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The family of orthogonal minimally aliased response surface or OMARS designs comprises traditional response surface designs, such as central composite designs and Box-Behnken designs, as well as definitive screening designs. Key features of OMARS designs are the facts that they are orthogonal for the main effects and that the main effects are not at all aliased with any two-factor interaction effect or with any quadratic effect. In this article, we present a method to arrange the runs of an OMARS design in blocks of equal size, so that the main effects can be estimated independently from the blocks, and the interaction effects and the quadratic effects are confounded as little as possible with the blocks. We show that our new method for blocking OMARS designs offers much flexibility when it comes to choosing the number of runs, the number of blocks and the block sizes, and that it often outperforms the blocking arrangements of definitive screening designs available in the literature and in commercial software.

Intracellular delivery is critical for a plethora of biomedical applications, including mRNA transfection and gene editing. High transfection efficiency and low cytotoxicity, however, are often beyond the capabilities of bulk techniques and synonymous with extensive empirical optimization. Moreover, bulk techniques are not amenable to large screening applications. Here, we propose an expeditious workflow for achieving optimal electroporation-based intracellular delivery. Using the multiplexing ability of a high-definition microelectrode array (MEA) chip, we performed a sequence of carefully designed experiments, multiple linear regression modelling and validation to obtain optimal conditions for on-chip electroporation of primary fibroblasts. Five electric pulse parameters were varied to generate 32 different electroporation conditions. The effect of the parameters on cytotoxicity and intracellular delivery could be evaluated with just two experiments. Most successful electroporation conditions resulted in no cell death, highlighting the low cytotoxicity of on-chip electroporation. The resulting delivery models were then used to achieve dosage-controlled delivery of small molecules, delivery of Cas9-GFP single-guide RNA complexes and transfection with an mCherry-encoding mRNA, resulting in previously unreported high-efficiency, single-cell transfection on MEAs: cells expressed mCherry on 81% of the actuated electrodes, underscoring the vast potential of CMOS MEA technology for the transfection of primary cells.

Current experimental design techniques for dynamical systems often only incorporate measurement noise, while dynamical systems also involve process noise. To construct experimental designs we need to quantify their information content. The Fisher information matrix is a popular tool to do so. Calculating the Fisher information matrix for linear dynamical systems with both process and measurement noise involves estimating the uncertain dynamical states using a Kalman filter. The Fisher information matrix, however, depends on the true but unknown model parameters. In this paper we combine two methods to solve this issue and develop a robust experimental design methodology. First, Bayesian experimental design averages the Fisher information matrix over a prior distribution of possible model parameter values. Second, adaptive experimental design allows for this information to be updated as measurements are being gathered. This updated information is then used to adapt the remainder of the design.

Designs for screening experiments usually include factors with two levels only. Adding a few four-level factors allows for the inclusion of multi-level categorical factors or quantitative factors with possible quadratic or third-order effects. Three examples motivated us to generate a large catalog of designs with two-level factors as well as four-level factors. To create the catalog, we considered three methods. In the first method, we select designs using a search table, and in the second method, we use a procedure that selects candidate designs based on the properties of their projections into fewer factors. The third method is actually a benchmark method, in which we use a general orthogonal array enumeration algorithm. We compare the efficiencies of the new methods for generating complete sets of non-isomorphic designs. Finally, we use the most efficient method to generate a catalog of designs with up to three four-level factors and up to 20 two-level factors for run sizes 16, 32, 64, and 128. In some cases, a complete enumeration was infeasible. For these cases, we used a bounded enumeration strategy instead. We demonstrate the usefulness of the catalog by revisiting the motivating examples., 37 pages, 1 figure, 13 tables

Two-level screening designs are widely applied in manufacturing industry to identify influential factors of a system. These designs have each factor at two levels and are traditionally constructed using standard algorithms, which rely on a pre-specified linear model. Since the assumed model may depart from the truth, two-level Q(B)-optimal designs have been developed to provide efficient parameter estimates for several potential models. These designs also have an overarching goal that models that are more likely to be the best for explaining the data are estimated more efficiently than the rest. However, there is no effective algorithm for constructing them. This article proposes two methods: a mixed-integer programming algorithm that guarantees convergence to the two-level Q(B)-optimal designs; and, a heuristic algorithm that employs a novel formula to find good designs in short computing times. Using numerical experiments, we show that our mixed-integer programming algorithm is attractive to find small optimal designs, and our heuristic algorithm is the most computationally-effective approach to construct both small and large designs, when compared to benchmark heuristic algorithms.

Experimental data are often highly structured due to the use of experimental designs. This does not only simplify the analysis, but it allows for tailored methods of analysis that extract more information from the data than generic methods. One group of three-level experimental designs that are suitable for such tailored methods are orthogonal minimally aliased response surface (OMARS) designs (Nunez Ares and Goos 2020), where all main effects are orthogonal to each other and to all second-order effects. The design based analysis method of Jones and Nachtsheim (2017) has shown significant improvement over existing methods in terms of powers to detect active effects. However, the application of their method is limited to only a small subgroup of OMARS designs known as definitive screening designs (DSDs). In our work, we not only improve upon the Jones and Nachtsheim method for DSDs, but we also generalize their analysis framework to the entire family of OMARS designs. Using extensive simulations, we show that our customized method for analyzing data from OMARS designs is highly effective in identifying active effects when compared to other modern (non-design based) analysis methods, especially in cases where the true model is complex and involves many second-order effects.

Despite the general use of endoxylanases in poultry feed to improve broiler performance, the abundance of different endoxylanase products and the variable response to their application in the field prevent a clear understanding of endoxylanase functionality in vivo. To gain insight into this functionality, we investigated the impact of endoxylanase type (Belfeed from Bacillus subtilis versus Econase XT from Nonomuraea flexuosa) and dose (10, 100, 1,000 mg/kg) in combination with broiler age on arabinoxylan (AX) hydrolysis and fermentation in broilers (Ross 308) fed a wheat-soy based diet. In a digestibility trial and a performance trial, a total of 1,057 one-day-old chicks received the control diet or 1 of the 6 endoxylanase supplemented wheat-soy based diets with, respectively, 5 replicate cages and 8 replicate pens per dietary treatment per trial. The AX content and structure, the AX digestibility values and the short-chain fatty acids produced were analysed at the level of the ileum, caeca and excreta at d 11 and 36. Endoxylanase supplementation resulted in a more extensive solubilisation of wheat AX and a reduction in the intestinal viscosity compared to the control (P

Formation of amyloid fibrils (i.e., protein structures containing a compact core of ordered β-sheet structures) from food proteins can improve their techno-functional properties. Wheat gluten is the most consumed cereal protein by humans and extensively present in food and feed systems. Hydrolysis of wheat gluten increases the solubility of its proteins and brings new opportunities for value creation. In this study, the formation of amyloid-like fibrils (ALFs) from wheat gluten peptides (WGPs) under food relevant processing conditions was investigated. Different hydrothermal treatments were tested to maximize the formation of straight ALFs from WGPs. Thioflavin T (ThT) fluorescence measurements and transmission electron microscopy (TEM) were performed to study the extent of fibrillation and the morphology of the fibrils, respectively. First, the formation of fibrils by heating solutions of tryptic WGPs [degrees of hydrolysis 2.0% (DH 2) or 6.0% (DH 6)] was optimized using a response surface design. WGP solutions were incubated at different pH values, times, and temperatures. DH 6 WGPs had a higher propensity for fibrillation than did DH 2 WGPs. Heating DH 6 WGPs at 2.0% (w/v) for 38 h at 85 °C and pH 7.0 resulted in optimal fibrillation. Second, trypsin, chymotrypsin, thermolysin, papain, and proteinase K were used to produce different DH 6 WGPs. After enzyme inactivation and subsequent heating at optimal fibrillation conditions, chymotrypsin and proteinase K DH 6 WGPs produced small worm-like fibrils, whereas fibrils prepared from trypsin DH 6 WGPs were long and straight. The surface hydrophobicity of the peptides was key for fibrillation. Third, peptides from the wheat gluten components gliadin and glutenin fractions formed smaller and worm-like fibrils than did WGPs. Thus, the peptides of both gluten protein fractions jointly contribute to gluten fibrillation. ispartof: JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY vol:69 issue:6 pages:1963-1974 ispartof: location:United States status: published