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Record W2609320377 · doi:10.7554/elife.23481

IL17 factors are early regulators in the gut epithelium during inflammatory response to Vibrio in the sea urchin larva

2017· article· en· W2609320377 on OpenAlexafffund
Katherine M. Buckley, Eric Ho, Taku Hibino, Catherine S. Schrankel, Nicholas W. Schuh, Guizhi Wang, Jonathan P. Rast

Bibliographic record

VenueeLife · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicInvertebrate Immune Response Mechanisms
Canadian institutionsSunnybrook HospitalUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsBiologySubfamilySea urchinImmune systemIntestinal epitheliumCell biologyGeneEpitheliumMicrobiologyImmunologyGenetics

Abstract

fetched live from OpenAlex

IL17 cytokines are central mediators of mammalian immunity. In vertebrates, these factors derive from diverse cellular sources. Sea urchins share a molecular heritage with chordates that includes the IL17 system. Here, we characterize the role of epithelial expression of IL17 in the larval gut-associated immune response. The purple sea urchin genome encodes 10 IL17 subfamilies (35 genes) and 2 IL17 receptors. Most of these subfamilies are conserved throughout echinoderms. Two IL17 subfamilies are sequentially strongly upregulated and attenuated in the gut epithelium in response to bacterial disturbance. IL17R1 signal perturbation results in reduced expression of several response genes including an IL17 subtype, indicating a potential feedback. A third IL17 subfamily is activated in adult immune cells indicating that expression in immune cells and epithelia is divided among families. The larva provides a tractable model to investigate the regulation and consequences of gut epithelial IL17 expression across the organism.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.014
GPT teacher head0.244
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations74
Published2017
Admission routes2
Has abstractyes

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