4,8-dicarboxyl-8,9-iridoid-1-glycoside Promotes Neural Stem Cell Differentiation Through MeCP2
Bibliographic record
Abstract
Background: Borojó (Borojoa patinoi Cuatrec) fruit has recently been shown to have a variety of health benefit, but the mechanisms have been little studied. The aim of this study was to investigate the effect of 4,8-dicarboxyl-8,9-iridoid-1-glycoside (388) on proliferation and differentiation of embryonic neural stem cells (NSCs). Methods: NSCs were treated with 388 and stem cell differentiation was determined by western blotting and immunofluorescence staining. The role of MeCP2 in 388-mediated embryonic NSCs differentiation was examined. Results: The results showed that in the presence of mitogen when NSCs proliferated and maintained their multipotency, treatment with 388 did not affect the viability of NSCs. Following mitogen withdrawal to initiate NSC differentiation, treatment with 388 at the doses of 10 and 50 μg/mL significantly increased neural differentiation in both cortex and spinal cord-derived culture. 388 also significantly up-regulated MeCP2 expression. The expression of the neuronal and oligodendrocytic markers was enhanced after addition of 388 in the differentiation culture. However, knockdown of MeCP2 results in inhibition of NSC differentiation, and the pro-differentiation effect of 388 was mostly abolished. Conclusions: This study confirmed that 388 stimulates differentiation of NSCs and identifies its mechanism of action by upregulating MeCP2.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".