Digestion under Duress: Nutrient Acquisition and Metabolism during Hypoxia in the Pacific Hagfish
Bibliographic record
Abstract
Hagfish feed by immersing themselves in the body cavities of decaying animals. This ensures a rich nutrient source for absorption via the gills, skin, and gut, but it may also subject hagfish to reduced levels of dissolved oxygen and elevated levels of the products of biological degradation. This study investigated the impacts of hypoxia and ammonia on the assimilation and metabolism of selected nutrients (glycine, l-alanine, and glucose) in Pacific hagfish (Eptatretus stoutii). Throughout exposure to hypoxia, plasma glucose levels increased. This was not accompanied by an increase in gut glucose transport, which suggests mobilization of glucose from body glycogen stores. Hypoxia preexposure enhanced glycine absorption across the gut and the gill, although l-alanine uptake was unchanged in these tissues. A 24-h period of exposure to hypoxia in hagfish concurrently exposed to waterborne radio-labeled glycine led to a large (5.7-fold) increase in brain glycine accumulation. Preexposure to high levels of waterborne ammonia (10 mM) for 24 h had no impact on gut or skin glycine uptake. These results indicate that hagfish are adapted to maintain nutrient assimilation despite environmental stressors and that tissue-specific absorption of key nutrients such as glycine can even be enhanced in order to sustain critical functions during hypoxia.
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".