Gas and Liquid Chromatography–Mass Spectrometry Investigation of <i>Viscum Album</i> Lipophilic Extracts
Bibliographic record
Abstract
Viscum album L. is a semiparasitic medicinal plant traditionally used in complementary medicine for integrative cancer treatment. Aqueous and ethanolic extracts of Viscum have been extensively studied, and their biological activities, especially anticancer, are well described. However, information on the chemical composition of the lipophilic fraction of V. album is scarce, limiting the understanding of its biological activities. The aim of this study was to perform a comprehensive analysis of Viscum album lipophilic extracts (VALE) via gas chromatography–mass spectrometry (GC–MS) and liquid chromatography–high resolution mass spectrometry (LC–HRMS) to unveil its complex chemical composition and understand the impact of VALE storage time and the Viscum host tree. Lipophilic extracts of V. album grown on Pinus sylvestris extracted from 2010 to 2020, and extracts from V. album grown on different host trees (Malus domestica, Quercus sp., Abies alba, and Ulmus sp.) were investigated by GC–MS and LC–HRMS. A total of 103 metabolites were identified using two analytical platforms. The combination of extract hydrolysis and derivatization allowed the identification and quantification of pentacyclic triterpenes, fatty acids, and phytosterols, among other compounds via GC–MS. The LC–MS analysis revealed a complementary profile with the annotation of flavonoids, organic acids, amino acids, and lipids, as well as a trend in sample grouping based on the extraction year. This study can improve the quality control and traceability of formulations containing VALE, as well as advance the understanding of the mechanism of action of VALE topical products used for treating certain types of skin cancer.
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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".