Application of a redox-proteomics toolbox to <i>Daphnia magna</i> challenged with model pro-oxidants copper and paraquat
Bibliographic record
Abstract
The redox status of cells is involved in the regulation of several cellular stress-response pathways. It is frequently altered by xenobiotics, as well as by environmental stressors. As such, there is an increasing interest in understanding the redox status of proteins in different scenarios. Recent advances in proteomics enable researchers to measure oxidative lesions in a wide range of proteins. This opens the door to the sensitive detection of toxicity targets and helps decipher the molecular impact of pollutants and environmental stressors. The present study applies the measurement of protein carbonyls, the most common oxidative lesion of proteins, to gel-based proteomics in Daphnia magna. Daphnids were exposed to copper and paraquat, 2 well-known pro-oxidants. Catalase activity was decreased by paraquat, whereas global measurement of protein carbonyls and thiols indicated no change with treatment. Despite the absence of observed oxidative stress, 2-dimensional electrophoresis of the daphnid proteins and measurement of their carbonylation status revealed that 32 features were significantly affected by the treatments, showing higher sensitivity than single measurements. Identified proteins affected by copper indicated a decrease in the heat-shock response, whereas paraquat affected glycolysis. The present study demonstrates the applicability of redox-proteomics in daphnids, and indicates that the heat-shock response plays a counterintuitive role in metal resistance in daphnids.
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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".