Microfluidic Multiculture Assay to Analyze Biomolecular Signaling in Angiogenesis
Bibliographic record
Abstract
Angiogenesis (the formation of blood vessels from existing blood vessels) plays a critical role in many diseases such as cancer, benign tumors, and macular degeneration. There is a need for cell culture methods capable of dissecting the intricate regulation of angiogenesis within the microenvironment of the vasculature. We have developed a microscale cell-based assay that responds to complex pro- and antiangiogenic soluble factors with an in vitro readout for vessel formation. The power of this system over traditional techniques is that we can incorporate the whole milieu of soluble factors produced by cells in situ into one biological readout (vessel formation), even if the identity of the factors is unknown. We have currently incorporated macrophages, endothelial cells, and fibroblasts into the assay, with the potential to include additional cell types in the future. Importantly, the microfluidic platform is simple to operate and multiplex to test drugs targeting angiogenesis in a more physiologically relevant context. As a proof of concept, we tested the effect of an enzyme inhibitor (targeting matrix metalloproteinase 12) on vessel formation; the triculture microfluidic assay enabled us to capture a dose-dependent effect entirely missed in a simplified coculture assay (p < 0.0001). This result underscores the importance of cell-based assays that capture chemical cross-talk occurring between cell types. The microscale dimensions significantly reduce cell consumption compared to conventional well plate platforms, enabling the use of limited primary cells from patients in future investigations and offering the potential to screen therapeutic approaches for individual patients in vitro.
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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".