Histopathological Evaluation of Infected Wistar Albino Rat Treated with Phyllanthus niruri L.
Bibliographic record
Abstract
Phyllanthus had been reported to have pharmacological effects such as antibacterial, antiviral activity against hepatitis. P. amarus has been used as chemoprotective agent and antimutagenic. Several active components have been identified in Phyllanthus , some of which are phyllantin, flavonoid, alkaloids, tannins, terpens, and sterols. Phyllanthus niruri L. (Euphorbiaceae) is a well-known hepatoprotective herbal plant. Due to the worldwide usage of Phyllanthus , this study focuses on the toxicology effect of the species in our environment in order to assess the biosafety of the plant. Apparently healthy Wistar albino rats were given 0.3 ml oral administration of Escherichia coli (ATCC 2522) of standard inoculum. The infected animals experienced reduction in the average body weight gain after three days inoculation, which increased drastically after a week and two weeks treatment, for positive and test animals respectively. At the end of the treatment, negative control and positive control have 6.37% and 15.21% average body weight gain respectively. In the test animals the least percentage weight gain was 10.83% (1200 mg/kgbw) and the highest percentage weight gain was 26.22% (300 mg/kgbw). The hyperchromasia of the liver tissue and vacuolations of the podocytes is suggestive of potential toxic properties of P. niruri L. in chronic administration.
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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) | 0.000 | 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) | 0.002 | 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".