Bibliographic record
Abstract
For most creatures, urea is a nasty toxin best got rid of, but for many elasmobranchs, it keeps them in balance with their salty environment. Yet despite this apparently amicable relationship, high tissue levels of urea still have nasty side effects on proteins. Jason Treberg in William Driedzic's Newfoundland Lab knew from George Somero and Paul Yancey's work that proteins become stable when the ratio of urea to methylamines is 2:1, but there were only a few measurements of this ratio in marine elasmobranchs. Was this ratio wide spread amongst elasmobranchs, and if so, were methylamines alone responsible for balancing their high urea levels? Treberg began measuring tissue levels of methylamines in a range of fish from the marine shark Chiloscyllium punctatum to the freshwater Brazilian stingray to find out whether the ratio held up to closer scrutiny(p. 860).Treberg admits that obtaining samples from a wide range of species was probably the most daunting aspect of this project. James Ballantyne, Ben Speers-Roesch and Alex Ip supplied Treberg with samples from a marine stingray, a shark and two freshwater stingrays (one that retains some urea while the other does not), while Peter Piermarini had access to a euryhaline stingray (able to tolerate marine and freshwater environnments) to add to the marine skate that Treberg could obtain himself.Sure enough, the methylamine levels behaved as Treberg had expected, with the highest detected in the marine species while the freshwater species had virtually none, and the euryhaline species carrying intermediate levels. And when Treberg calculated the ratio of urea to a methylamine trimethylamine N-oxide (TMAO), alone, it was approximately 2:1 in the marine species, while some of freshwater species' had a higher ratio and others lower. Were the freshwater adapted species turning to other osmolytes to stay in equilibrium with their environment?Turning to HPLC methods to discover which osmolytes these species carried,Treberg found that both freshwater species accumulated more β-amino acids than methylamines. When he calculated the urea to total osmolyte ratio and plotted the relationship on a graph, it was close to 2:1. Treberg explains that the urea levels in freshwater adapted species are so low that the ratio in the Brazilian stingray is only very approximate. Also, he suspects that the ratio isn't always driven by the need to counterbalance urea's detrimental effects, but to maintain the fishes' delicate osmotic equilibria with their aquatic environment.Curious to know whether the activities of the enzymes responsible for synthesising TMAO and betaine varied in line with the elasmobranch's methylamine levels, Treberg measured TMAoxidase levels from all seven species'and was surprised that only the shark possessed the enzyme; the rest probably derive TMAO from their diet. However, all of the elasmobranchs were capable of synthesising betaine. Treberg explains one possibility: that the shark is the only fish in this study to have retained TMAoxidase, while the rest may have lost the enzyme, deriving TMAO from their diet and supplementing with betaine when TMAO is scarce. But he adds that it is also possible that several species evolved TMAO synthesis independently, and it's impossible to be sure which is most likely.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".