Thyroid hormones alter the transcriptome of <i>in vitro</i>-produced bovine blastocysts
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".