A phenotype of IGFBP‐3 knockout mice revealed by dextran sulfate‐induced colitis
Bibliographic record
Abstract
BACKGROUND AND AIM: Insulin-like growth factor-1 (IGF-1) bioactivity has been shown to be attenuated by insulin-like growth factor binding protein-3 (IGFBP-3), one of six IGF-binding proteins. While prior work revealed no major phenotype associated with IGFBP-3 knockout mice, we explored the possibility that a phenotype could be revealed under specific conditions of gastrointestinal stress. METHODS: The dextran sodium sulfate (DSS) murine model of ulcerative colitis was used for this study. RESULTS: Insulin-like growth factor binding protein-3 knockout mice had significantly reduced colitis on exposure to DSS as measured by lower levels of pro-inflammatory cytokines IL-6 (P < 0.0001), TNF-α (P = 0.0035), and IL-1β (P = 0.0112), reduced weight loss (P < 0.0001), reduced myeloperoxidase activity (P = 0.0025), and maintenance of colorectal length (P < 0.05), all relative to wild-type mice exposed to DSS. IGFBP-3 knockout mice also exhibited increased colon epithelial cell proliferation (P < 0.0001) following DSS exposure. Semi-quantitative immunohistochemistry showed greater IGF-1 receptor activation in colon epithelial cells of IGFBP-3 knockout mice compared with control mice following DSS exposure. CONCLUSION: Our data demonstrate that IGFBP-3 influences severity of DSS-induced colitis. The observations suggest that in the absence of IGFBP-3, enhanced IGF bioactivity leads to increased epithelial proliferation and mucosal barrier repair, thereby lessening inflammation.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".