Lymphomagenesis, Hydronephrosis, and Autoantibodies Result from Dysregulation of IL-9 and Are Differentially Dependent on Th2 Cytokines
Bibliographic record
Abstract
Interleukin-9 is an immunoregulatory cytokine implicated in the development of asthma and allergy. To investigate the role of IL-9 in vivo, we have generated transgenic mice in which IL-9 is expressed from its own promoter. Strikingly, overexpression of IL-9 resulted in premature mortality associated with a complex phenotype characterized by the development of autoantibodies, hydronephrosis, and T cell lymphoma. By intercrossing IL-9 transgenic mice with a panel of Th2 cytokine-deficient mice, we demonstrate that these disorders represent distinct phenotypes that can be dissociated by their differential dependence on Th2 cytokines. Autoantibody production was ablated in IL-9 transgenic animals with a combined absence of IL-4, IL-5, and IL-13, coincident with a reduction in peritoneal B-1 cells. Hydronephrosis arose in 75% of IL-9 transgenic animals and was dependent on the presence of IL-4 and IL-13. In contrast, T cell lymphomas developed independently of the other Th2 cytokines, with the generation of rapidly proliferating CD8(+) or CD4(+)CD8(+) T cell clones that arose in the thymus before infiltrating both lymphoid and nonlymphoid tissues. Our data highlight potentially important new roles for IL-9, through its regulation of downstream Th2 effector cytokines, in autoantibody production and in hydronephrosis.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".