A fusion protein derived from plants holds promising potential as a new oral therapy for type 2 diabetes
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Bibliographic record
Abstract
The incretin hormone glucagon-like peptide-1 (GLP-1) is recognized as a promising candidate for the treatment of type 2 diabetes (T2D), with one of its mimetics, exenatide (synthetic exendin-4) having already been licensed for clinical use. We seek to further improve the therapeutic efficacy of exendin-4 (Ex-4) using innovative fusion protein technology. Here, we report the production in plants a fusion protein containing Ex-4 coupled with human transferrin (Ex-4-Tf) and its characterization. We demonstrated that plant-made Ex-4-Tf retained the activity of both proteins. In particular, the fusion protein stimulated insulin release from pancreatic β-cells, promoted β-cell proliferation, stimulated differentiation of pancreatic precursor cells into insulin-producing cells, retained the ability to internalize into human intestinal cells and resisted stomach acid and proteolytic enzymes. Importantly, oral administration of partially purified Ex-4-Tf significantly improved glucose tolerance, whereas commercial Ex-4 administered by the same oral route failed to show any significant improvement in glucose tolerance in mice. Furthermore, intraperitoneal (IP) injection of Ex-4-Tf showed a beneficial effect in mice similar to IP-injected Ex-4. We also showed that plants provide a robust system for the expression of Ex-4-Tf, producing up to 37 μg prEx-4-Tf/g fresh leaf weight in transgenic tobacco and 137 μg prEx-4-Tf/g freshweight in transiently transformed leaves of N. benthamiana. These results indicate that Ex-4-Tf holds substantial promise as a new oral therapy for type 2 diabetes. The production of prEx-4-Tf in plants may offer a convenient and cost-effective method to deliver the antidiabetic medicine in partially processed plant food products.
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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 it