Toxicity assessment of reference and natural freshwater sediments with the LuminoTox assay
Bibliographic record
Abstract
We examined the possibility of adapting the LuminoTox, a recently-commercialized bioanalytical testing procedure initially developed for aqueous samples, to assess the toxic potential of sediments. This portable fluorescent biosensor uses photosynthetic enzyme complexes (PECs) to rapidly measure photosynthetic efficiency. LuminoTox testing of 14 CRM (Certified Reference Material) sediments was first undertaken with (1) a "solid phase assay" (Lum-SPA) in which PECs are in intimate contact with sediment slurries for a 15 min exposure period and (2) an elutriate assay (Lum-ELU) in which PECs are exposed for 15 min to sediment water elutriates. CRM sediment toxicity data were then compared with those generated with the Microtox Solid Phase Assay (Mic-SPA). A significant correlation (P < 0.05) was shown to exist between Lum-SPA and Mic-SPA, indicating that both tests display a similar toxicity response pattern for CRM sediments having differing contaminant profiles. The sediment elutriate Lum-ELU assay displayed toxicity responses (i.e. measurable IC20s) for eight of the 14 CRM sediments, suggesting that it is capable of determining the presence of sediment contaminants that are readily soluble in an aqueous elutriate. Lum-SPA and Mic-SPA bioassays were further conducted on 12 natural freshwater sediments and their toxicity responses were more weakly, yet significantly, correlated. Finally, Lum-SPA testing undertaken with increasing mixtures of kaolin clay confirmed that its toxicity responses, in a manner similar to those reported for the Mic-SPA assay, are also subject to the influence of grain size. While further studies will be required to more fully understand the relationship between Lum-SPA assay responses and the physicochemical makeup of sediments (e.g., grain size, combined presence of natural and anthropogenic contaminants), these preliminary results suggest that LuminoTox testing could be a useful screen to assess the toxic potential of solid media.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".