Multiple biomarker responses in caged benthic gastropods Bellamya aeruginosa after in situ exposure to Taihu Lake in China
Bibliographic record
Abstract
Freshwater sediments have been recognized as a long-term sink and potential source for environmental pollutants released into the aquatic ecosystems. In this study, the sediment quality of Taihu Lake, which is susceptible to anthropogenic contamination, was assessed by a combination of chemical analytical and biological end points. Specifically, the snail Bellamya aeruginosa was caged in situ at two locations representing different pollution levels for different exposure times (7, 14 and 21 days). At each of these time points, biochemical parameters, i.e., phase I biotransformation enzymes ethoxyresorufin- O -deethylase (EROD), the antioxidant enzymes superoxide dismutase and catalase, reactive oxygen species, protein carbonyl content and lipid peroxidation, were evaluated in the hepatopancreas of snails. In addition, surface sediments were collected for analysis of contaminants of concern, including inorganic pollutants, organochlorine pesticides, polychlorinated biphenyls and polybrominated diphenyl ethers. Chemical analyses revealed that sediments from Taihu Lake were contaminated with trace elements and organic pollutants. Concentrations of trace elements (Cu, Ni and As) and organochlorinated pesticides (4,4′-DDE) exceeded their corresponding threshold effect level according to the sediment quality assessment values for freshwater ecosystems in Canada, indicating that adverse biological effects may occur. All biomarkers, except EROD activity, were induced in snails during all exposure times. The integrated biomarker response index (IBR) indicated that during the initial exposure phase (7 days), B. aeruginosa were subjected to significant environmental stress, which diminished during later sampling time points. Results showed that IBR correlated well with the levels of environmental contaminants, demonstrating the applicability of this biomonitoring approach to complex environmental exposure scenarios.
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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) | 0.000 | 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".