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Record W1982664732 · doi:10.1021/es8005332

A Matter of Potential Concern: Natural Organic Matter Alters the Electrical Properties of Fish Gills

2008· article· en· W1982664732 on OpenAlexafffundabout
Fernando Gálvez, Andrew Donini, Richard C. Playle, D. Scott Smith, Michael J. O’Donnell, Chris M. Wood

Bibliographic record

VenueEnvironmental Science & Technology · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsMcMaster UniversityWilfrid Laurier University
FundersCanada Research Chairs
KeywordsGillEnvironmental chemistryNatural organic matterChemistryBioavailabilityOrganic matterBiotic Ligand ModelDissolved organic carbonFish <Actinopterygii>BiologyFisheryPharmacology

Abstract

fetched live from OpenAlex

Natural organic matter (NOM) is an important constituent of aquatic environments; however, its influence on aquatic biota remains poorly studied. In the current study, NOM was isolated from nine different sites in southern Ontario, Canada, by the on-site treatment of water by reverse osmosis, followed by cation exchange. NOM from each site was reconstituted to 10 mg of C/L and pH 7.0 and exposed to either adult rainbow trout implanted with indwelling catheters or to in vitro primary cultures of the gill epithelium grown on semipermeable membranes. In both the in vivo and in vitro preparations, NOM was found to hyperpolarize transepithelial potential (TEP), with the magnitude of this change correlating extremely well to the absorptivity of the NOM at 340 nm, which is an index of its aromaticity. Gill hyperpolarization appeared to be independent of Ca2+ complexation by the NOM in all but two samples tested. We argue that NOM has direct actions on the ionic transport and/or permeability properties of fish gills. While NOM effects on the bioavailability of contaminants are well-known, NOM actions on such fundamental physiological properties of the gills have previously been overlooked. These may be of comparable or greater magnitude than commonly reported for other water-quality variables (e.g., hardness, pH, salinity) and therefore of critical importance in ecological understanding and risk assessment.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.009
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.007
GPT teacher head0.178
Teacher spread0.171 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations94
Published2008
Admission routes3
Has abstractyes

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