Monitoring of a flame retardant (tetrabromobisphenol A) toxicity on different microalgae assessed by flow cytometry
Bibliographic record
Abstract
Microalgae are key organisms in aquatic ecosystems. Emergent pollutants like the tetrabromobisphenol A (TBBPA) are potential threat for these primary producers at the base of the trophic chain. The effects of this flame retardant on three microalgae (Pseudokirchneriella subcapitata, Nitzschia palea and Chlamydomonas reinhardtii) commonly observed in freshwater ecosystems were studied using a flow cytometer. Each species was exposed to 1.8, 4.8, 9.2, 12.9 and 16.5 µmol L⁻¹ of TBBPA for 72 h. After staining with fluorescein diacetate (FDA), viable cells were discriminated in flow cytogram according to the chlorophyll autofluorescence and the intracellular enzyme activity (esterase) to assess the sensitivity of microalgae to the TBBPA with multi-parametric analysis. For P. subcapitata and N. palea, growth inhibitions of viable cells were lower when the viability was assessed with chlorophyll autofluorescence in comparison with esterase activity. These results are related to the appearance of cells presenting optimal chlorophyll fluorescence without intracellular esterase activity after exposure to TBBPA. Abundance increase of these cells was higher in N. palea than in P. subcapitata. No similar trends were observed in C. reinhardtii populations due to the very high mortality of this microalgal species exposed to TBBPA.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".