Protective effect of ganoderan on renal damage in rats with chronic glomerulonephritis
Bibliographic record
Abstract
PURPOSE: To investigate the protective effect of ganoderan on renal damage in rat models with chronic glomerulonephritis induced by adriamycin. METHODS: 48 healthy Sprague-Dawley rats were randomly divided into three groups: control, nephritic model and ganoderan treatment groups. Changes of the following indices in the three groups were observed 6 weeks after treatment: 24-hour urine protein, albumen, serum creatinine, cholesterol. Histopathological observations of the renal cortex were made by light and electron microscopy. RESULTS: Compared with controls, levels of 24-hour urine protein (9.60+/-0.57 mg/d vs. 82.50+/-3.18 mg/d), serum creatinine (35.25+/-2.63 micromol/L vs. 44.75+/-8.06 micromol/L) and cholesterol (1.15+/-0.10 mmol/L vs. 4.02+/-0.25 mmol/L) of rats in the nephritic model group were increased (P < 0.05), and the concentration of albumen was decreased (35.98+/-1.34 g/L vs. 19.05+/-0.62 g/L, P < 0.05). Ganoderan administration decreased 24-hour urine protein (82.50+/-3.18 mg/d vs. 45.01+/-3.94 mg/d, P < 0.05). Following ganoderan, the pathological changes in kidney tissue were improved compared with those in the nephritic model group. CONCLUSION: Ganoderan exerts protective effects in rats with chronic glomerulonephritis induced by ADR. Ganoderan reduced 24-hour urine protein, serum creatinine, cholesterol, improving renal function and reducing the severity of renal injury.
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 | 0.000 | 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".