Identifying transcriptomic indicators of tertiary treated municipal effluent in longnose dace (Rhinichthys cataractae) caged under semi-controlled conditions in experimental raceways
Bibliographic record
Abstract
To evaluate effects of tertiary treated wastewater treatment plant effluent (MWWE) on transcriptomic responses in longnose dace (Rhinichthys cataractae; LND) we conducted a semi-controlled study in experimental raceways (Advancing Canadian Water Assets facility) imbedded in the Pine Creek treatment plant (Calgary, AB). LND collected from a reference site in the Bow River (REF) were caged in raceways containing either 5 % Pine Creek effluent (PC) or Bow River water (BR; control) over 28 d. Liver transcriptomes were analyzed in males and females sampled on days 7, 14 and 28 from BR and PC, and compared to REF fish on day 0. Concurrent with the caging, selected environmental substances of concern were analyzed in the BR and PC. Significantly different unigenes (SDUs) in females (vs males) within both BR and PC raceways increased over time and compared to REF fish. Moreover, SDUs in females and males within the same treatment (i.e., BR, PC) showed a temporal increase as well as compared to REF fish. Time was the dominant factor affecting SDUs, whereas sex and treatment had less of an impact on the transcriptome profiling. Gene Set Enrichment Analysis of BR vs PC over time revealed effects on genes involved in growth, metabolism of carbohydrates and lipids, and immune system on day 7; however, by day 28, 80-100 % of the transcripts localized to enriched biomarkers were associated with tissue immune responses in both sexes. Exposure to 5 % effluent had significant effects on female liver somatic index but no effects were observed on other phenotypic health indices in either sex. BR was used as the source of reference water, but analyses showed trace amounts of ESOCs. Analyses did not point towards definitive response patterns that could be used in field-based ecotoxicogenomic studies on the impacts of well-treated MWWE but suggested compromised adaptive immune responses.
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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".