Identification of curcumin analogues with anti-seizure potential in vivo using chemical and genetic zebrafish larva seizure models
Bibliographic record
Abstract
Seizures are the outward manifestation of abnormally excessive or synchronous brain activity. While seizures can be somewhat symptomatically managed with anti-epileptic drugs (AEDs), many patients are still refractory to the currently available AEDs. As a result, there is a need to identify new molecules with anti-seizure properties. Curcumin is the principle curcuminoid of Curcuma longa, or colloquially turmeric, and has been experimentally proven to have anti-convulsive properties, but its poor bioavailability has dampened further therapeutic interest. Hence, this study aimed to ask if structural analogues of curcumin with an adequate bioavailability could have an anti-seizure effect in vivo. To do so, we tested these analogues following a multipronged approach combining the use of several zebrafish seizure models (chemically-induced and genetic) and complementary assays (behavioural and brain activity). Overall, from the 68 analogues tested, we found 15 different derivatives that were able to significantly decrease the behavioural hyperactivity induced by pentylenetetrazol. Of those, only a few showed an effect on the hyperactivity phenotype of two genetic models of brain seizures that are the gabra1 and gabrg2 knockouts. Two analogues, CA 80(1) and CA 74(1), were able to significantly alleviate brain seizures of gabrg2-mutant larvae. As a result, these analogues are good candidates as novel anti-seizure agents.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".