Neutralization of Interleukin-16 Protects Nonobese Diabetic Mice From Autoimmune Type 1 Diabetes by a CCL4-Dependent Mechanism
Bibliographic record
Abstract
OBJECTIVE: The progressive infiltration of pancreatic islets by lymphocytes is mandatory for development of autoimmune type 1 diabetes. This inflammatory process is mediated by several mediators that are potential therapeutic targets to arrest development of type 1 diabetes. In this study, we investigate the role of one of these mediators, interleukin-16 (IL-16), in the pathogenesis of type 1 diabetes in NOD mice. RESEARCH DESIGN AND METHODS: At different stages of progression of type 1 diabetes, we characterized IL-16 in islets using GEArray technology and immunoblot analysis and also quantitated IL-16 activity in cell migration assays. IL-16 expression was localized in islets by immunofluorescence and confocal imaging. In vivo neutralization studies were performed to assess the role of IL-16 in the pathogenesis of type 1 diabetes. RESULTS: The increased expression of IL-16 in islets correlated with the development of invasive insulitis. IL-16 immunoreactivity was found in islet infiltrating T-cells, B-cells, NK-cells, and dendritic cells, and within an insulitic lesion, IL-16 was derived from infiltrating cells. CD4(+) and CD8(+) T-cells as well as B220(+) B-cells were identified as sources of secreted IL-16. Blockade of IL-16 in vivo protected against type 1 diabetes by interfering with recruitment of CD4(+) T-cells to the pancreas, and this protection required the activity of the chemokine CCL4. CONCLUSIONS: IL-16 production by leukocytes in islets augments the severity of insulitis during the onset of type 1 diabetes. IL-16 and CCL4 appear to function as counterregulatory proteins during disease development. Neutralization of IL-16 may represent a novel therapy for the prevention of type 1 diabetes.
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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) | 0.002 | 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".