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Record W4403721623 · doi:10.1101/2024.10.23.619800

NINJ1 is activated by calcium-driven plasma membrane lipid scrambling during lytic cell death

2024· preprint· en· W4403721623 on OpenAlexaff
Jazlyn P. Borges, Liron David, Allen Volchuk, Brenda Carla Rosendo Martins, Ruiqi Cai, Hao Wu, Spencer A. Freeman, Neil M. Goldenberg, Michael W. Salter, Benjamin E. Steinberg

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsScramblingLytic cycleCalciumMembraneCell biologyChemistryProgrammed cell deathBiophysicsApoptosisBiochemistryBiologyVirologyComputer scienceVirus

Abstract

fetched live from OpenAlex

Abstract NINJ1 is the terminal executioner of cellular rupture in multiple lytic cell death pathways through its clustering in the plasma membrane. Its activation trigger, however, remains unknown. We found that NINJ1-mediated plasma membrane rupture depends on calcium influx into the cell, which suffices to induce NINJ1-mediated rupture. Using genetic and pharmacologic approaches in macrophages, we show calcium drives membrane rupture through phospholipid scrambling by the calcium-activated scramblase TMEM16F. We next tested whether this calcium-activated NINJ1 mechanism is the elusive pathway by which extracellular ATP stimulates cellular rupture. We show that ATP-stimulation of P2X7R induces NINJ1-mediated cell lysis via calcium influx and TMEM16F lipid scrambling, independently of inflammasomes, pannexins and gasdermin D. Our work reveals the mechanism of NINJ1 activation and solves the long-standing mystery of ATP-induced cytolysis. Summary Elevated cytosolic calcium drives NINJ1-mediated cellular rupture during lytic cell death through plasma membrane lipid scrambling.

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 score0.008

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
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 head0.012
GPT teacher head0.230
Teacher spread0.219 · 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

Citations10
Published2024
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicLipid Membrane Structure and BehaviorFrench-language works237,207