Aptamer-based surface plasmon sensor for thrombin detection

A series of surface plasmonic fibre devices were fabricated using multiple coatings deposited on a lapped section of a single mode fibre and post-fabrication UV laser irradiation processing with a phase mask, producing a surface relief grating structure. These devices showed high spectral sensitivity in the aqueous index regime ranging up to 4000 nm/RIU for wavelength and 800 dB/RIU for intensity. The devices were then coated with human thrombin binding aptamer. Several concentrations of thrombin in buffer solution were made, ranging from 1nM to 1µM. All the concentrations were detectable by the devices demonstrating that sub-nM concentrations may be monitored.

Reporter ion-based mass spectrometry approaches for the detection of non-enzymatic protein modifications in biological samples

Development of mass spectrometry techniques to detect protein oxidation, which contributes to signalling and inflammation, is important. Label-free approaches have the advantage of reduced sample manipulation, but are challenging in complex samples owing to undirected analysis of large data sets using statistical search engines. To identify oxidised proteins in biological samples, we previously developed a targeted approach involving precursor ion scanning for diagnostic MS3 ions from oxidised residues. Here, we tested this approach for other oxidations, and compared it with an alternative approach involving the use of extracted ion chromatograms (XICs) generated from high-resolution MSMS data using very narrow mass windows. This accurate mass XIC data methodology was effective at identifying nitrotyrosine, chlorotyrosine, and oxidative deamination of lysine, and for tyrosine oxidations highlighted more modified peptide species than precursor ion scanning or statistical database searches. Although some false positive peaks still occurred in the XICs, these could be identified by comparative assessment of the peak intensities. The method has the advantage that a number of different modifications can be analysed simultaneously in a single LC-MSMS run. This article is part of a Special Issue entitled: Posttranslational Protein modifications in biology and Medicine. Biological significance: The use of accurate mass extracted product ion chromatograms to detect oxidised peptides could improve the identification of oxidatively damaged proteins in inflammatory conditions. © 2013 Elsevier B.V.

A near real-time water surface detection method based on HSV transformation of MODIS multi-Spectral time series data

In the face of global population growth and the uneven distribution of water supply, a better knowledge of the spatial and temporal distribution of surface water resources is critical. Remote sensing provides a synoptic view of ongoing processes, which addresses the intricate nature of water surfaces and allows an assessment of the pressures placed on aquatic ecosystems. However, the main challenge in identifying water surfaces from remotely sensed data is the high variability of spectral signatures, both in space and time. In the last 10 years only a few operational methods have been proposed to map or monitor surface water at continental or global scale, and each of them show limitations. The objective of this study is to develop and demonstrate the adequacy of a generic multi-temporal and multi-spectral image analysis method to detect water surfaces automatically, and to monitor them in near-real-time. The proposed approach, based on a transformation of the RGB color space into HSV, provides dynamic information at the continental scale. The validation of the algorithm showed very few omission errors and no commission errors. It demonstrates the ability of the proposed algorithm to perform as effectively as human interpretation of the images. The validation of the permanent water surface product with an independent dataset derived from high resolution imagery, showed an accuracy of 91.5% and few commission errors. Potential applications of the proposed method have been identified and discussed. The methodology that has been developed 27 is generic: it can be applied to sensors with similar bands with good reliability, and minimal effort. Moreover, this experiment at continental scale showed that the methodology is efficient for a large range of environmental conditions. Additional preliminary tests over other continents indicate that the proposed methodology could also be applied at the global scale without too many difficulties

Spatially-multiplexed fibre-optic Bragg grating strain and temperature sensor system based on interferometric wavelength-shift detection

A prototype fibre-optic system using interferometric wavelength-shift detection, capable of multiplexing up to 32 fibre-optic Bragg grating strain and temperature sensors with identical characteristics, has been demonstrated. This system is based on a spatially multiplexed scheme for use with fibre-based low-coherence interferometric sensors, reported previously. Four fibre-optic Bragg grating channels using the same fibre grating have been demonstrated for measuring quasi-static strain and temperature.

Long-period fibre grating based biosensor for detection of DNA hybridisation

We implement an optical biosensor using long-period fibre grating immobilised with probe DNA. It has been used to detect hybridisation of target DNA, showing a high sensitivity and reusability function.

Self-Learning Fuzzy Spiking Neural Network as a Nonlinear Pulse-Position Threshold Detection Dynamic System Based on Second-Order Critically Damped Response Units

Architecture and learning algorithm of self-learning spiking neural network in fuzzy clustering task are outlined. Fuzzy receptive neurons for pulse-position transformation of input data are considered. It is proposed to treat a spiking neural network in terms of classical automatic control theory apparatus based on the Laplace transform. It is shown that synapse functioning can be easily modeled by a second order damped response unit. Spiking neuron soma is presented as a threshold detection unit. Thus, the proposed fuzzy spiking neural network is an analog-digital nonlinear pulse-position dynamic system. It is demonstrated how fuzzy probabilistic and possibilistic clustering approaches can be implemented on the base of the presented spiking neural network.

Real-time detection of DNA interactions with long-period fiber-grating-based biosensor

Using an optical biosensor based on a dual-peak long-period fiber grating, we have demonstrated the detection of interactions between biomolecules in real time. Silanization of the grating surface was successfully realized for the covalent immobilization of probe DNA, which was subsequently hybridized with the complementary target DNA sequence. It is interesting to note that the DNA biosensor was reusable after being stripped off the hybridized target DNA from the grating surface, demonstrating a function of multiple usability. © 2007 Optical Society of America.

Dehydroacetic acid based dioxaborine styryl dye:effective fluorescent probe for ammonia and amine detection

The newly synthesized dioxaborine dyes, derivatives of dehydroacetic acid, were tested for the detection of amines and ammonia. To discriminate the substance with efficient sensing parameters, series of ca. 20 dioxaborine dyes were synthesized and tested for reactivity with amines. The most promising one showed the fluorescent sensitivity to amines in the range of 1-4 ppm. © (2014) Trans Tech Publications.

Early Detection of Emergent Events Based on an Extremal Process Approach

2000 Mathematics Subject Classification: Primary 60G70, 62F03.

A sensing mechanism for the detection of carbon nanotubes using selective photoluminescent probes based on ionic complexes with organic dyes

The multifunctional properties of carbon nanotubes (CNTs) make them a powerful platform for unprecedented innovations in a variety of practical applications. As a result of the surging growth of nanotechnology, nanotubes present a potential problem as an environmental pollutant, and as such, an efficient method for their rapid detection must be established. Here, we propose a novel type of ionic sensor complex for detecting CNTs – an organic dye that responds sensitively and selectively to CNTs with a photoluminescent signal. The complexes are formed through Coulomb attractions between dye molecules with uncompensated charges and CNTs covered with an ionic surfactant in water. We demonstrate that the photoluminescent excitation of the dye can be transferred to the nanotubes, resulting in selective and strong amplification (up to a factor of 6) of the light emission from the excitonic levels of CNTs in the near-infrared spectral range, as experimentally observed via excitation-emission photoluminescence (PL) mapping. The chirality of the nanotubes and the type of ionic surfactant used to disperse the nanotubes both strongly affect the amplification; thus, the complexation provides sensing selectivity towards specific CNTs. Additionally, neither similar uncharged dyes nor CNTs covered with neutral surfactant form such complexes. As model organic molecules, we use a family of polymethine dyes with an easily tailorable molecular structure and, consequently, tunable absorbance and PL characteristics. This provides us with a versatile tool for the controllable photonic and electronic engineering of an efficient probe for CNT detection.

A rule-based approach to implicit emotion detection in text

Most research in the area of emotion detection in written text focused on detecting explicit expressions of emotions in text. In this paper, we present a rule-based pipeline approach for detecting implicit emotions in written text without emotion-bearing words based on the OCC Model. We have evaluated our approach on three different datasets with five emotion categories. Our results show that the proposed approach outperforms the lexicon matching method consistently across all the three datasets by a large margin of 17–30% in F-measure and gives competitive performance compared to a supervised classifier. In particular, when dealing with formal text which follows grammatical rules strictly, our approach gives an average F-measure of 82.7% on “Happy”, “Angry-Disgust” and “Sad”, even outperforming the supervised baseline by nearly 17% in F-measure. Our preliminary results show the feasibility of the approach for the task of implicit emotion detection in written text.

Graphene-based D-shaped polymer FBG for highly sensitive erythrocyte detection

Graphene-based silica fiber-optic sensors, with high sensitivity, fast response, and low cost, have shown great promise for gas sensing applications. In this letter, by covering a monolayer of p-doped graphene on a D-shaped microstructured polymer fiber Bragg grating (FBG), we propose and demonstrate a novel biochemical probe sensor, the graphene-based D-shaped polymer FBG (GDPFBG). Due to the graphene-based surface evanescent field enhancement, this sensor shows high sensitivity to detect surrounding biochemical parameters. By monitoring the Bragg peak locations of the GDPFBG online, human erythrocyte (red blood cell) solutions with different cellular concentrations ranging from 0 to 104 ppm were detected precisely, with the maximum resolution of sub-ppm. Such a sensor is structurally compact, is clinically acceptable, and provides good recoverability, offering a state-of-the-art polymer-fiber-based sensing platform for highly sensitive in situ and in vivo cell detection applications.

Biosensor based on excessively tilted fiber grating in thin-cladding optical fiber for sensitive and selective detection of low glucose concentration

We report a highly sensitive, high Q-factor, label free and selective glucose sensor by using excessively tilted fiber grating (Ex-TFG) inscribed in the thin-cladding optical fiber (TCOF). Glucose oxidase (GOD) was covalently immobilized on optical fiber surface and the effectiveness of GOD immobilization was investigated by the fluorescence microscopy and highly accurate spectral interrogation method. In contrast to the long period grating (LPG) and optical fiber (OF) surface Plasmon resonance (SPR) based glucose sensors, the Ex-TFG configuration has merits of nearly independent cross sensitivity of the environmental temperature, simple fabrication method (no noble metal deposition or cladding etching) and high detection accuracy (or Q-factor). Our experimental results have shown that Ex-TFG in TCOF based sensor has a reliable and fast detection for the glucose concentration as low as 0.1~2.5mg/ml and a high sensitivity of ~1.514nm·(mg/ml)−1, which the detection accuracy is ~0.2857nm−1 at pH 5.2, and the limit of detection (LOD) is 0.013~0.02mg/ml at the pH range of 5.2~7.4 by using an optical spectrum analyzer with a resolution of 0.02nm.