Purification of Cytochrome a of an L-Glutamate-producing Microorganism,Brevibacterium thiogenitalis

The respiratory chain system of Brev. thiogenitalis grown in the presence of copper ions contained cytochromes a, b and c. The cytochrome a was solubilized and purified from the cell-free extracts by means of Triton X-100 and cholate extraction, and DEAE-cellulose chromatography. It was purified about 130-fold from the cell-free extracts and was free from other cytochromes, The purified preparation contained 1.4 mμatom copper and 1.9 mμatom iron per mμmole heme a, respectively, and approximately 5 mμmoles heme a per mg protein.     

Rapid removal of glycerol from frozen‐thawed red blood cells

The storage of red blood cells (RBCs) in a refrigerated state allows a shelf life of a few weeks, whereas RBCs frozen in 40% glycerol have a shelf life of 10 years. Despite the clear logistical advantages of frozen blood, it is not widely used in transfusion medicine. One of the main reasons is that existing post‐thaw washing methods to remove glycerol are prohibitively time consuming, requiring about an hour to remove glycerol from a single unit of blood. In this study, we have investigated the potential for more rapid removal of glycerol. Using published biophysical data for human RBCs, we mathematically optimized a three‐step deglycerolization process, yielding a procedure that was less than 32 s long. This procedure was found to yield 70% hemolysis, a value that was much higher than expected. Consequently, we systematically evaluated three‐step deglycerolization procedures, varying the solution composition and equilibration time in each step. Our best results consisted of less than 20% hemolysis for a deglycerolization time of 3 min, and it is expected that even further improvements could be made with a more thorough optimization and more reliable biophysical data. Our results demonstrate the potential for significantly reducing the deglycerolization time compared with existing methods. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 29:609–620, 2013     

Transfer of Natural Micro Structures to Bionic Lightweight Design Proposals

The abstraction of complex biological lightweight structure features into a producible technical component is a funda- mental step within the transfer of design principles from nature to technical lightweight solutions. A major obstacle for the transfer of natural lightweight structures to technical solutions is their peculiar geometry. Since natural lightweight structures possess irregularities and often have extremely complex forms due to elaborate growth processes, it is usually necessary to simplify their design principles. This step of simplification/abstraction has been used in different biomimetic methods, but so far, it has an arbitrary component, i.e. it crucially depends on the competence of the person who executes the abstraction. This paper describes a new method for abstraction and specialization of natural micro structures for technical lightweight compo- nents. The new method generates stable lightweight design principles by using topology optimization within a design space of preselected biological archetypes such as diatoms or radiolarian. The resulting solutions are adapted to the technical load cases and production processes, can be created in a large variety, and may be further optimized e.g. by using parametric optimization.     

EDISON-WMW: Exact Dynamic Programing Solution of the Wilcoxon–Mann–Whitney Test

In many research disciplines, hypothesis tests are applied to evaluate whether findings are statistically significant or could be explained by chance. The Wilcoxon–Mann–Whitney(WMW) test is among the most popular hypothesis tests in medicine and life science to analyze if two groups of samples are equally distributed. This nonparametric statistical homogeneity test is commonly applied in molecular diagnosis. Generally, the solution of the WMW test takes a high combinatorial effort for large sample cohorts containing a significant number of ties. Hence, P value is frequently approximated by a normal distribution. We developed EDISON-WMW, a new approach to calculate the exact permutation of the two-tailed unpaired WMW test without any corrections required and allowing for ties. The method relies on dynamic programing to solve the combinatorial problem of the WMW test efficiently. Beyond a straightforward implementation of the algorithm, we presented different optimization strategies and developed a parallel solution. Using our program,the exact P value for large cohorts containing more than 1000 samples with ties can be calculated within minutes. We demonstrate the performance of this novel approach on randomly-generated data, benchmark it against 13 other commonly-applied approaches and moreover evaluate molecular biomarkers for lung carcinoma and chronic obstructive pulmonary disease(COPD). We foundthat approximated P values were generally higher than the exact solution provided by EDISONWMW. Importantly, the algorithm can also be applied to high-throughput omics datasets, where hundreds or thousands of features are included. To provide easy access to the multi-threaded version of EDISON-WMW, a web-based solution of our algorithm is freely available at http://www.ccb.uni-saarland.de/software/wtest/.     

Comparison of batch and continuous multi‐column protein A capture processes by optimal design

Multi‐column capture processes show several advantages compared to batch capture. It is however not evident how many columns one should use exactly. To investigate this issue, twin‐column CaptureSMB, 3‐ and 4‐column periodic counter‐current chromatography (PCC) and single column batch capture are numerically optimized and compared in terms of process performance for capturing a monoclonal antibody using protein A chromatography. Optimization is carried out with respect to productivity and capacity utilization (amount of product loaded per cycle compared to the maximum amount possible), while keeping yield and purity constant. For a wide range of process parameters, all three multi‐column processes show similar maximum capacity utilization and performed significantly better than batch. When maximizing productivity, the CaptureSMB process shows optimal performance, except at high feed titers, where batch chromatography can reach higher productivity values than the multi‐column processes due to the complete decoupling of the loading and elution steps, albeit at a large cost in terms of capacity utilization. In terms of trade‐off, i.e. how much the capacity utilization decreases with increasing productivity, CaptureSMB is optimal for low and high feed titers, whereas the 3‐column process is optimal in an intermediate region. Using these findings, the most suitable process can be chosen for different production scenarios.     

A novel algorithm with differential evolution and coral reef optimization for extreme learning machine training

Extreme learning machine (ELM) is a novel and fast learning method to train single layer feed-forward networks. However due to the demand for larger number of hidden neurons, the prediction speed of ELM is not fast enough. An evolutionary based ELM with differential evolution (DE) has been proposed to reduce the prediction time of original ELM. But it may still get stuck at local optima. In this paper, a novel algorithm hybridizing DE and metaheuristic coral reef optimization (CRO), which is called differential evolution coral reef optimization (DECRO), is proposed to balance the explorative power and exploitive power to reach better performance. The thought and the implement of DECRO algorithm are discussed in this article with detail. DE, CRO and DECRO are applied to ELM training respectively. Experimental results show that DECRO-ELM can reduce the prediction time of original ELM, and obtain better performance for training ELM than both DE and CRO.     

An improved neutral landscape model for recreating real landscapes and generating landscape series for spatial ecological simulations

Many studies have assessed the effect of landscape patterns on spatial ecological processes by simulating these processes in computer‐generated landscapes with varying composition and configuration. To generate such landscapes, various neutral landscape models have been developed. However, the limited set of landscape‐level pattern variables included in these models is often inadequate to generate landscapes that reflect real landscapes. In order to achieve more flexibility and variability in the generated landscapes patterns, a more complete set of class‐ and patch‐level pattern variables should be implemented in these models. These enhancements have been implemented in Landscape Generator (LG), which is a software that uses optimization algorithms to generate landscapes that match user‐defined target values. Developed for participatory spatial planning at small scale, we enhanced the usability of LG and demonstrated how it can be used for larger scale ecological studies. First, we used LG to recreate landscape patterns from a real landscape (i.e., a mountainous region in Switzerland). Second, we generated landscape series with incrementally changing pattern variables, which could be used in ecological simulation studies. We found that LG was able to recreate landscape patterns that approximate those of real landscapes. Furthermore, we successfully generated landscape series that would not have been possible with traditional neutral landscape models. LG is a promising novel approach for generating neutral landscapes and enables testing of new hypotheses regarding the influence of landscape patterns on ecological processes. LG is freely available online.