SCH772984 ameliorates lipopolysaccharide-induced hypoglycemia in mice through reversing MEK/ERK/Foxo1-mediated gluconeogenesis suppression
Bibliographic record
Abstract
Lipopolysaccharide (LPS) results in a lethal hypoglycemic response. However, the main molecular mechanism involved in LPS-induced glucose metabolism disorder is poorly understood. This study intends to investigate the signaling pathways involved in LPS-induced hypoglycemia and potential efficacy of extracellular signal-regulated kinase (ERK) inhibitor SCH772984. The effects of LPS and SCH772984 on gluconeogenesis, glucose absorption, and glycogenolysis were evaluated by pyruvate tolerance test, oral glucose tolerance test, and glucagon test, respectively. After a single intraperitoneal injection of 0.5 mg/kg LPS, the mice's blood glucose levels and gluconeogenesis ability were significantly lower than that of control group. Besides, mRNA and protein expression of glucose-6-phosphatase (G6Pase) and phosphoenolpyruvate carboxykinase (PEPCK) decreased significantly after LPS treatment. LPS induced the phosphorylation of ERK1/2, MEK1/2 (mitogen-activated protein kinase), and Foxo1 while inhibited Foxo1 expression in the nucleus, indicating an important role of the MEK/ERK/Foxo1 signaling in the inhibition of gluconeogenesis by LPS. Furthermore, SCH772984 elevated blood glucose, increased the G6Pase and PEPCK expression, and inhibited pERK1/2 and pFoxo1 expression in LPS-induced mice. In summary, LPS inhibited gluconeogenesis and induced hypoglycemia through the MEK/ERK/Foxo1 signal pathway, and ERK inhibitor could effectively reverse decreased blood glucose in mice with LPS treatment. These findings provide a novel therapeutic target for LPS-induced hypoglycemia.
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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 | 0.000 |
| 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".