CD11c+ cells are required for lymphocyte trafficking into previously infiltrated pancreatic islets during type 1 diabetes.
Bibliographic record
Abstract
Abstract Type 1 diabetes (T1D) is a largely T cell mediated autoimmune disease that destroys the beta cells of the pancreatic islets. Initiation of T1D requires T cell activation in the pancreatic lymph node, and then activated T cells must enter the islets to destroy beta cells. The requirements for lymphocyte entry into islets are not fully understood. We show that lymphocyte entry into previously infiltrated islets is dependent on CD11c+ cells in the islets. T cells and B cells transferred prior to CD11c+ cell depletion were able to enter the islets; whereas, short-term CD11c+ cell depletion rapidly prevented further entry. CD11c+ cells are highly efficient antigen presenters; however, entry into the islets was not reliant on antigen for either activated or naïve T cells. An alternative role for CD11c+ cells in lymphocyte entry into the islets is the production of chemokines and cytokines, which can have direct chemotactic effects on lymphocytes or can activate vascular endothelium. CD11c+ cells in the islets express high levels of CXCL9, a chemoattractant for T and B lymphocytes. CXCR3, the receptor for CXCL9, is present on both T and B lymphocytes in the islets. We hypothesize that CD11c+ cells facilitate lymphocyte recruitment to the islets through a combination of chemokine production and activation of the islet vascular endothelium. Chemokine and cytokine production by CD11c+ cells may be targeted therapeutically for the treatment of T1D to prevent T cell entry into remaining or transplanted islets.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".