The Soy Peptide Phe–Leu–Val Reduces TNFα-Induced Inflammatory Response and Insulin Resistance in Adipocytes
Why this work is in the frame
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Bibliographic record
Abstract
Obesity-induced adipose inflammation plays a crucial role in the development of obesity-induced metabolic disorders such as insulin resistance and type 2 diabetes. In the presence of obesity, hypertrophic adipocytes release inflammatory mediators, including tumor necrosis factor-alpha (TNFα) and monocyte chemoattractant protein-1 (MCP-1), which enhance the recruitment and activation of macrophages, and in turn augment adipose inflammation. We demonstrate that the soy peptide Phe-Leu-Val (FLV) reduces inflammatory responses and insulin resistance in mature adipocytes. Specifically, the soy peptide FLV inhibits the release of inflammatory cytokines (TNFα, MCP-1, and IL-6) from both TNFα-stimulated adipocytes and cocultured adipocytes/macrophages. This inhibition is mediated by the inactivation of the inflammatory signaling molecules c-Jun N-terminal kinase (JNK) and IκB kinase (IKK), and the downregulation of IκBα in the adipocytes. In addition, soy peptide FLV enhances insulin responsiveness and increases glucose uptake in adipocytes. More importantly, we, for the first time, found that adipocytes express peptide transporter 2 (PepT2) protein, and the beneficial action of the soy peptide FLV was disrupted by the peptide transporter inhibitor GlySar. These findings suggest that soy peptide FLV is transported into adipocytes by PepT2 and then downregulates TNFα-induced inflammatory signaling, thereby increasing insulin responsiveness in the cells. The soy peptide FLV, therefore, has the potential to prevent obesity-induced adipose inflammation and insulin resistance.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it