Revealing the bovine embryo transcript profiles during early <i>in vivo</i> embryonic development
Why this work is in the frame
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Bibliographic record
Abstract
Gene expression profiling is proving to be a powerful approach for the identification of molecular mechanisms underlying complex cellular functions such as the dynamic early embryonic development. The objective of this study was to perform a transcript abundance profiling analysis of bovine early embryonic development in vivo using a bovine developmental array. The molecular description of the first week of life at the mRNA level is particularly challenging when considering the important fluctuations in RNA content that occur between developmental stages. Accounting for the different intrinsic RNA content between developmental stages was achieved by restricting the reaction time during the global amplification steps and by using spiked controls and reference samples. Analysis based on intensity values revealed that most of the transcripts on the array were present at some point during in vivo bovine early embryonic development, while the varying number of genes detected in each developmental stage confirmed the dynamic profile of gene expression occurring during embryonic development. Pair-wise comparison of gene expression showed a marked difference between oocytes and blastocysts profiles, and principal component analysis revealed that the majority of the transcripts could be regrouped into three main clusters representing distinct RNA abundance profiles. Overall, these data provide a detailed temporal profile of the abundance of mRNAs revealing the richness of signaling processes in early mammalian development. Results presented here provide better knowledge of bovine in vivo embryonic development and contribute to the progression of our current knowledge regarding the first week of life in mammals.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it