Liquid crystals have a long history of use as materials that respond to external stimuli (e.g., electrical and optical fields). More recently, a series of investigations have reported the design of liquid crystalline materials that undergo ordering transitions in response to a range of biological interactions, including interactions involving proteins, nucleic acids, viruses, bacteria and mammalian cells. A central challenge underlying the design of liquid crystalline materials for such applications is the tailoring of the interface of the materials so as to couple targeted biological interactions to ordering transitions. This review describes recent progress toward design of interfaces of liquid crystalline materials that are suitable for biological applications. Approaches addressed in this review include the use of lipid assemblies, polymeric membranes containing oligopeptides, cationic surfactant-DNA complexes, peptide-amphiphiles, interfacial protein assemblies and multi-layer polymeric films.

A basic problem in gene synthesis is the acquisition of many short oligonucleotide sequences needed for the assembly of genes. Photolithographic methods for the massively parallel synthesis of high-density oligonucleotide arrays provides a potential source, once appropriate methods have been devised for their elution in forms suitable for enzyme-catalyzed assembly. Here, we describe a method based on the photolithographic synthesis of long (>60mers) single-stranded oligonucleotides, using a modified maskless array synthesizer. Once the covalent bond between the DNA and the glass surface is cleaved, the full-length oligonucleotides are selected and amplified using PCR. After cleavage of flanking primer sites, a population of unique, internal 40mer dsDNA sequences are released and are ready for use in biological applications. Subsequent gene assembly experiments using this DNA pool were performed and were successful in creating longer DNA fragments. This is the first report demonstrating the use of eluted chip oligonucleotides in biological applications such as PCR and assembly PCR.

Surface-induced ordering of liquid crystals (LCs) offers the basis of a label-free analytical technique for the detection of surface-bound biomolecules. The orientation-dependent energy of interaction of a LC with a surface (anchoring energy of LC), in particular, is both sensitive to the presence of surface-bound molecules and easily quantified. Herein we report a study that analyzes a simple model of twisted nematic LC systems and thereby identifies surfaces with LC anchoring energies in the range of 0.5 μJ/m 2 to 2.0 μJ/m 2 to be optimal for use with LC-based analytical methods. Guided by these predictions, we demonstrate that analytic surfaces possessing anchoring energies within this range can be fabricated with a high level of precision (< 0.1 μJ/m 2 ) through formation of monolayers of organothiols (with ω-functional groups corresponding to oligoethyleneglycols and amines) on gold films deposited by physical vapor deposition at oblique angles of incidence. Finally, by using the human epidermal growth factor receptor (EGFR) as a model protein analyte, we have characterized the influence of the anchoring energies of the surfaces on the response of the LC to the presence of surface-bound EGFR. These results, when combined with 32 P-radiolabeling of the EGFR to independently quantify the surface concentration of EGFR, permit identification of surfaces that allow use of LCs to report surface densities of EGFR of 70-90 pg/mm 2 . Overall, the results reported in this paper guide the design of surfaces for use in LC-based analytical systems.

We report methods for the acquisition and analysis of optical images formed by thin films of twisted nematic liquid crystals (LCs) placed into contact with surfaces patterned with bio/chemical functionality relevant to surface-based assays. The methods are simple to implement and are shown to provide easily interpreted maps of chemical transformations on surfaces that are widely exploited in the preparation of analytic devices. The methods involve acquisition of multiple images of the LC as a function of the orientation of a polarizer; data analysis condenses the information present in the stack of images into a spatial map of the twist angle of the LC on the analytic surface. The potential utility of the methods is illustrated by mapping (i) the displacement of a monolayer formed from one alkanethiol on a gold film by a second thiol in solution, (ii) coadsorption of mixtures of amineterminated and ethyleneglycol-terminated alkanethiols on gold films, which leads to a type of mixed monolayer that is widely exploited for immobilization of proteins on analytic surfaces, and (iii) patterns of antibodies printed onto surfaces. These results show that maps of the twist angle of the LC constructed from families of optical images can be used to reveal surface features that are not apparent in a single image of the LC film. Furthermore, the twist angles of the LC can be used to quantify the energy of interaction of the LC with the surface with a spatial resolution of <10 µm. When combined, the results described in this paper suggest non-destructive methods to monitor and validate chemical transformations on surfaces of the type that are routinely employed in the preparation of surface-based analytic technologies.

An important problem in terrain analysis is modeling how water flows across a terrain and creates floods by filling up depressions. In this article, we study a number of flood-risk related problems: Given a terrain Σ, represented as a triangulated xy-monotone surface with n vertices, a rain distribution R, and a volume of rain ψ , determine which portions of Σ are flooded. We develop efficient algorithms for flood-risk analysis under the multiflow-directions (MFD) model, in which water at a point can flow along multiple downslope edges and which more accurately represent flooding events. We present three main results: First, we present an O (n log n)-time algorithm to answer a terrain-flood query: if it rains a volume ψ according to a rain distribution R, determine what regions of Σ will be flooded. Second, we present a O (n log n + nm)-time algorithm for preprocessing Σ containing m sinks into a data structure of size O (nm) for answering point-flood queries: Given a rain distribution R, a volume of rain ψ falling according to R, and point q ∈ Σ, determine whether q will be flooded. A point-flood query can be answered in O (|R|k + k 2) time, where k is the number of maximal depressions in Σ containing the query point q and |R| is the number of vertices in R with positive rainfall. Finally, we present algorithms for answering a flood-time query: given a rain distribution R and a point q ∈ Σ, determine the volume of rain that must fall before q is flooded. Assuming that the product of two k × k matrices can be computed in O (k ω) time, we show that a flood-time query can be answered in O (nk + k ω) time. We also give an α-approximation algorithm, for α > 1, which runs in O (n log n log α ρ)-time, where ρ is a variable on the terrain that depends on the ratio between depression volumes. We implemented our algorithms for computing terrain and point-flood queries as well as approximate flood-time queries. We tested the efficacy and efficiency of these algorithms on three real terrains of different types (urban, suburban, and mountainous.