Organic solvents for the glucocorticoid inducer dexamethasone: are they toxic and unnecessary in hydroponic systems?
Bibliographic record
Abstract
Hydroponic cultivation systems provide convenient means of delivering chemical inducers of gene expression to transgenic plants. The glucocorticoid dexamethasone is a water-insoluble inducer and is usually prepared as a stock solution in an organic solvent before addition to the hydroponic nutrient solution. We investigated the effects of ethanol, methanol, and dimethyl sulfoxide (DMSO) on plant appearance and root bacterial growth in nonsterile hydroponic Arabidopsis thaliana (L.) Heynh. culture after 8 d of exposure to the solvent. Ethanol and methanol promoted root bacterial growth and visibly affected overall plant appearance at levels as low as 0.001%, and the effects increased in direct relation to alcohol concentration. DMSO promoted root bacterial growth to a lesser extent than the alcohols and plant appearance was negatively affected only at concentrations of DMSO above 0.01%, suggesting that DMSO may be the best solvent choice. We also demonstrated, however, that dexamethasone prepared as a suspension in water, without dissolution in an organic solvent, was completely effective at inducing transcription of the transgene, thus eliminating the potentially confounding effects of solvents in the interpretation of results.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".