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Record W2107251344 · doi:10.1017/s0967199415000167

Thyroid hormones alter the transcriptome of <i>in vitro</i>-produced bovine blastocysts

2015· article· en· W2107251344 on OpenAlexaff
F. A. Ashkar, Tamás Révay, Na-Young Rho, Pavneesh Madan, Isabelle Dufort, Claude Robert, Laura A. Favetta, Chris Schmidt, W.A. King

Bibliographic record

VenueZygote · 2015
Typearticle
Languageen
FieldMedicine
TopicReproductive Biology and Fertility
Canadian institutionsUniversité LavalUniversity of Guelph
FundersNational Institutes of Health
KeywordsTranscriptomeHormoneIn vitroThyroid hormonesThyroidChemistryCell biologyAndrologyBiologyEndocrinologyBiochemistryGene expressionMedicineGene

Abstract

fetched live from OpenAlex

Thyroid hormones (THs) have been shown to improve in vitro embryo production in cattle by increasing blastocyst formation rate, and the average cell number of blastocysts and by significantly decreasing apoptosis rate. To better understand those genetic aspects that may underlie enhanced early embryo development in the presence of THs, we characterized the bovine embryonic transcriptome at the blastocyst stage, and examined differential gene expression profiles using a bovine-specific microarray. We found that 1212 genes were differentially expressed in TH-treated embryos when compared with non-treated controls (>1.5-fold at P < 0.05). In addition 23 and eight genes were expressed uniquely in control and treated embryos, respectively. The expression of genes specifically associated with metabolism, mitochondrial function, cell differentiation and development were elevated. However, TH-related genes, including those encoding TH receptors and deiodinases, were not differentially expressed in treated embryos. Furthermore, the over-expression of 52 X-chromosome linked genes in treated embryos suggested a delay or escape from X-inactivation. This study highlights the significant impact of THs on differential gene expression in the early embryo; the identification of TH-responsive genes provides an insight into those regulatory pathways activated during development.

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)0.001
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 score0.351
Threshold uncertainty score0.281

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.032
GPT teacher head0.280
Teacher spread0.248 · 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

Citations6
Published2015
Admission routes1
Has abstractyes

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