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A Clinical-Scale Microfluidic Respiratory Assist Device with 3D Branching Vascular Networks.

ABSTRACT: Recent global events such as COVID-19 pandemic amid rising rates of chronic lung diseases highlight the need for safer, simpler, and more available treatments for respiratory failure, with increasing interest in extracorporeal membrane oxygenation (ECMO). A key factor limiting use of this technology is the complexity of the blood circuit, resulting in clotting and bleeding and necessitating treatment in specialized care centers. Microfluidic oxygenators represent a promising potential solution, but have not reached the scale or performance required for comparison with conventional hollow fiber membrane oxygenators (HFMOs). Here the development and demonstration of the first microfluidic respiratory assist device at a clinical scale is reported, demonstrating efficient oxygen transfer at blood flow rates of 750 mL min⁻¹ , the highest ever reported for a microfluidic device. The central innovation of this technology is a fully 3D branching network of blood channels mimicking key features of the physiological microcirculation by avoiding anomalous blood flows that lead to thrombus formation and blood damage in conventional oxygenators. Low, stable blood pressure drop, low hemolysis, and consistent oxygen transfer, in 24-hour pilot large animal experiments are demonstrated - a key step toward translation of this technology to the clinic for treatment of a range of lung diseases.

SUBMITTER: Isenberg BC

PROVIDER: S-EPMC10288269 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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A Clinical-Scale Microfluidic Respiratory Assist Device with 3D Branching Vascular Networks.

Isenberg Brett C BC Vedula Else M EM Santos Jose J Lewis Diana J DJ Roberts Teryn R TR Harea George G Sutherland David D Landis Beau B Blumenstiel Samuel S Urban Joseph J Lang Daniel D Teece Bryan B Lai WeiXuan W Keating Rose R Chiang Diana D Batchinsky Andriy I AI Borenstein Jeffrey T JT

Advanced science (Weinheim, Baden-Wurttemberg, Germany) 20230424 18

Recent global events such as COVID-19 pandemic amid rising rates of chronic lung diseases highlight the need for safer, simpler, and more available treatments for respiratory failure, with increasing interest in extracorporeal membrane oxygenation (ECMO). A key factor limiting use of this technology is the complexity of the blood circuit, resulting in clotting and bleeding and necessitating treatment in specialized care centers. Microfluidic oxygenators represent a promising potential solution, ...[more]

PMID: 37092588

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Project description:BackgroundA central problem in computational metabolic modelling is how to find biochemically plausible pathways between metabolites in a metabolic network. Two general, complementary frameworks have been utilized to find metabolic pathways: constraint-based modelling and graph-theoretical path finding approaches. In constraint-based modelling, one aims to find pathways where metabolites are balanced in a pseudo steady-state. Constraint-based methods, such as elementary flux mode analysis, have typically a high computational cost stemming from a large number of steady-state pathways in a typical metabolic network. On the other hand, graph-theoretical approaches avoid the computational complexity of constraint-based methods by solving a simpler problem of finding shortest paths. However, while scaling well with network size, graph-theoretic methods generally tend to return more false positive pathways than constraint-based methods.ResultsIn this paper, we introduce a computational method, ReTrace, for finding biochemically relevant, branching metabolic pathways in an atom-level representation of metabolic networks. The method finds compact pathways which transfer a high fraction of atoms from source to target metabolites by considering combinations of linear shortest paths. In contrast to current steady-state pathway analysis methods, our method scales up well and is able to operate on genome-scale models. Further, we show that the pathways produced are biochemically meaningful by an example involving the biosynthesis of inosine 5'-monophosphate (IMP). In particular, the method is able to avoid typical problems associated with graph-theoretic approaches such as the need to define side metabolites or pathways not carrying any net carbon flux appearing in results. Finally, we discuss an application involving reconstruction of amino acid pathways of a recently sequenced organism demonstrating how measurement data can be easily incorporated into ReTrace analysis. ReTrace is licensed under GPL and is freely available for academic use at http://www.cs.helsinki.fi/group/sysfys/software/retrace/.ConclusionReTrace is a useful method in metabolic path finding tasks, combining some of the best aspects in constraint-based and graph-theoretic methods. It finds use in a multitude of tasks ranging from metabolic engineering to metabolic reconstruction of recently sequenced organisms.

Dataset Information

A Clinical-Scale Microfluidic Respiratory Assist Device with 3D Branching Vascular Networks.

Publications

A Clinical-Scale Microfluidic Respiratory Assist Device with 3D Branching Vascular Networks.

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