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Record W6993097268

Nod1 and Nod2 in Innate Immune Responses, Adaptive Immunity and Bacterial Infection

2009· dissertation· en· W6993097268 on OpenAlexfundno aff

Bibliographic record

VenueTSpace · 2009
Typedissertation
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchFondation pour la Recherche MédicaleHoward Hughes Medical Institute
KeywordsNOD1NOD2Pattern recognition receptorInnate immune systemAcquired immune systemReceptorImmune systemTLR4Nod
DOInot available

Abstract

fetched live from OpenAlex

The last decade has been witness to a number of seminal discoveries in the field of innate immunity. The discovery that microbial molecules and endogenous danger signals can be detected by germ-line encoded receptors has changed the way we study the immune system. Indeed, the characterization of Toll in Drosophila as a sensor of microbial products in 1997 then led to the discovery of a family of Toll Like Receptors (TLRs) in mammals. TLRs are critical for the induction of inflammatory responses and the generation of a successful adaptive immune response. The array of ligands that these transmembrane proteins recognized mediates defense against bacteria, viruses, fungus and parasites, as well as, possibly, cancerous cells. In addition to this membrane-bound family of recognition proteins, two families of pattern recognition receptors have been recently shown to respond to microbial and chemical ligands within the cytosol. These represent the Nod Like Receptors (NLRs) and RIGI-like helicase receptor (RLH) families. Nod1 and Nod2 are members of the NLR family of proteins, which are responsible for the recognition of components derived from the bacterial cell wall, more precisely, moieties of peptidoglycan. As such, Nod1 and Nod2 are implicated in the recognition and the defense against bacterial pathogens. Importantly, the genes encoding these two proteins have also been linked to the etiology of several inflammatory disorders such as Crohn’s disease and asthma. In this thesis, we show that recognition of Nod1 and Nod2 ligands generates a rapid and transient inflammatory response in vivo. When co-injected with a model protein, Nod1 and Nod2 ligands exhibit adjuvant properties that lead to the generation of an antigen-specific Th2 type adaptive immune response. Surprisingly, recognition of the Nod1 ligand in non-hematopoietic cells is critical for the generation of this immune response. In contrast, TLRs classically tip the balance towards a Th1 response and interestingly, co-injection of TLR and Nod ligands synergize to generate a more potent immune response characterized by the generation of Th1, Th2 and Th17 T cell respones. To study the role of Nod1 and Nod2 in the context of a bacterial infection in vivo, we used an intestinal mouse pathogen, Salmonella enterica serovar Typhimurium. We were able to show that Nod1-deficient mice, but not Nod2-deficient mice, are more susceptible to the strain of this bacterium, which enters the host through the active pickup in the intestinal lumen by underlying myeloid cells. This sampling mechanism is mediated by a subset of dendritic cells that populate the intestinal lamina propria. Accordingly, the defect seen in Nod1-deficient mice localizes to the mucosal barrier where these dendritic cells appear to have an impaired response towards the bacteria. Taken together, these results increase our knowledge on the general role of Nod1 and Nod2 in immunity and might generate new avenues of research and potential therapeutic targets.

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: Other · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.011
GPT teacher head0.286
Teacher spread0.274 · 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
GenreOther

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

Citations0
Published2009
Admission routes1
Has abstractyes

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