Identification and Bioactivities of IFN-γ in Rainbow Trout <i>Oncorhynchus mykiss</i> : The First Th1-Type Cytokine Characterized Functionally in Fish
Bibliographic record
Abstract
IFN-gamma is one of the key cytokines in defining Th1 immune responses. In this study, an IFN-gamma homologue has been identified in rainbow trout Oncorhynchus mykiss, and its biological activities have been characterized. The trout IFN-gamma cDNA is 1034 bp in length and translates into a 180-aa protein. The first intron of the trout IFN-gamma gene contains highly polymorphic GACA minisatellites and 44-bp DNA repeats, giving rise to at least six alleles. IFN-gamma is structurally conserved among vertebrates, and a signature motif has been identified. A nuclear localization sequence known to be crucial for IFN-gamma biological activities is also present in the C-terminal region of the trout IFN-gamma. The IFN-gamma expression was induced in head kidney leukocytes by stimulation with PHA or poly(I:C) and in kidney and spleen of fish injected with poly(I:C). rIFN-gamma produced in Escherichia coli significantly stimulated gene expression of IFN-gamma-inducible protein 10 (gammaIP-10), MHC class II beta-chain, and STAT1, and enhanced respiratory burst activity in macrophages. Deletion of 29-aa residues from the C terminus containing the nuclear localization sequence motif resulted in loss of activity with respect to induction of gammaIP-10 in RTS-11 cells. Moreover, IFN-gamma-induced gammaIP-10 expression was completely abolished by the protein kinase C inhibitor staurosporine, and partially reduced by U0126, a specific inhibitor for ERKs. Taken together, the present study has demonstrated for the first time a functional IFN-gamma homologue in a fish species, strongly suggesting a conserved Th1 immune response is most likely present in lower vertebrates.
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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) | 0.000 | 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".