Identification of Porcine Oocyte Proteins That Are Associated with Somatic Cell Nuclei after Co-Incubation1
Bibliographic record
Abstract
Relatively little is known with respect to the oocyte proteins that are involved in nuclear reprogramming of somatic cells in mammals. The aim of the present study was to use a cell-free incubation system between porcine oocyte proteins and somatic cell nuclei and to identify oocyte proteins that remain associated with these somatic cell nuclei. In two separate experiments, porcine oocytes were either labeled with biotin to label total proteins at the germinal vesicle stage or metaphase II stage or they were labeled with 0.1 mM (35)S-methionine either during the first 6 h or 22-28 h of in vitro maturation to characterize protein synthesis during two distinct phases. To determine which oocyte proteins associate with somatic nuclei, labeled proteins were incubated in a collecting buffer and energy-regenerating system with isolated ovarian epithelial-like cell nuclei. After incubation, the nuclei were subjected to a novel affinity-binding system to recover biotin-labeled oocyte proteins or two-dimensional SDS-PAGE for separation and visualization of radiolabeled proteins. Proteins of interest were sent for identification using either matrix-assisted laser desorption/ionization time of flight or liquid chromatography-tandem mass spectrometry. Of the proteins that remain associated with isolated nuclei after incubation, 4 were identified using the affinity-binding system and 24 were identified using mass spectrometry and the two-dimensional gel interface. This study has identified porcine oocyte proteins that associate with somatic cell nuclei in a cell-free system using proteomics techniques, providing a novel way to identify oocyte proteins potentially functionally involved in nuclear reprogramming.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".