Optimized St. John's Wort (Hypericum perforatum L.) Germplasm Lines Exert Cytotoxicity in HT-29 Colon Cancer Cells via Downregulation of NF-?B
Bibliographic record
Abstract
Extracts of two germplasm lines of St. Johns wort (SJW; Hypericum perforatum L.) selected for enhanced hypericin and hyperforin content were evaluated for potential activity against colon cancer. Bioactivity was assessed in signaling pathways of tumor necrosis factor-a (TNF-?) and nuclear transcription factor-?B (NF-?B) in HT-29 colon cancer cells. Both extracts and the hypericin standard significantly inhibited growth of HT-29 cells. Levels of active NF-?B were reduced in cells treated with either of the plant extracts or hypericin, but the purified hyperforin standard was comparatively ineffective. The combination of TNF-? and SJW treatments had significantly higher cytotoxic effects, and reduced the expression of NF-?B, inhibitor of NF-?Bs (I?Ba), I?B kinase b (IKKb), and TNF receptor-1. These observations indicate the potential of SJW as a source of cancer therapies, including those that act synergistically with TNF-?. The phytochemical complexity of SJW tissues necessitates consistent, optimized plant extracts for optimal results and the data indicate that additional, possibly unidentified, phytochemicals from SJW have potential in the treatment or prevention of colon cancer.
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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".