Faculty Opinions recommendation of The NALP3 inflammasome is involved in the innate immune response to amyloid-beta.
Bibliographic record
Abstract
The fibrillar peptide amyloid-beta (A beta) has a chief function in the pathogenesis of Alzheimer's disease. Interleukin 1 beta (IL-1 beta) is a key cytokine in the inflammatory response to A beta. Insoluble materials such as crystals activate the inflammasome formed by the cytoplasmic receptor NALP3, which results in the release of IL-1 beta. Here we identify the NALP3 inflammasome as a sensor of A beta in a process involving the phagocytosis of A beta and subsequent lysosomal damage and release of cathepsin B. Furthermore, the IL-1 beta pathway was essential for the microglial synthesis of proinflammatory and neurotoxic factors, and the inflammasome, caspase-1 and IL-1 beta were critical for the recruitment of microglia to exogenous A beta in the brain. Our findings suggest that activation of the NALP3 inflammasome is important for inflammation and tissue damage in Alzheimer's disease. PMID: 18604209 Funding information This work was supported by: NIA NIH HHS, United States Grant ID: AG20255 NIA NIH HHS, United States Grant ID: R01 AG020255-06A1 NIA NIH HHS, United States Grant ID: R01 AG020255 NIAID NIH HHS, United States Grant ID: R01 AI065483 NIGMS NIH HHS, United States Grant ID: R37 GM054060 NIGMS NIH HHS, United States Grant ID: R01 GM054060 NIAID NIH HHS, United States Grant ID: AI065483 NIGMS NIH HHS, United States Grant ID: GM54060 More Less keyboard_arrow_down
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.068 | 0.046 |
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".