Abstract 592: Nutrigenomic Screening of Functional Foods Regulating Gluconeogenesis: A Zebrafish Pilot Study
Bibliographic record
Abstract
Introduction/rationale: Current anti-diabetic drug treatments have a variety of adverse side effects. Identifying functional foods with anti-diabetic properties may be the key to preventing and managing T2DM while minimizing side effects. Studies found that Pck-1 gene is often down-regulated by anti-diabetic drugs, as its enzyme is responsible for catalyzing the rate-limiting step of gluconeogenesis. In our study, we screened for functional foods that can down-regulate the expression of the Pck-1 gene. The newly emerged zebrafish (Danio rerio) is aptly suited for in vivo nutrigenomic screening due to its large clutch size and conservation of molecular pathways with humans, including those involved in glucose regulation. Methods: We exposed zebrafish larve (Tg(Pck-1:luc), a luminescent reporter line for Pck-1), at 4 days post fertilization (dpf) to extracts from forty functional fruits and vegetables. The level of Pck-1 expression was quantified by luminescence at 6 dpf. Extracts which resulted in a lower reading of luminescence were interpreted as functional foods that could successfully down-regulate Pck-1 expression, and therefore may be potential therapeutic for T2DM. We further validated our results using a fluorescent reporter line for Pck-1 (Pck-1:eGFP). Results: We completed toxicity assays on the functional food extracts to determine the optimal concentrations and conditions for nutrigenomic screening. Preliminary results show that bamboo and cherry extracts significantly reduced Pck-1 gene expression by two fold (p<0.05). Other functional food extracts, such as grape, cucumber, cabbage, spinach, flat beans, and lemon also reduced Pck-1 gene expression. Interestingly, garlic extracts increased Pck-1 gene expression. Conclusion and Discussion: We identified two functional food extracts that successfully reduced Pck-1 expression in zebrafish models. Increasing the intake of these two functional foods may regulate blood glucose levels in T2DM patients. Further research elucidating the active ingredient in these foods is required. The Pck-1 zebrafish model can be employed for further nutrigenomic screening and/or for drug discovery purposes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".