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Record W6949555552 · doi:10.5281/zenodo.16092971

MAPL regulates gasdermin-mediated release of mtDNA from lysosomes to drive pyroptotic cell death

2025· dataset· en· W6949555552 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typedataset
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsMcGill University
Fundersnot available
KeywordsProgrammed cell deathMitochondrionMitochondrial fissionPyroptosismitochondrial fusionMitochondrial DNACellMitophagy

Abstract

fetched live from OpenAlex

Mitochondrial control of cell death is of central importance to disease mechanisms from cancer to neurodegeneration. Mitochondrial anchored protein ligase (MAPL) is an outer mitochondrial membrane small ubiquitin-like modifier ligase that is a key determinant of cell survival, yet how MAPL controls the fate of this process remains unclear. Combining genome-wide functional genetic screening and cell biological approaches, we found that MAPL induces pyroptosis through an inflammatory pathway involving mitochondria and lysosomes. MAPL overexpression promotes mitochondrial DNAShould have "(mtDNA)" after as this is the first instance it is mentioned. trafficking in mitochondrial-derived vesicles to lysosomes, which are permeabilized in a process requiring gasdermin pores. This triggers the release of mtDNA into the cytosol, activating the DNA sensor cGAS, required for cell death. Additionally, multiple Parkinson’s disease-related genes, including VPS35 and LRRK2, also regulate MAPL-induced pyroptosis. Notably, depletion of MAPL, LRRK2 or VPS35 inhibited inflammatory cell death in primary macrophages, placing MAPL and the mitochondria–lysosome pathway at the nexus of immune signalling and cell death.

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)0.003
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: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.019
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0020.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.015

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 head0.249
Teacher spread0.230 · 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
GenreDataset

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

Citations0
Published2025
Admission routes1
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)→Same topicPrenatal Screening and Diagnostics→French-language works237,207→