Glycerol uptake is by passive diffusion in the heart but by facilitated transport in RBCs at high glycerol levels in cold acclimated rainbow smelt (Osmerus mordax)
Bibliographic record
Abstract
Rainbow smelt (Osmerus mordax) is a small fish that accumulates glycerol at low winter seawater temperatures. In laboratory-held fish, glycerol concentration typically reaches 225 mM in plasma and in all cells. Glycerol uptake by the heart and red blood cells (RBCs) was assessed by tracking [(14)C(U)]glycerol into the acid-soluble pool. In fish acclimated to 9-10°C a decrease in perfusion/incubation temperature from 8 to 1°C resulted in a decrease in glycerol uptake with a Q(10) of 3.2 in heart and 2.4 in RBCs. Acclimation to ∼1.5°C did not result in an adaptive enhancement of glycerol uptake as rates were unchanged in heart and RBCs. Glycerol uptake at 1°C was by passive diffusion in heart as evidenced by a linear relationship between glycerol uptake and extracellular glycerol concentration and a lack of inhibition by phloretin. In contrast, in RBCs, glycerol uptake with respect to glycerol concentration showed two linear relationships with a transition point around 50 mM extracellular glycerol. The slope of the second phase was much steeper and eliminated with the inclusion of phloretin. In RBCs from Atlantic salmon (Salmo salar), a related species that does not accumulate glycerol, glycerol uptake showed only a single linear curve and was not inhibited by phloretin. The data imply a strong facilitated component to glycerol uptake in rainbow smelt RBCs at high glycerol concentrations. We propose this is related to cyclic changes in RBC glycerol content involving a loss of glycerol at the gill and a reaccumulation during passage through the liver.
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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".