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Peptidoglycan: a critical activator of the mammalian immune system during infection and homeostasis

2011· review· en· W2131966979 on OpenAlexaff
Matthew T. Sorbara, Dana J. Philpott

Bibliographic record

VenueImmunological Reviews · 2011
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPeptidoglycanBiologyImmune systemNOD1MicrobiologyCell biologyInnate immune systemCell wallNOD2ImmunologyGenetics

Abstract

fetched live from OpenAlex

Peptidoglycan is a conserved structural component of the bacterial cell wall with molecular motifs unique to bacteria. The mammalian immune system takes advantage of these properties and has evolved to recognize this microbial associated molecular pattern. Mammals have four secreted peptidoglycan recognition proteins, PGLYRP-1-4, as well as two intracellular sensors of peptidoglycan, Nod1 and Nod2. Recognition of peptidoglycan is important in initiating and shaping the immune response under both homeostatic and infection conditions. During infection, peptidoglycan recognition drives both cell-autonomous and whole-organism defense responses. Here, we examine recent advances in the understanding of how peptidoglycan recognition shapes mammalian immune responses in these diverse contexts.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.003

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 head0.053
GPT teacher head0.307
Teacher spread0.254 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations134
Published2011
Admission routes1
Has abstractyes

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