Possible Angiogenic Roles of Insulin-Like Growth Factor II and Its Receptors in Uterine Vascular Adaptation to Pregnancy
Bibliographic record
Abstract
Adaptation of the maternal uterine vasculature is essential for normal fetal and placental development in which angiogenesis is considered one of the most critical adaptive changes during pregnancy. Highly expressed in cytotrophoblasts and maternal endothelial cells during pregnancy, IGF-II promotes cell migration and regulates fetal and placental growth. We hypothesized that IGF-II regulates uterine angiogenesis during pregnancy. Both uterine vasculature and isolated uterine microvascular endothelial cells expressed high levels of IGF-II and IGF-II/mannose-6 phosphate receptor mRNA as shown by in situ hybridization. Physiological concentrations of IGF-II significantly increased vessel formation, as shown by a three-dimensional angiogenesis assay in vitro or a chicken chorionallantoic membrane assay in vivo. The angiogenic response of IGF-II could be reversed by the addition of beta-galactosidase or rabbit-antihuman IGF-II/M6P receptor antiserum, whereas blocking antibodies against IGF-I receptor or insulin receptor influenced IGF-II-induced sprout formation. IGF-II promoted migration of endothelial cells (10-250 ng/ml) tested in a modified Boyden chamber, but no stimulating effect on proliferation was observed. The application of several intracellular signal transduction molecules and their inhibitors indicated that protein kinase C and G(i) protein might play a role in the IGF-II-induced angiogenesis. Our results suggest an important angiogenic role of IGF-II in the vascular adaptation to pregnancy.
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 | 0.001 |
| 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".