The protective role of silicon in the <i>Arabidopsis</i> –powdery mildew pathosystem
Bibliographic record
Abstract
The role and essentiality of silicon (Si) in plant biology have been debated for >150 years despite numerous reports describing its beneficial properties. To obtain unique insights regarding the effect of Si on plants, we performed a complete transcriptome analysis of both control and powdery mildew-stressed Arabidopsis plants, with or without Si application, using a 44K microarray. Surprisingly, the expression of all but two genes was unaffected by Si in control plants, a result contradicting reports of a possible direct effect of Si as a fertilizer. In contrast, inoculation of plants, treated or not with Si, altered the expression of a set of nearly 4,000 genes. After functional categorization, many of the up-regulated genes were defense-related, whereas a large proportion of down-regulated genes were involved in primary metabolism. Regulated defense genes included R genes, stress-related transcription factors, genes involved in signal transduction, the biosynthesis of stress hormones (SA, JA, ethylene), and the metabolism of reactive oxygen species. In inoculated plants treated with Si, the magnitude of down-regulation was attenuated by >25%, an indication of stress alleviation. Our results demonstrate that Si treatment had no effect on the metabolism of unstressed plants, suggesting a nonessential role for the element but that it has beneficial properties attributable to modulation of a more efficient response to pathogen stress.
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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".