Accumulation of 1,3-β-d-glucans, in Response to Aluminum and Cytosolic Calcium in Triticum aestivum
Bibliographic record
Abstract
One of the most rapid responses to aluminum (Al) stress in plants is enhanced synthesis and deposition of 1,3-beta-D-glucans (callose) in root tips. Ironically, Al-induced synthesis and deposition of callose occurs in vivo, despite evidence from in vitro systems that suggests that Al is a powerful inhibitor of 1,3-beta-D-glucan synthase. We set out to test the hypothesis that an Al-induced increase in the activity of free calcium in the cytoplasm ([Ca(2+)](cyt)) is the trigger for enhanced synthesis of callose in in vivo systems, an effect that would not be observed in in vitro systems. Root tips of an Al-sensitive cultivar of Triticum aestivum were treated with Al (0-100 microM) or the Ca ionophore A23187 (0-3 micro M) for 3-24 h, and the effects on [Ca(2+)](cyt) and synthesis of callose were measured using confocal laser scanning microscopy. Treatment with Al induced a rapid increase in both [Ca(2+)](cyt) (4.7-fold) and synthesis of callose (30-fold). Treatment with the Ca ionophore, A23187, also elicited an increase in [Ca(2+)](cyt) (6.6-fold). Despite a greater increase in [Ca(2+)](cyt) in the presence of A23187, this increase was accompanied by a smaller increase in callose deposition (11-fold) than was observed in the presence of Al. These data suggest that an increase in [Ca(2+)](cyt) is not the only factor modulating increases in callose synthesis and deposition in the presence of Al.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".