Transcribing In Vivo Blood Vessel Networks into In Vitro Perfusable Microfluidic Devices
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
Abstract The 3D architecture of blood vessel networks dictates how nutrients, waste, and drugs are transported. These transport processes are difficult to study in vivo, leading researchers to develop methods to construct vessel networks in vitro. However, existing methods require expensive, customized equipment and cannot create large (>1 cm 3 ) constructs. This makes them inaccessible to many researchers or educators. Here, a method that transcribes 3D images of blood vessel networks into physical microfluidic devices is developed. The method takes 3D images of blood vessel networks and uses fused‐filament 3D fabrication with standard polylactic acid (PLA) filament to print the imaged vessel network. The 3D printout is cast in polydimethylsiloxane (PDMS) and dissolved, producing vessel channels that are lined with endothelial cells. Devices imprinted with different vessel networks including small intestinal villi, pancreatic islets, and tumors from mice and humans are created. The method replicates the complex geometries of blood vessel networks in an in vitro device with commonly available equipment and materials. This increases the accessibility of this technology by allowing researchers or educators without access to expensive laser ablation microscope set‐ups or custom 3D printers to be able to create vasculature network devices.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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