Myeloid-Cell Protein Tyrosine Phosphatase-1B Deficiency in Mice Protects Against High-Fat Diet and Lipopolysaccharide-Induced Inflammation, Hyperinsulinemia, and Endotoxemia Through an IL-10 STAT3-Dependent Mechanism
Bibliographic record
Abstract
Protein tyrosine phosphatase-1B (PTP1B) negatively regulates insulin and leptin signaling, rendering it an attractive drug target for treatment of obesity-induced insulin resistance. However, some studies suggest caution when targeting macrophage PTP1B, due to its potential anti-inflammatory role. We assessed the role of macrophage PTP1B in inflammation and whole-body metabolism using myeloid-cell (LysM) PTP1B knockout mice (LysM PTP1B). LysM PTP1B mice were protected against lipopolysaccharide (LPS)-induced endotoxemia and hepatic damage associated with decreased proinflammatory cytokine secretion in vivo. In vitro, LPS-treated LysM PTP1B bone marrow-derived macrophages (BMDMs) displayed increased interleukin (IL)-10 mRNA expression, with a concomitant decrease in TNF-α mRNA levels. These anti-inflammatory effects were associated with increased LPS- and IL-10-induced STAT3 phosphorylation in LysM PTP1B BMDMs. Chronic inflammation induced by high-fat (HF) feeding led to equally beneficial effects of macrophage PTP1B deficiency; LysM PTP1B mice exhibited improved glucose and insulin tolerance, protection against LPS-induced hyperinsulinemia, decreased macrophage infiltration into adipose tissue, and decreased liver damage. HF-fed LysM PTP1B mice had increased basal and LPS-induced IL-10 levels, associated with elevated STAT3 phosphorylation in splenic cells, IL-10 mRNA expression, and expansion of cells expressing myeloid markers. These increased IL-10 levels negatively correlated with circulating insulin and alanine transferase levels. Our studies implicate myeloid PTP1B in negative regulation of STAT3/IL-10-mediated signaling, highlighting its inhibition as a potential anti-inflammatory and antidiabetic target in obesity.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".