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Pyroptosis: host cell death and inflammation
Open accessAbstract
Eukaryotic cells can initiate several distinct programmes of self-destruction, and the nature of the cell death process (non-inflammatory or proinflammatory) instructs responses of neighbouring cells, which in turn dictates important systemic physiological outcomes. Pyroptosis, or caspase 1-dependent cell death, is inherently inflammatory, is triggered by various pathological stimuli, such as stroke, heart attack or cancer, and is crucial for controlling microbial infections. Pathogens have evolved mechanisms to inhibit pyroptosis, enhancing their ability to persist and cause disease. Ultimately, there is a competition between host and pathogen to regulate pyroptosis, and the outcome dictates life or death of the host.
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Metadata
- Authors
- Bergsbaken, T., Fink, S. L., & Cookson, B. T.
- Venue
- Nature Reviews Microbiology
- Published
- 2009-02
- Volume
- 7
- Issue
- 2
- Pages
- 99-109
- ISSN
- 1740-1526 (ISSN-L)
- 1740-1534
- OpenAlex
- W1985970823
- Cited by
- 3,183
- References
- 15
- FWCI
- 3.81
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.