Chronic Exposure to TNFα Impairs Secretion of Glucagon-Like Peptide-1
Bibliographic record
Abstract
Obesity is associated with systemic inflammation and elevated levels of TNFα, leading to impaired glucose tolerance. In humans, obesity is also associated with reduced nutrient-stimulated secretion of the intestinal incretin hormone, glucagon-like peptide-1 (GLP-1). We hypothesized that TNFα plays a direct role in the impairment of GLP-1 secretion from the enteroendocrine L-cell and that blocking TNFα can restore both GLP-1 secretion and glucose homeostasis. Expression of the TNFα receptor subytpe-1 was detected in the human NCI-H716 and murine GLUTag L-cell models and in mouse ileal sections. Although TNFα acutely increased GLP-1 release from NCI-H716 cells (P < .05-.001), preincubation with TNFα for 24 hours reduced proglucagon mRNA (P < .05) and GLP-1 cellular (P < .05) levels without affecting cell viability. Furthermore, both NCI-H716 and GLUTag cells pretreated with TNFα for 24 hours no longer responded to known GLP-1 secretagogues, an effect that was reversed by coincubation with the Nuclear Factor Kappa B inhibitor, 5-aminosalicylic acid, in the NCI-H716 cells. Mice given a high-fat diet (HFD) for 12 weeks developed impaired glucose tolerance, hyperinsulinemia, and increased TNFα mRNA expression in fat and ileal tissue. Hyperglycemia and hyperinsulinemia were reduced in HFD mice treated with the anti-TNFα biological, etanercept, for 2 weeks. In primary intestinal cultures from these animals, HFD control mice had impaired GLP-1 secretion, and this was not observed in the HFD etanercept-derived cultures (P < .05). In conclusion, chronic exposure to TNFα directly impairs GLP-1 secretion at the level of the intestinal L-cell, an effect that is reversed by anti-TNFα therapy in association with improved glucose tolerance.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".