Quantitative proteomics analysis of parthenogenetically induced pluripotent stem cells
Bibliographic record
Abstract
Parthenogenetic embryonic stem (pES) cells isolated from parthenogenetic activation of oocytes and embryos, also called parthenogenetically induced pluripotent stem cells, exhibit pluripotency evidenced by both in vitro and in vivo differentiation potential. Differential proteomic analysis was performed using differential in-gel electrophoresis and isotope-coded affinity tag-based quantitative proteomics to investigate the molecular mechanisms underlying the developmental pluripotency of pES cells and to compare the protein expression of pES cells generated from either the in vivo-matured ovulated (IVO) oocytes or from the in vitro-matured (IVM) oocytes with that of fertilized embryonic stem (fES) cells derived from fertilized embryos. A total of 76 proteins were upregulated and 16 proteins were downregulated in the IVM pES cells, whereas 91 proteins were upregulated and 9 were downregulated in the IVO pES cells based on a minimal 1.5-fold change as the cutoff value. No distinct pathways were found in the differentially expressed proteins except for those involved in metabolism and physiological processes. Notably, no differences were found in the protein expression of imprinted genes between the pES and fES cells, suggesting that genomic imprinting can be corrected in the pES cells at least at the early passages. The germline competent IVM pES cells may be applicable for germ cell renewal in aging ovaries if oocytes are retrieved at a younger age.
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 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 | 0.001 | 0.001 |
| 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".