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Record W2081128359 · doi:10.1002/cyto.a.20911

Development of a novel, cell‐based chemical screen to identify inhibitors of intraphagosomal lipolysis in macrophages

2010· article· en· W2081128359 on OpenAlexaff
Brian C. VanderVen, Albin Hermetter, Amy Y. Huang, Frederick R. Maxfield, David G. Russell, Robin M. Yates

Bibliographic record

VenueCytometry Part A · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSphingolipid Metabolism and Signaling
Canadian institutionsUniversity of Calgary
FundersNational Institute of Allergy and Infectious DiseasesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Heart, Lung, and Blood Institute
KeywordsContext (archaeology)MacrophageLipolysisCell biologyPhagosomeChemistryBiochemistryBiologyPhagocytosisAdipose tissueIn vitro

Abstract

fetched live from OpenAlex

Macrophages play a central role in tissue homeostasis and the immune system. Their primary function is to internalize cellular debris and microorganisms for degradation within their phagosomes. In this context, their capacity to process and sequester lipids such as triacylglycerides and cholesteryl esters makes them key players in circulatory diseases, such as atheroclerosis. To discover new inhibitors of lipolytic processing within the phagosomal system of the macrophage, we have developed a novel, cell-based assay suitable for high-throughput screening. We employed particles carrying a fluorogenic triglyceride substrate and a calibration fluor to screen for inhibitors of phagosomal lipolysis. A panel of secondary assays were employed to discriminate between lipase inhibitors and compounds that perturbed general phagosomal trafficking events. This process enabled us to identify a new structural class of pyrazole-methanone compounds that directly inhibit lysosomal and lipoprotein lipase activity.

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: Methods · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.287
Teacher spread0.274 · 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
GenreMethods

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

Citations16
Published2010
Admission routes1
Has abstractyes

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Same venueCytometry Part ASame topicSphingolipid Metabolism and SignalingFrench-language works237,207