Effect of salt and brine-beet juice de-icer on osmoregulatory physiology of the freshwater amphipod <i>Hyalella azteca</i> (Saussure, 1858) (Amphipoda: Hyalellidae)
Bibliographic record
Abstract
Abstract The anthropogenic salinization of freshwater is concerning because it can negatively impact the success and survival of freshwater animals. Road salt (NaCl) in cold climates contributes to salinization and organic based de-icers have been developed to mitigate the effects of NaCl on freshwater. One of these de-icers is sugar beet juice, and few studies have examined its effects on freshwater animals. We exposed Hyalella azteca (Saussure, 1858), a freshwater amphipod, to different concentrations of NaCl (salt-contaminated water or SCW) and a NaCl brine and beet-juice mixture used as a de-icing product (brine-beet juice de-icer, BBJD). The LC50 of NaCl on H. azteca was 12.8 g l–1 and for BBJD was 4.6% (which at that percentage contained ~ 4.2 g l–1 Na+). Sub-lethal doses of SCW elevated hemolymph Na+ and BBJD exposure resulted in elevated K+ concentration as well as acidification of the hemolymph. Both Na+/K+ ATPase (NKA) and V-type H+-ATPase (VA) were localized to the coxal gills, whereas only NKA was found in the sternal gills. There was a qualitatively apparent decrease in expression of NKA in the gills of SCW-treated amphipods. NKA and VA expression qualitatively increased with BBJD exposure in the gut. The NKA and VA activity in whole-body homogenates was lower in BBJD and SCW. Results show that Hyalella azteca responds to SCW and BBJD by altering parameters of ionoregulatory physiology in different ways.
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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 | 0.001 |
| 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".