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Record W2889817330 · doi:10.3390/environments5090102

Cytosolic Distribution of Metals (Cd, Cu) and Metalloids (As, Se) in Livers and Gonads of Field-Collected Fish Exposed to an Environmental Contamination Gradient: An SEC-ICP-MS Analysis

2018· article· en· W2889817330 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEnvironments · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsCadmiumMetallothioneinInductively coupled plasma mass spectrometryMetalloidEnvironmental chemistryChemistryContaminationBiomoleculeMetalArsenicFish <Actinopterygii>ChromatographyMass spectrometryBiochemistryBiologyEcologyFishery

Abstract

fetched live from OpenAlex

The distribution of As, Cd, Cu and Se among biomolecules of different molecular weight (MW) in the heat-treated cytosolic fraction of livers and gonads of white suckers (WS; Catostomus commersonii) collected in a reference lake and in a lake subject to multi-metal contamination was investigated. Distribution profiles were obtained by separation of the heat-stable protein and peptide (HSP) fractions using size-exclusion high performance-liquid chromatography, coupled online to an inductively coupled plasma mass spectrometer, to quantify the associated metals. Metal-handling strategies did not vary between the reference and exposed fish, with the exception of As. Cadmium and Cu appeared associated with the heat-stable peptides metallothioneins (MTs), indicating their reasonable detoxification and regulation in WS. In contrast, Se and As were not bound to MTs, but rather, to biomolecules of lower MW (&lt;2 kDa). Arsenic was found associated with the same biomolecules in fish from both lakes, but their proportions changed between reference and exposed fish. For future work, the identification of the Se and As binding biomolecules would be of great interest to determine if these metalloids are detoxified or if, conversely, the biomolecules are metal-sensitive and their binding to Se or As represents a threat for the health of these fish.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.307
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.009
GPT teacher head0.234
Teacher spread0.224 · 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