Effects of<i>Agaricus brasiliensis</i>mushroom in Walker-256 tumor-bearing rats
Bibliographic record
Abstract
Agaricus brasiliensis is a mushroom native to São Paulo State, Brazil, that is studied for its medicinal proprieties. This work aimed to investigate the antitumoral activity of A. brasiliensis extracts and pure powdered basidiocarp preparation using Walker-256 (W256) tumor-bearing rats, a model for cancer-related cachexia studies. The rats were treated for 14 days by gavage (136 mg/kg) and at the end of the experiment tumors were collected to calculate mass and volume. Blood was collected for determination of plasma glucose, albumin, alanine aminotransferase (ALT), and aspartate aminotransferase (AST). Hepatic and tumor enzymes indicating oxidative stress were also evaluated. The results showed that all 4 treatments (pure powdered basidiocarp and aqueous, acid, and alkaline extracts) significantly reduced tumor size and promoted gain in body weight. Plasmatic analysis showed a reduction in AST level and increased glycemia in the treated rats. Pure basidiocarp preparations improved the liver catalase and superoxide dismutase activity, but did not change the glutathione S-transferase activity. The data collected from the W256 tumor-bearing rats revealed the beneficial effects of A. brasiliensis in tumor treatment, mainly related to cachexia. The benefits can be partly related to antioxidant activity and to reduction of weight loss and tumor growth.
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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 | 0.001 |
| 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".