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Abstract Inadequate oxygenation is a major challenge in cell encapsulation, a therapy which holds potential to treat many diseases including type I diabetes. In such systems, cellular oxygen (O 2 ) delivery is limited to slow passive diffusion from transplantation sites through the poorly O 2 -soluble encapsulating matrix, usually a hydrogel. This constrains the maximum permitted distance between the encapsulated cells and host site to within a few hundred micrometers to ensure cellular function. Inspired by the natural gas-phase tracheal O 2 delivery system of insects, we present herein the design of a biomimetic scaffold featuring internal continuous air channels endowed with 10,000-fold higher O 2 diffusivity than hydrogels. We incorporate the scaffold into a bulk hydrogel containing cells, which facilitates rapid O 2 transport through the whole system to cells several millimeters away from the device-host boundary. A computational model, validated by in vitro analysis, predicts that cells and islets maintain high viability even in a thick (6.6 mm) device. Finally, the therapeutic potential of the device is demonstrated through the correction of diabetes in immunocompetent mice using rat islets for over 6 months. 

Microbes (bacteria, yeasts, molds), in addition to plants and animals, were domesticated for their roles in food preservation, nutrition and flavor. Aspergillus oryzae is a domesticated filamentous fungal species traditionally used during fermentation of Asian foods and beverage, such as sake, soy sauce, and miso. To date, little is known about the extent of genome and phenotypic variation of A. oryzae isolates from different clades. Here, we used long-read Oxford Nanopore and short-read Illumina sequencing to produce a highly accurate and contiguous genome assemble of A. oryzae 14160, an industrial strain from China. To understand the relationship of this isolate, we performed phylogenetic analysis with 90 A. oryzae isolates and 1 isolate of the A. oryzae progenitor, Aspergillus flavus . This analysis showed that A. oryzae 14160 is a member of clade A, in comparison to the RIB 40 type strain, which is a member of clade F. To explore genome variation between isolates from distinct A. oryzae clades, we compared the A. oryzae 14160 genome with the complete RIB 40 genome. Our results provide evidence of independent evolution of the alpha-amylase gene duplication, which is one of the major adaptive mutations resulting from domestication. Synteny analysis revealed that both genomes have three copies of the alpha-amylase gene, but only one copy on chromosome 2 was conserved. While the RIB 40 genome had additional copies of the alpha-amylase gene on chromosomes III, and V, 14160 had a second copy on chromosome II and an third copy on chromosome VI. Additionally, we identified hundreds of lineage specific genes, and putative high impact mutations in genes involved in secondary metabolism, including several of the core biosynthetic genes. Finally, to examine the functional effects of genome variation between strains, we measured amylase activity, proteolytic activity, and growth rate on several different substrates. RIB 40 produced significantly higher levels of amylase compared to 14160 when grown on rice and starch. Accordingly, RIB 40 grew faster on rice, while 14160 grew faster on soy. Taken together, our analyses reveal substantial genome and phenotypic variation within A. oryzae . 

Methods based on Gaussian stochastic process (GSP) models and expected improvement (EI) functions have been promising for box-constrained expensive optimization problems. These include robust design problems with environmental variables having set-type constraints. However, the methods that combine GSP and EI sub-optimizations suffer from the following problem, which limits their computational performance. Efficient global optimization (EGO) methods often repeat the same or nearly the same experimental points. We present a novel EGO-type constraint-handling method that maintains a so-called tabu list to avoid past points. Our method includes two types of penalties for the key “infill” optimization, which selects the next test runs. We benchmark our tabu EGO algorithm with five alternative approaches, including DIRECT methods using nine test problems and two engineering examples. The engineering examples are based on additive manufacturing process parameter optimization informed using point-based thermal simulations and robust-type quality constraints. Our test problems span unconstrained, simply constrained, and robust constrained problems. The comparative results imply that tabu EGO offers very promising computational performance for all types of black-box optimization in terms of convergence speed and the quality of the final solution.