Abstract 453: Adiponectin Increases AdipoR1/R2 Cell Surface Expression And M1-M2 Macrophage Subpopulations In AdipoR Knockdown Conditions
Bibliographic record
Abstract
Introduction: Adiponectin is an adipose-tissue secreted hormone that exerts its anti-inflammatory and anti-atherogenic functions through its two main receptors, adiponectin receptor 1 (AdipoR1) and AdipoR2, which are highly expressed in monocyte-derived macrophages (Mϕs). In response to various stimuli, Mϕs can acquire a more pro-inflammatory M1, or anti-inflammatory M2 phenotype. Herein, we investigated the effect of single AdipoR1, single AdipoR2 and double AdipoR1/R2 knockdown conditions in response to adiponectin on M1 and M2 Mϕ subpopulations. Methods: siRNA-mediated knockdown of AdipoR1 and/or AdipoR2 was performed in THP-1 monocyte-derived Mϕs, and treated in the presence or absence of adiponectin. Flow cytometry was performed to assess AdipoR1/R2, M1 Mϕ subpopulation (CD86/CD80), and M2 Mϕ subpopulation (CD206/CD163). Magnetic bead-based immunoassays were performed on cell culture supernatants to assess 12 pro-inflammatory (TNF-α, MCP-1, IL-1β, IL-6, IL-8, IL-12p40, IL-12p70) and anti-inflammatory (IL-1Rα, IL-4, IL-10, TGF-β1 and CCL17) cytokines and chemokines. Results: In response to adiponectin, flow cytometry analyses for single AdipoR1, single AdipoR2, and double AdipoR1/R2 siRNA resulted in a significant increase in double-positive AdipoR1/R2 Mϕs. Although adiponectin treatment of single AdipoR1, single AdipoR2 and double AdipoR1/R2 siRNA significantly increased both Mϕ subpopulations, this increase was more prominent in M2 Mϕ subpopulation. Immunoassay analyses in knockdown conditions demonstrated a mixed pro- and anti-inflammatory cytokine and chemokine profile in response to adiponectin; levels of TNF-α, MCP-1 were increased and IL-1β decreased, while TGF-β1 and CCL17 were decreased. Conclusions: Adiponectin treatment increases the amount of AdipoR1/R2 cell surface expression on Mϕs without being limited by intracellular AdipoR knockdown conditions. Furthermore, although adiponectin promoted both Mϕ subpopulations, a greater shift towards M2 Mϕs was noted, while producing a heterogeneous pro- and anti-inflammatory cytokine and chemokine profile. Our current work will unravel the underlying mechanisms of the role of the adiponectin-AdipoR pathway in regulating M1-M2 Mϕ phenotypes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".