Comparative transcriptome analysis of the hepatopancreas of <i>Eriocheir sinensis</i> following oral gavage with enrofloxacin
Bibliographic record
Abstract
Enrofloxacin is an important drug that is widely used in the treatment of the diseased Eriocheir sinensis. This study compared transcriptome differences in the hepatopancreas of E. sinensis following oral gavage with enrofloxacin. Our study produced 80 228 728 and 88 888 706 raw reads from control and treatment groups, and after filtering and quality checks of the raw sequence reads, our analysis yielded 78 843 613 and 87 628 922 clean reads with a mean length of 126 bp from control and treatment groups, respectively. A total of 15 797 transcripts were assembled, with 11 975 transcripts annotated. Moreover, 2795 transcripts were judged to be differentially expressed genes. Gene ontology terms “biological process” and “metabolic process” were the most enriched in the oxidation–reduction process, translational initiation, membrane, cytoplasmic part, and hydrolase activity. Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that metabolic and signal transduction pathways were significantly enriched. Furthermore, we found that gshB and the CYP450 enzyme system plays a role in the metabolism of enrofloxacin in the hepatopancreas of E. sinensis. This study identified differential transcripts related to transmembrane transport and drug metabolism in E. sinensis that could help develop understanding of the molecular basis of enrofloxacin metabolism in this economically important aquaculture species.
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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".