in vascular-related gene expression in response to an auxin transport inhibitor-induced vascular overgrowth. We used microarray analyses to identify 336 genes that were up-regulated > or =2-fold in shoot tissues of Arabidopsis thaliana showing vascular overgrowth. Promoter-marker gene fusions revealed that 38 out of 40 genes with > or =4-fold up-regulation in vascular overgrowth tissues had vascular-related expression in transgenic Arabidopsis plants. Obtained expression patterns included cambial tissues and differentiating xylem, phloem and fibers. A total of 15 genes were found to have vascular-specific expression patterns in the leaves and/or inflorescence stems. This study provides empirical evidence of the efficiency of the approach and describes for the first time the in situ expression patterns of the majority of the assessed genes.
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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".