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Record W3210700654 · doi:10.1242/jeb.237412

Hypoxic hagfish gills binge calcium

2021· article· en· W3210700654 on OpenAlexaffabout
Brittney G. Borowiec

Bibliographic record

VenueJournal of Experimental Biology · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsHagfishCalciumOxygenGillHypoxia (environmental)ChemistryZoologyAnatomyBiologyFish <Actinopterygii>FisheryBiochemistryVertebrate

Abstract

fetched live from OpenAlex

Slimy, tentacle-faced hagfish look like aliens and, accordingly, possess several PhD theses’ worth of unusual traits. Their body fluids have a similar number of dissolved salts to seawater, although because hagfish control the levels of some ions like calcium in their blood, the mix of salts is slightly different. Hagfish are also famously tolerant of low oxygen conditions (hypoxia), which comes in handy when they burrow inside rotting whales to dine. In some fishes, hypoxia disrupts how they manage the delicate balance between their internal salts and the salts in their surroundings as they cut back on the energy-intensive process of ion movement to save energy. But what about hagfish with their unusual balance of salts? And what happens when oxygen is scarce? Chris Glover of Athabasca University, Canada, and Greg Goss of the University of Alberta, Canada, decided to find out.Glover and Goss hypothesized that their slimy beasts would do the same as other fish when oxygen was in short supply: decreasing calcium uptake and accumulation. They tested this idea by placing hagfish in air-tight jars and tracking the movement of mildly radioactive calcium into their tissues as they used up the available oxygen.Unlike the hagfish in open jars, the hagfish in sealed jars moved calcium quickly into most of their tissues, including skin, liver, muscle, heart, plasma and brain. Low oxygen levels also bumped up the rates of calcium build-up in their gut and especially their gills; the guts of the fish in the low oxygen conditions had nearly 4 times more calcium than the guts of the fish in oxygen-rich conditions after adjusting for calcium contained in the blood flowing through the tissue. Since hagfish have no bones to leech calcium from, these results meant that, contrary to expectations, hagfish responded to hypoxia by importing more calcium into their bodies.When an animal does something you don't expect, the next questions are usually: how and why? Tackling the first question, Glover and Goss focused on how calcium moved across hagfish skin and gut tissue when it was isolated from the rest of the body with the goal of understanding the role each tissue played in the hypoxic fish's calcium binge.They discovered that low oxygen in the environment reduced calcium uptake by the skin, but only when the experiment was performed in unnaturally low calcium conditions, so this was unlikely to be a major mechanism of calcium accumulation in living animals. However, the results in the gut tissue were more puzzling. Despite surging calcium levels in the gut under hypoxia, there were no differences in the calcium uptake rates between the guts of the hagfish that had been kept in normal levels of oxygen and those that were oxygen starved. The authors mused that perhaps the sealed-in hagfish had gulped down seawater as a reaction to the stress, accidently flushing the tissue with calcium in the process. With the skin and gut ruled out as major importers of calcium into the body, the researchers determined that the gills were the source of the calcium detected in the closed-jar hagfish, which squares with the impressive rate of calcium accumulation observed in this tissue.Hagfish are peculiar creatures, so it's perhaps unsurprising that they respond so differently from most other earthbound fishes. As for why hypoxic hagfish pull in so much calcium through their gills, that remains a mystery. Calcium could possibly aid in coping with low oxygen conditions by constricting blood vessels or protecting brains cells. Alternatively, the calcium accumulation might not be a strategy at all and could simply be a result of hagfish moving more water – and consequently calcium – through their gills; but that's a study for another time.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.033
GPT teacher head0.287
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes2
Has abstractyes

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