Analysis of the Biochemical and Histopathological Impact of Polystyrene Microplastic on Channa Punctata (Bloch, 1793) Fish.
Bibliographic record
Abstract
Background: Polystyrene microplastics (PS-MS) are emerging contaminants in aquatic ecosystems and a serious threat to aquatic organisms. The toxicological effects of PS-MS on Channa punctata were evaluated by biochemical, histopathological, and physiological parameters. Methods: Four groups (Control, (1 mg/l) Dose 1, (5 mg/l Dose 2, (10 mg/l) Dose 3) of fish were exposed to PS-MS for 28 days. Fulton’s Condition Factor (K), Hepatosomatic Index (HSI), and Kidney Somatic Index (KSI) were measured as biometric indices. Serum biochemical markers of liver (ALT, AST) and kidney (Creatinine, BUN) function were measured. Structural abnormalities in liver and kidney tissues were observed by histopathological analysis. Results: Significant dose-dependent reductions in biometric indices were observed, consistent with physiological stress. Dose-dependent increases in liver and kidney function markers confirmed hepatic and renal toxicity. Liver tissues and kidney tissues showed severe vacuolization, necrosis sinusoidal congestion in liver tissues and tubular degeneration, glomerular atrophy, and necrosis in kidney tissues, particularly at higher doses. Conclusion: Channa punctata exposed to PS-MS experiences significant dose-dependent physiological and cellular disruptions. The findings underscore the need for immediate action to mitigate microplastic pollution and protect aquatic biodiversity.
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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 | 0.001 | 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 | 0.000 |
| 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".