Adjustments of cardiac mitochondrial phenotype in a warmer thermal habitat is associated with oxidative stress in European perch, Perca fluviatilis
Bibliographic record
Abstract
Mitochondria are playing key roles in setting the thermal limits of fish, but how these organelles participate in selection mechanisms during extreme thermal events associated with climate warming in natural populations is unclear. Here, we investigated the thermal effects on mitochondrial metabolism, oxidative stress, and mitochondrial gene expression in cardiac tissues of European perch (Perca fluviatilis) collected from an artificially heated ecosystem, the "Biotest enclosure", and an adjacent reference area in the Baltic sea with normal temperatures (~ 23 °C and ~ 16 °C, respectively, at the time of capture in summer). Fish were sampled one month after a heat wave that caused the Biotest temperatures to peak at ~ 31.5 °C, causing significant mortality. When assayed at 23 °C, Biotest perch maintained high mitochondrial capacities, while reference perch displayed depressed mitochondrial functions relative to measurements at 16 °C. Moreover, mitochondrial gene expression of nd4 (mitochondrial subunit of complex I) was higher in Biotest fish, likely explaining the increased respiration rates observed in this population. Nonetheless, cardiac tissue from Biotest perch displayed higher levels of oxidative damage, which may have resulted from their chronically warm habitat, as well as the extreme temperatures encountered during the preceding summer heat wave. We conclude that eurythermal fish such as perch are able to adjust and maintain mitochondrial capacities of highly aerobic organs such as the heart when exposed to a warming environment as predicted with climate change. However, this might come at the expense of exacerbated oxidative stress, potentially threatening performance in nature.
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) | 0.000 | 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".