<i>C. elegans</i> as an <i>in vivo</i> model system for the phenotypic drug discovery for treating paraquat poisoning
Why this work is in the frame
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Bibliographic record
Abstract
Background Paraquat (PQ) is an effective and widely used herbicide and causes numerous fatalities by accidental or voluntary ingestion. However, neither the final cytotoxic mechanism nor effective treatments for PQ poisoning have been discovered. Phenotypic drug discovery (PDD), which does not rely on the molecular mechanism of the diseases, is having a renaissance in recent years owing to its potential to address the incompletely understood complexity of diseases. Herein, the C. elegans PDD model was established to pave the way for the future phenotypic discovery of potential agents for treating PQ poisoning. Methods C. elegans were treated with PQ-containing solid medium followed by statistical analysis of worm survival, pharyngeal pumping, and movement ability. Furthermore, coenzyme Q10 (CoQ10) was used to test the C. elegans model of PQ poisoning by measuring the levels of reactive oxygen species (ROS) and malondialdehyde (MDA), mitochondrial morphology, and worm survival rate. Additionally, we used the classic mice model of PQ intoxication to evaluate the validity of the C. elegans model of PQ poisoning by measuring the effect of CoQ10 as a potential antidote for PQ poisoning. Results In the C. elegans model of PQ poisoning, 5 mg/mL PQ increased the levels of ROS, MDA content, mitochondrial fragments, which significantly shortened the lifespan, while CoQ10 alleviated these phenotypes. In the mice model of PQ poisoning, CoQ10 increased the chance of survival in PQ poisoned mice while reducing ROS, MDA content in lung tissue and inhibiting PQ-induced lung edema. Moreover, CoQ10 alleviated the lung morphopathological changes induced by PQ. Conclusion Here we established a C. elegans model of PQ poisoning, whose validity was confirmed by the classic mice model of PQ intoxication.
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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 | 0.000 | 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 | 0.001 | 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 it