Regulation of NLRPs by reactive oxygen species: A story of crosstalk
Bibliographic record
Abstract
The nucleotide oligomerization domain (NOD)-like receptors containing pyrin (NLRP) family of cytosolic pattern-recognition receptors play an integral role in host defense following exposure to a diverse set of pathogenic and sterile threats. The canonical event following ligand recognition is the formation of a heterooligomeric signaling complex termed the inflammasome that produces pro-inflammatory cytokines. Dysregulation of this process is associated with many autoimmune, cardiovascular, metabolic, and neurodegenerative diseases. Despite the range of activating stimuli which affect varied cell types, recent literature makes evident that reactive oxygen species (ROS) are integral to the initiation and propagation of inflammasome signaling. Notably, ROS production and inflammasome activation act in a positive feedback loop to promote this potent immune response. While NLRP3 is by far the most extensively studied NLRP, there is also sufficient literature to make these conclusions for other NLRPs family members. In all cases, a knowledge gap exists regarding the molecular targets and effects of ROS. Future research to define these targets and to parse the order and timing of ROS-mediated NLRP activation will provide meaningful insights into inflammasome biology. This will create novel therapeutic opportunities for the numerous illnesses that are impacted by inflammasome activity.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.007 | 0.018 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".