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Record W1517191359 · doi:10.4049/jimmunol.180.6.4082

Activation of Human NK Cells by the Bacterial Pathogen-Associated Molecular Pattern Muramyl Dipeptide

2008· article· en· W1517191359 on OpenAlexaff
Verónica Athié-Morales, Geraldine M. O’Connor, Clair M. Gardiner

Bibliographic record

VenueThe Journal of Immunology · 2008
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsTrinity College
Fundersnot available
KeywordsMuramyl dipeptideBiologyCell biologySecretionPathogenMicrobiologyImmunologyImmune systemBiochemistry

Abstract

fetched live from OpenAlex

Muramyl dipeptide (MDP) is a bacterial pathogen associated molecular pattern derived from both Gram-positive and -negative bacteria. It is a specific ligand for nuclear oligomerization domain 2, a pattern recognition receptor best characterized for its role in immunosurveillance in the gut. In this study, we demonstrate that human peripheral blood NK cells express nuclear oligomerization domain 2 and respond to MDP. NK cells naturally internalize MDP leading to direct cell activation, including signaling through NFkappaB: characterized by p50/p65 heterodimers at early stimulations times and sustained activation of p50 homodimers. Moreover, MDP synergizes with IFN-alpha and IL-12 to activate NK cells and stimulate IFN-gamma secretion, suggesting a role for accessory cells in induction of an optimal NK cell response. Although IL-12 costimulation leads to a greater IFN-gamma response by NK cells, higher levels of CD69 in response to MDP are induced in the presence of IFN-alpha, suggesting that different pathogen-induced cytokine profiles will affect downstream NK cell responses. In contrast, MDP alone or in combination with either IFN-alpha or IL-12 only poorly increases NK cell cytotoxicity. In summary, this report identifies MDP as a bacterial pathogen associated molecular pattern that activates human NK cells.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.004
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.010
GPT teacher head0.214
Teacher spread0.204 · 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.

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

Citations43
Published2008
Admission routes1
Has abstractyes

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