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Record W2088885715 · doi:10.1139/g04-087

Endonuclease banding reveals that atrazine-induced aneuploidy resembles spontaneous chromosome loss in <i>Crassostrea gigas</i>

2005· article· en· W2088885715 on OpenAlexvenueno aff
Karine Bouilly, Alexandra Leitão, Raquel Chaves, Henrique Guedes‐Pinto, Pierre Boudry, Sylvie Lapègue

Bibliographic record

VenueGenome · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyCrassostreaPacific oysterAneuploidyKaryotypeGeneticsChromosomeHaeIIIRestriction enzymeAtrazineMolecular biologyOysterPolymerase chain reactionDNAFisheryGeneEcologyRestriction fragment length polymorphism

Abstract

fetched live from OpenAlex

Aneuploidy has previously been observed in the Pacific oyster, Crassostrea gigas, and shown to be negatively correlated with growth. Moreover, a significant impact of atrazine exposure has been described in C. gigas, and persistence of that effect has been observed between generations. Evidence of differential chromosome loss has been demonstrated in aneuploid karyotypes of C. gigas using the G-banding technique. Pairs 1, 5, 9, and 10 are characterized by the loss of 1 chromosome. As restriction enzyme (RE) digestion chromosome banding allows a better identification of chromosome pairs, we used this technique to identify which chromosomes are affected when aneuploidy is increased by exposure to atrazine. The progeny of oysters contaminated by atrazine were analysed using the restriction enzyme HaeIII. The study of 26 RE-banded aneuploid karyotypes showed that the same chromosome pairs (1, 5, 9, and 10) were affected by the loss of 1 chromosome (61%, 15%, 42%, and 42%, respectively). Further investigation is required to enable a better understanding of aneuploidy in oysters, especially with respect to why some chromosomes are more easily lost than others, and why cells tolerate the loss of these chromosomes.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.817
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.004

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 head0.021
GPT teacher head0.289
Teacher spread0.268 · 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; both teacher heads agree on what is shown here.

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

Citations20
Published2005
Admission routes1
Has abstractyes

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