T-Cell Protein Tyrosine Phosphatase Attenuates STAT3 and Insulin Signaling in the Liver to Regulate Gluconeogenesis
Bibliographic record
Abstract
OBJECTIVE: Insulin-induced phosphatidylinositol 3-kinase (PI3K)/Akt signaling and interleukin-6 (IL-6)-instigated JAK/STAT3-signaling pathways in the liver inhibit the expression of gluconeogenic genes to decrease hepatic glucose output. The insulin receptor (IR) and JAK1 tyrosine kinases and STAT3 can serve as direct substrates for the T-cell protein tyrosine phosphatase (TCPTP). Homozygous TCPTP-deficiency results in perinatal lethality prohibiting any informative assessment of TCPTP's role in glucose homeostasis. Here we have used Ptpn2+/- mice to investigate TCPTP's function in glucose homeostasis. RESEARCH DESIGN AND METHODS: We analyzed insulin sensitivity and gluconeogenesis in chow versus high-fat-fed (HFF) Ptpn2+/- and Ptpn2+/+ mice and insulin and IL-6 signaling and gluconeogenic gene expression in Ptpn2+/- and Ptpn2+/+ hepatocytes. RESULTS: HFF Ptpn2+/- mice exhibited lower fasted blood glucose and decreased hepatic glucose output as determined in hyperinsulinemic euglycemic clamps and by the decreased blood glucose levels in pyruvate tolerance tests. The reduced hepatic glucose output coincided with decreased expression of the gluconeogenic genes G6pc and Pck1 and enhanced hepatic STAT3 phosphorylation and PI3K/Akt signaling in the fasted state. Insulin-induced IR-beta-subunit Y1162/Y1163 phosphorylation and PI3K/Akt signaling and IL-6-induced STAT3 phosphorylation were also enhanced in isolated Ptpn2+/- hepatocytes. The increased insulin and IL-6 signaling resulted in enhanced suppression of G6pc and Pck1 mRNA. CONCLUSIONS: Liver TCPTP antagonises both insulin and STAT3 signaling pathways to regulate gluconeogenic gene expression and hepatic glucose output.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".