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Record W4223420165 · doi:10.1038/s41420-022-00998-3

Cell pyroptosis in health and inflammatory diseases

2022· article· en· W4223420165 on OpenAlexaff
Yongqi Wu, Jing Zhang, Sihui Yu, Yan Li, Jinrong Zhu, Kai Zhang, Rongxin Zhang

Bibliographic record

VenueCell Death Discovery · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammasome and immune disorders
Canadian institutionsToronto Metropolitan University
FundersNational Natural Science Foundation of China
KeywordsPyroptosisInflammationProinflammatory cytokineImmunologyMedicineCancerProgrammed cell deathMechanism (biology)InflammasomeBiologyApoptosis

Abstract

fetched live from OpenAlex

Inflammation is a defense mechanism that can protect the host against microbe invasion. A proper inflammatory response can maintain homeostasis, but continuous inflammation can cause many chronic inflammatory diseases. To properly treat inflammatory disorders, the molecular mechanisms underlying the development of inflammation need to be fully elucidated. Pyroptosis is an inflammation-related cell death program, that is different from other types of cell death. Pyroptosis plays crucial roles in host defense against infections through the release of proinflammatory cytokines and cell lysis. Accumulating evidence indicates that pyroptosis is associated with inflammatory diseases, such as arthritis, pneumonia, and colonitis. Furthermore, pyroptosis is also closely involved in cancers that develop as a result of inflammation, such as liver cancer, esophageal cancer, pancreatic cancer, and colon cancer. Here, we review the function and mechanism of pyroptosis in inflammatory disease development and provide a comprehensive description of the potential role of pyroptosis in inflammatory diseases.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.005
GPT teacher head0.205
Teacher spread0.201 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations111
Published2022
Admission routes1
Has abstractyes

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