A microfluidic device designed to induce media flow throughout pancreatic islets while limiting shear-induced damage
Bibliographic record
Abstract
Pancreatic islets are heavily vascularized in vivo with fenestrated endothelial cells (ECs) to facilitate blood glucose-sensing and endocrine hormone secretion. The close proximity of insulin secreting beta cells and ECs also plays a critical role in modulating the proliferation and survival of both cell types with the mechanisms governing this interaction poorly understood. Isolated islets lose EC morphology and mass over a period of days in culture prohibiting study of this interaction in vitro. The loss of ECs also limits the efficacy of islet transplant revascularization in the treatment of Type 1 diabetes. We previously showed that microfluidically driven flow positively affects beta-cell function and EC survival in culture due to enhanced transport of media into the tissue. However, holding islets stationary in media flow using a dam-wall design also resulted in reduced glucose-stimulated metabolic and Ca(2+) responses at the periphery of the tissue consistent with shear-induced damage. We have now created a device that traps islets into sequential cup-shaped nozzles. This hydrodynamic trap design limits flow velocity around the perimeter of the islet while enhancing media flow through the tissue. We demonstrate the feasibility of this device to dynamically treat and collect effluent from islets. We further show that treating islets in this device enhances EC morphology without reducing glucose-stimulate Ca(2+) responses. These data reveal a microfluidic device to study EC and endocrine cell interaction that can be further leveraged to prime islets prior to transplantation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 0.004 |
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; both teacher heads agree on what is shown here.
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".