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Abstract 15494: Characterization of Adiponectin Kinetics and Adiponectin R2 Pathway in Thp-1 Macrophages and Foam Cells

2022· article· en· W4380716298 on OpenAlexaff
Anouar Hafiane, Jean-Claude Bertrand, Stella S. Daskalopoulou

Bibliographic record

VenueCirculation · 2022
Typearticle
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsMcGill University
Fundersnot available
KeywordsFoam cellAdiponectinInternal medicineReceptorAdipokineEndocrinologyMolecular biologyMedicineBiologyCholesterolLipoproteinInsulin resistanceInsulin

Abstract

fetched live from OpenAlex

Background: Adiponectin (APN) is an adipokine most abundantly secreted by adipocytes and possesses vasculoprotective properties. We and others have previously showed that APN receptor 2 (adipoR2) pathway is impaired in foam cells when compared to macrophages. Nevertheless, the functional role of adipoR2 pathway in foam cells has not been fully investigated. We hypothesize that APN kinetics involving AdipoR2 and its subsequent downstream signaling peroxisome proliferator-activated receptor-α (PPAR-α) expression are altered in foam cells when compared to macrophages. Methods: We used THP-1 human macrophage-derived foam cells loaded with oxidized LDL (60μg/ml) and 3H-cholesterol (2μCi/ml) versus control macrophages. APN isomers and PPAR-α protein expression were detected by gradient SDS-PAGE, and Western blotting, respectively. Media cell cultures mixtures were analysed under protease inhibitor by a size-exclusion centrifugal filter molecular weight cut-off 10 kDa. Results: PPAR-α activation significantly increased in APN-treated macrophages (24h) when compared with APN-treated foam cells (24h) with a maximum fold difference of 1.90±1.21, p=0.002 at 10μg APN/mL (PPAR-α: β actin ratio, spectral count; n=10 repeats for each). As a result, in foam cells, APN stimulated PPAR-α with a lower Km molar efficiency (0.06 ± 0.13 μM) and lower velocity Vmax 0.67±0.08 /h-as compared to macrophages (0.023±0.02 μM and 1.37±0.11 /h respectively, p=0.01 for both). In macrophages, APN had smaller dissociation constant Kd (0.037±0.56 μM) than in foam cells (0.10±1.30 μM). APN increased significantly PPAR-α activity rate over time reaching a maximum of 2h, with 1.19±0.02 PPAR-α protein expression in macrophages vs 0.85±0.057 in foam cells. Additionally, the APN dimer/monomer ratio increased over 24h when compared to foam cells, reaching a maximum at 2h in macrophages. Strong correlations were noted between PPARα and APN dimers: in macrophages (r=0.85; p=0.006) and in foam cells (r=0.68, p=0.05). Conclusion: APN stimulates PPARα activity in macrophages, but significantly less in foam cells (weaker kinetic affinity process), suggesting that APN interaction and binding with adipoR2 and subsequent downstream PPARα expression are affected in foam cells.

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 score0.008

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 integrity0.0000.000
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 head0.012
GPT teacher head0.231
Teacher spread0.219 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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