Vascular progenitors derived from murine bone marrow stromal cells are regulated by fibroblast growth factor and are avidly recruited by vascularizing tumors
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
Bone marrow-derived stromal cells (BMSC) possess a population of vascular progenitor cells that enable them to acquire a histology and immunophenotype coherent with endothelial cells (EC). Recent evidence indicates that a hypoxic environment such as that encountered in tumor masses regulates BMSC angiogenic properties by pathways that remain to be defined. It is also unclear as to what extent these marrow-derived precursor cells could contribute to the growth of endothelium-lined vessels at the vicinity of tumor masses. In this study, we found that BMSC exhibited the ability to generate three-dimensional capillary-like networks on Matrigel, and that this property was up-regulated by growth factors-enriched conditioned media isolated from several tumor-derived cell lines. In particular, basic fibroblast growth factor, a key mediator of angiogenesis, was found to be the most potent growth factor for inducing BMSC proliferation, migration, and tubulogenesis. The setup of a new two-dimensional in vitro co-culture assay further showed that BMSC were massively recruited when cultured in the presence of either cancerous or differentiated EC lines. In vivo, subcutaneous co-injection of BMSC with U-87 glioma cells in nude mice resulted in the formation of highly vascularized tumors, where BMSC differentiated into CD31-positive cells and localized at the lumen of vascular structures. Our data suggest that BMSC could be recruited at the sites of active tumor neovascularization through paracrine regulation of their angiogenic properties. These observations may have crucial implications in the development of novel therapies using BMSC engineered to secrete anti-cancerous agents and to antagonize tumor progression.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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