Exposure to NaCl and beet juice brine de-icers alters the function of Malpighian tubules and anal papillae of chironomids (<i>Chironomus riparius</i>)
Bibliographic record
Abstract
Salinization of freshwater by anthropogenic activities is a global issue and the use of de-icers in cold climates is turning out to be a major contributor to this problem. The most common de-icer is sodium chloride (NaCl) in the form of rock salt or brine, but because the harmful accumulation of NaCl in nearby freshwater systems is well recognized, newer organic de-icers, such as sugar beet juice, have been developed. Detrimental effects of NaCl on freshwater animals have been documented but the potential effects of organic based de-icers are virtually unknown. Insects are one of the most abundant groups of freshwater animals that perform services vital to ecosystem health. Hence, the aim of this study is to examine the effects of NaCl and a commercially available brine beet juice de-icer (BBJD) on the osmoregulatory physiology of a ubiquitous freshwater insect, the larvae of the midge Chironomus riparius. Larvae were exposed to sub-lethal doses of the de-icers for 24 h, and the osmoregulatory status of the larvae, and function of the Malpighian tubules (MTs) and anal papillae (AP) were assessed. Hemolymph [K+] was tightly regulated, while [Na+] was elevated by both de-icers. BBJD caused some dehydration. Larvae reduced ion uptake by the AP where Na+ secretion occurred with the NaCl treatment. BBJD also altered MT function such that the MTs cleared more K+. BBJD presents its own significant challenges to the osmoregulatory physiology of C. riparius larvae, and the relatively high levels of K+ from the sugar beets could pose a new issue for freshwater habitats.
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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) | 0.002 | 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".