ROS-Induced anthocyanin production provides feedback protection by scavenging ROS and maintaining photosynthetic capacity in Arabidopsis
Bibliographic record
Abstract
Anthocyanins are water-soluble pigments with antioxidant activities. In plants, multiple factors can trigger the accumulation of anthocyanins, including chemicals and environmental factors. Reactive oxygen species (ROS) are common by-products produced under different biotic and abiotic conditions and cause oxidative stress when accumulated at a high level in plant cells. This in turn leads to the production of anthocyanins. However, the mechanisms of ROS-induced anthocyanin accumulation and the role of anthocyanins in the response of plants to different stresses are largely unknown. We have recently reported the cross-regulation between ROS and anthocyanin production through analyzing ten Arabidopsis mutants covering the main anthocyanin regulatory and biosynthetic genes grown under different ROS-generating stresses. Here, we describe the general phenotypic response of anthocyanin mutants under normal and ROS-generating stress conditions, showing the changing levels of anthocyanin accumulation and their sensitivity to stresses. In addition, we propose a model that describes a particular gene interaction that highlights how the cross-regulation mechanisms between ROS and anthocyanin production are essential for plant resistance to various stresses through removing excessive ROS and maintaining photosynthetic capacity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".