Beneficial Effects of Exendin-4 on Experimental Polyneuropathy in Diabetic Mice
Bibliographic record
Abstract
OBJECTIVE: The therapeutic potential of exendin-4, an agonist of the glucagon-like peptide-1 receptor (GLP-1R), on diabetic polyneuropathy (DPN) in streptozotocin (STZ)-induced diabetic mice was investigated. RESEARCH DESIGN AND METHODS: The presence of the GLP-1R in lumbar dorsal root ganglion (DRG) was evaluated by immunohistochemical analyses. DRG neurons were dissected from C57BL6/J mice and cultured with or without Schwann cell-conditioned media in the presence or absence of GLP-1 (7-37) or exendin-4. Then neurite outgrowth was determined. In animal-model experiments, mice were made diabetic by STZ administration, and after 12 weeks of diabetes, exendin-4 (10 nmol/kg) was intraperitoneally administered once daily for 4 weeks. Peripheral nerve function was determined by the current perception threshold and motor and sensory nerve conduction velocity (MNCV and SNCV, respectively). Sciatic nerve blood flow (SNBF) and intraepidermal nerve fiber densities (IENFDs) also were evaluated. RESULTS: The expression of the GLP-1R in DRG neurons was confirmed. GLP-1 (7-37) and exendin-4 significantly promoted neurite outgrowth of DRG neurons. Both GLP-1R agonists accelerated the impaired neurite outgrowth of DRG neurons cultured with Schwann cell-conditioned media that mimicked the diabetic condition. At the doses used, exendin-4 had no effect on blood glucose or HbA(1c) levels. Hypoalgesia and delayed MNCV and SNCV in diabetic mice were improved by exendin-4 without affecting the reduced SNBF. The decreased IENFDs in sole skins of diabetic mice were ameliorated by exendin-4. CONCLUSIONS: Our findings indicate that exendin-4 ameliorates the severity of DPN, which may be achieved by its direct actions on DRG neurons and their axons.
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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".