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14 pages, 4271 KB

Open AccessArticle

Surface-Enhanced Raman Spectroscopic Analysis of Flavoenzyme Cofactors: Guidance for Flavin-Related Bio- and Chemo- Sensors

by Yawen Liu, Hao Ma, Junqi Zhao, Jihong Wang, Xiaoxia Han and Bing Zhao

Chemosensors 2023, 11(3), 190; https://doi.org/10.3390/chemosensors11030190 - 12 Mar 2023

Cited by 3 | Viewed by 3213

Abstract

Flavin mononucleotides (FMNs) and flavin adenine nucleotide (FAD) play vital roles in the electron-transfer processes in diverse enzymatic reactions. Owing to the isoalloxazine chromophore, flavins are easily detectable by surface-enhanced Raman spectroscopy (SERS), a surface-sensitive technique. However, the details of the adsorption of flavins on SERS-active materials have never been investigated. In this study, a comprehensive SERS analysis of flavins containing lumichrome and lumiflavin on silver nanoparticles was conducted. With the aid of density-functional-theory calculations, our results suggested that the flavin molecules were adsorbed on the silver nanoparticles via the N₃ site of the isoalloxazine moiety, which had a stronger adsorption ability than the adenine moiety in the FAD. The SERS spectra of the flavins at different pH values also supported this conclusion. This study demonstrated the feasibility of SERS for the structural characterization of flavins, paving the way for the functional exploration of flavin-labeled detection sensors and flavoprotein researches. Full article

(This article belongs to the Special Issue SERS: Analytical and Biological Challenges)

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23 pages, 4919 KB

Open AccessReview

Recent Progresses in NIR-II Luminescent Bio/Chemo Sensors Based on Lanthanide Nanocrystals

by Tingyu Yang, Jinglei Qin, Jinling Zhang, Lanying Guo, Mu Yang, Xi Wu, Mei You and Hongshang Peng

Chemosensors 2022, 10(6), 206; https://doi.org/10.3390/chemosensors10060206 - 30 May 2022

Cited by 9 | Viewed by 3885

Abstract

Fluorescent bio/chemosensors are widely used in the field of biological research and medical diagnosis, with the advantages of non-invasiveness, high sensitivity, and good selectivity. In particular, luminescent bio/chemosensors, based on lanthanide nanocrystals (LnNCs) with a second near-infrared (NIR-II) emission, have attracted much attention, owing to greater penetration depth, aside from the merits of narrow emission band, abundant emission lines, and long lifetimes. In this review, NIR-II LnNCs-based bio/chemo sensors are summarized from the perspectives of the mechanisms of NIR-II luminescence, synthesis method of LnNCs, strategy of luminescence enhancement, sensing mechanism, and targeted bio/chemo category. Finally, the problems that exist in present LnNCs-based bio/chemosensors are discussed, and the future development trend is prospected. Full article

(This article belongs to the Special Issue Chemical and Biosensors: A Theme Issue in Honor of Professor Otto S. Wolfbeis)

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16 pages, 5670 KB

Open AccessArticle

An FPGA-Based Machine Learning Tool for In-Situ Food Quality Tracking Using Sensor Fusion

by Daniel Enériz, Nicolas Medrano and Belen Calvo

Biosensors 2021, 11(10), 366; https://doi.org/10.3390/bios11100366 - 30 Sep 2021

Cited by 19 | Viewed by 4810

Abstract

The continuous development of more accurate and selective bio- and chemo-sensors has led to a growing use of sensor arrays in different fields, such as health monitoring, cell culture analysis, bio-signals processing, or food quality tracking. The analysis and information extraction from the amount of data provided by these sensor arrays is possible based on Machine Learning techniques applied to sensor fusion. However, most of these computing solutions are implemented on costly and bulky computers, limiting its use in in-situ scenarios outside complex laboratory facilities. This work presents the application of machine learning techniques in food quality assessment using a single Field Programmable Gate Array (FPGA) chip. The characteristics of low-cost, low power consumption as well as low-size allow the application of the proposed solution even in space constrained places, as in food manufacturing chains. As an example, the proposed system is tested on an e-nose developed for beef classification and microbial population prediction. Full article

(This article belongs to the Special Issue Feature Issue of Biosensors and Bioelectronic Devices Section)

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13 pages, 2429 KB

Open AccessArticle

Thermochemically Stable Liquid-Crystalline Gold(I) Complexes Showing Enhanced Room Temperature Phosphorescence

by Yuki Kuroda, Shin-ya Nakamura, Katam Srinivas, Arruri Sathyanarayana, Ganesan Prabusankar, Kyohei Hisano and Osamu Tsutsumi

Crystals 2019, 9(5), 227; https://doi.org/10.3390/cryst9050227 - 27 Apr 2019

Cited by 17 | Viewed by 5361

Abstract

Gold(I) complexes are some of the most attractive materials for generating aggregation-induced emission (AIE), enabling the realization of novel light-emitting applications such as chemo-sensors, bio-sensors, cell imaging, and organic light-emitting diodes (OLEDs). In this study, we propose a rational design of luminescent gold complexes to achieve both high thermochemical stability and intense room temperature phosphorescence, which are desirable features in practical luminescent applications. Here, a series of gold(I) complexes with ligands of N-heterocyclic carbene (NHC) derivatives and/or acetylide were synthesized. Detailed characterization revealed that the incorporation of NHC ligands could increase the molecular thermochemical stability, as the decomposition temperature was increased to ~300 °C. We demonstrate that incorporation of both NHC and acetylide ligands enables us to generate gold(I) complexes exhibiting both high thermochemical stability and high room-temperature phosphorescence quantum yield (>40%) under ambient conditions. Furthermore, we modified the length of alkoxy chains at ligands, and succeeded in synthesizing a liquid crystalline gold(I) complex while maintaining the relatively high thermochemical stability and quantum yield. Full article

(This article belongs to the Special Issue Synthesis and Properties of Light-emitting Liquid Crystals)

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16 pages, 4747 KB

Open AccessArticle

Remote Microwave and Field-Effect Sensing Techniques for Monitoring Hydrogel Sensor Response

by Olutosin Charles Fawole, Subhashish Dolai, Hsuan-Yu Leu, Jules Magda and Massood Tabib-Azar

Micromachines 2018, 9(10), 526; https://doi.org/10.3390/mi9100526 - 17 Oct 2018

Cited by 6 | Viewed by 4131

Abstract

This paper presents two novel techniques for monitoring the response of smart hydrogels composed of synthetic organic materials that can be engineered to respond (swell or shrink, change conductivity and optical properties) to specific chemicals, biomolecules or external stimuli. The first technique uses microwaves both in contact and remote monitoring of the hydrogel as it responds to chemicals. This method is of great interest because it can be used to non-invasively monitor the response of subcutaneously implanted hydrogels to blood chemicals such as oxygen and glucose. The second technique uses a metal-oxide-hydrogel field-effect transistor (MOHFET) and its associated current-voltage characteristics to monitor the hydrogel’s response to different chemicals. MOHFET can be easily integrated with on-board telemetry electronics for applications in implantable biosensors or it can be used as a transistor in an oscillator circuit where the oscillation frequency of the circuit depends on the analyte concentration. Full article

(This article belongs to the Special Issue MEMS Technology for Biomedical Imaging Applications)

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31 pages, 5893 KB

Open AccessReview

Luminescent Metal Nanoclusters for Potential Chemosensor Applications

by Muthaiah Shellaiah and Kien Wen Sun

Chemosensors 2017, 5(4), 36; https://doi.org/10.3390/chemosensors5040036 - 19 Dec 2017

Cited by 48 | Viewed by 11972

Abstract

Studies of metal nanocluster (M-NCs)-based sensors for specific analyte detection have achieved significant progress in recent decades. Ultra-small-size (<2 nm) M-NCs consist of several to a few hundred metal atoms and exhibit extraordinary physical and chemical properties. Similar to organic molecules, M-NCs display absorption and emission properties via electronic transitions between energy levels upon interaction with light. As such, researchers tend to apply M-NCs in diverse fields, such as in chemosensors, biological imaging, catalysis, and environmental and electronic devices. Chemo- and bio-sensory uses have been extensively explored with luminescent NCs of Au, Ag, Cu, and Pt as potential sensory materials. Luminescent bi-metallic NCs, such as Au-Ag, Au-Cu, Au-Pd, and Au-Pt have also been used as probes in chemosensory investigations. Both metallic and bi-metallic NCs have been utilized to detect various analytes, such as metal ions, anions, biomolecules, proteins, acidity or alkalinity of a solution (pH), and nucleic acids, at diverse detection ranges and limits. In this review, we have summarized the chemosensory applications of luminescent M-NCs and bi-metallic NCs. Full article

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28 pages, 6662 KB

Open AccessArticle

A Neural Network Approach to Smarter Sensor Networks for Water Quality Monitoring

by Edel O’Connor, Alan F. Smeaton, Noel E. O’Connor and Fiona Regan

Sensors 2012, 12(4), 4605-4632; https://doi.org/10.3390/s120404605 - 10 Apr 2012

Cited by 28 | Viewed by 9607

Abstract

Environmental monitoring is evolving towards large-scale and low-cost sensor networks operating reliability and autonomously over extended periods of time. Sophisticated analytical instrumentation such as chemo-bio sensors present inherent limitations because of the number of samples that they can take. In order to maximize their deployment lifetime, we propose the coordination of multiple heterogeneous information sources. We use rainfall radar images and information from a water depth sensor as input to a neural network (NN) to dictate the sampling frequency of a phosphate analyzer at the River Lee in Cork, Ireland. This approach shows varied performance for different times of the year but overall produces output that is very satisfactory for the application context in question. Our study demonstrates that even with limited training data, a system for controlling the sampling rate of the nutrient sensor can be set up and can improve the efficiency of the more sophisticated nodes of the sensor network. Full article

(This article belongs to the Section Sensor Networks)

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