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Biological effects of tritium on fish cells in the concentration range of international drinking water standards

2016· article· en· W6977420018 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicRadioactive contamination and transfer
Canadian institutionsnot available
Fundersnot available
KeywordsMinnowTritiumCatfishGenotoxicityEcotoxicologyMicronucleus testFish <Actinopterygii>Micronucleus

Abstract

fetched live from OpenAlex

<i>Purpose:</i> To evaluate whether the current Canadian tritium drinking water limit is protective of aquatic biota, an <i>in-vitro</i> study was designed to assess the biological effects of low concentrations of tritium, similar to what would typically be found near a Canadian nuclear power station, and higher concentrations spanning the range of international tritium drinking water standards. <i>Materials and methods:</i> Channel catfish peripheral blood B-lymphoblast and fathead minnow testis cells were exposed to 10-100,000 Bq L<sup>−1</sup> of tritium, after which eight molecular and cellular endpoints were assessed. <i>Results:</i> Increased numbers of DNA strand breaks were observed and ATP levels were increased. There were no increases in γH2AX-mediated DNA repair. No differences in cell growth were noted. Exposure to the lowest concentrations of tritium were associated with a modest increase in the viability of fathead minnow testicular cells. Using the micronucleus assay, an adaptive response was observed in catfish B-lymphoblasts. <i>Conclusions:</i> Using molecular endpoints, biological responses to tritium in the range of Canadian and international drinking water standards were observed. At the cellular level, no detrimental effects were noted on growth or cycling, and protective effects were observed as an increase in cell viability and an induced resistance to a large challenge dose.

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 categoriesInsufficient 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 score0.246
Threshold uncertainty score0.951

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0500.000

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 head0.016
GPT teacher head0.234
Teacher spread0.219 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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