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Record W4417200845 · doi:10.1091/mbc.e25-09-0443

Membrane curvature elastic stress triggers recruitment of PML-II onto the inner nuclear membrane

2025· article· en· W4417200845 on OpenAlexaff
Michael McPhee, Jayme Salsman, Allison A. Newman, Nikol Voutsina, Andrew H. Crosby, Graham Dellaire, Neale D. Ridgway

Bibliographic record

VenueMolecular Biology of the Cell · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNuclear Structure and Function
Canadian institutionsDalhousie University
Fundersnot available
KeywordsInner membraneDiacylglycerol kinaseNuclear membraneMembrane curvatureLaminMembraneCell membranePromyelocytic leukemia proteinCell nucleus

Abstract

fetched live from OpenAlex

Promyelocytic leukemia (PML) protein isoform II is a component of PML nuclear bodies (PML NBs) that also forms patches on nuclear lipid droplets (nLDs) and the inner nuclear membrane (INM). Here we tested whether different metabolic treatments that induce membrane curvature elastic stress (CES) in the INM, detected by recruitment of CTP:phosphocholine cytidylyltransferase α (CCTα) and a nuclear diacylglycerol (DAG) biosensor, are a precondition for PML-II membrane association. We found that treatment of U2OS cells with unsaturated 18-carbon fatty acids and DAG acyltransferase inhibitors caused the rapid formation of PML patches on the INM that coincided with DAG enrichment and the recruitment and stabilization of CCTα, all of which were reversed upon removal of the CES stimulus. PML patches were depleted of canonical PML NB-associated proteins, occurred at sites of lamin depletion, were specific for the PML-II isoform, and occurred in cells regardless of their capacity to assemble nLDs. Induction of INM curvature stress by knockout of the terminal enzymes of the CDP-choline pathway or lipid activators of CCTα also promoted PML patches as well as stabilization of CCTα on the INM. We conclude that CES in the INM promotes the reversible assembly of PML-II-dependent membrane-associated patches.

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 score0.074
Threshold uncertainty score0.441

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 science0.0010.000
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 head0.006
GPT teacher head0.234
Teacher spread0.227 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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