Inhibition of Candida albicans biofilm formation and modulation of gene expression by probiotic cells and supernatant
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Oral candidiasis is a disease caused by opportunistic species of Candida that normally reside on human mucosal surfaces. The transition of Candida from budding yeast to filamentous hyphae allows for covalent attachment to oral epithelial cells, followed by biofilm formation, invasion and tissue damage. In this study, combinations of Lactobacillus plantarum SD5870, Lactobacillus helveticus CBS N116411 and Streptococcus salivarius DSM 14685 were assessed for their ability to inhibit the formation of and disrupt Candida albicans biofilms. Co-incubation with probiotic supernatants under hyphae-inducing conditions reduced C. albicans biofilm formation by >75 % in all treatment groups. Likewise, combinations of live probiotics reduced biofilm formation of C. albicans by >67 %. When live probiotics or their supernatants were overlaid on preformed C. albicans biofilms, biofilm size was reduced by >63 and >65 % respectively. Quantitative real-time PCR results indicated that the combined supernatants of SD5870 and CBS N116411 significantly reduced the expression of several C. albicans genes involved in the yeast-hyphae transition: ALS3 (adhesin/invasin) by 70 % (P < 0.0001), EFG1 (hyphae-specific gene activator) by 47 % (P = 0.0061), SAP5 (secreted protease) by 49 % (P < 0.0001) and HWP1 (hyphal wall protein critical to biofilm formation) by >99 % (P < 0.0001). These findings suggest the combination of L. plantarum SD5870, L. helveticus CBS N116411 and S. salivarius DSM 14685 is effective at both preventing the formation of and removing preformed C. albicans biofilms. Our novel results point to the downregulation of several Candida genes critical to the yeast-hyphae transition, biofilm formation, tissue invasion and cellular damage.
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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