The number of primitive endoderm cells in the inner cell mass is regulated by platelet-derived growth factor signaling in porcine preimplantation embryos
Bibliographic record
Abstract
OBJECTIVE: Discovering the mechanism of cell specification is important to manipulate cellular lineages. To obtain lineage-specific cell lines, the target lineage needs to be promoted, and counterpart lineages should be suppressed. Embryos in the early blastocyst stage possess two different cell populations, the inner cell mass (ICM) and trophectoderm. Then, cells in the ICM segregate into epiblasts (Epi) and primitive endoderm (PrE). PrE cells in embryos show specific expression of platelet-derived growth factor (PDGF) and its receptor, PDGF receptor A (PDGFRA). In this study, we suppressed PDGF signaling using two methods (CRISPR/Cas9 injection and inhibitor treatment) to provide insight into the segregation of embryonic lineages. METHODS: CRISPR/Cas9 RNAs were injected into parthenogenetically activated and in vitro fertilized embryos. The PDGF receptor inhibitor AG1296 was treated at 0, 5, 10, and 20 μM concentration. The developmental competence of the embryos and the number of cells expressing marker proteins (SOX2 for ICM and SOX17 for PrE) were measured after the treatments. The expression levels of the marker genes with the inhibitor were examined during embryo development. RESULTS: Microinjection targeting the PDGF receptor (PDGFR) A reduced the number of SOX17-positive cell populations in a subset of day 7 blastocysts (n = 9/12). However, microinjection accompanied diminution of Epi cells in the blastocyst. The PDGF receptor inhibitor AG1296 (5 μM) suppressed SOX17-positive cells without reducing SOX2-positive cells in both parthenogenetic activated and in vitro fertilized embryos. Within the transcriptional target of PDGF signaling, the inhibitor significantly upregulated the Txnip gene in embryos. CONCLUSION: We identified that PDGF signaling is important to sustain the PrE population in porcine blastocysts. Additionally, treatment with inhibitors was a better method to suppress PrE cells than CRISPR/Cas9 microinjection of anti-PDGF receptor α gene, because microinjection suppressed number of Epi cells. The PDGF receptor might control the number of PrE cells by repressing the proapoptotic gene Txnip. Our results can help to isolate Epi-specific cell lines from blastocysts.
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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".