Interleukin‐1 family cytokines at the crossroads of microbiome regulation in barrier health and disease
Bibliographic record
Abstract
Recent advances in understanding how the microbiome can influence both the physiology and the pathogenesis of disease in humans have highlighted the importance of gaining a deeper insight into the complexities of the host-microbial dialogue. In tandem with this progress, has been a greater understanding of the biological pathways which regulate both homeostasis and inflammation at barrier tissue sites, such as the skin and the gut. In this regard, the Interleukin-1 family of cytokines, which can be segregated into IL-1, IL-18 and IL-36 subfamilies, have emerged as important custodians of barrier health and immunity. With established roles as orchestrators of various inflammatory diseases in both the skin and intestine, it is now becoming clear that IL-1 family cytokine activity is not only directly influenced by external microbes, but can also play important roles in shaping the composition of the microbiome at barrier sites. This review explores the current knowledge surrounding the evidence that places these cytokines as key mediators at the interface between the microbiome and human health and disease at the skin and intestinal barrier tissues.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".