In Vivo Expression of HGF/NK1 and GLP-1 From dsAAV Vectors Enhances Pancreatic β-Cell Proliferation and Improves Pathology in the <i>db/db</i> Mouse Model of Diabetes
Bibliographic record
Abstract
OBJECTIVE: The purpose of the current study was to determine whether double-stranded adeno-associated virus (dsAAV)-mediated in vivo expression of β-cell growth factors, glucagon-like peptide-1 (GLP-1) and the NK1 fragment of hepatocyte growth factor (HGF/NK1) in β-cells, improves pathology in the db/db mouse model of type 2 diabetes. RESEARCH DESIGN AND METHODS; The glucoregulatory actions of GLP-1 and full-length HGF are well characterized. Here, we test the ability of HGF/NK1 to induce proliferation of exogenous islets and MIN6 β-cells. In addition, we target both GLP-1 and HGF/NK1 to endogenous β-cells using dsAAV vectors containing the mouse insulin-II promoter. We compare the abilities of these gene products to induce islet proliferation in vitro and in vivo and characterize their abilities to regulate diabetes after AAV-mediated delivery to endogenous islets of db/db mice. RESULTS: Recombinant HGF/NK1 induces proliferation of isolated islets, and dsAAV-mediated expression of both GLP-1 and HGF/NK1 induces significant β-cell proliferation in vivo. Furthermore, both GLP-1 and HGF/NK1 expressed from dsAAV vectors enhance β-cell mass and insulin secretion in vivo and significantly delay the onset of hyperglycemia in db/db mice. CONCLUSIONS: A single treatment with dsAAV vectors expressing GLP-1 or HGF/NK1 enhances islet growth and significantly improves pathology in a mouse model of type 2 diabetes. This represents the first example of a successful use of HGF/NK1 for diabetes therapy, providing support for direct AAV-mediated in vivo delivery of β-cell growth factors as a novel therapeutic strategy for the treatment of type 2 diabetes.
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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) | 0.001 | 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".