Hypergammaglobulinemia sustains the development of regulatory responses during chronic <i>Leishmania donovani</i> infection in mice
Bibliographic record
Abstract
Abstract Visceral leishmaniasis, a chronic, potentially fatal disease, is characterized by high production of low‐affinity antibodies. In humans, hypergammaglobulinemia is prediction of disease progression. Nevertheless, the contribution of hypermutated and/or class‐switched immunoglobulins to disease pathogenesis has never been studied. Using Aicda −/− mice and the experimental model of Leishmania donovani infection, we demonstrate that the absence of hypermutated and/or class‐switched antibodies was associated with increased resistance to disease, stronger protective Th1 responses, and a lower frequency of regulatory IFNγ + IL‐10 + CD4 T cells. Interestingly, stronger Th1 responses and the absence of IFNγ + IL‐10 + CD4 T cells during chronic infection in infected Aicda −/− mice were not caused by a T‐cell intrinsic effect of AID, but by changes in the cytokine environment during chronic disease. Indeed TNF, IL‐10 and IFN‐ß expressions were only upregulated in the presence of hypermutated, class‐switched antibodies and hypergammaglobulinemia at later stages of infection. Taken together, our results suggest that hypergammaglobulinemia sustains inhibitory responses during chronic visceral leishmaniasis.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".