Proteomics reveals substantial differences between in vitro matured abattoir-derived and in vivo matured oocytes in cattle
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In vitro production (IVP) of bovine embryos still has its limitations, such as low blastocyst rate and lower embryo quality, resulting in lower pregnancy rates following transfer compared to in vivo produced embryos. Transcriptional studies comparing both types of embryos mainly utilized oocytes retrieved from slaughterhouse material for IVP, thereby introducing the possibility, that differences between IVP and in vivo embryos are in part attributable to differing sources of oocytes. The aim of the present study was therefore to compare the proteome of oocytes retrieved from slaughterhouse material, with and without a period of in vitro maturation, and in vivo matured oocytes obtained from superovulated donor cattle. For each group the protein pattern of four technical replicates containing ten oocytes each were analyzed via SWATH™-MS. In total, 1208 proteins were detected, 160 of which were differentially abundant in at least one group comparisons. Clustering analysis revealed that oocyte maturation environment is the primary driver of molecular difference, with the in vitro matured oocytes exhibiting a highly distinct proteome compared to both the in vivo matured and immature oocytes. In vitro matured oocytes were characterized by an overall enhanced translational activity affecting mainly proteins involved in energy metabolism, transcription and translation, and oocyte activation. An organized regulation of key pathways was observed during oocyte maturation in vivo, e.g. activation of autophagy and apoptosis pathways, while changes in protein abundance in vitro seem to be undirected. This deregulation of the proteome in in vitro matured oocytes likely negatively affect subsequent developmental events.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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