Synthesis of benzoyl esters of β-amyrin and lupeol and evaluation of their antibiofilm and antidiabetic activities
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Bibliographic record
Abstract
Diabetes as well as the enhanced microbial multidrug resistance resulting from biofilm formation, constitutes some of the major health problems around the world. Triterpenoids and their derivatives have been shown to have a great contribution in this domain. A small library of benzoyl esters of lupeol and β-amyrin was synthesized and their structures were characterized by electronic ionization mass spectrometry (EIMS). Their inhibitory potential on pathogenic bacteria biofilms, as well as their inhibitory action on α-amylase and β-glucosidase activities were evaluated. The mass fragmentation patterns from the EIMS data confirm the success of the reactions. The minimal inhibitory concentrations (MIC) varied from 250 to 1000 µg/mL in the antimicrobial activities. Biofilm inhibitory potential of the compounds on S. aureus, E. coli and C. albicans were performed at MIC and sub-MIC concentrations and the results showed concentration-dependent inhibition of biofilms. At MIC, the highest biofilm inhibition was exhibited by compound 7 on S. aureus (60.8 ± 3.2%), compound 3 on E. coli (60.5 ± 2.8%) and compound 8 on C. albicans (56.9 ± 2.5%). For all tested compounds, percentage inhibition of violacein production was 100% at MIC except for the starting compounds 1 and 2. At 24.24 µg/mL the percentage of inhibition varied from 22.9 ± 1.2% to 42.1 ± 1.0% for α-amylase inhibition and at a concentration of 10 µg/mL the percentage of inhibition varied from 49.8 ± 0.3% to 69.3 ± 1.0% for β-glucosidase inhibition. The highest inhibition was shown by compounds 7 and 8 on α-amylase and β-glucosidase assays, respectively. The results show that introduction of benzoyl ester groups at C-3 of lupeol and β-amyrin considerably improves their antibiofilm and antidiabetic potentials.
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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) | 0.000 | 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