<i>Osgstu3</i> and <i>osgtu4</i>, encoding tau class glutathione <i>S</i>‐transferases, are heavy metal‐ and hypoxic stress‐induced and differentially salt stress‐responsive in rice roots<sup>1</sup>
Bibliographic record
Abstract
Glutathione S-transferases (GSTs) have poorly understood roles in plant responses to environmental stresses. A polyethylene glycol (PEG)-induced tau class GST was identified in rice roots by protein microsequencing. PEG and the heavy metals Cd (20 microM), Zn (30 microM), Co and Ni rapidly and markedly induced osgstu4 and osgstu3 in rice seedling roots. Osgstu4 and osgstu3 were also induced in roots by hypoxic stress but not by cold nor heat shock. Salt stress and abscisic acid (ABA) rapidly induced osgstu3 in rice roots, whereas osgstu4 exhibited a late salt stress and no ABA response. Salicylic acid, jasmonic acid and the auxin alpha-naphthalene acetic acid triggered osgstu4 and osgstu3 expression. Osgstu4 and osgstu3 were rapidly and markedly induced by the antioxidant dithiothreitol and the strong oxidant hydrogen peroxide, which suggested that redox perturbations and reactive oxygen species are involved in their stress response regulations.
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) | 0.002 | 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".