Evaluation of sample preparation methods for nuclear magnetic resonance metabolic profiling studies with<i>Eisenia fetida</i>
Bibliographic record
Abstract
The earthworm Eisenia fetida is frequently used in ecotoxicological studies; however, it has not yet been investigated using proton nuclear magnetic resonance ((1)H NMR) metabolic profiling methods. The present study investigates the impact of depuration time, sample homogenization, and different extraction solvents on the quality and reproducibility of the (1)H NMR spectra of E. fetida with the goal of determining whether this species is suitable for future metabonomic studies. A depuration time of 96 h, followed by intact lyophilization before homogenization and extraction into a deuterium oxide (D(2)O)-based phosphate buffer, was found to produce extracts with excellent (1)H NMR reproducibility. The D(2)O buffer extracted the largest quantity of the widest variety of earthworm metabolites, which is consistent with the results from other studies using different earthworm species. Nuclear magnetic resonance assignments of the major metabolites in the D(2)O-based buffer also were performed and found to be similar to those for other earthworm species, such as Eisenia veneta, but also to have characteristic attributes in E. fetida. The major metabolites identified include amino acids (alanine, arginine, glutamic acid, glutamine, glycine, leucine, lysine, phenylalanine, serine, tyrosine, and valine), two sugars (glucose and maltose), the sugar alcohol mannitol, and the polyalcohol inositol. Two other earthworm species (Lumbricus rubellus and Lumbricus terrestris) also were examined using protocols developed for E. fetida, and of the three species, the (1)H NMR spectra of E. fetida had the least variation, indicating this species is well-suited for future metabolomic-based ecotoxicity studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".