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Chronic inflammation: importance of NOD2 and NALP3 in interleukin-1β generation

2006· review· en· W2060198845 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinical & Experimental Immunology · 2006
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammasome and immune disorders
Canadian institutionsUniversity of Toronto
FundersAugustinus FondenHertz Foundation
KeywordsNALP3NOD2InflammasomeInflammationImmunologyImmune systemAutoimmunityMedicinePattern recognition receptorInterleukinBiologyCytokineInnate immune system

Abstract

fetched live from OpenAlex

Inflammation is part of the non-specific immune response that occurs in reaction to any type of bodily injury. In some disorders, the inflammatory process - which under normal conditions is self-limiting - becomes continuous and chronic inflammatory diseases might develop subsequently. Pattern recognition molecules (PRMs) represent a diverse collection of molecules responsible for sensing danger signals, and together with other immune components they are involved in the first line of defence. NALP3 and NOD2, which belong to a cytosolic subgroup of PRMs, dubbed Nod-like-receptors (NLRs), have been associated recently with inflammatory diseases, specifically Crohn's disease and Blau syndrome (NOD2) and familial cold autoinflammatory syndrome, Muckle-Wells syndrome and chronic infantile neurological cutaneous and articular syndrome (NALP3). The exact effects of the defective proteins are not fully understood, but activation of nuclear factor (NF)-kappaB, transcription, production and secretion of interleukin (IL)-1beta and activation of the inflammasome are some of the processes that might hold clues, and the present review will provide a thorough update in this area.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.969
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.046
GPT teacher head0.391
Teacher spread0.345 · 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