Three-dimensional hydrogel structures as optical sensor arrays, for the detection of specific DNA sequences

2012 ◽  
Vol 421 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Francine Kivlehan ◽  
Marta Paolucci ◽  
Des Brennan ◽  
Ioannis Ragoussis ◽  
Paul Galvin
Keyword(s):  
Dna Sequences ◽  
Optical Sensor ◽  
Three Dimensional ◽  
Sensor Arrays

Three-Dimensional Structure of Cloned T3 Connector Protein at 1.6nm Resolution

1990 ◽  
Vol 48 (1) ◽  
pp. 282-283
Author(s):  
José L. Carrascosa ◽  
José M. Valpuesta ◽  
Hisao Fujisawa
Keyword(s):  
Dna Sequences ◽  
Expression Vector ◽  
Three Dimensional ◽  
Deae Cellulose ◽  
Dna Packaging ◽  
Dimensional Structure ◽  
Two Dimensional ◽  
Freezing And Thawing ◽  
Three Dimensional Structure ◽  
Dimensional Reconstruction

The head to tail connector of bacteriophages plays a fundamental role in the assembly of viral heads and DNA packaging. In spite of the absence of sequence homology, the structure of connectors from different viruses (T4, Ø29, T3, P22, etc) share common morphological features, that are most clearly revealed in their three-dimensional structure. We have studied the three-dimensional reconstruction of the connector protein from phage T3 (gp 8) from tilted view of two dimensional crystals obtained from this protein after cloning and purification.DNA sequences including gene 8 from phage T3 were cloned, into Bam Hl-Eco Rl sites down stream of lambda promotor PL, in the expression vector pNT45 under the control of cI857. E R204 (pNT89) cells were incubated at 42°C for 2h, harvested and resuspended in 20 mM Tris HC1 (pH 7.4), 7mM 2 mercaptoethanol, ImM EDTA. The cells were lysed by freezing and thawing in the presence of lysozyme (lmg/ml) and ligthly sonicated. The low speed supernatant was precipitated by ammonium sulfate (60% saturated) and dissolved in the original buffer to be subjected to gel nitration through Sepharose 6B, followed by phosphocellulose colum (Pll) and DEAE cellulose colum (DE52). Purified gp8 appeared at 0.3M NaCl and formed crystals when its concentration increased above 1.5 mg/ml.

scholarly journals Macromolecular Optical Sensor Arrays

2021 ◽  
Vol 3 (2) ◽  
pp. 506-530 ◽  
Author(s):  
Linda Mitchell ◽  
Elizabeth J. New ◽  
Clare S. Mahon
Keyword(s):  
Optical Sensor ◽  
Sensor Arrays

scholarly journals Three-Dimensional Arterial Pulse Signal Acquisition in Time Domain Using Flexible Pressure-Sensor Dense Arrays

Micromachines ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 569
Author(s):  
Jianzhong Chen ◽  
Ke Sun ◽  
Rong Zheng ◽  
Yi Sun ◽  
Heng Yang ◽  
...  
Keyword(s):  
Radial Artery ◽  
Pressure Sensor ◽  
Pulse Width ◽  
Printed Circuit Boards ◽  
Color Doppler ◽  
Three Dimensional ◽  
Pressure Sensors ◽  
Sensor Arrays ◽  
Signal Acquisition ◽  
Dynamic Pulse

In this study, we developed a radial artery pulse acquisition system based on finger-worn dense pressure sensor arrays to enable three-dimensional pulse signals acquisition. The finger-worn dense pressure-sensor arrays were fabricated by packaging 18 ultra-small MEMS pressure sensors (0.4 mm × 0.4 mm × 0.2 mm each) with a pitch of 0.65 mm on flexible printed circuit boards. Pulse signals are measured and recorded simultaneously when traditional Chinese medicine practitioners wear the arrays on the fingers while palpating the radial pulse. Given that the pitches are much smaller than the diameter of the human radial artery, three-dimensional pulse envelope images can be measured with the system, as can the width and the dynamic width of the pulse signals. Furthermore, the array has an effective span of 11.6 mm—3–5 times the diameter of the radial artery—which enables easy and accurate positioning of the sensor array on the radial artery. This study also outlines proposed methods for measuring the pulse width and dynamic pulse width. The dynamic pulse widths of three volunteers were measured, and the dynamic pulse width measurements were consistent with those obtained by color Doppler ultrasound. The pulse wave velocity can also be measured with the system by measuring the pulse transit time between the pulse signals at the brachial and radial arteries using the finger-worn sensor arrays.

Optical Sensor Arrays for Medical Diagnostics

2002 ◽  
Author(s):  
Keith Albert ◽  
Caroline Schauer ◽  
David Walt
Keyword(s):  
Optical Sensor ◽  
Sensor Arrays ◽  
Medical Diagnostics

scholarly journals Development of a Pattern Recognition Tool for the Classification of Electronic Tongue Signals Using Machine Learning

2021 ◽  
Vol 5 (1) ◽  
pp. 21
Author(s):  
Edgar G. Mendez-Lopez ◽  
Jersson X. Leon-Medina ◽  
Diego A. Tibaduiza
Keyword(s):  
Machine Learning ◽  
Dimensionality Reduction ◽  
Performance Measures ◽  
Sensor Array ◽  
Three Dimensional ◽  
Electronic Tongue ◽  
Sensor Arrays ◽  
Classification Performance ◽  
Supervised Machine Learning ◽  
Electrochemical Tests

Electronic tongue type sensor arrays are made of different materials with the property of capturing signals independently by each sensor. The signals captured when conducting electrochemical tests often have high dimensionality, which increases when performing the data unfolding process. This unfolding process consists of arranging the data coming from different experiments, sensors, and sample times, thus the obtained information is arranged in a two-dimensional matrix. In this work, a description of a tool for the analysis of electronic tongue signals is developed. This tool is developed in Matlab® App Designer, to process and classify the data from different substances analyzed by an electronic tongue type sensor array. The data processing is carried out through the execution of the following stages: (1) data unfolding, (2) normalization, (3) dimensionality reduction, (4) classification through a supervised machine learning model, and finally (5) a cross-validation procedure to calculate a set of classification performance measures. Some important characteristics of this tool are the possibility to tune the parameters of the dimensionality reduction and classifier algorithms, and also plot the two and three-dimensional scatter plot of the features after reduced the dimensionality. This to see the data separability between classes and compatibility in each class. This interface is successfully tested with two electronic tongue sensor array datasets with multi-frequency large amplitude pulse voltammetry (MLAPV) signals. The developed graphical user interface allows comparing different methods in each of the mentioned stages to find the best combination of methods and thus obtain the highest values of classification performance measures.

High-Speed, High Dynamic-Range Optical Sensor Arrays

2009 ◽  
Vol 56 (3) ◽  
pp. 1069-1075 ◽  
Author(s):  
Stuart Kleinfelder ◽  
Shiuh-Hua Wood Chiang ◽  
Wei Huang ◽  
Ashish Shah ◽  
Kris Kwiatkowski
Keyword(s):  
Optical Sensor ◽  
High Speed ◽  
Dynamic Range ◽  
Sensor Arrays ◽  
High Dynamic Range ◽  
High Dynamic

Randomly Ordered Addressable High-Density Optical Sensor Arrays

1998 ◽  
Vol 70 (7) ◽  
pp. 1242-1248 ◽  
Author(s):  
Karri L. Michael ◽  
Laura C. Taylor ◽  
Sandra L. Schultz ◽  
David R. Walt
Keyword(s):  
Optical Sensor ◽  
Sensor Arrays ◽  
High Density
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