Principles Of Experimental Design Research Articles

Improving productivity of citramalate from CO2 by Synechocystis sp. PCC 6803 through design of experiment

BackgroundCyanobacteria have long been suggested as an industrial chassis for the conversion of carbon dioxide to products as part of a circular bioeconomy. The slow growth, carbon fixation rates, and limits of carbon partitioning between biomass and product in cyanobacteria must be overcome to fully realise this industrial potential. Typically, flux towards heterologous pathways is limited by the availability of core metabolites. Citramalate is produced in a single enzymatic step through the condensation of the central metabolites pyruvate and acetyl-CoA; improvements in citramalate productivity can, therefore, be used as a measure of overcoming this limitation. Furthermore, citramalate is a useful biomaterial precursor and provides a route to renewable methyl methacrylate and poly(methyl methacrylate), which is often traded as Perspex or Plexiglas.ResultsHere, we describe a phenomenon where the concerted optimisation of process parameters significantly increased citramalate production in Synechocystis sp. PCC 6803. Design of experiment principles were used to determine the optima for each parameter and the interplay between multiple parameters. This approach facilitated a ~ 23-fold increase in citramalate titre from initial unoptimised experiments. The process of scale-up from batch cultures to 0.5, 2, and 5 L photobioreactors is described. At the 2-L scale, citramalate titres from carbon dioxide reached 6.35 g/L with space–time yields of 1.59 g/L/day whilst 5-L PBRs yielded 3.96 ± 0.23 g/L with a productivity of 0.99 ± 0.06 g/L/day. We believe the decrease in productivity from 2-L to 5-L scale was likely due to the increased pathlength and shading for light delivery reducing incident light per cell. However, changes in productivity and growth characteristics are not uncommon when scaling up biotechnology processes and have numerous potential causes.ConclusionsThis work demonstrates that the use of a process parameter control regime can ameliorate precursor limitation and enhance citramalate production. Since pyruvate and/or acetyl-CoA give rise to numerous products of biotechnological interest, the workflow presented here could be employed to optimise flux towards other heterologous pathways. Understanding the factors controlling and thus increasing carbon partitioning to product will help progress cyanobacteria as part of a carbon–neutral circular bioeconomy. This is the first study using design of experiment to optimise overall carbon fixation rate and carbon partitioning to product, with the goal of improving the performance of a cyanobacterium as a host for biological carbon capture.

A hybrid approach for the machinability analysis of Incoloy 825 using the entropy-MOORA method

Abstract With its exceptional qualities, Incoloy 825 is highly valued in a range of industries, including nuclear power plants, petrochemical plants, and chemical industries. Nevertheless, the unique combination of these properties presents a formidable challenge when it comes to machining Incoloy 825. Its low heat conductivity, rapid strain hardening, strong chemical affinity, and the presence of hard and abrasive particles in its microstructure all contribute to the difficulty. The objective of this study is to examine important factors related to the machinability of Incoloy 825. To achieve this, a hybrid tool called entropy coupled with MOORA will be used to determine the optimal cutting conditions. In order to achieve this, three specific input parameters were chosen: the spindle speed, feed rate, and depth of cut. Meanwhile, the major outcomes taken into account were the cutting force, cutting temperature, material removal rate, roughness of the machined surface, and flank wear. The experiments were conducted using Taguchi’s L27 orthogonal array, following the principles of experimental design. The findings indicate that the proposed hybrid approach is capable of accurately determining the best combination of parameters for cutting the chosen work material and can be employed in structural applications. For turning Incoloy 825, the optimal parametric setting was determined to be a spindle speed of 1,285 rpm, a feed rate of 0.0625 mm·rev−1, and a depth of cut of 0.3 mm.

Investigating immersion and migration decisions for agent-based modelling: Acautionary tale.

Agent-based modelling provides an appealing methodological choice for simulating human behaviour and decisions. The currently dominant approaches based on static transition rates or unverified assumptions are restrictive, and could be enhanced with insights from cognitive experiments on actual decision making. Here, one common concern is that standard surveys or experiments may lack ecological validity, limiting the extent to which research findings can be generalised to real-life settings. For complex, highly emotive decision-making scenarios, such as those related to irregular migration, the typically used short, methodical survey questions may not appropriately map onto complex real-world decisions of interest. Immersive contexts may offer more accurate representations of reality, potentially enhancing the usefulness of experimental information in multi-disciplinary modelling endeavours. This preregistered study, aimed directly at examining the effect of immersion on risk-taking in the context of migration decisions, and indirectly at informing a multi-disciplinary construction of an agent-based model of migration, presents a choice-based interactive fiction game in which players make migration decisions to advance through a story. (N = 1000 Prolific users) took part in one of four experimental conditions, three involving different renditions of the game attempting to create immersion, with the last condition presenting the decisions in standard survey format. Although addressing the lack of ecological validity in survey data is important for improving agent-based modelling methodology, the experimental design used to tackle this issue, while responding directly to modelling needs, proved too complex. The created experimental conditions ended up too distinct from each other, involving stimuli that differed in quantity and content. This introduced several unintended and uncontrolled confounds, making it impossible to meaningfully interpret the results of this experiment on its own. Our results act as a cautionary tale for agent-based modellers, highlighting that the modelling needs should not override the principles of experimental design, and provide motivation for more rigorous research on this topic.

Optimization of Progressive Freeze Crystallization Process by Response Surface Methodology for the Treatment of Electroplating Wastewater for Copper (II) Sulphate Recovery

<p style="line-height:200%;text-align:justify;text-indent:0cm;text-justify:inter-ideograph;"><span style="line-height:200%;" lang="EN-US">For the copper-containing electroplating wastewater generated by a semiconductor company, the recovery of copper salts by progressive freeze crystallization and its process parameters were experimentally optimized and studied. Based on the results of single-factor experiments, according to the principles of Box-Behnken Design experimental design for response surface methodology to investigate the effects of coolant temperature, agitation rate, and freezing time on salt removal and optimize process parameters. The optimization results of the response surface method showed that the optimal conditions were when the coolant temperature was -8°C, the stirring rate was 264 r</span><span style="font-family:Symbol;line-height:200%;" lang="EN-US">×</span><span style="line-height:200%;" lang="EN-US">min<sup>-1</sup>, and the freezing time was 78 min. Three validation experiments were conducted under optimum conditions, and salt removal was obtained as 60.13 ± 4.10%, which is more in line with the predicted values. Treatment of copper-containing electroplating wastewater using tertiary freezing under response surface optimized experimental conditions. At this time, the total ice rate of the wastewater was about 65.00%, and the conductivity was also concentrated from 2.17 mS</span><span style="font-family:Symbol;line-height:200%;" lang="EN-US">×</span><span style="line-height:200%;" lang="EN-US">cm<sup>-1</sup> of the raw water to 2.99 mS</span><span style="font-family:Symbol;line-height:200%;" lang="EN-US">×</span><span style="line-height:200%;" lang="EN-US">cm<sup>-1</sup> with a total concentration ratio of 1.38. In addition, a higher concentration of concentrated liquid was obtained in the third freezing, while a crystalline salt precipitated from the bottom of the reactor. The precipitate was analyzed mainly as copper sulfate pentahydrate using XRD, XRF, EDS, and other characterization techniques.</span><span lang="EN-US"> Theoretical calculations show that pre-cooling of raw wastewater reduces energy consumption by up to 20.40%.</span></p>

Construction of Optimal Regeneration System for Chrysanthemum '11-C-2' Stem Segment with Buds.

Chrysanthemum morifolium '11-C-2' is a variety of chrysanthemums with high ornamental and tea value, experiencing significant market demand. However, as cultivation areas expand, issues such as viral infection, germplasm degradation, low proliferation coefficient, and slow proliferation rate arise, necessitating the establishment of an efficient in vitro regeneration system. This study, based on the principles of orthogonal experimental design, explored the regeneration system of Chrysanthemum cultivar '11-C-2' using sterile seedlings. The research focused on three key stages: adventitious bud differentiation, rooting culture, and acclimatization-transplantation, employing shoot-bearing stem segments and leaves as explants. The findings indicate that the optimal explant for the Chrysanthemum '11-C-2' sterile seedlings is the shoot-bearing stem segment. The best medium for adventitious bud differentiation was determined to be MS supplemented with 1.5 mg/L 6-BA and 0.5 mg/L NAA. Bud differentiation began on day 17 with a 100% differentiation rate, completing around day 48. The maximum differentiation coefficient reached 87, with an average of 26.67. The adventitious buds were then cultured for rooting in the optimal medium of 1/2 MS supplemented with 0.1 mg/L NAA. Rooting was initiated on day 4 and was completed by day 14, achieving a rooting rate of 97.62%. After a 5-day acclimatization under natural light, the rooted seedlings were transplanted into a growth substrate with a peat-to-vermiculite ratio of 1:2. The plants exhibited optimal growth, with a transplantation survival rate of 100%. The findings provide data support for the efficient large-scale propagation of '11-C-2' and lay the foundation for germplasm preservation and genetic transformation research of tea chrysanthemums.

Principles in experimental design for evaluating genomic forecasts

Abstract Over the past decade, there has been a rapid increase in the development of predictive models at the intersection of molecular ecology, genomics, and global change. The common goal of these ‘genomic forecasting’ models is to integrate genomic data with environmental and ecological data in a model to make quantitative predictions about the vulnerability of populations to climate change. Despite rapid methodological development and the growing number of systems in which genomic forecasts are made, the forecasts themselves are rarely evaluated in a rigorous manner with ground‐truth experiments. This study reviews the evaluation experiments that have been done, introduces important terminology regarding the evaluation of genomic forecasting models, and discusses important elements in the design and reporting of ground‐truth experiments. To date, experimental evaluations of genomic forecasts have found high variation in the accuracy of forecasts, but it is difficult to compare studies on a common ground due to different approaches and experimental designs. Additionally, some evaluations may be biased toward higher performance because training data and testing data are not independent. In addition to independence between training data and testing data, important elements in the design of an evaluation experiment include the construction and parameterization of the forecasting model, the choice of fitness proxies to measure for test data, the construction of the evaluation model, the choice of evaluation metric(s), the degree of extrapolation to novel environments or genotypes, and the sensitivity, uncertainty and reproducbility of forecasts. Although genomic forecasting methods are becoming more accessible, evaluating their limitations in a particular study system requires careful planning and experimentation. Meticulously designed evaluation experiments can clarify the robustness of the forecasts for application in management. Clear reporting of basic elements of experimental design will improve the rigour of evaluations, and in turn our understanding of why models work in some cases and not others.

Study on the Permanent Deformation and Dynamic Stress–Strain of Coarse-Grained Subgrade Filler under Cyclic Loading

Using coal gangue as a subgrade filler will produce good benefits, and its application prospects are very broad. It is of great engineering and scientific value to study the improvement method and dynamic characteristics of coal gangue subgrade filler under traffic load. Combining the properties of coal gangue material, fly ash and lime and soil were added to improve the bearing behavior of coal gangue subgrade filler. Then, a compaction test was carried out using the principle of orthogonal experimental design. By analyzing the compaction test results, the optimal proportion of each additive was obtained. A large-scale dynamic triaxial test was carried out with the proportion of each admixture in the maximum dry density group in the compaction test. Based on the dynamic triaxial test results, the effect of confining pressure on the permanent strain was analyzed, the analysis model of permanent deformation and cycle number of traffic loading was proposed, and the correctness of the model was verified. In addition, a modified Hardin–Drnevich model was established, which can describe the dynamic stress–dynamic strain curve of coal gangue subgrade filler under traffic load, and then, the dynamic modulus and damping ratio were analyzed.

A Methodology for Robust Multislice Ptychography.

While multislice electron ptychography can provide thermal vibration limited resolution and structural information in 3D, it relies on properly selecting many intertwined acquisition and computational parameters. Here, we outline a methodology for selecting acquisition parameters to enable robust ptychographic reconstructions. We develop two physically informed metrics, areal oversampling and Ronchigram magnification, to describe the selection of these parameters in multislice ptychography. Through simulations, we comprehensively evaluate the validity of these two metrics over a broad range of conditions and show that they accurately guide reconstruction success. Further, we validate these conclusions with experimental ptychographic data and demonstrate close agreement between trends in simulated and experimental data. Using these metrics, we achieve experimental multislice reconstructions at a scan step of 2.1Å/px, enabling large field-of-view, data-efficient reconstructions. These experimental design principles enable the routine and robust use of multislice ptychography for 3D characterization of materials at the atomic scale.

A Combined Paddy Field Inter-Row Weeding Wheel Based on Display Dynamics Simulation Increasing Weed Mortality

Weeds compete with rice for sunlight and nutrients and are prone to harboring pathogens, leading to reduced rice yields. Addressing the issues of low weeding efficiency and weed mortality rates in existing inter-row weeding devices, the study proposes the design of a combination paddy field inter-row weeding wheel. The device’s operation process is theoretically analyzed based on the weed control requirements in the northeastern region of China, leading to the determination of specific structural parameters. This research conducted experiments on the mechanical properties of weed cutting to obtain geometric parameters for paddy field weeds. It was found that the range for the cutting gap of the dynamic–fixed blade is between 0.6 mm to 1.4 mm and the cutting angle is between 5° to 15°, resulting in the lowest peak cutting force for weeds. Using LS-DYNA R12.0.0 dynamic simulation software, a fluid–structure interaction (FSI) model of the weeding wheel–water–soil system was established. By employing the central composite experimental design principle and considering the soil stir rate and coupling stress as indicators, the optimal structural parameter combination for the device is obtained: a dynamic–fixed blade cutting gap of 1.4 mm, a cutting angle of 10.95°, and a dynamic blade install angle of −3.44°. Field experiments demonstrated that the device achieved an average weeding rate of 89.7% and an average seedling damage rate of 1.9%, indicating excellent performance. This study contributes to improving weed mortality rates and provides valuable guidance for inter-row mechanical weeding technology.

Machine learning for bending behavior of sandwich beams with 3D‐printed core and natural fiber‐reinforced composite face sheets

AbstractThe primary objective of this study was to demonstrate the effectiveness of machine learning (ML) in predicting the mechanical behavior of sandwich structures. To achieve this, the study focused on assessing the bending response of environmentally friendly sandwich beams consisting of auxetic cores made from polylactic acid (PLA) and flax/epoxy composite face sheets reinforced with halloysite nanotubes (HNTs). Two ML techniques, specifically shallow neural networks (SNNs) and deep neural networks (DNNs), were employed to predict the specific energy absorption (SEA) and load‐deflection curves of these sandwich beams, respectively. The key design parameters under consideration included the HNT content in the face sheets and three geometric characteristics of the auxetic cells. Subsequently, 16 distinct specimens were meticulously designed for manufacturing, following Taguchi's experimental design principles. The cores of the structures were produced using 3D printing techniques, while the face sheets were meticulously fabricated using a hand layup process. These prepared specimens were then subjected to a three‐point bending test, and the collected data were employed to train the aforementioned neural networks. The outcomes of this study revealed that an SNN with a single hidden layer comprising seven neurons effectively predicted the SEA of the structures across various design parameter values. Additionally, the remarkable performance of a DNN, consisting of five hidden layers with 128, 64, 32, 16, and 8 units, respectively, was demonstrated by comparing its predicted results with the experimental results for a randomly designed sandwich beam.Highlights ML techniques were used for bending behavior of sandwich beams. The beams were made of flax/epoxy/HNT face sheets and 3D‐printed auxetic core. SNN was successfully employed to predict the SEA of the structures. DNN effectively predicted the load‐deflection curves. HNT content and auxetic cells significantly impacted the bending properties.

Optimization of the Green Fibre Paper Film Preparation Process Based on Box–Behnken Response Surface Methodology

To improve the utilization rate of flax straw and the clean treatment of livestock manure, an experimental study was conducted on the process and performance of making fibre paper films by mixing cow dung and flax straw fibre. Cow dung and flax straw were used as the main raw materials, and functional additives were not added. The whole technological process of the pretreatment, the beating process, the determination of the beating degree, the basis weight of the paper, papermaking, drying, sample cutting, and the determination and analysis of the related mechanical properties of the film-making materials were studied. In this study, the Box–Behnken experimental design principle in the response surface methodology was adopted, and the effect of each factor on the tensile strength and tear strength of fibre paper film made of mixed fibres was determined using the combined experimental design comprising four factors and three levels centres. The results showed that the optimum technological parameters were as follows: the beating degree of the cow dung fibre was 37 °SR, the beating degree of the flax straw fibre was 85 °SR, the paper basis weight was 80 g/m2, and the addition of flax straw fibre was 65%. At a drying temperature of 80 °C and a drying time of 8 min, under the conditions of the hybrid fibre paper film placed in the laboratory environment (humidity of 30%~40%, temperature of 18 °C) for 24 h, the measured tensile strength was about 8.26 MPa, and the tear strength was about 19.91 N/mm. This study provides a reference that can be used for the further study of fibre paper film.

Investigating immersion and migration decisions for agent-based modelling: A cautionary tale

Background Agent-based modelling provides an appealing methodological choice for simulating human behaviour and decisions. The currently dominant approaches based on static transition rates or unverified assumptions are restrictive, and could be enhanced with insights from cognitive experiments on actual decision making. Here, one common concern is that standard surveys or experiments may lack ecological validity, limiting the extent to which research findings can be generalised to real-life settings. For complex, highly emotive decision-making scenarios, such as those related to migration, the typically used short, methodical survey questions may not appropriately map onto complex real-world decisions of interest. Immersive contexts may offer more accurate representations of reality, potentially enhancing the usefulness of experimental information in multi-disciplinary modelling endeavours. Methods This pre-registered study of migration decisions, aimed at informing a multi-disciplinary construction of an agent-based model of migration, presents a choice-based interactive fiction game in which players make migration decisions to advance through a story. Participants (N = 1000 Prolific users) were randomly assigned to one of four experimental conditions, three involving different renditions of the game attempting to create immersion, with the last condition presenting the decisions in standard survey format. Results Although addressing the lack of ecological validity in survey data is important for improving agent-based modelling methodology, the experimental design used to tackle this issue, while responding directly to modelling needs, proved too complex. The created experimental conditions ended up too distinct from each other, involving stimuli that differed in quantity and content. This introduced several unintended and uncontrolled confounds, making it impossible to meaningfully interpret the results of this experiment on its own. Our results act as a cautionary tale for agent-based modellers, highlighting that the modelling needs should not override the principles of experimental design, and provide motivation for more rigorous research on this topic.

Simulation and Experiment of Fertilizer Discharge Characteristics of Spiral Grooved Wheel with Different Working Parameters

Fertilizer particles have strong hygroscopicity and agglomeration often occurs during their storage, which leads to a blocked phenomenon during the operation of the external grooved wheel fertilizer discharger. In this study, the bond model of fertilizer block was constructed based on the discrete element method (DEM) to further explore the effect of different working parameters of the spiral grooved wheel on the fertilizer discharge characteristics. According to the Box–Behnken experimental design principle, a three-factor and three-level simulation experiment was carried out with the factors of grooved wheel speed, grooved wheel section shape, and spiral rise angle. The simulation results showed the variation coefficient of fertilizer uniformity was affected, from important to secondary, mainly by the rotating speed of the grooved wheel, the cross-sectional shape of the grooved wheel, and the spiral rise angle. The broken rate of fertilizer block bond was affected, from important to secondary, mainly by the spiral rise angle, the cross-sectional shape of the grooved wheel, and the rotational speed of the grooved wheel. The optimal combination of working parameters was obtained by optimizing and analyzing the data; the rotating speed of the grooved wheel was 21 r/min, the scoop section, and the spiral rise angle was 70°. Under the best working parameters, the variation coefficient of fertilizer uniformity was 8.56%, and the broken rate of fertilizer block bond was 97.67%. The validation experiment results showed that the variation coefficient of fertilizer uniformity was 9.23%, the broken rate of fertilizer block bond was 94.28%, and the relative data error was less than 10%. The experimental results are close to the simulation results. The research results can provide a reference for the structural design and parameter optimization of spiral grooved wheel fertilizer discharger.

Row selection in remote sensing from four-row plots of maize and sorghum based on repeatability and predictive modeling.

Remote sensing enables the rapid assessment of many traits that provide valuable information to plant breeders throughout the growing season to improve genetic gain. These traits are often extracted from remote sensing data on a row segment (rows within a plot) basis enabling the quantitative assessment of any row-wise subset of plants in a plot, rather than a few individual representative plants, as is commonly done in field-based phenotyping. Nevertheless, which rows to include in analysis is still a matter of debate. The objective of this experiment was to evaluate row selection and plot trimming in field trials conducted using four-row plots with remote sensing traits extracted from RGB (red-green-blue), LiDAR (light detection and ranging), and VNIR (visible near infrared) hyperspectral data. Uncrewed aerial vehicle flights were conducted throughout the growing seasons of 2018 to 2021 with data collected on three years of a sorghum experiment and two years of a maize experiment. Traits were extracted from each plot based on all four row segments (RS) (RS1234), inner rows (RS23), outer rows (RS14), and individual rows (RS1, RS2, RS3, and RS4). Plot end trimming of 40cm was an additional factor tested. Repeatability and predictive modeling of end-season yield were used to evaluate performance of these methodologies. Plot trimming was never shown to result in significantly different outcomes from non-trimmed plots. Significant differences were often observed based on differences in row selection. Plots with more row segments were often favorable for increasing repeatability, and excluding outer rows improved predictive modeling. These results support long-standing principles of experimental design in agronomy and should be considered in breeding programs that incorporate remote sensing.

OPTIMIZATION OF THE MANUFACTURING OF METASEQUOIA-BASED THREE-LAYER STRUCTURE PARQUET FLOORING BY A RESPONSE SURFACE METHODOLOGY

On the basis of a single-factor experiment, a mathematical model was established by the response surface analysis method based on the Box-Behnken experimental design principle. The effects of three factors, including hot-pressing temperature, hot-pressing time, and hot-pressing pressure, and their interactions on the modulus of rupture (MOR) of Metasequoia-based three-layered structure parquet flooring were studied. The results show that the quadratic polynomial model in the regression equation is significant, and the correlation between the value predicted by the model and the experimental value is 91.17%. The optimized best hot-pressing process parameters are determined to be as follows: hot-pressing temperature of 96.03°C, hot-pressing time of 6.70 min, and hot-pressing pressure of 8 kg·cm-2. Under these conditions, the best MOR are obtained, reaching a value of 102.05 MPa. The theoretically predicted value is in good agreement with the experimental results.

Performance simulation and perforated parameters optimize for perforated wells with compaction zone and drilling damage in tight gas reservoirs

It is essential to understand how to improve the production of perforated well in tight reservoirs. In this paper, based on the experiment of experiment evaluation of perforation tunnel and perforation compaction zone, the drilling mud invasion zone and stress sensitivity, a new productivity numerical model is established considering the damaged zone being drilling, and the compaction zone being penetrated and the sensitivity in tight gas reservoirs. Considering perforation interaction, drill damage and seepage interference, the production rate under different parameters of perforation, compaction zone, damaged zone is discussed to yield the highest productivity. The numerical results show that it exists an optimal hole density in specific formation and when the perforated hole penetrates the invasion zone, increasing the depth of the perforation hole by the same amount would not result in a significant increase in gas production. The invasion and compaction zone permeability have little effect on the cumulative gas production, but an inflexion point still existed. Further, according to the principle of orthogonal experimental design, forty-one groups of orthogonal experimental calculations are designed and conducted. By analyzing the experimental results, the perforation density, hole diameter, invasion thickness, compaction zone thickness, invasion permeability, compaction zone permeability and stress sensitivity on productivity of perforated well is in descending order. The work presented in this paper can offer a technological basis and theoretical foundation for optimizing perforation parameters in specific tight gas reservoirs.

Discussion of ‘Is designed data collection still relevant in the Big Data era?'

AbstractGiven the popularity of Big Data (BD), there can be an impression that fields such as design of experiments (DOE) are now irrelevant. We would like to thank the authors for starting the conversation about the possible relationship between these two fields. A key contribution of this paper is in showing how DOE principles, as summarized under the name designed data collection (DDC), can be applied throughout the BD process. This name is quite appropriate, demonstrating that these principles apply not just to designed experiments, but to any form of data collection. This is especially important for situations where designed experiments are either impossible (i.e., assessing how a country's economy may impact certain responses) or unethical (i.e., certain sensitive types of medical studies). It shows that DOE is more than a particular choice of design type, but is rather a methodology for approaching data collection. One that seeks to extract the most relevant information from the data while also taking into account the various nuances and constraints of physical and social processes, which are ever present, even in massive datasets. The paper divides BD efforts into three general phases: Before BD, During BD, and After BD. As such, we have grouped our discussion accordingly, with general comments provided for the suggested contributions of DDC in each phase. We then close with some additional thoughts.

Is designed data collection still relevant in the big data era? – A discussion

Is designed data collection still relevant in the big data era? – A discussion

Rapid Development of Cell State Identification Circuits with Poly-Transfection.

Mammalian genetic circuits have demonstrated the potential to sense and treat a wide range of disease states, but optimization of the levels of circuit components remains challenging and labor-intensive. To accelerate this process, our lab developed poly-transfection, a high-throughput extension of traditional mammalian transfection. In poly-transfection, each cell in the transfected population essentially performs a different experiment, testing the behavior of the circuit at different DNA copy numbers and allowing users to analyze a large number of stoichiometries in a single-pot reaction. So far, poly-transfections that optimize ratios of three-component circuits in a single well of cells have been demonstrated; in principle, the same method can be used for the development of even larger circuits. Poly-transfection results can be easily applied to find optimal ratios of DNA to co-transfect for transient circuits or to choose expression levels for circuit components for the generation of stable cell lines. Here, we demonstrate the use of poly-transfection to optimize a three-component circuit. The protocol begins with experimental design principles and explains how poly-transfection builds upontraditional co-transfection methods. Next, poly-transfection of cells is carried out and followed by flow cytometry a few days later. Finally, the data is analyzed by examining slices of the single-cell flow cytometry data that correspond to subsets of cells with certain component ratios. In the lab, poly-transfection has been used to optimize cell classifiers, feedback and feedforward controllers, bistable motifs, and many more. This simple but powerful method speeds up design cycles for complex genetic circuits in mammalian cells.

Single-Case Experimental Design in Rehabilitation: Basic Concepts, Advantages, and Challenges.

Single-case experimental design is a family of experimental methods that can be used to examine the efficacy of interventions by testing a small number of patients or cases. This article provides an overview of single-case experimental design research for use in rehabilitation as another option along with traditional group-based research when studying rare cases and rehabilitation interventions of unknown efficacy. Basic concepts related to single-case experimental design and the characteristics of common subtypes ( N-of-1 randomized controlled trial, withdrawal design, multiple-baseline design, multiple-treatment design, changing criterion/intensity design, and alternating treatment design) are introduced. The advantages and disadvantages of each subtype are discussed along with challenges in data analysis and interpretation. Criteria and caveats for interpreting single-case experimental design results and their use in evidence-based practice decisions are discussed. Recommendations are provided for appraising single-case experimental design articles as well as using single-case experimental design principles to improve real-world clinical evaluation.