Engineering New Microvascular Networks On-Chip: Ingredients,Assembly, and Best Practices

Tissue engineered grafts show great potential as regenerative implants for diseased or injured tissues within the human body. However, these grafts suffer from poor nutrient perfusion and waste transport, thus decreasing their viability post-transplantation. Graft vascularization is therefore a major area of focus within tissue engineering because biologically relevant conduits for nutrient and oxygen perfusion can improve viability post-implantation. Many researchers used microphysiological systems as testing platforms for potential grafts owing to an ability to integrate vascular networks as well as biological characteristics such as fluid perfusion, 3D architecture, compartmentalization of tissue-specific materials, and biophysical and biochemical cues. Although many methods of vascularizing these systems exist, microvascular self-assembly has great potential for bench-to-clinic translation as it relies on naturally occurring physiological events. In this review, the past decade of literature is highlighted, and the most important and tunable components yielding a self-assembled vascular network on chip are critically discussed: endothelial cell source, tissue-specific supporting cells, biomaterial scaffolds, biochemical cues, and biophysical forces. This paper discusses the bioengineered systems of angiogenesis, vasculogenesis, and lymphangiogenesis and includes a brief overview of multicellular systems. It concludes with future avenues of research to guide the next generation of vascularized microfluidic models.     

Proton-Detected Solid-State NMR of the Cell-Free Synthesized α-Helical Transmembrane Protein NS4B from Hepatitis C Virus

Proton-detected 100 kHz magic-angle-spinning (MAS) solid-state NMR is an emerging analysis method for proteins with only hundreds of microgram quantities, and thus allows structural investigation of eukaryotic membrane proteins. This is the case for the cell-free synthesized hepatitis C virus (HCV) nonstructural membrane protein 4B (NS4B). We demonstrate NS4B sample optimization using fast reconstitution schemes that enable lipid-environment screening directly by NMR. 2D spectra and relaxation properties guide the choice of the best sample preparation to record 2D ¹H-detected ¹H,¹⁵N and 3D ¹H,¹³C,¹⁵N correlation experiments with linewidths and sensitivity suitable to initiate sequential assignments. Amino-acid-selectively labeled NS4B can be readily obtained using cell-free synthesis, opening the door to combinatorial labeling approaches which should enable structural studies.     

HA/β-TCP plasma sprayed coatings on Ti substrate for biomedical applications

The present work focuses on the fabrication of βTCP (β-tricalcium phosphate) and HA/βTCP (hydroxyapatite/β-tricalcium phosphate) composite coatings by plasma spraying. The starting powders were produced via solid-state method using 2 wt% MgO to stabilize βTCP phase. The synthesized powders were preliminarily granulated to be used by the plasma spray process. Coatings obtained on titanium substrates are uniform and well adherent but due to the high temperature and cooling rate typical for plasma spraying process, βTCP phase is almost totally transformed into the α allotrope. Thermal treatment at 800 °C allows the reconversion of the phase αTCP→ βTCP. It is therefore possible to produce coatings with tuneable dissolution properties by selecting the proper initial powder mixture and the specific thermal treatment.     

Group sequential crossover trial designs with strong control of the familywise error rate

Crossover designs are an extremely useful tool to investigators, and group sequential methods have proven highly proficient at improving the efficiency of parallel group trials. Yet, group sequential methods and crossover designs have rarely been paired together. One possible explanation for this could be the absence of a formal proof of how to strongly control the familywise error rate in the case when multiple comparisons will be made. Here, we provide this proof, valid for any number of initial experimental treatments and any number of stages, when results are analyzed using a linear mixed model. We then establish formulae for the expected sample size and expected number of observations of such a trial, given any choice of stopping boundaries. Finally, utilizing the four-treatment, four-period TOMADO trial as an example, we demonstrate that group sequential methods in this setting could have reduced the trials expected number of observations under the global null hypothesis by over 33%.     

Reoptimization framework and policy analysis for maritime inventory routing under uncertainty

We study a maritime inventory routing problem, in which shipments between production and consumption nodes are carried out by a fleet of vessels. The vessels have specific capacities and can be chartered under different agreements. The inventory levels of all consumption nodes and some production nodes should be maintained within specified bounds; for the remaining production nodes, orders should be picked up within pre-defined time windows. We propose a discrete-time mixed-integer programming model. In the face of new information and uncertainty, this optimization model has to be re-solved, as the horizon is rolled forward. We discuss how to account for different sources of uncertainty. We present a rolling-horizon reoptimization framework that allows us to study different policies that impact the quality of the implemented solution, so we can identify the optimal set of policies.     

Carbon Chain Length Modulates MDA-MB-231 Breast Cancer Cell Killing Mechanisms by Mitochondrially Targeted Aryl−Urea Fatty Acids

Targeting the tumor cell mitochondrion could produce novel anticancer agents. We designed an aryl−urea fatty acid ( 1 g ; 16({[4-chloro-3-(trifluoromethyl)phenyl]carbamoyl}amino)hexadecanoic acid) that disrupted the mitochondrion and decreased MDA-MB-231 breast cancer cell viability. To optimize the aryl−ureas the present study evaluated mitochondrial targeting by 1 g analogues containing alkyl chains between 10–17 carbons. Using the dye JC-1, the C12−C17 analogues efficiently disrupted the mitochondrial membrane potential (IC₅₀s 3.5±1.2 to 7.6±1.1 μM) and impaired ATP production; shorter analogues were less active. 7-Aminoactinomycin D/annexin V staining and flow cytometry showed that these agents activated the killing mechanisms of necrosis and apoptosis to varying extents (7-aminoactinomycin D/annexin V staining ratios 4.3–6.0). Indeed, 1 g and its C17 analogue preferentially activated necrosis and apoptosis, respectively (ratios 2.1 and 16). Taken together, alkyl chain length is a determinant of mitochondrial targeting by aryl−ureas and can be varied to develop analogues that activate apoptosis or necrosis in a regulated fashion.     

Computational Analysis of the Solid-State and Solvation Properties of Carbamazepine in Relation to its Polymorphism

The solvent-dependent polymorphism of the active pharmaceutical ingredient (API) carbamazepine is interpreted from calculations of the solid-state and API-solvent intermolecular interactions. These simulations suggested that apolar solute-solute interactions could be disrupted by apolar solvents. In contrast, the polar solute-solute interactions were found to be easily disrupted by polar and protic solvents. This is consistent with experimental observations that the crystallization of the metastable form II is more dominant in apolar solvents. The Mercury program remains the gold standard in terms of usability; however, further expansion into more complex simulation techniques could make this package of even greater use in pharmaceutical manufacturing workflows.