Protein synthesis is lowered by 4EBP1 and eIF2-α signaling while protein degradation may be maintained in fasting, hypoxic Amazonian cichlid, <i>Astronotus ocellatus</i>
Bibliographic record
Abstract
The Amazonian cichlid, Astronotus ocellatus, is highly tolerant to hypoxia, and is known to reduce its metabolic rate by reducing the activity of energetically expensive metabolic processes when oxygen is lacking in their environment. Our objectives were to determine how protein metabolism is regulated in A. ocellatus during hypoxia. Fish were exposed to a stepwise decrease in air saturation (100%, 20%, 10% and 5%) for 2 hours at each level, and sampled throughout the experiment. A flooding dose technique using a stable isotope allowed us to observe an overall decrease in protein synthesis during hypoxia in liver, muscle, gill and heart. We estimate that this decrease in rates of protein synthesis accounts for a 20 to 36% decrease in metabolic rate, which would enable oscars to maintain stable levels of ATP and prolong survival. It was also determined for the first time in fish that a decrease in protein synthesis during hypoxia is likely controlled by signaling molecules (4EBP1 and eIF2-α), and not simply due to a lack of ATP. We could not detect any effects of hypoxia on protein degradation as the levels of NH4 excretion, indicators of the ubiquitin proteasome pathway, and enzymatic activities of lysosomal and non-lysosomal proteolytic enzymes were maintained throughout the experiment.
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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".