Islet-infiltrating B-Cells in Nonobese Diabetic Mice Predominantly Target Nervous System Elements
Bibliographic record
Abstract
B-cells accumulate in pancreatic islets during the autoimmune response that precedes the onset of type 1 diabetes. However, the role and antigenic specificity of these cells remain a mystery. To elucidate the antigenic repertoire of islet-infiltrating B-cells in type 1 diabetes, we generated hybridoma cell lines of islet-infiltrating B-cells from nonobese diabetic (NOD) mice and NOD mice expressing a diabetogenic T-cell receptor (8.3-NOD). Surprisingly, characterization of the tissue specificity of the antibodies secreted by these cells revealed that a predominant fraction of these hybridomas produce antibodies specific for the pancreatic nervous system. Similar results were obtained with B-cell hybridomas derived from mild insulinic lesions of diabetes-resistant (NOD x NOR)F1 and 8.3-(NOD x NOR)F1 mice. Immunoglobulin class analyses further indicated that most islet-derived hybridomas had arisen from B-cells that had undergone immunoglobulin class switch recombination, suggesting that islet-associated B-cells are involved in active, T-helper-driven immune responses against local antigenic targets. This is the first evidence showing the existence of a predominant active B-cell response in situ against pancreatic nervous system elements in diabetogenesis. Our data are consistent with the idea that this B-cell response precedes the progression of insulitis to overt diabetes, thus strongly supporting the idea that pancreatic nervous system elements are early targets in 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 | 0.001 | 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) | 0.003 | 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".