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Record W4390498581 · doi:10.1038/s41467-023-44559-3

ApoL6 associates with lipid droplets and disrupts Perilipin1-HSL interaction to inhibit lipolysis

2024· article· en· W4390498581 on OpenAlexaff
Yuhui Wang, Hai P. Nguyen, Pengya Xue, Ying Xie, Danielle Yi, Frances Lin, Jennie Dinh, José A. Viscarra, Nnejiuwa U. Ibe, Robin E. Duncan, Hei Sook Sul

Bibliographic record

VenueNature Communications · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid metabolism and biosynthesis
Canadian institutionsUniversity of Waterloo
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesU.S. Department of Health and Human Services
KeywordsLipolysisPerilipinAdipose tissueLipid dropletEndocrinologyInternal medicineWhite adipose tissueAdipose triglyceride lipaseGene knockdownChemistryFatty acid-binding proteinBiologyBiochemistryMedicineApoptosisGene

Abstract

fetched live from OpenAlex

Adipose tissue stores triacylglycerol (TAG) in lipid droplets (LD) and release fatty acids upon lipolysis during energy shortage. We identify ApoL6 as a LD-associated protein mainly found in adipose tissue, specifically in adipocytes. ApoL6 expression is low during fasting but induced upon feeding. ApoL6 knockdown results in smaller LD with lower TAG content in adipocytes, while ApoL6 overexpression causes larger LD with higher TAG content. We show that the ApoL6 affects adipocytes through inhibition of lipolysis. While ApoL6, Perilipin 1 (Plin1), and HSL can form a complex on LD, C-terminal ApoL6 directly interacts with N-terminal Plin1 to prevent Plin1 binding to HSL, to inhibit lipolysis. Thus, ApoL6 ablation decreases white adipose tissue mass, protecting mice from diet-induced obesity, while ApoL6 overexpression in adipose brings obesity and insulin resistance, making ApoL6 a potential future target against obesity and diabetes.

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 score0.006

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 head0.008
GPT teacher head0.284
Teacher spread0.276 · 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

Citations34
Published2024
Admission routes1
Has abstractyes

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Same venueNature CommunicationsSame topicLipid metabolism and biosynthesisFrench-language works237,207