<i>Candida albicans</i> Primes TLR Cytokine Responses through a Dectin-1/Raf-1–Mediated Pathway
Bibliographic record
Abstract
The immune system is essential to maintain homeostasis with resident microbial populations, ensuring that the symbiotic host-microbial relationship is maintained. In parallel, commensal microbes significantly shape mammalian immunity at the host mucosal surface, as well as systemically. Candida albicans is an opportunistic pathogen that lives as a commensal on skin and mucosa of healthy individuals. Little is known about its capacity to modulate responses toward other microorganisms, such as colonizing bacteria (e.g., intestinal microorganisms). The aim of this study was to assess the cytokine production of PBMCs induced by commensal bacteria when these cells were primed by C. albicans. We show that C. albicans and β-1,3-glucan induce priming of human primary mononuclear cells and this leads to enhanced cytokine production upon in vitro stimulation with TLR ligands and bacterial commensals. This priming requires the β-1,3-glucan receptor dectin-1 and the noncanonical Raf-1 pathway. In addition, although purified mannans cannot solely mediate the priming, the presence of mannosyl residues in the cell wall of C. albicans is nevertheless required. In conclusion, C. albicans is able to modify cytokine responses to TLR ligands and colonizing bacteria, which is likely to impact the inflammatory reaction during mucosal diseases.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".