Isolation, Characterization, and Breast Cancer Cytotoxic Activity of Gyrophoric Acid from the Lichen Umbilicaria muhlenbergii
Bibliographic record
Abstract
Lichens produce a large variety of secondary metabolites with diverse bioactivities, chemical structures, and physicochemical properties. For this reason, there is a growing interest in the use of lichen-derived bioactive molecules for drug discovery and development. Here, we report on the isolation, identification, and cytotoxic evaluation of gyrophoric acid (GA) from the lichen Umbilicaria muhlenbergii, a largely unexplored and scantly described lichen species. A simple purification protocol was developed for the fractionation of lichen crude extracts with silica gel column chromatography using solvents with changing polarity. GA was identified in one of the fractions with Fourier transform infrared spectroscopy (FTIR), ion trap mass spectrometry (MS), and nuclear magnetic resonance spectroscopy (1H-NMR and 13C-NMR). The FTIR spectra demonstrated the presence of aromatic and ester functional groups C=C, C-H, and C=O bonds, with the most remarkable signals recorded at 1400 cm−1 for the aromatic region, at 1400 cm−1 for the CH3 groups, and at 1650 cm−1 for the carbonyl groups in GA. The MS spectra showed a molecular ion [M-1]− at (m/z) 467 with a molecular weight of 468.4 and the molecular formula C24H20O10. that correspond to GA. The 1H-NMR and 13C-NMR spectra verified the chemical shifts that are typical for GA. GA reduced the cell viability of breast cancer cells from the MCF-7 cell line by 98%, which is indicative of the strong cytotoxic properties of GA and its significant potential to serve as a potent anticancer drug.
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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 | 0.001 | 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 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".