The Dietary Flavonoid, Luteolin, Negatively Affects Neuronal Differentiation
Bibliographic record
Abstract
Luteolin, a polyphenolic plant flavonoid, has been attributed with numerous beneficial properties like anti-cancer, antioxidant, and anti-inflammatory action. Luteolin has been reported earlier to be neuroprotective in models of spinal cord injury and traumatic brain injury and also induces neurite outgrowth in PC12 cells. However, the effect of luteolin on early differentiation, which might be important for its beneficial effects, is unknown. In this report, we show that luteolin negatively affects early differentiation of embryonic stem cells, hampering the formation of embryoid bodies. At later stages of differentiation, luteolin specifically inhibits neuronal differentiation, where the expression of early neuronal markers is suppressed, whereas luteolin treatment does not inhibit expression of meso- and endodermal markers. Further, in a developing zebrafish model, luteolin treatment leads to fewer numbers of mitotic cells in the brain. These specific effects of luteolin on neuronal differentiation could possibly be due to its ability to inhibit the lysine acetyltransferase, p300, since the structurally closely related p300 non-inhibitor flavonoid, apigenin, does not inhibit neuronal differentiation. These results show that luteolin perturbs neuronal differentiation of embryonic stem cells.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".