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Record W3029241703 · doi:10.26508/lsa.202000751

Lipid-associated PML structures assemble nuclear lipid droplets containing CCTα and Lipin1

2020· article· en· W3029241703 on OpenAlexafffund
Jong‐Hwa Lee, Jayme Salsman, Jason Foster, Graham Dellaire, Neale D. Ridgway

Bibliographic record

VenueLife Science Alliance · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid metabolism and biosynthesis
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health ResearchUniversity College LondonFrancis Crick InstituteBeatrice Hunter Cancer Research InstituteNova Scotia Health Research FoundationCancer Research Institute
KeywordsLipid dropletChemistryNanotechnologyMaterials scienceBiochemistry

Abstract

fetched live from OpenAlex

Nuclear lipid droplets (nLDs) form on the inner nuclear membrane by a mechanism involving promyelocytic leukemia (PML), the protein scaffold of PML nuclear bodies. We report that PML structures on nLDs in oleate-treated U2OS cells, referred to as lipid-associated PML structures (LAPS), differ from canonical PML nuclear bodies by the relative absence of SUMO1, SP100, and DAXX. These nLDs were also enriched in CTP:phosphocholine cytidylyltransferase α (CCTα), the phosphatidic acid phosphatase Lipin1, and DAG. Translocation of CCTα onto nLDs was mediated by its α-helical M-domain but was not correlated with its activator DAG. High-resolution imaging revealed that CCTα and LAPS occupied distinct polarized regions on nLDs. PML knockout U2OS (PML KO) cells lacking LAPS had a 40-50% reduction in nLDs with associated CCTα, and residual nLDs were almost devoid of Lipin1 and DAG. As a result, phosphatidylcholine and triacylglycerol synthesis was inhibited in PML KO cells. We conclude that in response to excess exogenous fatty acids, LAPS are required to assemble nLDs that are competent to recruit CCTα and Lipin1.

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)0.001
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 score0.453
Threshold uncertainty score0.752

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.018
GPT teacher head0.246
Teacher spread0.228 · 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

Citations47
Published2020
Admission routes2
Has abstractyes

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