Decorin Is a Novel VEGFR-2 Binding Antagonist for the Human Extravillous Trophoblast.
Bibliographic record
Abstract
Extravillous trophoblast (EVT) cells of the human placenta invade the uterine decidua and its arteries to nourish the fetus. We identified two decidua-derived molecules TGF-β, and a TGF-β binding small leucine-rich proteoglycan decorin (DCN) which independently controlled EVT cell proliferation, migration and invasiveness. Multiple tyrosine kinase receptors EGF-R, IGFR-1 and VEGFR-2 were shown to mediate these DCN actions. Since DCN binding to VEGFR-2 has never been reported before, we explored the characteristics of this binding and the identity of VEGFR-2 binding sites of DCN in our human first trimester EVT cell line HTR-8/SVneo; and whether this binding antagonised VEGF-induced cellular proliferation and migration. DCN binding to VEGFR-2 in EVT cell lysate or pure recombinant VEGFR-2/Fc chimera was shown with far-western blotting and co-immunoprecipitation. VEGFR-2 lacking Human Embryonic kidney (HEK) cells were used as a negative control. The binding was abrogated with a VEGFR-2 blocking antibody indicating an overlap between the ligand-binding and the DCN-binding domains of VEGFR-2. 125I-labeled VEGF-E (a VEGFR-2 specific ligand) bound to intact EVT cells, with a Kd of 566 pM, and DCN displaced this binding with a Ki of 5.78nM, indicating a 10 fold lower affinity of DCN for VEGFR-2. DCN peptide fragments in the leucine-rich repeat (LRR)-5 domain that preferentially blocked DCN-VEGFR-2 binding in EVT cell proteins also blocked VEGF-induced EVT cell proliferation and migration, indicative of functional VEGFR-2 binding sites of DCN. Our novel findings of DCN as an antagonistic ligand for VEGFR-2 and its ability to block EVT cell migration has implications for pathobiology of preeclampsia, a trophoblast hypo-invasive disorder in pregnancy, and explains its anti-angiogenic role. (Supported by funds from the Canadian Institutes of Health Research to PKL) (poster)
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 | 0.000 | 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 | 0.001 |
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".