Extraction of bioactive moieties of Cupressus arizonica and Cupressus sempervirens wood knots
Why this work is in the frame
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Bibliographic record
Abstract
This research was aimed to determine the hydrophilic bioactive extractives of Arizona cypress. The extractives of Arizona cypress were isolated and characterized by gas chromatography-mass spectrometry (GC-MS). Hydrophilic compounds of the extractives were mildly isolated by soaking the wood flour in ethanol: water (9:1 v/v) solution followed by n-hexane extraction to remove the lipophilic moieties. Raw extract of Arizona cypress was further purified to isolate the bioactive phenols using dichloromethane-ethanol in a solvent-solvent system and precipitation with potassium acetate. The bioactivity of the hydrophilic extracts of Cupressus arizonica was determined and compared with the raw hydrophilic extractives of Cupressus sempervirens and Picea excelsa. The total phenol content was determined according to the folin-ciocalteu method. The antioxidant capacity was determined by iron (II) chelating activity and the 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging assay. From the GC/MS analysis, different amounts of bioactive moieties, including matairesinol (MAT), curcumin, dienestrol, arctigenin (ARC) and sescoisolariciresinol (SEC), were found in the extract of C. arizonica wood knots. Comparative evaluation of the total phenolics by folin-ciocalteu analysis showed that extraction by simple soaking could precisely indicate the quantity of phenolic compounds in the extracts. The antioxidant activity of extracts indicated by DPPH radical scavenging and iron (II) chelating capacity showed that the antioxidant activity is dependent on the amount and category of bioactive phenols in the extracts.
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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 it