Hypericium perforatum extract (St. John's Wort) and hypericin induce apoptosis in leukemic HL-60 cells by effecting h-TERT activity.
Bibliographic record
Abstract
Hypericin is the main active component of Hypericium perforatum (St. John's Wort). Hypericin has been proven to have antitumoral effect in in vitro condition against solid tumors by deteriorating the mitochondrial functions. It has also anti-leukemic effect in in vitro conditions. However, there has not been any comparative study with hypericin and extract obtained from Hypericium perforatum L. In this study, it has been aimed to investigate the potential cytotoxic role of the extract obtained from Hypericium perforatum grown in Ege region on leukemic cell line, to compare the cytotoxic effects of both extract and hypericin in HL-60 cells, and to clarify the underlying mechanism(s) of this cytotoxicity. Hypericium perforatum extract was used in dilutions as 1/1000, 1/5000, 1/10.000, 1/50.000 and the IC50 value was found to be as 1/10.000 dilution. Hypericin was found to have cytotoxicity in HL-60 cells in time and dose dependent manner between the doses of 1nM to 100 μM with IC50 dose of 0.5 μM. Hypericin with the dose of 0.5 μM had similar cytotoxicity pattern with the cytotoxicity curve obtained with 1/10000 diluted extract. Apoptosis as an underlying mechanism of this cytoxocity was shown in HL-60 cells after incubation with IC50 dose of hypericin which was more remarkable at 48th hours by using acridine orange/ethidium bromide dye method. Total RNA was isolated concomittantly and h-TERT mRNA expression was analyzed at Light Cycler Real-time online polymerase chain reaction and it was found that the mRNA expression was meaningfully decreased at 48th hour of incubation of cells with hypericin. According to results of this study, we have shown that hypericin, as main cytotoxic compound of Hypericium perforatum L, induces apoptosis in HL-60 cells via effecting h-TERT mRNA expression.
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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 | 0.001 |
| 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".