Bacterial suppression of intestinal fungi via activation of human gut γδ T-cells
Bibliographic record
Abstract
Abstract Gut symbionts condition mucosal immunity to resist infection by enteropathogens, but the specific microbes and mechanisms involved differ significantly between host species. In higher primates, bacterial metabolite HMB-PP is sensed by a specialized population of Vγ9Vδ2+T-cells, which we now report can potently suppress growth of endogenous fungi in human intestinal organ cultures. In healthy intestine, HMB-PP-stimulated Vδ2+T-cells restricted outgrowth of keystone fungus Candida albicans via a mechanism that required IL-22. In contrast, Crohn’s disease (CD) patients with reduced Vδ2+T-cell numbers displayed outgrowth of C. albicans strains that readily formed toxin-producing filaments, triggered neutrophil extracellular traps, and induced macrophage IL-1β release ex vivo . Genomic and proteomic analysis of the Candida isolates suggested increased tissue adhesion of CD-derived strains, which rapidly invaded the gut barrier in an ‘intestine-on-a-chip’ model. These data reveal that bacterial activation of Vδ2+T-cells suppresses fungal pathobionts in human gut via an IL-22-dependent mechanism that is dysregulated in CD.
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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) | 0.004 | 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".