Regulation of contact sensitivity in non‐obese diabetic (NOD) mice by innate immunity
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Bibliographic record
Abstract
Background Genetic background influences allergic immune responses to environmental stimuli. Non‐obese diabetic (NOD) mice are highly susceptible to environmental stimuli. Little is known about the interaction of autoimmune genetic factors with innate immunity in allergies, especially skin hypersensitivity. Objectives To study the interplay of innate immunity and autoimmune genetic factors in contact hypersensitivity (CHS) by using various innate immunity‐deficient NOD mice. Methods Toll‐like receptor (TLR) 2‐deficient, TLR9‐deficient and MyD88‐deficient NOD mice were used to investigate CHS. The cellular mechanism was determined by flow cytometry in vitro and adoptive cell transfer in vivo. To investigate the role of MyD88 in dendritic cells (DCs) in CHS, we also used CD11c MyD88+ MyD88 −/− NOD mice, in which MyD88 is expressed only in CD11c + cells . Results We found that innate immunity negatively regulates CHS, as innate immunity‐deficient NOD mice developed exacerbated CHS accompanied by increased numbers of skin‐migrating CD11c + DCs expressing higher levels of major histocompatibility complex II and CD80. Moreover, MyD88 −/− NOD mice had increased numbers of CD11c + CD207 − CD103 + DCs and activated T effector cells in the skin‐draining lymph nodes. Strikingly, re‐expression of MyD88 in CD11c + DCs (CD11c MyD88+ MyD88 −/− NOD mice) restored hyper‐CHS to a normal level in MyD88 −/− NOD mice. Conclusion Our results suggest that the autoimmune‐prone NOD genetic background aggravates CHS regulated by innate immunity, through DCs and T effector cells.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it