Impact of Azo Dyes and Ibuprofen on the Proteome of Serratia nematodiphilasp. MB307
Bibliographic record
Abstract
BACKGROUND: Micropollutants comprise organic/mineral substances that cause an undesirable impact on the environment, by affecting life at all scales. In this study, we explored the changes they impart on the global proteome of a soil bacterium Serratia nematodiphila MB307, for two classes of pollutants, i.e., Azo dyes (Methyl orange, Congo red) and a pharmaceutical (Ibuprofen). METHODS: The 100 μg pollutant supplemented alteration of pure S. nematodiphila MB307 culture after 24 hours of incubation at 37 °C and its control was analyzed using a differential proteomics approach. MaxQuant software with the Perseus package was used for data analysis purposes. RESULTS: Prominently, ribosomal proteins and chaperones were up or downregulated in the whole cell and membranous fraction. CONCLUSION: This illustrates dynamic protein production adaptation of bacteria, to cope with stress and cell growth/division trade-off for survival. A collective pattern of survival under stress or pollution resistance could not be decrypted for all classes of pollutants, portraying dissimilar mechanisms of coping with differently structured pollutant moieties.
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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".