THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

http://www.biotek.lu.se/fileadmin/bioteknik/Utbildning/Kurser/KKKA05/ProgressETOHprocess.pdf

Progress in bioethanol processing

Statistics--with confidence?

Nearly 30% of currently approved recombinant therapeutic proteins are produced in Escherichia coli. Due to its well-characterized genetics, rapid growth and high-yield production, E. coli has been a preferred choice and a workhorse for expression of non-glycosylated proteins in the biotech industry. There is a wealth of knowledge and comprehensive tools for E. coli systems, such as expression vectors, production strains, protein folding and fermentation technologies, that are well tailored for industrial applications. Advancement of the systems continues to meet the current industry needs, which are best illustrated by the recent drug approval of E. coli produced antibody fragments and Fc-fusion proteins by the FDA. Even more, recent progress in expression of complex proteins such as full-length aglycosylated antibodies, novel strain engineering, bacterial N-glycosylation and cell-free systems further suggests that complex proteins and humanized glycoproteins may be produced in E. coli in large quantities. This review summarizes the current technology used for commercial production of recombinant therapeutics in E. coli and recent advances that can potentially expand the use of this system toward more sophisticated protein therapeutics.

Industrial production of recombinant therapeutics in Escherichia coli and its recent advancements.

Microalgae invite the attention of scientists due to their unique properties, including their ability to grow quickly, accumulate lipids and other valuable materials, fix carbon dioxide and treat wastewater. Several studies have aimed to identify cost-effective production methods for microalgae biomass. In this paper, several potential inexpensive waste materials for microalgae Chlorella sp. biomass production rate were investigated, including technical glycerol and liquid waste (i.e., the liquid fraction of the digestate after biogas production). In addition, the cultivation of microalgae biomass was optimized using these materials. The optimization procedure was performed using response surface methodology. Biomass cultivation process was optimized depending on the amount of technical glycerol and the nitrogen concentrations in the growth medium, which was prepared using liquid waste. The highest Chlorella sp. biomass concentration of 2.41 g L− 1 was achieved in the growth medium that contained 0.114 g L− 1 nitrogen and 2.70 g L− 1 technical glycerol.

Optimization of mixotrophic cultivation of microalgae Chlorella sp. for biofuel production using response surface methodology

An optimized fed-batch cultivation process for the production of the polyoma virus capsid protein VP1 in recombinant Escherichia coli BL21 bacteria is presented. The optimization procedure maximizing the amount of desired protein is based on a mathematical model. The model distinguishes an initial cell growth phase from a protein production phase initiated by inducer injection. A new approach to model the target protein formation rate was elaborated, where product formation is primarily dependent on the specific biomass growth rate. Lower growth rates led to higher specific protein concentrations. The model was identified from a series of fed-batch experiments designed for parameter identification purposes and possesses good prediction quality. Then the model was used to determine optimal open-loop control profiles by manipulating the substrate feed rates in both phases as well as the induction time. Feed-rate optimization has been solved using Pontryagin's maximum principle. The solution was validated experimentally. A significant improvement of the process performance index was achieved.

Model-based optimization of viral capsid protein production in fed-batch culture of recombinant Escherichia coli.

A new simple strategy for a reliable and robust automatic control of the specific growth rate in fed-batch cultivation processes is presented. Its advantages over model supported control is that the algorithm only needs a minimum of information about the process. Moreover, it is independent of the specific microorganism, the cultivation phase and the biomass level. Also, only a minimum of soft- and hardware is required. Hence, the approach is attractive for industrial production processes that do not have specialized instrumentation. Its accuracy is comparable with model supported control and thus sufficient for most industrial applications. Simulations and experimental tests of the technique performed for the example of a fed-batch cultivation of E. coli demonstrate a good controller performance for various cultivation conditions and process disturbances. Preferred applications will be production systems where the productivity is critically dependent on the growth rate, e.g. in recombinant protein or antibiotic productions.

Automatic control of the specific growth rate in fed-batch cultivation processes based on an exhaust gas analysis

Biodiesel fuel was produced by the transesterification of microalgae oil using sodium hydroxide as a catalyst. The oil was extracted from heterotrophic cultivated algae biomass. The transesterification process was optimized using response surface methodologyto increase the yield of methyl esters. The Box–Behnken design and fractional factorial design 24-1 points were used to investigate the interaction of process variables, such as the methanol/oil molar ratio, the percentage of sodium hydroxide, the temperature, and the reaction time in the production of biodiesel fuel, and to predict the optimum process conditions for the FAME yield. Based on the results, the optimal conditions for the synthesis of biodiesel fuel were as follows: methanol/oil molar ratio, 7:1; catalyst concentration, 1.0% (by weight of algae oil); temperature, 67°C, and reaction time, 51 minutes. The yield of FAME was confirmed by gas chromatography analysis.

The optimization of biodiesel fuel production from microalgae oil using response surface methodology.

Inferential control algorithms and systems for set-point control of the specific growth rate in fed-batch cultivation processes are presented. Realization of the proposed control systems does not require mathematical model and a priori knowledge of the culture of microorganisms under control. Feed-back signal in PID control loops of the investigated systems is based on measurements of the O2 concentration in exhaust gas and the air supply rate, however, measurements of the other technological parameters related to the culture growth dynamics can also be applied.

Donatas Levišauskas

Papers

Optimization of mixotrophic cultivation of microalgae Chlorella sp. for biofuel production using response surface methodology

Model-based optimization of viral capsid protein production in fed-batch culture of recombinant Escherichia coli.

Automatic control of the specific growth rate in fed-batch cultivation processes based on an exhaust gas analysis

The optimization of biodiesel fuel production from microalgae oil using response surface methodology.

Inferential control of the specific growth rate in fed-batch cultivation processes