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Record W2102460036 · doi:10.4049/jimmunol.1301136

CD4+CD25+Foxp3+ Regulatory T Cells Promote Th17 Responses and Genital Tract Inflammation upon Intracellular <i>Chlamydia muridarum</i> Infection

2013· article· en· W2102460036 on OpenAlexafffund
Jessica Moore-Connors, Robert Fraser, Scott A. Halperin, Jun Wang

Bibliographic record

VenueThe Journal of Immunology · 2013
Typearticle
Languageen
FieldImmunology and Microbiology
TopicReproductive tract infections research
Canadian institutionsNova Scotia Health AuthorityIzaak Walton Killam Health CentreDalhousie University
FundersCanadian Institutes of Health ResearchCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsFOXP3ChlamydiaImmunologyIL-2 receptorImmune systemInflammationBiologyProinflammatory cytokineRegulatory T cellT cell

Abstract

fetched live from OpenAlex

The functional role of CD4⁺CD25⁺Foxp3⁺ regulatory T cells (Tregs) in host responses to intracellular bacterial infection was investigated in an in vitro coculturing system and a murine model of Chlamydia muridarum genital tract infection. Remarkably, C. muridarum infection subverted the immune suppressive role of CD4⁺CD25⁺Foxp3⁺ Tregs; instead of hampering immune responses, Tregs not only promoted Th17 differentiation from conventional CD4⁺ T cells but also themselves converted into proinflammatory Th17 cells in both in vitro and in vivo settings. Anti-CD25 mAb PC61 treatment to deplete ∼50% of pre-existing Tregs prior to C. muridarum genital tract infection markedly reduced the frequency and the total number of Th17 but not Th1 CD4⁺ cells at both immune induction and memory phases. Most importantly, Treg-depleted mice displayed significantly attenuated inflammation, neutrophil infiltration, and reduced severity of oviduct pathology upon C. muridarum genital infection. To our knowledge, this is the first report demonstrating that the level of pre-existing CD4⁺CD25⁺Foxp3⁺ Tregs in Chlamydia-infected hosts has a major impact on the development Chlamydia-associated diseases.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.179
Threshold uncertainty score0.889

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.010
GPT teacher head0.239
Teacher spread0.229 · 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 designBench or experimental
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

Citations44
Published2013
Admission routes2
Has abstractyes

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