Differences in the transcriptome response in the gills of sea lamprey acutely exposed to 3-trifluoromethyl-4-nitrophenol (TFM), niclosamide or a TFM:niclosamide mixture
Bibliographic record
Abstract
Abstract Sea lamprey ( Petromyzon marinus ) control in the Laurentian Great Lakes of North America makes use of two pesticides: 3-trifluoromethyl-4-nitrophenol (TFM) and niclosamide, which are often co-applied. Sea lamprey appear to be vulnerable to these agents resulting from a lack of detoxification responses with evidence suggesting that lampricide mixtures produce a synergistic effect. However, there is a lack of information pertaining to the physiological responses of sea lamprey to niclosamide and TFM:niclosamide mixtures. Here, we characterized the transcriptomic responses of the sea lamprey to TFM, niclosamide, and a TFM:niclosamide (1.5%) mixture in the gill. Along with a control, larval sea lamprey were exposed to each treatment for 6 h, after which gill tissues were extracted for measuring whole-transcriptome responses using RNA sequencing. Differential gene expression patterns were summarized, which included identifying the broad roles of genes and common expression patterns among the treatments. While niclosamide treatment resulted in no differentially expressed genes, TFM- and mixture-treated fish had several differentially expressed genes that were associated with the cell cycle, DNA damage, metabolism, immune function, and detoxification. However, there was no common differential expression among treatments. For the first time, we characterized the transcriptomic response of sea lamprey to niclosamide and a TFM:niclosamide mixture and identified that these agents impact mRNA transcript abundance of genes associated with the cell cycle and cellular death, and immune function, which are likely mediated through mitochondrial dysregulation. These results may help to inform the production of more targeted and effective lampricides in sea lamprey control efforts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".