Adaptive recognition of small molecules by nucleic acid aptamers through a label-free approach

We report a novel label-free method for the investigation of the adaptive recognition of small molecules by nucleic acid aptamers using capillary electrophoresis analysis. Cocaine and argininamide were chosen as model molecules, and the two corresponding DNA aptamers were used. These single-strand DNAs folded into their specific secondary structures, which were mainly responsible for the binding of the target molecules with high affinity and specificity. For molecular recognition, the nucleic acid structures then underwent additional conformational changes, while keeping the target molecules stabilized by intermolecular hydrogen bonds. The intrinsic chemical and physical properties of the target molecules enabled them to act as indicators for adaptive binding. Thus any labeling or modification of the aptamers or target molecules were made obsolete. This label-free method for aptamer-based molecular recognition was also successfully applied to biological fluids and therefore indicates that this approach is a promising tool for bioanalysis.

CE with electrochemical detection for investigation of label-free recognition of amino acid amides by guanine-rich DNA aptamers

In this work, we report a simple and effective investigation into adaptive interactions between guanine-rich DNA aptamers and amino acid amides by CE with electrochemical (EC) detection. Argininamide (Arm) and tyrosinamide (Tym) were chosen as model molecules. On a copper electrode, Arm generated a good EC signal in 60 mM NaOH at 0.7 V (vs Ag/ AgCl), while Tym. was detected well on a platinum electrode at 1. 3 V in 20 mM phosphate of pH 7.0. Based on their EC properties, the ligands themselves were used as indicators for the adaptive interactions investigated by CE-EC, making any step of labeling and/or modification of aptamers with indicators exempted. Hydrophilic ionic liquid was used as an additive in running buffer of CE to improve the sensitivity of Arm detection, whereas the additive was not used for Tym. detection due to its negative effect. Two guanine-rich DNA aptamers were used for molecular recognition of Arm and Tym. When the aptamers were incubated with ligands, they bound the model molecules with high affinity and specificity, reflected by obvious decreases in the signals of ligands but no changes in those of the control molecules. However, the ligands were hardly affected by the control ssDNAs after incubation. The results revealed the specific recognition of Arm and Tym. by the aptamers.

Structural diversity of lanthanide-amino acid complexes under near physiological pH conditions and their recognition of single-stranded DNA

We reported here four structures of lanthanide-amino acid complexes obtained under near physiological pH conditions and their individual formula can be described as [Tb-2(DL-Cys)(4)(H2O)(8)]Cl-2 (1), [Eu-4(mu(3)-OH)(4)(L-Asp)(2)(L-HAsp)(3)(H2O)(7)] Cl center dot 11.5H(2)O (2), [Eu-8-(L-HVal) (16)(H2O)(32)]Cl-24 center dot 12.5H(2)O (3), and [Tb-2(DL-HVal)(4)(H2O)(8)]Cl-6 center dot 2H(2)O (4). These complexes showed diverse structures and have shown potential application in DNA detection. We studied the interactions of the complexes with five single-stranded DNA and found different fluorescence enhancement, binding affinity and binding stoichiometry when the complexes are bound to DNA.

Electrochemical recognition of alkali metal ions at the micro-water 1,2-dichloroethane interface using a calix[4]arene derivative

In this paper, a calix[4]arene derivative, 5,11,17,23-butyl-25,26,27,28-tetra-(ethanoxycarbonyl)-methoxy-calix[4]arene (L), is investigated as a host to recognize alkali metal ions (Li+, Na+, K+, Rb+ and Cs+) at the interface between two immiscible electrolyte solutions (ITIES). Well-defined cyclic voltammograms are obtained at the micro- and nano-water \ 1,2-dichloroethane (W \ DCE) interfaces supported at micro- and nano-pipets.

Automatic Recognition of Tractability in Inference Relations

A procedure is given for recognizing sets of inference rules that generate polynomial time decidable inference relations. The procedure can automatically recognize the tractability of the inference rules underlying congruence closure. The recognition of tractability for that particular rule set constitutes mechanical verification of a theorem originally proved independently by Kozen and Shostak. The procedure is algorithmic, rather than heuristic, and the class of automatically recognizable tractable rule sets can be precisely characterized. A series of examples of rule sets whose tractability is non-trivial, yet machine recognizable, is also given. The technical framework developed here is viewed as a first step toward a general theory of tractable inference relations.

Recognition of Surface Reflectance Properties from a Single Image under Unknown Real-World Illumination

This paper describes a machine vision system that classifies reflectance properties of surfaces such as metal, plastic, or paper, under unknown real-world illumination. We demonstrate performance of our algorithm for surfaces of arbitrary geometry. Reflectance estimation under arbitrary omnidirectional illumination proves highly underconstrained. Our reflectance estimation algorithm succeeds by learning relationships between surface reflectance and certain statistics computed from an observed image, which depend on statistical regularities in the spatial structure of real-world illumination. Although the algorithm assumes known geometry, its statistical nature makes it robust to inaccurate geometry estimates.

Mid-Level Vision and Recognition of Non-Rigid Objects

We address mid-level vision for the recognition of non-rigid objects. We align model and image using frame curves - which are object or "figure/ground" skeletons. Frame curves are computed, without discontinuities, using Curved Inertia Frames, a provably global scheme implemented on the Connection Machine, based on: non-cartisean networks; a definition of curved axis of inertia; and a ridge detector. I present evidence against frame alignment in human perception. This suggests: frame curves have a role in figure/ground segregation and in fuzzy boundaries; their outside/near/top/ incoming regions are more salient; and that perception begins by setting a reference frame (prior to early vision), and proceeds by processing convex structures.

Three-Dimensional Recognition of Solid Objects from a Two-Dimensional Image

This thesis addresses the problem of recognizing solid objects in the three-dimensional world, using two-dimensional shape information extracted from a single image. Objects can be partly occluded and can occur in cluttered scenes. A model based approach is taken, where stored models are matched to an image. The matching problem is separated into two stages, which employ different representations of objects. The first stage uses the smallest possible number of local features to find transformations from a model to an image. This minimizes the amount of search required in recognition. The second stage uses the entire edge contour of an object to verify each transformation. This reduces the chance of finding false matches.

Recognition of Topological Invariants by Iterative Arrays

A study is made of the recognition and transformation of figures by iterative arrays of finite state automata. A figure is a finite rectangular two-dimensional array of symbols. The iterative arrays considered are also finite, rectangular, and two-dimensional. The automata comprising any given array are called cells and are assumed to be isomorphic and to operate synchronously with the state of a cell at time t+1 being a function of the states of it and its four nearest neighbors at time t. At time t=0 each cell is placed in one of a fixed number of initial states. The pattern of initial states thus introduced represents the figure to be processed. The resulting sequence of array states represents a computation based on the input figure. If one waits for a specially designated cell to indicate acceptance or rejection of the figure, the array is said to be working on a recognition problem. If one waits for the array to come to a stable configuration representing an output figure, the array is said to be working on a transformation problem.

Computer Recognition of Prismatic Solids

An investigation is made into the problem of constructing a model of the appearance to an optical input device of scenes consisting of plane-faced geometric solids. The goal is to study algorithms which find the real straight edges in the scenes, taking into account smooth variations in intensity over faces of the solids, blurring of edges and noise. A general mathematical analysis is made of optimal methods for identifying the edge lines in figures, given a raster of intensities covering the entire field of view. There is given in addition a suboptimal statistical decision procedure, based on the model, for the identification of a line within a narrow band on the field of view given an array of intensities from within the band. A computer program has been written and extensively tested which implements this procedure and extracts lines from real scenes. Other programs were written which judge the completeness of extracted sets of lines, and propose and test for additional lines which had escaped initial detection. The performance of these programs is discussed in relation to the theory derived from the model, and with regard to their use of global information in detecting and proposing lines.

Computer Recognition of Three-Dimensional Objects in a Visual Scene

Methods are presented (1) to partition or decompose a visual scene into the bodies forming it; (2) to position these bodies in three-dimensional space, by combining two scenes that make a stereoscopic pair; (3) to find the regions or zones of a visual scene that belong to its background; (4) to carry out the isolation of objects in (1) when the input has inaccuracies. Running computer programs implement the methods, and many examples illustrate their behavior. The input is a two-dimensional line-drawing of the scene, assumed to contain three-dimensional bodies possessing flat faces (polyhedra); some of them may be partially occluded. Suggestions are made for extending the work to curved objects. Some comparisons are made with human visual perception. The main conclusion is that it is possible to separate a picture or scene into the constituent objects exclusively on the basis of monocular geometric properties (on the basis of pure form); in fact, successful methods are shown.

Influence of depression in a sample of people with hallux valgus

Hallux valgus (HV) is a highly-prevalent forefoot deformity associated with progressive subluxation and osteoarthritis of the first metatarsophalangeal joint; it is believed to be associated with depression. The aim of the present study was to determine the association of patients with varying degrees of HV involvement to depression using the Beck Depression Inventory (BDI). The sample consisted of 102 participants (mean age: 45.1±1.6), who attended an outpatient centre where self-report data were recorded. The degree of HV deformity was determined in both feet, and the scores on the BDI were compared. A total of 38.24% of the sample had depression, with an average BDI score of 10.55±12.36 points. There was a statistically-significant association between the degree and presence of HV in both feet (P=0.0001). People with a greater degree of HV deformity in any foot also have a significant increase in depression based on BDI scores, regardless of sex.