4D force patterning enables spatial control of angiogenesis
Bibliographic record
Abstract
Abstract Engineering organized microvascular networks remains a critical challenge in tissue engineering and regenerative medicine. While biochemical approaches for patterning angiogenesis via growth factor delivery have shown promise, their inability to pattern sustained growth factors with spatiotemporal control limits effectiveness. Here, we demonstrate that dynamically patterned mechanical forces enable precise spatiotemporal control over angiogenic sprouting. We developed a magnetically actuated human vessel-on-a-chip platform that integrates a perfusable endothelialized microchannel within a collagen matrix and allows non-invasive and tunable mechanical stimulation across three spatial dimensions and time (4D). Using an automated 3-axis actuator, we systematically investigated how strain magnitude, frequency, and direction modulate endothelial cell behavior and vessel morphogenesis. Dynamic mechanical stimulation at physiological strain magnitudes (5–15%) enhanced endothelial alignment and barrier function while promoting angiogenesis in a strain-magnitude–dependent manner: lower dynamic strain (5%) maximized sprout initiation, whereas higher dynamic strain (15%) promoted elongation of sprouts. Sequential reorientation of strain direction reprogrammed sprouting trajectories along X, Y, and Z directions, generating complex sprout geometries such as L-shaped branches. RNA sequencing revealed mechanically induced transcriptional profiles distinct from unstimulated controls, characterized by upregulation of genes associated with angiogenesis, mechanotransduction, and extracellular matrix remodeling. Functional perturbation of Piezo1 reduced strain-induced sprouting without altering barrier stabilization, indicating that dynamic mechanical stimulation engages multiple mechanotransduction pathways to regulate angiogenesis. Collectively, these findings establish a strategy for spatiotemporally controlled angiogenesis through 4D force patterning to program vascular morphogenesis while preserving function. This approach provides a foundation for engineering hierarchically organized vascular networks for tissue regeneration. Significance Generation of spatially organized, perfusable microvascular networks is essential for building functional human tissues. Biochemical approaches to pattern angiogenesis rely on diffusive growth factors, which limit control over spatiotemporal sprouting dynamics. Here, we demonstrate that dynamically patterned mechanical forces direct vascular morphogenesis across three spatial dimensions and time (4D). Using a magnetically actuated human vessel-on-a-chip, we show how strain magnitude and orientation govern angiogenic sprouting and reveal transcriptional programs linking mechanical cues to observed functional changes. For the first time, we show that dynamic reorientation of imposed forces can reprogram angiogenic trajectories in real-time. This platform enables programmable mechanical control of angiogenesis and systematic dissection of mechanotransduction pathways, advancing strategies for tissue vascularization, and modeling mechanically regulated vascular diseases.
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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 | 0.000 |
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 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".