Alterations in histopathological features and brain acetylcholinesterase activity in stinging catfish Heteropneustes fossilis exposed to polluted river water
Bibliographic record
Abstract
Abstract Responses of stinging catfish (Heteropneustes fossilis) to pollution were studied in three freshwater rivers, namely Buriganga, Turag, and Shitalakkhya (Dhaka, Bangladesh), which are potentially affected by anthropogenic pollution originating from industrial and sewage dumping. Partial parameters about water quality (temperature, dissolved oxygen, and pH) and seasonal plankton fluctuation were recorded at wet and dry seasons. Histopathology and acetylcholinesterase (AChE) activity were used as biomarkers to assess water toxic effects in 7-and 10-day exposures of H. fossilis to three rivers waters, respectively. The lowest level of dissolved oxygen was recorded as 0.7 ± 0.1 mg/l, and the lowest count of plankton genera was 21 at lean period. Furthermore, the 7-day exposure of fish to polluted water abruptly altered the normal structure of various organs. Major structural damages were partial and total epidermal loss, dermis and muscle separation, melanin pigment and vacuole in skin muscle; missing of lamellae, clubbing, fungal granuloma, hyperplasia and hemorrhage in gills; hyperplasia, hemorrhage, pyknosis, vacuole, necrosis, nuclear alteration, fatty degeneration, lipid droplets in liver; degenerating glomerular and tubule, hemorrhage, pyknosis and vacuole in kidneys; and scattered spermatozoa and prominent interstitial space in the testis. After subsequent exposure to polluted water, a significant (P < 0.05) inhibition of AChE activity in the fish brain was observed with the following order of potency: 102.00 ± 5.00 nmol/min/mg protein (Turag) ≥ 104.00 ± 5.00 nmol/min/mg protein (Buriganga) > 130.67 ± 3.51 nmol/min/mg protein (Shitalakkhya). This study confirmed the utility of biomarkers in biomonitoring studies and reflected the potential hazards of pollution to aquatic biota.
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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 | 0.000 |
| 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".