A tissue-engineered endothelialized dermis to study the modulation of angiogenic and angiostatic molecules on capillary-like tube formation in vitro
Bibliographic record
Abstract
BACKGROUND: Because angiogenesis is a major feature of different physiological and pathological situations, the identification of factors that stimulate or inhibit this process and the elucidation of their mechanisms of action are most certainly of clinical relevance. We have produced a new model of endothelialized reconstructed dermis that promotes the spontaneous formation of a human capillary-like network and its stabilization in vitro for a period longer than 1 month. OBJECTIVES: The aim of this work was to describe the three-dimensional structure of the capillary-like network. Thereafter we strove to study, quantitatively and qualitatively, the influence of angiogenic and angiostatic drugs on capillary-like tube (CLT) formation in vitro in the model. METHODS: The endothelialized dermis was prepared by coculturing two human cell types, dermal fibroblasts and umbilical vein endothelial cells, in a collagen sponge biomaterial. RESULTS: The visualization by confocal microscopy of the tubes present in the model showed that the endothelial structures were not cord-like but rather CLTs with well-defined lumina. Moreover, these tubes were organized in a complex network of branching structures. When angiogenic factors (vascular endothelial growth factor 10 ng mL-1 or basic fibroblast growth factor 10 ng mL-1) were added to the model, 1.8 and 1.4 times more capillaries, respectively, were observed, whereas the addition of progesterone (10 microg x mL(-1)) reduced by 2.4 times the number of tubes compared with the control. CONCLUSIONS: These results suggest that this model is a highly efficient assay for the screening of potentially angiogenic and angiostatic compounds.
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How this classification was reachedexpand
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) | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".