Reproduction Stage Differentiates the Time-Course Regulation of Metabolites in <i>Daphnia magna</i>
Bibliographic record
Abstract
Daphnia magna is a keystone indicator zooplankton used in environmental quality assessments. Comparative metabolomics, which contrasts small biomolecular regulations under different conditions, has emerged as a sensitive and informative investigation tool for the assessment of environmental stressors on D. magna . Baseline metabolomic variation is likely impacted by the asexual reproduction cycle of D. magna; however, the relationship between metabolite concentration regulation and reproduction cycle has not been investigated. This study investigated the time-course regulation of 51 metabolites during different reproduction stages to determine how the reproduction cycle controlled the metabolite profile of D. magna . Two-way analysis of variance (ANOVA) results reveal that most metabolites show significantly differentiated concentrations by individual or a combination of reproduction stages and sampling time. On the basis of the partial least-squares-discriminant analysis (PLS-DA) and ANOVA-simultaneous component analysis (ANOVA-SCA), stages 2 and 3 of reproduction show similarity in metabolite abundance regulation compared to stage 1. Metabolites were classified as being either dependent or independent of reproduction in the pairwise concentration correlation based on Pearson correlation coefficients. This study observed that the D. magna reproduction stage is an important consideration and potential variable and should be considered carefully when conducting metabolomic experiments using 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) | 0.000 | 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".