Impact of organic matter of different origins on lanthanum speciation, bioavailability and toxicity toward a green alga
Bibliographic record
Abstract
Natural dissolved organic matter (DOM) is a heterogeneous mixture of a variety of organic compounds, with a great importance for the environmental fate of metals and their ecotoxicity. However, its complex nature and variable composition make the understanding of its role a challenge. Lanthanum (La) has a strong affinity for DOM and is one of the rare earth elements that is widely used in many electronic and green technologies, and for which the demand may potentially increase for the foreseeable future. The present study examines the links between the optical and chemical properties of organic matter and its influence on the bioavailability and toxicity of La toward the green microalga Chlorella fusca . A total of four DOMs, two natural organic matter samples from Ontario (Luther Marsh and Bannister Lake) and two Suwannee River fulvic and humic acids, were characterized by absorbance and fluorescence spectroscopy as well as by asymmetrical flow field-flow fractionation. These suggest that Luther Marsh and the Suwannee River humic acid have higher molecular weight and are more aromatic, compared to the other two DOMs. The concentrations of free metal ion La 3+ were measured by an ion exchange technique and a partial ultrafiltration method, and related to biological response. Toxicity tests over 96 h at pH = 5.0 were separately conducted with and without 3 mg C·L −1 of each DOM. All DOM samples reduced La bioavailability but as opposed to what can be expected based on the Biotic Ligand Model, the presence of DOM exacerbated the toxicity of La and its accumulation in algal cells when only the free La 3+ ion concentration was considered. These results indicate that the role of natural organic matter in modulating metal bioavailability remains to be deciphered.
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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) | 0.009 | 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".