Antidiabetic Activity and Inhibitory Effects of Derivatives of Advanced Aminoguanidine Glycation
Bibliographic record
Abstract
Aminoguanidine is a drug that prevents the formation of AGEs by reacting with initial glycation products and is effective in improving proteinuria and vessel elasticity, preventing diabetic retinopathy, and treating patients with diabetic nephropathy. Structural modifications of this molecule were carried out, and 19 derivatives were studied to present a potential hypoglycemic and antiglicante effect, preventing such complications for diabetics. For this purpose, an in vitro cytotoxicity test was initially carried out by colorimetric assay with MTT [3-(4,5-dimethylthiazol-2-yl)-2,5 diphenyltetrazolium], in macrophages of the J774 lineage. The AGEs were produced in vitro from the junction of glucose with bovine serum albumin and tested for evaluation of the antiglicante activity with reading in a fluorescence spectrophotometer. Derivatives with the best in vitro response were submitted to in vivo acute toxicity tests with Wistar rats and later evaluation of their antidiabetic and antiglycant potential in rats with streptozotocin-induced diabetes. After euthanasia, the heart, kidney, liver, and pancreas were removed for histopathological examination, and the blood for blood count and glycated hemoglobin, glucose, insulin, triglycerides, total cholesterol, HDL cholesterol, serum albumin, fructosamine, TGO, TGP, and GGT were collected. It is possible to conclude that the studied derivatives have the potential for the production of a drug that can be produced with them or associated with them and that is capable of reducing the glycemic indices and, at the same time, having an antiglicant action protecting individuals from macro- and microvascular complications.
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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".