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Record W2994647402 · doi:10.1128/mbio.02985-19

RIP1, RIP3, and MLKL Contribute to Cell Death Caused by Clostridium perfringens Enterotoxin

2019· article· en· W2994647402 on OpenAlexfundno aff
Archana Shrestha, Iman Mehdizadeh Gohari, Bruce A. McClane

Bibliographic record

VenuemBio · 2019
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsNecroptosisClostridium perfringensEnterotoxinProgrammed cell deathMicrobiologyApoptosisKinaseNecrosisVirulenceBiologyChemistryCell biologyBiochemistryEscherichia coliBacteriaGene

Abstract

fetched live from OpenAlex

C. perfringens type F strains are a common cause of food poisoning and antibiotic-associated diarrhea. Type F strain virulence requires production of C. perfringens enterotoxin (CPE). In Caco-2 cells, high CPE concentrations cause necrosis while low enterotoxin concentrations induce apoptosis. The current study determined that receptor-interacting serine/threonine-protein kinases 1 and 3 are involved in both CPE-induced apoptosis and necrosis in Caco-2 cells, while mixed-lineage kinase domain-like pseudokinase (MLKL) oligomerization is involved in CPE-induced necrosis, thereby indicating that this form of CPE-induced cell death involves necroptosis. High CPE concentrations also caused necroptosis in T84 and Vero cells. Calpain activation was identified as a key intermediate for CPE-induced necroptosis. These results suggest inhibitors of RIP1, RIP3, MLKL oligomerization, or calpain are useful therapeutics against CPE-mediated 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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.270
Teacher spread0.256 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations31
Published2019
Admission routes1
Has abstractyes

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