Continuous Adaptive Population Reduction (CAPR) for Differential Evolution Optimization.

Differential evolution (DE) has been applied extensively in drug combination optimization studies in the past decade. It allows for identification of desired drug combinations with minimal experimental effort. This article proposes an adaptive population-sizing method for the DE algorithm. Our new method presents improvements in terms of efficiency and convergence over the original DE algorithm and constant stepwise population reduction-based DE algorithm, which would lead to a reduced number of cells and animals required to identify an optimal drug combination. The method continuously adjusts the reduction of the population size in accordance with the stage of the optimization process. Our adaptive scheme limits the population reduction to occur only at the exploitation stage. We believe that continuously adjusting for a more effective population size during the evolutionary process is the major reason for the significant improvement in the convergence speed of the DE algorithm. The performance of the method is evaluated through a set of unimodal and multimodal benchmark functions. In combining with self-adaptive schemes for mutation and crossover constants, this adaptive population reduction method can help shed light on the future direction of a completely parameter tune-free self-adaptive DE algorithm.

Rapid optimization of drug combinations for the optimal angiostatic treatment of cancer.

Drug combinations can improve angiostatic cancer treatment efficacy and enable the reduction of side effects and drug resistance. Combining drugs is non-trivial due to the high number of possibilities. We applied a feedback system control (FSC) technique with a population-based stochastic search algorithm to navigate through the large parametric space of nine angiostatic drugs at four concentrations to identify optimal low-dose drug combinations. This implied an iterative approach of in vitro testing of endothelial cell viability and algorithm-based analysis. The optimal synergistic drug combination, containing erlotinib, BEZ-235 and RAPTA-C, was reached in a small number of iterations. Final drug combinations showed enhanced endothelial cell specificity and synergistically inhibited proliferation (p < 0.001), but not migration of endothelial cells, and forced enhanced numbers of endothelial cells to undergo apoptosis (p < 0.01). Successful translation of this drug combination was achieved in two preclinical in vivo tumor models. Tumor growth was inhibited synergistically and significantly (p < 0.05 and p < 0.01, respectively) using reduced drug doses as compared to optimal single-drug concentrations. At the applied conditions, single-drug monotherapies had no or negligible activity in these models. We suggest that FSC can be used for rapid identification of effective, reduced dose, multi-drug combinations for the treatment of cancer and other diseases.

Discovery of a low order drug-cell response surface for applications in personalized medicine.

The cell is a complex system involving numerous components, which may often interact in a non-linear dynamic manner. Diseases at the cellular level are thus likely to involve multiple cellular constituents and pathways. As some drugs, or drug combinations, may act synergistically on these multiple pathways, they might be more effective than the respective single target agents. Optimizing a drug mixture for a given disease in a particular patient is particularly challenging due to both the difficulty in the selection of the drug mixture components to start out with, and the all-important doses of these drugs to be applied. For n concentrations of m drugs, in principle, n(m) combinations will have to be tested. As this may lead to a costly and time-consuming investigation for each individual patient, we have developed a Feedback System Control (FSC) technique which can rapidly select the optimal drug-dose combination from the often millions of possible combinations. By testing this FSC technique in a number of experimental systems representing different disease states, we found that the response of cells to multiple drugs is well described by a low order, rather smooth, drug-mixture-input/drug-effect-output multidimensional surface. The main consequences of this are that optimal drug combinations can be found in a surprisingly small number of tests, and that translation from in vitro to in vivo is simplified. This points to the possibility of personalized optimal drug mixtures in the near future. This unexpectedly simple input-output relationship may also lead to a simple solution for handling the issue of human diversity in cancer therapeutics.

Towards constructing multi-bit binary adder based on Belousov-Zhabotinsky reaction.

It has been proposed that the spatial excitable media can perform a wide range of computational operations, from image processing, to path planning, to logical and arithmetic computations. The realizations in the field of chemical logical and arithmetic computations are mainly concerned with single simple logical functions in experiments. In this study, based on Belousov-Zhabotinsky reaction, we performed simulations toward the realization of a more complex operation, the binary adder. Combining with some of the existing functional structures that have been verified experimentally, we designed a planar geometrical binary adder chemical device. Through numerical simulations, we first demonstrated that the device can implement the function of a single-bit full binary adder. Then we show that the binary adder units can be further extended in plane, and coupled together to realize a two-bit, or even multi-bit binary adder. The realization of chemical adders can guide the constructions of other sophisticated arithmetic functions, ultimately leading to the implementation of chemical computer and other intelligent systems.

Accurate and Effective Live Bacteria Microarray Patterning on Thick Polycationic Polymer Layer Co-Patterned with HMDS.

A new bacteria microarray patterning technique is developed by patterning thick polycationic polymers on glass surface, which generates high-coverage and high-precision E. coli cell patterns. Cell immobilization efficiency is greatly improved, compared to conventional monolayer surface patterning approach. Cell viability tests show very low cytotoxicity of polyethyleneimine (PEI). This advancement should further accelerate biomedical and bacteriological researches in the micro scale.

An agar gel membrane-PDMS hybrid microfluidic device for long term single cell dynamic study.

Significance of single cell measurements stems from the substantial temporal fluctuations and cell-cell variability possessed by individual cells. A major difficulty in monitoring surface non-adherent cells such as bacteria and yeast is that these cells tend to aggregate into clumps during growth, obstructing the tracking or identification of single-cells over long time periods. Here, we developed a microfluidic platform for long term single-cell tracking and cultivation with continuous media refreshing and dynamic chemical perturbation capability. The design highlights a simple device-assembly process between PDMS microchannel and agar membrane through conformal contact, and can be easily adapted by microbiologists for their routine laboratory use. The device confines cell growth in monolayer between an agar membrane and a glass surface. Efficient nutrient diffusion through the membrane and reliable temperature maintenance provide optimal growth condition for the cells, which exhibited fast exponential growth and constant distribution of cell sizes. More than 24 h of single-cell tracking was demonstrated on a transcription-metabolism integrated synthetic biological model, the gene-metabolic oscillator. Single cell morphology study under alcohol toxicity allowed us to discover and characterize cell filamentation exhibited by different E. coli isobutanol tolerant strains. We believe this novel device will bring new capabilities to quantitative microbiology, providing a versatile platform for single cell dynamic studies.

Efficient dielectrophoretic patterning of embryonic stem cells in energy landscapes defined by hydrogel geometries.

In this study, we have developed an integrated microfluidic platform for actively patterning mammalian cells, where poly(ethylene glycol) (PEG) hydrogels play two important roles as a non-fouling layer and a dielectric structure. The developed system has an embedded array of PEG microwells fabricated on a planar indium tin oxide (ITO) electrode. Due to its dielectric properties, the PEG microwells define electrical energy landscapes, effectively forming positive dielectrophoresis (DEP) traps in a low-conductivity environment. Distribution of DEP forces on a model cell was first estimated by computationally solving quasi-electrostatic Maxwell's equations, followed by an experimental demonstration of cell and particle patterning without an external flow. Furthermore, efficient patterning of mouse embryonic stem (mES) cells was successfully achieved in combination with an external flow. With a seeding density of 107 cells/mL and a flow rate of 3 µL/min, trapping of cells in the microwells was completed in tens of seconds after initiation of the DEP operation. Captured cells subsequently formed viable and homogeneous monolayer patterns. This simple approach could provide an efficient strategy for fabricating various cell microarrays for applications such as cell-based biosensors, drug discovery, and cell microenvironment studies.

Cell kinase activity assay based on surface enhanced Raman spectroscopy.

Kinases control many important aspects of cell behavior, such as signal transduction, growth/differentiation, and tumorogenesis. Current methods for assessing kinase activity often require specific antibodies, and/or radioactive labeling. Here we demonstrated a novel detection method to assess kinase activity based on surface enhanced Raman spectroscopy (SERS). Raman signal was obtained after amplification by silver nanoparticles. The sensitivity of this method was comparable to fluorescence measurement of peptide concentration. When purified kinase enzyme was used, the detection limit was comparable to conventional radio-labeling method. We further demonstrated the feasibility to measure kinase activity in crude cell lysate. We suggested this SERS-based kinase activity assay could be a new tool for biomedical research and application.

Surface molecular property modifications for poly(dimethylsiloxane) (PDMS) based microfluidic devices.

Fast advancements of microfabrication processes in past two decades have reached to a fairly matured stage that we can manufacture a wide range of microfluidic devices. At present, the main challenge is the control of nanoscale properties on the surface of lab-on-a-chip to satisfy the need for biomedical applications. For example, poly(dimethylsiloxane) (PDMS) is a commonly used material for microfluidic circuitry, yet the hydrophobic nature of PDMS surface suffers serious nonspecific protein adsorption. Thus the current major efforts are focused on surface molecular property treatments for satisfying specific needs in handling macro functional molecules. Reviewing surface modifications of all types of materials used in microfluidics will be too broad. This review will only summarize recent advances in nonbiofouling PDMS surface modification strategies applicable to microfluidic technology and classify them into two main categories: (1) physical approach including physisorption of charged or amphiphilic polymers and copolymers, as well as (2) chemical approach including self assembled monolayer and thick polymer coating. Pros and cons of a collection of available yet fully exploited surface modification methods are briefly compared among subcategories.