Person:

Yarmush, Martin

Normothermic machine perfusion has previously been demonstrated to restore damaged warm ischemic livers to transplantable condition in animal models. However, the mechanisms of recovery are unclear, preventing rational optimization of perfusion systems and slowing clinical translation of machine perfusion. In this study, organ recovery time and major perfusate shortcomings were evaluated using a comprehensive metabolic analysis of organ function in perfusion prior to successful transplantation. Two groups, Fresh livers and livers subjected to 1 hr of warm ischemia (WI) received perfusion for a total preservation time of 6 hrs, followed by successful transplantation. 24 metabolic fluxes were directly measured and 38 stoichiometrically-related fluxes were estimated via a mass balance model of the major pathways of energy metabolism. This analysis revealed stable metabolism in Fresh livers throughout perfusion while identifying two distinct metabolic states in WI livers, separated at t = 2 hrs, coinciding with recovery of oxygen uptake rates to Fresh liver values. This finding strongly suggests successful organ resuscitation within 2 hrs of perfusion. Overall perfused livers regulated metabolism of perfusate substrates according to their metabolic needs, despite supraphysiological levels of some metabolites. This study establishes the first integrative metabolic basis for the dynamics of recovery during perfusion treatment of marginal livers. Our initial findings support enhanced oxygen delivery for both timely recovery and long-term sustenance. These results are expected to lead the optimization of the treatment protocols and perfusion media from a metabolic perspective, facilitating translation to clinical use.

Transient cell therapy is an emerging drug class that requires new approaches for pharmacological monitoring during use. Human mesenchymal stem cells (MSCs) are a clinically-tested transient cell therapeutic that naturally secrete anti-inflammatory factors to attenuate immune-mediated diseases. MSCs were used as a proof-of-concept with the hypothesis that measuring the release of secreted factors after cell transplantation, rather than the biodistribution of the cells alone, would be an alternative monitoring tool to understand the exposure of a subject to MSCs. By comparing cellular engraftment and the associated serum concentration of secreted factors released from the graft, we observed clear differences between the pharmacokinetics of MSCs and their secreted factors. Exploration of the effects of natural or engineered secreted proteins, active cellular secretion pathways, and clearance mechanisms revealed novel aspects that affect the systemic exposure of the host to secreted factors from a cellular therapeutic. We assert that a combined consideration of cell delivery strategies and molecular pharmacokinetics can provide a more predictive model for outcomes of MSC transplantation and potentially other transient cell therapeutics.

We report an all-in-one platform – ScanDrop – for the rapid and specific capture, detection, and identification of bacteria in drinking water. The ScanDrop platform integrates droplet microfluidics, a portable imaging system, and cloud-based control software and data storage. The cloud-based control software and data storage enables robotic image acquisition, remote image processing, and rapid data sharing. These features form a “cloud” network for water quality monitoring. We have demonstrated the capability of ScanDrop to perform water quality monitoring via the detection of an indicator coliform bacterium, Escherichia coli, in drinking water contaminated with feces. Magnetic beads conjugated with antibodies to E. coli antigen were used to selectively capture and isolate specific bacteria from water samples. The bead-captured bacteria were co-encapsulated in pico-liter droplets with fluorescently-labeled anti-E. coli antibodies, and imaged with an automated custom designed fluorescence microscope. The entire water quality diagnostic process required 8 hours from sample collection to online-accessible results compared with 2–4 days for other currently available standard detection methods.