Self-self hybridization as an alternative experiment design to dye swap for two-color microarrays

Dye-specific bias effects, commonly observed in the two-color microarray platform, are normally corrected using the dye swap design. This design, however, is relatively expensive and labor-intensive. We propose a self-self hybridization design as an alternative to the dye swap design. In this design, the treated and control samples are labeled with Cy5 and Cy3 (or Cy3 and Cy5), respectively, without dye swap, along with a set of self-self hybridizations on the control sample. We compare this design with the dye swap design through investigation of mouse primary hepatocytes treated with three peroxisome proliferator-activated receptor-alpha (PPARalpha) agonists at three dose levels. Using Agilent's Whole Mouse Genome microarray, differentially expressed genes (DEG) were determined for both the self-self hybridization and dye swap designs. The DEG concordance between the two designs was over 80% across each dose treatment and chemical. Furthermore, 90% of DEG-associated biological pathways were in common between the designs, indicating that biological interpretations would be consistent. The reduced labor and expense for the self-self hybridization design make it an efficient substitute for the dye swap design. For example, in larger toxicogenomic studies, only about half the chips are required for the self-self hybridization design compared to that needed in the dye swap design.     

Adaptive Dc-optimal designs for dose finding based on a continuous efficacy endpoint

We introduce a new optimal design for dose finding with a continuous efficacy endpoint. This design is studied in the context of a flexible model for the mean of the dose-response. The design incorporates aspects of both D- and c-optimality and can be used when the study goals under consideration include dose-response estimation, followed by identification of the target dose. Different optimality criteria are considered. Simulations are shown with results comparing our adaptive design to the fixed allocation (without adaptations). We show that both the estimation of dose-response and identification of the minimum effective dose are improved using our design.     

Principles of the design and operational considerations of large scale high performance liquid chromatography (HPLC) systems for proteins and peptides purification.

This review introduces concepts of design of large scale HPLC systems for purification of proteins and peptides. It is addressed to users of large scale HPLC systems to aid in system selection and help in customizing the design. Major techniques used for large scale HPLC purification of proteins and peptides are briefly reviewed. Engineering aspects of system design are discussed in detail. The review of selected relevant literature is provided as well as author's experience with the existing designs and his own systems. Commercial publications have been used in preparation of this review but only the most significant are listed as examples. The design process for any new system should be related to the performance of existing systems, if possible of a large scale. Laboratory data are also very useful in aiding the design process since they provide a lead, as to which chromatography techniques may succeed in providing required separation levels. The expertise needed for system design and operation comes from many areas: protein and peptide chemistry, chromatographic theory, mass transfer and hydrodynamics, machine design and material science. All these factors have to be blended together during the system design process. The controls must ensure flexibility in adapting to changing system configuration, depending on the operational requirements for various products. Extensive interfacing with the operator during the process run is essential. This work is focused mostly on system design and operation for reversed-phase chromatography and hydrophobic interaction chromatography, but it also covers aspects associated with other chromatographic techniques. The reviewed design principles would also apply to design other than HPLC large scale chromatography systems for biotechnology and pharmaceutical operations.     

Specific primer design for the polymerase chain reaction

The design of primers has a major impact on the success of PCR in relation to the specificity and yield of the amplified product. Here, we introduce the applications of PCR as well as the definition and characteristics for PCR primer design. Recent primer design tools based on Primer3, along with several computational intelligence-based primer design methods which have been applied in primer design, are also reviewed. In addition, characteristics of population-based methods used in primer design are discussed in detail.     

生态工程设计研究进展及特点——以黑龙江省肇东市玉米生态工程为例

生态工程设计是生态工程建设的核心。明确生态工程设计的特点,是进行良好的生态工程设计的根本。通过生态设计研究进展的综述,从１０个方面,以肇东市玉米生态工程设计为例,分析了生态工程设计的特点,并在此基础上,提出了今后进行生态工程设计应采取的策略。     

Quality-by-Design II: Application of Quantitative Risk Analysis to the Formulation of Ciprofloxacin Tablets

Qualitative risk assessment methods are often used as the first step to determining design space boundaries; however, quantitative assessments of risk with respect to the design space, i.e., calculating the probability of failure for a given severity, are needed to fully characterize design space boundaries. Quantitative risk assessment methods in design and operational spaces are a significant aid to evaluating proposed design space boundaries. The goal of this paper is to demonstrate a relatively simple strategy for design space definition using a simplified Bayesian Monte Carlo simulation. This paper builds on a previous paper that used failure mode and effects analysis (FMEA) qualitative risk assessment and Plackett-Burman design of experiments to identity the critical quality attributes. The results show that the sequential use of qualitative and quantitative risk assessments can focus the design of experiments on a reduced set of critical material and process parameters that determine a robust design space under conditions of limited laboratory experimentation. This approach provides a strategy by which the degree of risk associated with each known parameter can be calculated and allocates resources in a manner that manages risk to an acceptable level.     

Scale-up of cell culture bioreactors using biomechatronic design

Scale-up of cell culture bioreactors is a challenging engineering work that requires wide competence in cell biology, mechanical engineering and bioprocess design. In this article, a new approach for cell culture bioreactor scale-up is suggested that is based on biomechatronic design methodology. The approach differs from traditional biochemical engineering methodology by applying a sequential design procedure where the needs of the users and alternative design solutions are systematically analysed. The procedure is based on the biological and technical functions of the scaled-up bioreactor that are derived in functional maps, concept generation charts and scoring and interaction matrices. Basic reactor engineering properties, such as mass and heat transfer and kinetics are integrated in the procedure. The methodology results in the generation of alternative design solutions that are thoroughly ranked with help of the user needs. Examples from monoclonal antibodies and recombinant protein production illuminate the steps of the procedure. The methodology provides engineering teams with additional tools that can significantly facilitate the design of new production methods for cell culture processes.     

BIOASSAY SYSTEMS FOR THE PYRETHRINS

The special properties of pyrethrum assays with crawling insects by the film technique lend themselves to the twin cross-over design, hitherto restricted to assays with graded responses. The conditions under which this design is appropriate, and the treatment of control responses, are discussed. The design is particularly efficient with laboratory cultures of insects with fairly stable tolerance levels, and is also useful with heterogeneous populations collected in the field. Examples of the increased precision afforded are considered. The reversibility of the primary responses of grain weevils to the pyrethrins is also demonstrated.     

均衡独立样本设计的研究

均衡独立样本设计是一种把独立样本设计与差异显著性检验相结合的试验设计．它基本上可以保证参试的优劣个体在所分样本（或组）间的分布相对均匀一致,使所分样本既具有独立性又具有均衡性,以增强对处理效果反应的灵敏度,提高试验的准确度．     

Design and Analysis of Crossover Trials for Absorbing Binary Endpoints

Summary The crossover is a popular and efficient trial design used in the context of patient heterogeneity to assess the effect of treatments that act relatively quickly and whose benefit disappears with discontinuation. Each patient can serve as her own control as within‐individual treatment and placebo responses are compared. Conventional wisdom is that these designs are not appropriate for absorbing binary endpoints, such as death or HIV infection. We explore the use of crossover designs in the context of these absorbing binary endpoints and show that they can be more efficient than the standard parallel group design when there is heterogeneity in individuals' risks. We also introduce a new two‐period design where first period “survivors” are rerandomized for the second period. This design combines the crossover design with the parallel design and achieves some of the efficiency advantages of the crossover design while ensuring that the second period groups are comparable by randomization. We discuss the validity of the new designs and evaluate both a mixture model and a modified Mantel–Haenszel test for inference. The mixture model assumes no carryover or period effects while the Mantel–Haenszel approach conditions out period effects. Simulations are used to compare the different designs and an example is provided to explore practical issues in implementation.     

External cross-validation for unbiased evaluation of protein family detectors: application to allergens

Key issues in protein science and computational biology are design and evaluation of algorithms aimed at detection of proteins that belong to a specific family, as defined by structural, evolutionary, or functional criteria. In this context, several validation techniques are often used to compare different parameter settings of the detector, and to subsequently select the setting that yields the smallest error rate estimate. A frequently overlooked problem associated with this approach is that this smallest error rate estimate may have a large optimistic bias. Based on computer simulations, we show that a detector's error rate estimate can be overly optimistic and propose a method to obtain unbiased performance estimates of a detector design procedure. The method is founded on an external 10-fold cross-validation (CV) loop that embeds an internal validation procedure used for parameter selection in detector design. The designed detector generated in each of the 10 iterations are evaluated on held-out examples exclusively available in the external CV iterations. Notably, the average of these 10 performance estimates is not associated with a final detector, but rather with the average performance of the design procedure used. We apply the external CV loop to the particular problem of detecting potentially allergenic proteins, using a previously reported design procedure. Unbiased performance estimates of the allergen detector design procedure are presented together with information about which algorithms and parameter settings that are most frequently selected.     

Experimental design methods for bioengineering applications

Experimental design is a form of process analysis in which certain factors are selected to obtain the desired responses of interest. It may also be used for the determination of the effects of various independent factors on a dependent factor. The bioengineering discipline includes many different areas of scientific interest, and each study area is affected and governed by many different factors. Briefly analyzing the important factors and selecting an experimental design for optimization are very effective tools for the design of any bioprocess under question. This review summarizes experimental design methods that can be used to investigate various factors relating to bioengineering processes. The experimental methods generally used in bioengineering are as follows: full factorial design, fractional factorial design, Plackett–Burman design, Taguchi design, Box–Behnken design and central composite design. These design methods are briefly introduced, and then the application of these design methods to study different bioengineering processes is analyzed.     

Cardiovascular system simulation requirements.

Circulatory system characteristics are considered with respect to specifying model design parameters for simulators and pulse duplicators. The requirements are investigated to determine what characteristics and parameters are important in design and construction. The specific design depends on the functions of the device to be investigated. The single most important quantity is the modeled proximal capacitance or compliance of the large vessels. More detailed study specifications require more detailed models.     

单形格子和单形重心设计统计模型的优化分析方法

单形格子和单形重心设计是两种非常实用的配方试验设计方法,但其统计模型的优化分析却很困难．本文通过对单形格子和单形重心设计基本原理的分析,根据数学规划理论,构建了专门对这两种试验设计的统计模型进行优化分析的方法,同时给出了应用实例．     

Directed evolution of (betaalpha)(8)-barrel enzymes

Natural molecular evolution supplies us with manifold examples of protein engineering. The imitation of these natural processes in the design of new enzymes has led to surprising and insightful results. Well-suited for design by evolutionary methods are enzymes with the common and versatile (betaalpha)(8)-barrel fold. Studies of enzyme stability, folding and design as well as the evolution of (betaalpha)(8)-barrel enzymes are discussed.     

Design – an inappropriate concept in evolutionary theory*

The concept of accident in evolution refers to causes which are stochastic with respect to selective demands arising from the external environment and acting on the organism, while the concept of design refers to causes which meet the requirement of these selective demands. The condition ‘with respect to selective demands’ is generally forgotten so that evolutionary changes are described as being design modifications. Design is an invalid synonym for adaptation. Further it implies a designer and has been used by some authors since before Darwin to argue that design in organisms demonstrates the existence of a designer and hence a plan. Yet if evolution depends on two simultaneously acting causes, one of which is accidental, then the process of evolution and all attributes of organisms are accidental. The concept of design is inappropriate in biology and should be eliminated from all biological explanations.     

RosettaSurf—A surface-centric computational design approach

Proteins are typically represented by discrete atomic coordinates providing an accessible framework to describe different conformations. However, in some fields proteins are more accurately represented as near-continuous surfaces, as these are imprinted with geometric (shape) and chemical (electrostatics) features of the underlying protein structure. Protein surfaces are dependent on their chemical composition and, ultimately determine protein function, acting as the interface that engages in interactions with other molecules. In the past, such representations were utilized to compare protein structures on global and local scales and have shed light on functional properties of proteins. Here we describe RosettaSurf, a surface-centric computational design protocol, that focuses on the molecular surface shape and electrostatic properties as means for protein engineering, offering a unique approach for the design of proteins and their functions. The RosettaSurf protocol combines the explicit optimization of molecular surface features with a global scoring function during the sequence design process, diverging from the typical design approaches that rely solely on an energy scoring function. With this computational approach, we attempt to address a fundamental problem in protein design related to the design of functional sites in proteins, even when structurally similar templates are absent in the characterized structural repertoire. Surface-centric design exploits the premise that molecular surfaces are, to a certain extent, independent of the underlying sequence and backbone configuration, meaning that different sequences in different proteins may present similar surfaces. We benchmarked RosettaSurf on various sequence recovery datasets and showcased its design capabilities by generating epitope mimics that were biochemically validated. Overall, our results indicate that the explicit optimization of surface features may lead to new routes for the design of functional proteins.     

On the design of check-sheets

Check sheets are now widely used for recording the behavior of primates. This paper is concerned with their design. The need for selecting the material to be recorded with regard to specified goals is emphasized. Various aspects of design, including the nature of the units chosen, the number, scope and mutual exclusiveness of categories, and their physical arrangement on the sheet, are discussed. Recording in time blocks or at predetermined intervals each has its own advantages and difficulties. Check sheets for recording sequences of behavior are considered briefly. The conclusions to be drawn from check sheet data depend on the design of the sheet.     

The design of in vivo multifraction experiments to estimate the alpha-beta ratio

Using statistical methods, the designs of multifraction experiments which are likely to give the most precise estimate of the alpha-beta ratio in the linear-quadratic model are investigated. The aim of the investigation is to try to understand what features of an experimental design make it efficient for estimating alpha/beta rather than to recommend a specific design. A plot of the design on an nd2 versus nd graph is suggested, and this graph is called the design plot. The best designs are those which have a large spread in the isoeffect direction in the design plot, which means that a wide range of doses per fraction should be used. For binary response assays, designs with expected response probabilities near to 0.5 are most efficient. Furthermore, dose points with expected response probabilities outside the range 0.1 to 0.9 contribute negligibly to the efficiency with which alpha/beta can be estimated. For "top-up" experiments, the best designs are those which replace as small a portion as possible of the full experiment with the top-up scheme. In addition, from a statistical viewpoint, it makes no difference whether a single large top-up dose or several smaller top-up doses are used; however, other considerations suggest that two or more top-up doses may be preferable. The practical realities of designing experiments as well as the somewhat idealized statistical considerations are discussed.     

Experimental design for gene expression microarrays

We examine experimental design issues arising with gene expression microarray technology. Microarray experiments have multiple sources of variation, and experimental plans should ensure that effects of interest are not confounded with ancillary effects. A commonly used design is shown to violate this principle and to be generally inefficient. We explore the connection between microarray designs and classical block design and use a family of ANOVA models as a guide to choosing a design. We combine principles of good design and A-optimality to give a general set of recommendations for design with microarrays. These recommendations are illustrated in detail for one kind of experimental objective, where we also give the results of a computer search for good designs.