Cardiogenic effects of characterized <i>Geum urbanum</i> extracts on adipose-derived human mesenchymal stem cells
Bibliographic record
Abstract
Stem cell therapy is considered as a promising treatment for cardiovascular diseases. Adipose-derived mesenchymal stem cells (ADMSCs) have the ability to undergo cardiomyogenesis. Medicinal plants are effective and safe candidates for cell differentiation. Therefore, the aim of our study was to investigate cardiogenic effects of characterized (HPLC-UV) extracts of Geum urbanum on ADMSCs of adipose tissue. The methanolic extracts of the root and aerial parts of G. urbanum were obtained and MTT assay was used for studying their cytotoxic effects. Then, cells were treated with 50 or 100 μg/mL of the extracts from root and aerial parts of G. urbanum. MTT assay showed that the extracts of G. urbanum did not have any toxic effects on ADMSCs. Immunostaining results showed increase in the expression of α-actinin and cardiac troponin I (cTnI), and quantitative real-time reverse-transcription PCR data confirmed the upregulation of ACTN, ACTC1, and TNNI3 genes in ADMSCs after treatment. According to HPLC fingerprinting, some cardiogenic effects of G. urbanum extracts are probably due to ellagic and gallic acid derivatives. Our findings indicated that G. urbanum extracts effectively upregulated some essential cardiogenic markers, which confirmed the therapeutic role of this plant as a traditional cardiac medicine.
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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 | 0.000 |
| 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 | 0.000 | 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".