Nod‐like proteins in inflammation and disease
Bibliographic record
Abstract
The field of innate immunity has undergone an enormous upheaval during the last decade. The discovery of different groups of proteins, called pattern recognition molecules (PRMs), which detect microbial components, so-called pathogen-associated molecular patterns (PAMPs) and trigger protective responses, had a huge impact on the understanding of innate immune responses. Among the PRMs, the intracellular Nod-like receptors (NLRs) have recently been identified as key mediators of inflammatory and immune responses. The NLR family is divided into subfamilies on the basis of their different signal transduction domains, and recent studies have highlighted the role of certain NLRs, including Nod1, Nod2, Nalp3, Ipaf and Naip5, in the detection of intracellular microbes and possibly 'danger signals'. In this review, we summarize the current knowledge on the function of these proteins in immunity and inflammation, with a focus on their participation in different disease pathologies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".