Antimicrobial actions of α-mangostin against oral streptococci
Bibliographic record
Abstract
The increasing prevalence of dental caries is making it more of a major world health problem. Caries is the direct result of acid production by cariogenic oral bacteria, especially Streptococcus mutans. New and better antimicrobial agents active against cariogenic bacteria are badly needed, especially natural agents derived directly from plants. We have evaluated the inhibitory actions of α-mangostin, a xanthone purified from ethanolic extracts of the tropical plant Garcinia mangostana L., by repeated silica gel chromatography. α-Mangostin was found to be a potent inhibitor of acid production by S. mutans UA159, active against membrane enzymes, including the F(H+)-ATPase and the phosphoenolpyruvate - sugar phosphotransferase system. α-Mangostin also inhibited the glycolytic enzymes aldolase, glyceraldehyde-3-phosphate dehydrogenase, and lactic dehydrogenase. Glycolysis by intact cells in suspensions or biofilms was inhibited by α-mangostin at concentrations of 12 and 120 µmol·L⁻¹, respectively, in a pH-dependent manner, with greater potency at lower pH values. Other targets for inhibition by α-mangostin included (i) malolactic fermentation, involved in alkali production from malate, and (ii) NADH oxidase, the major respiratory enzyme for S. mutans. The overall conclusion is that α-mangostin is a multitarget inhibitor of mutans streptococci and may be useful as an anticaries agent.
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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 | 0.000 | 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) | 0.001 | 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".