Neuroprotective Effect of Urolithin A against Cerebellum Changes in Streptozotocin‐Induced Alzheimer’s Disease Rat Model
Bibliographic record
Abstract
Abstract Background Microbiota of the distal part of the intestine produces Urolithin A (Uro A) as a derivative of ellagitannins hydrolysis. Recently, the mitophagy, anti‐inflammatory, and antioxidant properties of Uro A have focused more attention on its probable beneficial effects on neurodegenerative states. The purpose of this research was to study the impact of Uro A on the histopathology of the cerebellum in a rat model of streptozotocin‐induced Alzheimer’s disease. Methods Young male Wistar rats underwent stereotaxic surgery and infused streptozotocin (STZ; 3 mg/Kg body weight, dissolved in 10 µl vehicle of ascorbic acid‐saline 0.1%), intracerebroventricularly. After that, rats of experimental groups 1 and 2 were administered daily (i.p.) Uro A at two different doses; 10 and 20 mg/kg body weight, respectively. At the end of the experimental period (2 weeks), rats were deeply anesthetized, perfused (10% formalin solution), and decapitated, and their brains were removed and post‐fixed in the same fixator. Then, the cerebellums were separated and processed for histological preparation. Paraffin sections (5 µm thickness) were stained (H&E) and examined under a light microscope. Result The microscopic photos of cerebellum sections of control, negative control, and experimental rats are presented in Figure 1. The photos show that, in comparison with the control, the disruption in the continuity of the Purkinje cell layer, as well as the abnormal morphology and lower density of Purkinje cells are obvious in the negative control section. Conclusion It seems that Uro A treatment could somehow limit the destructive effects of STZ on the cerebellar Purkinje cell layer. Previously, decreased densities of Purkinje cells and notable morphological changes have been reported in the cerebellum of Alzheimer’s patients (Baloyannis et al., 2000).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".