Honokiol: a promising small molecular weight natural agent for the growth inhibition of oral squamous cell carcinoma cells
Bibliographic record
Abstract
Honokiol (HNK) is a small organic molecule purified from magnolia species and has demonstrated anticancer activities in a variety of cancer cell lines; however, its effect on oral squamous cell carcinoma (OSCC) cells is unknown. We investigated the antitumor activities of HNK on OSCC cells in vitro for the first time. The inhibitory effects of HNK on the growth and proliferation of OSCC cells were demonstrated via in vitro 3-(4,5-dimethyl thiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and propidium iodide (PI) assays, and the apoptotic cells were investigated by the observation of morphological changes and detection of DNA fragmentation via PI, TdT-mediated dUTP-biotin nick end labeling (TUNEL), and DNA ladder assays, as well as flow cytometry assay. The results showed that HNK inhibited the growth and proliferation of OSCC cells in vitro in a time and dose-dependent manner. The inhibitory effect was associated with the cell apoptosis induced by HNK, evidenced by the morphological features of apoptotic cells, TUNEL-positive cells and a degradation of chromosomal DNA into small internucleosomal fragments. The study also demonstrated here that the inhibition or apoptosis mediated by 15 microg x mL(-1) or 20 microg x mL(-1) of HNK were more stronger compared with those of 20 microg x mL(-1) 5-fluorouracil (5-Fu, the control) applied to OSCC cells, when the ratio of OSCC cell numbers were measured between the treatment of different concentrations of HNK to the 5-Fu treatment for 48 h. HNK is a promising compound that can be potentially used as a novel treatment agent for human OSCC.
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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".