Pump‐Less Platform Enables Long‐Term Recirculating Perfusion of 3D Printed Tubular Tissues
Bibliographic record
Abstract
The direction and pattern of fluid flow affect vascular structure and function, in which vessel-lining endothelial cells exhibit variable cellular morphologies and vessel remodeling by mechanosensing. To recapitulate this microenvironment, some approaches have been reported to successfully apply unidirectional flow on endothelial cells in organ-on-a-chip systems. However, these platforms encounter drawbacks such as the dependency on pumps or confinement to closed microfluidic channels. These constraints impede their synergy with advanced biofabrication techniques like 3D bioprinting, thereby curtailing the potential to introduce greater complexity into engineered tissues. Herein, a pumpless recirculating platform (UniPlate) that enables unidirectional media recirculation through 3D printed tubular tissues, is demonstrated.The device is made of polystyrene via injection molding in combination with 3D printed sacrifical gelatin templates. Tubular blood vessels with unidirectional perfusion are firstly engineered. Then the design is expanded to incorporate duo-recirculating flow for culturing vascularized renal proximal tubules with glucose reabsorption function. In addition to media recirculation, human monocyte recirculation in engineered blood vessels is also demonstrated for over 24 h, with minimal loss of cells, cell viability, and inflammatory activation. UniPlate can be a valuable tool to more precisely control the cellular microenvironment of organ-on-a-chip systems for drug discovery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.000 | 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".