γ-Glutamylvaline Prevents Low-Grade Chronic Inflammation via Activation of a Calcium-Sensing Receptor Pathway in 3T3-L1Mouse Adipocytes
Bibliographic record
Abstract
The calcium-sensing receptor (CaSR), a G-protein receptor, is well recognized for its role in the regulation of adipocyte proliferation, in modulating adipose tissue dysfunction, and as a potential target for therapeutic intervention. In the present study, we investigate the anti-inflammatory effect of γ-glutamylvaline (γ-EV) on mouse adipocytes and explore the role of γ-EV-activated CaSR in the regulation of cellular homeostasis using the mouse 3T3-L1 cell line in vitro model. Our results indicate that the 3T3-L1 adipocyte-like cells accumulated lipids and expressed CaSR after 2 days of differentiation and 7 days of maturation period. The pretreatment with γ-EV (10 μM) suppressed the production of TNF-α-induced pro-inflammatory cytokines, i.e., IL-6 (23.92 ± 5.45 ng/mL, p < 0.05)) and MCP-1 (101.17 ± 39.93 ng/mL, p < 0.05), while enhancing the expression of PPARγ (1.249 ± 0.109, p < 0.001) and adiponectin (7.37 ± 0.59 ng/mL, p < 0.05). Elevated expression of Wnt5a was detected in γ-EV-treated cells (115.90 ± 45.50, p < 0.001), suggesting the involvement of the Wnt/β-catenin pathway. Also, phosphorylation of β-catenin was shown to be significantly inhibited (0.442 ± 0.034) by TNF-α but restored when cells were pretreated with γ-EV (0.765 ± 0.048, p < 0.05). These findings suggest that γ-EV-induced CaSR activation not only prevents TNF-α-induced inflammation in adipocytes but also modulates the cross-talk between Wnt and PPARγ pathways. Concentrations of serine phosphorylated IRS-1 were shown to be lower in γ-EV-treated cells, indicating γ-EV may also prevent inflammation in the context of insulin resistance. Thus, γ-EV-activated CaSR plays a significant role in the cross-talk between adipocyte inflammatory and metabolic pathways through the regulation of extracellular sensing.
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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 | 0.001 |
| 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) | 0.001 | 0.000 |
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.
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".