Do co-solvents used in exposure studies equally perturb the metabolic profile of <i>Daphnia magna</i>?
Bibliographic record
Abstract
Dissolution methods such as co-solvents are used to solubilize insoluble compounds in exposure experiments. Several exposure studies have followed the guidelines from the Organization for Economic Co-operation and Development where co-solvents are applied at 0.01% v/v of the total exposure volume. Although no observable apical endpoint abnormalities were reported following these guidelines, little is known about the molecular-level impacts of co-solvents used in exposure studies. A targeted metabolomics approach using liquid chromatography coupled with triple quadrupole mass spectrometry was used to assess Daphnia magna responses to four commonly used co-solvents, including acetone (ACT), acetonitrile (ACN), methanol (MeOH), and dimethyl sulfoxide (DMSO), at three different levels (0.01%, 0.05%, and 0.1% v/v) over 48 hr. Based on the observed metabolic disruptions, exposure to MeOH and DMSO induced higher metabolic perturbations in amino acid levels and associated biochemical pathways in comparison to ACT and ACN exposures. However, as with mixtures, when co-solvents are combined with the pollutants under investigation, there is a possibility for additive, synergistic, or antagonistic interactions. Hence, to examine the possible impairments in co-solvent and pollutant mixtures, ACT and ACN applied at 0.01% v/v were chosen to be tested with phenanthridine (PN). Daphnia magna exposure to PN dissolved in ACT had less disruptions; in contrast to PN prepared in ACN, which triggered a higher degree of antagonism in the D. magna metabolic profile. Consequently, exposing D. magna to ACT applied at 0.01% v/v resulted in the lowest metabolic perturbation in both parts of this study, suggesting that it is the least disruptive co-solvent for molecular-level exposure studies involving D. magna.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".