New Terpenoids from Chamaecyparis formosensis (Cupressaceae) Leaves with Modulatory Activity on Matrix Metalloproteases 2 and 9
Bibliographic record
Abstract
Chamaecyparis formosensis is Taiwan’s most representative tree, and has high economic value. To date, only a few active chemical constituents have been reported for C. formosensis. In this study, 37 secondary metabolites, including three new compounds (1–3), were extracted from the leaves of C. formosensis. The compounds isolated from the ethyl acetate layer were used at different concentrations to treat HT-1080 human fibrosarcoma cells and to evaluate their effects on matrix metalloprotease 2 (MMP-2) and 9 (MMP-9) expression. Based on extensive analysis of data from high-resolution mass spectrometry (HR-MS) as well as nuclear magnetic resonance (NMR), infrared (IR), and ultraviolet (UV) spectroscopy, the new compounds were identified as 11,12-dihydroxyisodaucenoic acid (1), 12-hydroxyisodaucenoic acid (2), and 1-oxo-2α,3β-dihydroxytotarol (3). Known compounds 4–37 were identified by comparing their spectroscopic data with data reported in the literature. Biological activity tests by gelatin zymographic analysis revealed that seven compounds, including new compound 2, have no cytotoxic effect on HT-1080 cells and were found to increase MMP-2 or MMP-9 expression by 1.25- to 1.59-fold at lower concentrations of 10–50 µM. These naturally derived regulatory compounds could potentially serve as a novel pharmaceutical basis for medical purposes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".