Cardiovascular autonomic neuropathy in spontaneously diabetic rats with and without application of EGb 761.
Bibliographic record
Abstract
Cardiovascular autonomic neuropathy causes abnormalities in the diabetic heart with various clinical sequelae, including exercise intolerance, arrhythmias and painless myocardial infarction. Little is known about (ultra)structural alterations of the myocardial nervous network. On the assumption that this diabetes-specific neuropathy develops due to permanently increased oxidative stress by liberation of oxygen-free radicals, adjuvant application of antioxidative therapeutics appears promising in preventing or delaying long-term diabetic complications. We have investigated the effects of Ginkgo biloba extract (EGb 761), a radical scavenger, against diabetes-induced myocardial nervous damage in spontaneously diabetic BioBreeding/Ottawa Karlsburg (BB/OK) rats. Morphological and morphometric parameters were evaluated by electron microscopy. We used immunohistochemistry to investigate protein expression of protein gene product 9.5, S100 protein, and thyroxin hydroxylase as a neuronal marker. Alterations of cardiac sympathetic activity were measured using the in vivo 123I-metaiodobenzyl-guanidine imaging, and the immunofluorescent labeling of beta1-adrenergic receptors and adenylate cyclase. Our results revealed that A) Diabetes results in slight to moderate ultrastructural alterations (hydrops, disintegration of substructure) of autonomic nerve fibers and related Schwann cells in untreated BB diabetic rats; B) Cardiac sympathetic integrity and activity is impaired due to alterations in the presynaptic nerve terminals and the postsynaptic ß1-AR-AC coupling system; C) Pre-treatment of diabetic myocardium with EGb results in an improvement of most of these parameters compared to unprotected myocardium. In conclusion, EGb may act as a potent therapeutic adjuvant in diabetics with respect to cardiovascular autonomic neuropathy, which may contribute to the prevention of late complications in diabetes.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".