Cytotoxicity of various chemicals and mycotoxins in fresh primary duck embryonic fibroblasts: a comparison to HepG2 cells
Bibliographic record
Abstract
To screen cost-effectively the overall toxicity of a sample, particularly in the case of food and feed ingredient quality control, a sensitive bioassay is necessary. With the wide variety of cytotoxicity assays, performance comparison between assays using different cells has become of interest. Fresh primary duck embryonic fibroblasts (DEF) were hypothesized to be a sensitive tool for in vitro cytotoxicity screening; cell viability of DEF in response to various cytotoxins was determined and compared with response of HepG2 cells. The IC50 values by the alamar blue assay in the DEF cells had a high correlation (R(2) = 0.96) with those obtained in HepG2 cells. Within the same toxin, primary DEF yielded significantly lower IC50 values than that obtained from HepG2 cells using the MTT and alamar blue assay. Additionally, primary DEF responded to all mycotoxins tested using the alamar blue assay, while HepG2 was less sensitive, particularly at short exposure times. The estimated IC50 for aflatoxin B1 , fumonisins B1 and deoxynivalenol in DEF after 72 h incubation were 3.69, 4.19 and 1.26 μg ml(-1) , respectively. Results from the current study suggest that primary DEF are more sensitive to cytotoxins and mycotoxins compared to HepG2, and thus may have great potential as an effective tool for cytotoxicity assessment. The question remains whether in vitro IC50 values can accurately predict in vivo toxicity; however, the current study accentuates the need for further attention to identify sensitive cell models for in vitro cytotoxicity screening and subsequent exploration of species-specific prediction models for in vivo toxicity. Copyright © 2016 John Wiley & Sons, Ltd.
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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) | 0.001 | 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) | 0.000 | 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 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".