Thorium Exposure Drives Fatty Acid and Metal Transfer from Biofilms to the Grazer <i>Lymnaea</i> sp.
Bibliographic record
Abstract
Abstract Aquatic ecotoxicological risks associated with tetravalent metallic elements such as thorium (Th) are still poorly understood. Periphytic biofilm represents an important food source in aquatic environments; thus, such risks could severely affect nutrient and energy cycling in these ecosystems. The present study investigated the potential for Th to change the fatty acid composition of biofilm communities. Bioaccumulation of Th and fatty acids were measured after 4 wk to 2 exposure conditions: a control (C0) and Th exposure (C10). Some major fatty acids such as C16:1n-7 and docosahexaenoic acid C22:6n-3 differed significantly between control and C10 conditions. To determine if Th can be trophically transferred and to investigate the impacts of nutritional quality changes on primary consumers, common pond snails (Lymnaea sp.) were fed for 4 wk with control and Th-exposed biofilm. Thorium appeared to be trophically transferable to the grazers, although we cannot exclude that part of the Th accumulated by the snails may have been taken from the water through release from the biofilms. The composition of major fatty acids observed in the grazers was also significantly affected, notably by a decrease of total polyunsaturated fatty acids. These results indicate that very low Th concentrations can decrease the nutritional quality of organisms at the base of the food chain. Environ Toxicol Chem 2021;40:2220–2228. © 2021 SETAC Abstract Thorium (Th) waterborne exposure induced bioaccumulation in biofilms and a reduction in fatty acids (FAs) such as C20:2n-6. The Th-exposed biofilm diet caused a decrease in polyunsaturated FAs and n-6 FAs in grazers, as well as Th bioaccumulation in soft bodies. PUFA = polyunsaturated FA.
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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".