Urea and KCl have differential effects on enzyme activities in liver and muscle of estivating versus nonestivating species
Bibliographic record
Abstract
The effects of 300 mM urea or 300 mM KCl on the maximal activities of 25 enzymes of intermediary metabolism were assessed in extracts of liver and muscle from spadefoot toads (Scaphiopus couchii), leopard frogs (Rana pipiens), and rats to assess their sensitivity to these osmolytes. During estivation, toads can lose -50% of total body water, and urea, which is known for its action as a protein denaturant, accumulates to 200-300 mM. The data show that the maximal activities of toad liver enzymes were not affected when assayed in the presence of 300 mM urea in vitro whereas urea inhibited the activities of seven enzymes in frog and 11 enzymes in rat liver. High KCl affected 12 or 13 enzymes in liver of each species causing inhibition in eight or nine cases each, and for frog and rat enzymes, inhibition was frequently more pronounced than for urea. Both urea and KCl affected enzyme activities in muscle extracts of all three species, but whereas their effects were largely negative for frog and rat enzymes, the enzymes affected by urea or KCl in toad muscle were primarily activated by these osmolytes (six out of nine enzymes affected by urea and eight of 15 enzymes affected by KCl). Urea, KCl, and polyethylene glycol (a protein crowding agent) also had species-specific effects on the dissociation constant (Ka) for cAMP of protein kinase A. The data suggest that the accumulation of urea by water-stressed anurans not only contributes to minimizing cell volume reduction, but by doing so also limits the increase in intracellular ionic strength that occurs and thereby helps to minimize the potential inhibitory effects of high salts on metabolic enzymes.
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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".