Impacts of severity and region of gill tissue resection on regeneration in Atlantic salmon (Salmo salar)
Bibliographic record
Abstract
In a previous study, we demonstrated successful regeneration of Atlantic salmon gill tissue following up to 50 % filament resection. The present study explored 1) the capacity of gill tissue to regenerate following more severe trauma, 2) if regeneration potential varies across regions of the arch, and 3) how tissue loss impacts the physiology of neighboring unresected filaments. Fish were divided between two resected groups and a control non-resected one. In resection group-1, fish underwent 50 % and 75 % resection in the ventral and medial-dorsal regions of the first arch, while in resection group-2, the location of resection levels was reversed. The degree of filament regeneration and physiology of unresected filaments were measured at 4, 12 and 20 weeks-post-resection (WPR). Overall, the degree of regeneration was significantly higher in 50 % resected filaments relative to 75 % resected filaments. The degree of regeneration did not differ significantly between the resected groups for either of resection levels, suggesting negligible impact of filament location on arch on regeneration. The concentration of oxidized glutathione (GSSG), total glutathione (GSH), and citrate synthase activity (CSA) in intact filaments were comparable between resected and control fish at both 4 and 20 WPR. However, GSH concentration varied among resected fish with those exhibited higher GSH in intact filaments showed lower regeneration of 50 % resected filaments at 20 WPR. Our results indicate that gill tissue loss exceeding 50 % may significantly impair regeneration and that this level of tissue loss is not associated with a compensatory response (e.g. GSSG, GSH, CSA) of neighboring gill tissue.
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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 | 0.001 |
| 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".