Stress resistance of <i>Escherichia coli</i> and <i>Bacillus subtilis</i> is modulated by auxins
Bibliographic record
Abstract
Two bacterial species, Gram-negative Escherichia coli and Gram-positive Bacillus subtilis, were exposed to different auxins to examine possible effects of these substances on bacterial stress tolerance. Bacterial resistance to UV irradiation, heat shock, and streptomycin was assessed with and without previous exposure to the following auxins: indole-3-acetic acid (IAA), indole-3-butyric acid (IBA), and 1-naphthalene acetic acid (NAA). Escherichia coli and B. subtilis cultures pretreated with any of the 3 auxins survived UV irradiation better than the untreated cultures. Also, B. subtilis cultures pretreated with IBA or NAA survived prolonged heat exposure better than the untreated cultures, while IAA pretreatment had no effect on heat shock survival. In contrast, auxin pretreatment rendered E. coli more sensitive to heat shock. Escherichia coli cultures pretreated with auxins were also more sensitive to streptomycin, while auxin pretreatment had no effect on sensitivity of B. subtilis to streptomycin. These results show that auxins may either enhance or reduce bacterial tolerance to different stressors, depending on the bacterial species and the type and level of the stress. Auxins usually had similar effects on the same bacterial species in cases when the same type and level of stress were applied.
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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".