Modeling gas-diffusion electrodes for CO2 reduction.

CO2 reduction conducted in electrochemical cells with planar electrodes immersed in an aqueous electrolyte is severely limited by mass transport across the hydrodynamic boundary layer. This limitation can be minimized by use of vapor-fed, gas-diffusion electrodes (GDEs), enabling current densities that are almost two orders of magnitude greater at the same applied cathode overpotential than what is achievable with planar electrodes in an aqueous electrolyte. The addition of porous cathode layers, however, introduces a number of parameters that need to be tuned in order to optimize the performance of the GDE cell. In this work, we develop a multiphysics model for gas diffusion electrodes for CO2 reduction and used it to investigate the interplay between species transport and electrochemical reaction kinetics. The model demonstrates how the local environment near the catalyst layer, which is a function of the operating conditions, affects cell performance. We also examine the effects of catalyst layer hydrophobicity, loading, porosity, and electrolyte flowrate to help guide experimental design of vapor-fed CO2 reduction cells.

Anion-exchange membranes with internal microchannels for water control in CO2 electrolysis.

Electrochemical reduction of carbon dioxide (CO2R) poses substantial promise to convert abundant feedstocks (water and CO2) to value-added chemicals and fuels using solely renewable energy. However, recent membrane-electrode assembly (MEA) devices that have been demonstrated to achieve high rates of CO2R are limited by water management within the cell, due to both consumption of water by the CO2R reaction and electro-osmotic fluxes that transport water from the cathode to the anode. Additionally, crossover of potassium (K+) ions poses concern at high current densities where saturation and precipitation of the salt ions can degrade cell performance. Herein, a device architecture incorporating an anion-exchange membrane (AEM) with internal water channels to mitigate MEA dehydration is proposed and demonstrated. A macroscale, two-dimensional continuum model is used to assess water fluxes and local water content within the modified MEA, as well as to determine the optimal channel geometry and composition. The modified AEMs are then fabricated and tested experimentally, demonstrating that the internal channels can both reduce K+ cation crossover as well as improve AEM conductivity and therefore overall cell performance. This work demonstrates the promise of these materials, and operando water-management strategies in general, in handling some of the major hurdles in the development of MEA devices for CO2R.

Development and application of a high-content virion display human GPCR array.

Human G protein-coupled receptors (GPCRs) respond to various ligands and stimuli. However, GPCRs rely on membrane for proper folding, making their biochemical properties difficult to study. By displaying GPCRs in viral envelopes, we fabricated a Virion Display (VirD) array containing 315 non-olfactory human GPCRs for functional characterization. Using this array, we found that 10 of 20 anti-GPCR mAbs were ultra-specific. We further demonstrated that those failed in the mAb assays could recognize their canonical ligands, suggesting proper folding. Next, using two peptide ligands on the VirD-GPCR array, we identified expected interactions and novel interactions. Finally, we screened the array with group B Streptococcus, a major cause of neonatal meningitis, and demonstrated that inhibition of a newly identified target, CysLTR1, reduced bacterial penetration both in vitro and in vivo. We believe that the VirD-GPCR array holds great potential for high-throughput screening for small molecule drugs, affinity reagents, and ligand deorphanization.

miRge - A Multiplexed Method of Processing Small RNA-Seq Data to Determine MicroRNA Entropy.

Small RNA RNA-seq for microRNAs (miRNAs) is a rapidly developing field where opportunities still exist to create better bioinformatics tools to process these large datasets and generate new, useful analyses. We built miRge to be a fast, smart small RNA-seq solution to process samples in a highly multiplexed fashion. miRge employs a Bayesian alignment approach, whereby reads are sequentially aligned against customized mature miRNA, hairpin miRNA, noncoding RNA and mRNA sequence libraries. miRNAs are summarized at the level of raw reads in addition to reads per million (RPM). Reads for all other RNA species (tRNA, rRNA, snoRNA, mRNA) are provided, which is useful for identifying potential contaminants and optimizing small RNA purification strategies. miRge was designed to optimally identify miRNA isomiRs and employs an entropy based statistical measurement to identify differential production of isomiRs. This allowed us to identify decreasing entropy in isomiRs as stem cells mature into retinal pigment epithelial cells. Conversely, we show that pancreatic tumor miRNAs have similar entropy to matched normal pancreatic tissues. In a head-to-head comparison with other miRNA analysis tools (miRExpress 2.0, sRNAbench, omiRAs, miRDeep2, Chimira, UEA small RNA Workbench), miRge was faster (4 to 32-fold) and was among the top-two methods in maximally aligning miRNAs reads per sample. Moreover, miRge has no inherent limits to its multiplexing. miRge was capable of simultaneously analyzing 100 small RNA-Seq samples in 52 minutes, providing an integrated analysis of miRNA expression across all samples. As miRge was designed for analysis of single as well as multiple samples, miRge is an ideal tool for high and low-throughput users. miRge is freely available at http://atlas.pathology.jhu.edu/baras/miRge.html.

Hyaluronic acid hydrogel stiffness and oxygen tension affect cancer cell fate and endothelial sprouting.

Three-dimensional (3D) tissue culture models may recapitulate aspects of the tumorigenic microenvironment in vivo, enabling the study of cancer progression in vitro. Both hypoxia and matrix stiffness are known to regulate tumor growth. Using a modular culture system employing an acrylated hyaluronic acid (AHA) hydrogel, three hydrogel matrices with distinctive degrees of viscoelasticity - soft (78±16 Pa), medium (309± 57 Pa), and stiff (596± 73 Pa) - were generated using the same concentration of adhesion ligands. Oxygen levels within the hydrogel in atmospheric (21 %), hypoxic (5 %), and severely hypoxic (1 %) conditions were assessed with a mathematical model. HT1080 fibrosarcoma cells, encapsulated within the AHA hydrogels in high densities, generated nonuniform oxygen distributions, while lower cell densities resulted in more uniform oxygen distributions in the atmospheric and hypoxic environments. When we examined how varying viscoelasticity in atmospheric and hypoxic environments affects cell cycles and the expression of BNIP3 and BNIP3L (autophagy and apoptosis genes), and GLUT-1 (a glucose transport gene), we observed that HT1080 cells in 3D hydrogel adapted better to hypoxic conditions than those in a Petri dish, with no obvious correlation to matrix viscoelasticity, by recovering rapidly from possible autophagy/apoptotic events and alternating metabolism mechanisms. Further, we examined how HT1080 cells cultured in varying viscoelasticity and oxygen tension conditions affected endothelial sprouting and invasion. We observed that increased matrix stiffness reduced endothelial sprouting and invasion in atmospheric conditions; however, we observed increased endothelial sprouting and invasion under hypoxia at all levels of matrix stiffness with the upregulation of vascular endothelial growth factor (VEGF) and angiopoeitin-1 (ANG-1). Overall, HT1080 cells encapsulated in the AHA hydrogels under hypoxic stress recovered better from apoptosis and demonstrated greater angiogenic induction. Thus, we propose that oxygen tension more profoundly influences cell fate and the angiogenic potential of 3D cultured HT1080 fibrosarcoma cells than does matrix stiffness.