<scp>CD</scp>8α<sup>−</sup><scp>DC</scp> is the major <scp>DC</scp> subset which mediates inhibition of allergic responses by <i><scp>S</scp>chistosoma</i> infection
Why this work is in the frame
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Bibliographic record
Abstract
Our and others' previous studies have shown that Schistosoma japonicum (SJ) infection can inhibit allergic reactions. We recently reported that DCs played an important role in SJ infection-mediated inhibition of allergy, which was associated with enhanced IL-10 and T regulatory cell responses. Here, we further compared the role of CD8α(+) DC and CD8α(-) DC subsets for the inhibitory effect. We sorted CD8α(+) DC (SJCD8α(+) DC) and CD8α(-) DC (SJCD8α(-) DC) from SJ-infected mice and tested their ability to modulate allergic responses in vivo. The data showed that the adoptive transfer of SJCD8α(-) DC was much more efficient than SJCD8α(+) DC for the suppression of allergic airway eosinophilia, mucus overproduction, antigen-specific IgE responses, and Th2 cytokines (IL-4 and IL-5). More importantly, we found that the transfer of SJCD8α(-) DC, but not SJCD8α(+) DC, significantly increased IL-10 and TGF-β production following OVA exposure. As control, the transfer of DC subsets from naïve mice had no significant effect on allergic inflammation. In addition, SJCD8α-DC expressed significantly higher IL-10 but lower IL-12, CD80 and CD86 than SJCD8α(+) DC, fitting a tolerogenic phenotype. The results suggest that CD8α(-) DC is the predominant DC subset which is involved in the parasitic infection-mediated inhibition of allergic inflammation and possibly through enhancing immunomodulatory cytokine (IL-10 and TGF-β) production.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.007 |
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