Influence of Carbon Sources on the Phenolic Compound Production by Euglena gracilis Using an Untargeted Metabolomic Approach
Bibliographic record
Abstract
Industrial development and urbanization has led to the diverse presence of metals in wastewater that are often improperly treated. The microalgae Euglena gracilis can tolerate high concentrations of metal via the excretion of organic metabolites, including phenolics. This study aims to evaluate how carbon amendment stimulates phenolic compound production by E. gracilis. The number, relative intensity and molecular composition of the phenolic compounds were significantly different between each of four carbon amended cultures (i.e., glutamic acid, malic acid, glucose, reduced glutathione) during the log phase. Phenolic compounds were mainly produced during the minimum growth rate, likely a response to stressful conditions. A better understanding of phenolic compounds production by E. gracilis and the impact of growth conditions will help identify conditions that favor certain phenolic compounds for dietary and metal chelation applications.
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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".