Autophagy‐related gene regulation in liver and muscle of rainbow trout ( <i>Oncorhynchus mykiss</i> ) upon exposure to chloroquine, deoxynivalenol and nutrient restriction
Bibliographic record
Abstract
Autophagy is important for maintaining homeostasis, nutrient availability and muscle mass in fish. The effect of chloroquine (CQ) and deoxynivalenol (DON) on autophagy-related gene (Atg) regulation was examined in rainbow trout fed with either CQ or DON and compared with pair-fed (nutrient restriction [NR]) and optimally-fed group. Rainbow trout were divided into four groups and, respectively, fed optimal diet (control), diet-containing CQ (6 mg/g), diet-containing DON (0.005 mg/g) or pair-fed the control diet. On days 0, 1, 3, 7, 14 and 21, liver and muscle were sampled to evaluate the expression of atg4, atg5, atg7, atg12, atg13, atg16, bec-1, gabarap and lc3. In both liver and muscle, CQ induced the highest number of Atgs, with eight in liver and seven in muscle; DON-induced six Atgs in liver and three in muscle; and pair-fed induced three Atgs in liver and two in muscle. In vitro, the effect of NR and CQ on Atg was examined in the RTL-W1 cell line. NR induced all Atg in RTL-W1, with the exception of bec-1. Furthermore, NR combined with CQ enhanced Atg expression greater than NR alone. Overall, CQ and DON can modulate Atg in rainbow trout, which can influence physiology and growth in aquaculture.
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".