MétaCan
Menu
Back to cohort
Record W2112663666 · doi:10.1093/infdis/jir276

A Modulatory Interleukin-10 Response to Staphylococcal Peptidoglycan Prevents Th1/Th17 Adaptive Immunity to Staphylococcus aureus

2011· article· en· W2112663666 on OpenAlexafffund
Vanessa Frodermann, Thu Chau, Samar Sayedyahossein, Judit Toth, David E. Heinrichs, Joaquı́n Madrenas

Bibliographic record

VenueThe Journal of Infectious Diseases · 2011
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsWestern University
FundersCanadian Institutes of Health Research
KeywordsStaphylococcus aureusPeptidoglycanMicrobiologyImmunityAcquired immune systemStaphylococcal infectionsImmunologyImmune systemInterleukinBiologyChemistryCytokineBacteria

Abstract

fetched live from OpenAlex

Toll-like receptor (TLR) 2 on antigen-presenting cells (APCs) enables these cells to recognize peptidoglycan-embedded lipopeptides and glycopolymers in the Staphylococcus aureus cell wall and mount an inflammatory response to this microbe. TLR2 signalling can also modulate immunity to S. aureus by inducing an interleukin (IL)-10 response in APCs. What determines the balance between proinflammatory and modulatory responses to S. aureus is unknown. We show that the modulatory IL-10 response preferentially occurs upon CD14- and CD36-independent TLR2 signaling, triggering PI3K activation, and is restricted to monocytes and monocyte-derived macrophages (MΦs). In contrast, monocyte-derived dendritic cells (DCs) produce mostly IL-12 and IL-23. The differential APC polarization induced by staphylococcal peptidoglycan translates into differential T helper responses: MΦs primarily trigger IL-10 and weak IL-17 responses, whereas DCs trigger a robust Th1/Th17 response. Exploitation of TLR2 signalling plasticity by S. aureus may explain the wide range of outcomes of human encounters with this microbe.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.001

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 head0.015
GPT teacher head0.240
Teacher spread0.225 · 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 source (direct Gemma or distilled Codex), 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

Citations98
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of Infectious DiseasesSame topicImmune Response and InflammationFrench-language works237,207