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Record W2156437908 · doi:10.1002/gene.10205

Metaphase FISHing of transgenic mice recommended: FISH and SKY define BAC‐mediated balanced translocation

2003· article· en· W2156437908 on OpenAlexaff
Brett S. Abrahams, Annabelle C.O. Chong, M. Barakath Nisha, Danielle Milette, David A. Brewster, Melissa L. Berry, Farkhad Muratkhodjaev, Sabine Mai, Evica Rajcan‐Separovic, Elizabeth M. Simpson

Bibliographic record

Venuegenesis · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Genetics and Reproduction
Canadian institutionsUniversity of ManitobaCancerCare ManitobaChildren's & Women's Health Centre of British ColumbiaUniversity of British Columbia
FundersNational Institute of Mental Health
KeywordsTransgeneChromosomal translocationBreakpointMetaphaseBiologyBacterial artificial chromosomeGeneticsFish <Actinopterygii>Genetically modified mouseGeneMolecular biologyChromosomeGenomeFishery

Abstract

fetched live from OpenAlex

The evolving trend to use larger transgenes and their associated increased chance of unexpected genetic events mandates more careful characterization of transgenic mice. In characterizing our five new mouse strains transgenic for the BAC, bEMS4, we have identified the highest copy number reported to date: the stable incorporation of approximately 40 copies of a 194-kb expressed transgene in a single insertion site. We caution, however, that standard molecular techniques failed to identify a balanced translocation in another strain, and an inappropriate site of insertion in a third. Molecular cytogenetic analysis using metaphase FISH was the minimum level of characterization needed to reveal these unexpected genetic events. In addition, we combined FISH and SKY to identify the transgene at the breakpoints of the balanced translocation, t(3;9). This is the first description of a BAC-mediated chromosomal rearrangement and the first application of SKY to identify transgene-induced chromosomal rearrangements.

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 categoriesnone
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 score0.029
Threshold uncertainty score0.457

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)0.0000.000

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 head0.012
GPT teacher head0.229
Teacher spread0.216 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations15
Published2003
Admission routes1
Has abstractyes

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