Th17 Polarized Cells from Nonobese Diabetic Mice Following Mycobacterial Adjuvant Immunotherapy Delay Type 1 Diabetes
Bibliographic record
Abstract
IL-17-producing T cells are regarded as potential pathogenic T cells in the induction of autoimmune diseases. Previously, we have shown that injection of adjuvants containing Mycobacterium, such as CFA or bacillus Calmette-Guérin, can prevent type 1 diabetes in NOD mice. We injected NOD mice with mycobacterial products s.c. and analyzed the IL-17-producing cells from the draining lymph nodes and spleen by restimulating whole-cell populations or CD4(+) T cells in vitro with or without IL-17-polarizing cytokines. Mice receiving CFA had a concomitant rise in the level of IL-17, IL-22, IL-10, and IFN-gamma in the draining lymph node and spleen. Adoptive transfer of splenocytes from CFA-injected NOD mice polarized with TGF-beta plus IL-6 or IL-23 delayed the development of diabetes in recipient mice. IL-17-producing cells induced by CFA maintained their IL-17-producing ability in the recipient mice. Injection of CFA also changed the cytokine profile of cells in pancreatic tissue by increasing IL-17, IL-10, and IFN-gamma cytokine gene expression. We suggest that the rise in the level of IL-17 after adjuvant therapy in NOD mice has a protective effect on type 1 diabetes development.
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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 | 0.002 |
| 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".