A peptide inhibitor of synuclein- reduces neovascularization of human endometriotic lesions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Endometriosis is a chronic painful gynecological condition characterized by adherence and growth of endometrium outside of the uterine cavity. Neovascularization is essential to the developing endometriosis lesion to support its growth. Synuclein-γ (SNCG), a protein implicated in cellular proliferation, is associated with a broad range of malignancies as well as endometriosis. We hypothesized that SNCG plays an important role in the neovascularization and growth of endometriosis and blocking of SNCG will interfere with survival of endometriotic lesions in a mouse model. We developed SP012, a novel 12 amino acid peptide inhibitor of SNCG. SP012 inhibited three-dimensional endothelial cell tube formation in a dose-dependent manner. Using intravital microscopy, SP012 was shown to be successfully delivered to human endometriotic lesions in a xenograft mouse model in vivo. Alymphoid (BALB/c-Rag2-/-Il2rγ-/- lacking T, B and NK cells) mice were surgically induced with human endometriotic lesions and treated with SP012 or phosphate-buffered saline control. SP012 treated endometriotic lesions had decreased growth, development and vascularization at the time of necroscopy. Endometriotic lesions treated with SP012 also had fewer isolectin (+) microvessels. These results, using a mouse model, indicate that SNCG plays a role in the neovascularization and subsequent growth of human endometriotic lesions. Targeting SNCG function using peptide inhibitor might provide a potential therapeutic option for the treatment of endometriosis in the future.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| 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) | 0.000 | 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 it