A Zebrafish Embryo Model to Screen Potential Therapeutic Compounds in Sapindaceae Poisoning
Bibliographic record
Abstract
Hypoglycin A (HGA) and methylenecyclopropylglycine (MCPrG) are protoxins produced by Sapindaceae plants, particularly Acer pseudoplatanus, and are responsible for causing atypical myopathy (AM) in equids. These protoxins metabolise into toxic compounds, such as methylenecyclopropylacetyl-CoA (MCPA-CoA), which alters energy metabolism and induces severe rhabdomyolysis. Currently, no specific treatment exists for this poisoning, in vitro models fail to reproduce HGA’s toxic effects on equine primary myoblasts, and mammalian models are impractical for large-scale drug screening. This study aimed to develop a zebrafish embryo model for screening therapeutic compounds against AM. Zebrafish embryos were exposed to various concentrations of HGA, MCPrG, and methylenecyclopropylacetate (MCPA) for 72 h. MCPrG did not induce toxicity, while HGA and MCPA showed median lethal concentration (LC50) values of 1.7 µM and 1 µM after 72 h, respectively. The highest levels of the conjugated metabolite MCPA–carnitine were detected 24 h after HGA exposure, and the acylcarnitines profile was highly increased 48 h post-exposure. Isovaleryl-/2- methylbutyrylcarnitine levels notably rose after 24 h, suggesting potential exposition biomarkers. Glycine and carnitine effectively reduced mortality, whereas riboflavin showed no protective effect. These findings suggest that the zebrafish embryo represents a valuable model for identifying therapeutic compounds for Sapindaceae poisoning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".