Magnolol Affects Cellular Proliferation, Polyamine Biosynthesis and Catabolism-Linked Protein Expression and Associated Cellular Signaling Pathways in Human Prostate Cancer Cells in vitro
Bibliographic record
Abstract
Background: Prostate cancer is the most commonly diagnosed form of cancer in men in Canada and the United States. Both genetic and environmental factors contribute to the development and progression of many cancers, including prostate cancer.Context and purpose of this study: This study investigated the effects of magnolol, a compound found in the roots and bark of the magnolia tree Magnolia officinalis, on cellular proliferation and proliferation-linked activities of PC3 human prostate cancer cells in vitro.Results: PC3 cells exposed to magnolol at a concentration of 80 μM for 6 hours exhibited decreased protein expression of ornithine decarboxylase, a key regulator in polyamine biosynthesis, as well as affecting the expression of other proteins involved in polyamine biosynthesis and catabolism. Furthermore, protein expression of the R2 subunit of ribonucleotide reductase, a key regulatory protein associated with DNA synthesis, was significantly decreased. Finally, the MAPK (mitogen-activated protein kinase), PI3K (phosphatidylinositol 3-kinase), NFκB (nuclear factor of kappa-light-chain-enhancer of activated B cells) and AP-1 (activator protein 1) cellular signaling pathways were assayed to determine which, if any, of these pathways magnolol exposure would alter. Protein expressions of p-JNK-1 and c-jun were significantly increased while p-p38, JNK-1/2, PI3Kp85, p-PI3Kp85, p-Akt, NFκBp65, p-IκBα and IκBα protein expressions were significantly decreased.Conclusions: These alterations further support the anti-proliferative effects of magnolol on PC3 human prostate cancer cells in vitro and suggest that magnolol may have potential as a novel anti-prostate cancer agent.Key Words: prostate cancer cells, magnolol, polyamines, MAPK, PI3K, NFκB
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".