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Record W4402827484 · doi:10.3390/cells13191606

A Novel Bioluminescent Biosensor Quantifying Intramolecular Interaction and Levels of Pyroptosis Effector GSDMD

2024· article· en· W4402827484 on OpenAlexafffund
Tynan Kelly, Simran K. Bhandari, Madeleine Carew, Rachel Rubino, Christopher J.B. Nicol, Xiaolong Yang

Bibliographic record

VenueCells · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammasome and immune disorders
Canadian institutionsQueen's University
FundersCanadian Cancer Society
KeywordsPyroptosisBiosensorProgrammed cell deathEffectorChemistryApoptosisComputational biologyBiologyBiochemistry

Abstract

fetched live from OpenAlex

Gasdermin D (GSDMD) is a key executor of pyroptosis, a form of inflammation-induced programmed cell death. Recently, GSDMD has been shown to play important roles in the development of various inflammatory-related human diseases including heart failure and cancer, suggesting that it is a promising therapeutic target for these diseases. While extensive studies on GSDMD's role in pyroptosis have been reported, it is challenging to study its function due to the lack of enzymatic activity of GSDMD. In this study, we used the NanoBiT technology to develop a novel GSDMD bioluminescent biosensor (GSDMD-BS) that detects the amount of non-cleaved GSDMD. This sensor allows us to quantify GSDMD's intramolecular interactions, the amounts of uncleaved GSDMD after caspase-1 cleavage, and expression levels in living cells. In vitro experiments using purified GSDMD-BS also confirmed the sensor's accuracy in reporting GSDMD levels and cleavage. Moreover, the potential for in vivo application was demonstrated in a xenograft mouse model. In conclusion, we have developed a GSDMD biosensor that is a valuable tool for real-time monitoring of GSDMD dynamics and pyroptosis. This biosensor will significantly expedite pyroptosis research and can be used for high-throughput screening for drugs targeting GSDMD for the therapy of many inflammation-related 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.015
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

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

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 head0.019
GPT teacher head0.268
Teacher spread0.249 · 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 teacher head, 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

Citations3
Published2024
Admission routes2
Has abstractyes

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