High Performance Liquid Chromatography (HPLC) Profiling Analysis and Bioactivity of Baeckea frutescens L. (Myrtaceae)
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Bibliographic record
Abstract
Leaves of Baeckea frutescens were extracted by methanol, and then were subjected to chemical compound analysis through qualitative High Performance Liquid Chromatography (HPLC) profiling, bioactivity property. The total weight of B. frutescens leaves crude extract obtained was 2.532 g from 10 g of initial weight. The HPLC profiling used three solvents that are, Methanol, Acetonitrile and water. The profile spectrums from HPLC showed a few peaks that represent the chemicals that lie in the methanolic extract especially in methanol. The results from HPLC crude extract profile for leaves extract of B. frutescens showed many peaks at the retention time between 0 to 60 minutes. This showed that a lot of compounds have already been flushed out based on time and polarity range of the solvents. The two types of bioactivity study are antibacterial and cytotoxicity assay. In antibacterial assay, six pathogenic bacteria, were selected and used by using agar well diffusion method. All methanolic extract did not show any antibacterial activity or was not effective at all concentrations of 12.5-100 mg/µL. As a result, methanolic extract was not subjected to broth dilution method for the quantitative measurement of the microbiostatic (inhibitory). In cytotoxic assay the cell line used was HL- 60 that were treated with B. frutescens methanolic extract to evaluate the IC50 value, that is, which concentration of test compounds that cause 50 % inhibition or cell death. It is to compare the cytotoxic effect with 3T3 which acted as a control. B. frutescens methanolic extract is not effective for normal cell line. The methanolic extract of B. frutescens was cytotoxic to HL-60.Their IC50 of the crude extracts was moderate 21µg/ml.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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