A Protective Role for Glucagon-like Peptide-2 in Heat-stable Enterotoxin b (STb)-Induced L-Cell Toxicity
Bibliographic record
Abstract
Enterotoxigenic Escherichia coli (ETEC)-derived purified heat-stable enterotoxin b (STb) is responsible for secretory diarrhea in livestock and humans. STb disrupts intestinal fluid homeostasis, epithelial barrier function, and promotes cell death. Glucagon-like peptide-2 (GLP-2) is a potent intestinotrophic hormone secreted by enteroendocrine L cells. GLP-2 enhances crypt cell proliferation, epithelial barrier function, and inhibits enterocyte apoptosis. Whether STb can affect GLP-2 producing L cells remains to be elucidated. First, secreted-His-labeled STb from transformed E coli was collected and purified. When incubated with L-cell models (GLUTag, NCI-H716, and secretin tumor cell line [STC-1]), fluorescent immunocytochemistry revealed STb was internalized and was differentially localized in the cytoplasm and nucleus. Cell viability experiments with neutral red and resazurin revealed that STb was toxic in all but the GLUTag cells. STb stimulated 2-hour GLP-2 secretion in all cell models. Interestingly, GLUTag cells produced the highest amount of GLP-2 when treated with STb, demonstrating an inverse relationship in GLP-2 secretion and cell toxicity. To demonstrate a protective role for GLP-2, GLUTag-conditioned media (rich in GLP-2) blocked STb toxicity in STC-1 cells. Confirming a protective role of GLP-2, teduglutide was able to improve cell viability in cells treated with H2O2. In conclusion, STb interacts with the L cell, stimulates secretion, and may induce toxicity if GLP-2 is not produced at high levels. GLP-2 or receptor agonists have the ability to improve cell viability in response to toxins. These results suggest that GLP-2 secretion can play a protective role during STb intoxication. This work supports future investigation into the use of GLP-2 therapies in enterotoxigenic-related diseases.
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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 | 0.000 |
| 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".