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Record W2939723138 · doi:10.1002/eji.201847917

Hypergammaglobulinemia sustains the development of regulatory responses during chronic <i>Leishmania donovani</i> infection in mice

2019· article· en· W2939723138 on OpenAlexafffund
Sasha Silva‐Barrios, Simona Stäger

Bibliographic record

VenueEuropean Journal of Immunology · 2019
Typearticle
Languageen
FieldMedicine
TopicResearch on Leishmaniasis Studies
Canadian institutionsInstitut National de la Recherche Scientifique
FundersArmand-Frappier Foundation
KeywordsHypergammaglobulinemiaImmunologyBiologyAntibodyPathogenesisLeishmaniaChronic infectionLeishmania donovaniCytokineVisceral leishmaniasisVirologyLeishmaniasisImmune systemParasite hosting

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.791
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.264
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2019
Admission routes2
Has abstractyes

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