Candida albicans and Streptococcus salivarius modulate IL-6, IL-8, and TNF-alpha expression and secretion by engineered human oral mucosa cells
Bibliographic record
Abstract
We investigated the involvement of oral epithelial cells via two cytokines (IL-6 and TNF-alpha) and one chemokine (IL-8) in local defences against live yeast (Candida albicans) and bacteria (Streptococcus salivarius) using an engineered human oral mucosa model. We report that the yeast changed from the blastospore to the hyphal form and induced significant tissue disorganization at later contact periods (24 and 48 h) compared to the bacteria. However, this effect did not reduce the viability or total number of epithelial cells. Gene activation analyses revealed that IL-6, IL-8 and TNF-alpha mRNA levels rose in tissues in contact with live C. albicans or S. salivarius. Gene activation was followed by an upregulation of protein secretion. IL-6 levels were higher after contact with C. albicans than with S. salivarius. IL-8 levels after contact with S. salivarius were higher than with C. albicans. Our study suggests that S. salivarius is more efficient at inducing proinflammatory mediator release than C. albicans. These results provide additional evidence for the contribution of oral epithelial cells to the inflammatory response against fungi and bacteria.
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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".