Scaled-up Microfluidic Lung Assist Device for Artificial Placenta Application with High Gas Exchange Capacity
Bibliographic record
Abstract
Premature neonates with underdeveloped lungs experience respiratory issues and need respiratory support, such as mechanical ventilation or extracorporeal membrane oxygenation (ECMO). The "artificial placenta" (AP) is a noninvasive approach that supports their lungs and reduces respiratory distress, using a pumpless oxygenator connected to the systemic circulation, and can address some of the morbidity issues associated with ECMO. Over the past decade, microfluidic blood oxygenators have garnered significant interest for their ability to mimic physiological conditions and incorporate innovative biomimetic designs. Achieving sufficient gas transfer at a low enough pressure drop for a pumpless operation without requiring a large volume of blood to prime such an oxygenator has been the main challenge with microfluidic lung assist devices (LAD). In this study, we improved the gas exchange capacity of our microfluidic-based artificial placenta-type LAD while reducing its priming volume by using a modified fabrication process that can accommodate large-area thin film microfluidic blood oxygenator (MBO) fabrication with a very high gas exchange surface. Additionally, we demonstrate the effectiveness of a LAD assembled by using these scaled-up MBOs. The LAD based on our artificial placenta concept effectively increases oxygen saturation levels by 30% at a flow rate of 40 mL/min and a pressure drop of 23 mmHg in room air, which is sufficient to support partial oxygenation for 1 kg preterm neonates in respiratory distress. When the gas ambient environment was changed to pure oxygen at atmospheric pressure, the LAD would be able to support premature neonates weighing up to 2 kg. Furthermore, our experiments reveal that the LAD can handle high blood flow rates of up to 150 mL/min and increase oxygen saturation levels by ∼20%, which is equal to an oxygen transfer of 7.48 mL/min in an enriched oxygen environment and among the highest for microfluidic AP type devices. Such performance makes this LAD suitable for providing essential support to 1-2 kg neonates in respiratory distress.
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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".