Lipopolysaccharides-Mediated Increase in Glucose-Stimulated Insulin Secretion: Involvement of the GLP-1 Pathway
Bibliographic record
Abstract
Lipopolysaccharides (LPS) of the cell wall of gram-negative bacteria trigger inflammation, which is associated with marked changes in glucose metabolism. Hyperglycemia is frequently observed during bacterial infection and it is a marker of a poor clinical outcome in critically ill patients. The aim of the current study was to investigate the effect of an acute injection or continuous infusion of LPS on experimentally induced hyperglycemia in wild-type and genetically engineered mice. The acute injection of a single dose of LPS produced an increase in glucose disposal and glucose-stimulated insulin secretion (GSIS). Continuous infusion of LPS through mini-osmotic pumps was also associated with increased GSIS. Finally, manipulation of LPS detoxification by knocking out the plasma phospholipid transfer protein (PLTP) led to increased glucose disposal and GSIS. Overall, glucose tolerance and GSIS tests supported the hypothesis that mice treated with LPS develop glucose-induced hyperinsulinemia. The effects of LPS on glucose metabolism were significantly altered as a result of either the accumulation or antagonism of glucagon-like peptide 1 (GLP-1). Complementary studies in wild-type and GLP-1 receptor knockout mice further implicated the GLP-1 receptor-dependent pathway in mediating the LPS-mediated changes in glucose metabolism. Hence, enhanced GLP-1 secretion and action underlies the development of glucose-mediated hyperinsulinemia associated with endotoxemia.
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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) | 0.000 | 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 | 0.001 |
| 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".