Epithelial expression of IL-17 mediates a gut-associated inflammatory response in the purple sea urchin larva.
Bibliographic record
Abstract
Abstract Immune response to microbial disturbance in the gut involves coordinated activity of gut epithelial cells, motile immune cells and other cells throughout the organism. Many of these functions are ancient among bilaterians, although it is not yet clear how they relate among animal phyla. As morphologically simple organisms that share an important genetic heritage with vertebrates, sea urchin larvae offer a novel, experimentally tractable system in which to characterize the gut-associated immune response. We have developed a model to characterize gene regulatory control of this response using the marine bacterium Vibrio diazotrophicus. When exposed to Vibrio in the surrounding seawater, bacteria accumulate in the gut and later invade the body cavity. Bacteria that enter the blastocoel are rapidly cleared by a coordinated response of phagocytic and granular immune cells. Peripheral immune cells migrate through the body cavity and accumulate at the gut. RNA-Seq data indicate that the most acutely upregulated gene in the early phase of response are two types of IL17 genes. Whole mount in situ hybridization and BAC-based fluorescent protein reporters indicate that these genes are expressed within gut epithelial cells. Notably, perturbation of IL17 receptor signaling results in reduced levels of tnfaip3 (a negative feedback inhibitor of IL17), nfkbiz (an IL17 target gene in vertebrates), the transcription factors cebpα and cebpγ and soul1 (SOUL domains are evolutionarily widespread and involved in immune responses). These results indicate that the highly regulated IL17 expression in the gut epithelium and signaling through IL17R1 form a central axis of larval gut-associated immunity.
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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) | 0.002 | 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".