Bioavailability, Toxicity and Biotransformation of Selenium in Midge (<i>Chironomus dilutus</i>) Larvae Exposed via Water or Diet to Elemental Selenium Particles, Selenite, or Selenized Algae
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Elemental selenium (Se) is generally considered to be biologically inert due to its insolubility in water. It is a common form of Se in sediment near uranium mining and milling operations in northern Saskatchewan, Canada. Nanosized particles of many materials exhibit different properties compared with their bulk phases, in some cases posing health and ecological risks. Here we investigated the bioavailability and toxicity of Se nanoparticles (SeNPs) using 10-day waterborne and dietary exposures to larvae of Chironomus dilutus, a common benthic invertebrate. For comparison, larvae were also exposed to waterborne dissolved selenite and to dietary selenomethionine as selenized algae. Larval Se accumulation was evaluated using graphite furnace atomic absorption spectroscopy or inductively coupled plasma mass spectroscopy for total Se and X-ray absorption spectroscopy for Se chemical speciation. Exposure to nanoparticulate Se resulted in Se bioaccumulation, at high concentrations, inhibiting larval growth in both waterborne and dietary exposures; larvae predominantly accumulated selenomethionine-like species regardless of uptake route or form of Se tested. Despite the observed Se accumulation, our findings suggest there is little risk of direct SeNP toxicity to benthic invertebrates in Se-contaminated sediments in northern Saskatchewan. Nevertheless, elemental Se in sediments may be biologically available and may contribute directly or indirectly to the risk of Se toxicity to egg-laying vertebrates (fish and piscivorous birds) in Se-contaminated aquatic systems. It thus may be necessary to include elemental Se as a source of potential Se exposure in ecological risk assessments.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 it