Suppression of Streptococcus mutans and Candida albicans by Probiotics:an In vitro Study
Bibliographic record
Abstract
Oral infections caused by microorganisms have led to increased risk of oral health problems such as Dental Caries (DC), periodontitis and Oral Candidiasis (OC).Streptococcus mutans and Candida albicans are the primary organisms responsible for DC and OC, respectively.The goal of the presented study was to investigate the potential of probiotics to prevent and treat DC and OC.An in vitro assay was developed to investigate several probiotic strains for their ability to inhibit the aforementioned oral pathogens.Probiotic by-products present in probiotic supernatant and live probiotic cells were both investigated for their ability to inhibit the growth of S. mutans and C. albicans.The probiotic strains investigated were L. reuteri NCIMB 701359, L. reuteri NCIMB 701089, L. reuteri NCIMB 11951, L. reuteri NCIMB 702656, L. reuteri NCIMB 702655, L. fermentum NCIMB 5221, L. fermentum NCIMB 2797, L. fermentum NCIMB 8829, L. acidophilus ATCC 314, L. plantarum ATCC 14917 and L. rhamnosus ATCC 5310.The presented research demonstrates that live probiotic cells are needed to inhibit oral pathogens, as cell-free supernatant could not inhibit the pathogens.Further experiments were performed to investigate and optimize the dose-dependent inhibition of the pathogens by live probiotic cells.As desired, an increased inhibition was observed with an increase in dose, as demonstrated by the increasing size of the zones of clearance.In addition, the observed inhibition was dependent on the strain of the probiotic used.This research implies that probiotic bacteria are capable of inhibiting the selected oral pathogens, S. mutans and C. albicans, holding promise for the future development of a probiotic therapeutic to treat and prevent oral/dental diseases.Furthermore, the research proposes further investigations into the probiotic mechanism(s) of action and efficacy for the development of an optimal therapy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".