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Special Issue "Sensors for Biomedical, Environmental and Food Monitoring Applications"

A special issue of Sensors (ISSN 1424-8220).

Deadline for manuscript submissions: closed (31 March 2017)

Special Issue Editor

Guest Editor
Prof. Dr. Monica Florescu

“Transilvania” University of Brasov, Faculty of Medicine, Brasov, Romania
Website | E-Mail
Interests: electrochemical and optical sensors/biosensors for medical, environmental and food applications

Special Issue Information

Dear Colleagues,

Detection methods include various techniques, such as electric (conductometric, dielectric impedance, etc.), electrochemical (amperometric, voltammetric, potentiometric, electrochemical impedance spectroscopy), optical (Surface Plasmon Resonance, Raman spectroscopy, etc.), or even piezoelectric or thermal detection. All these approaches have earned considerable interest in recent years, and they show great promise for a wide range of applications in biological research, medical diagnostics, environmental monitoring or food monitoring applications.

We invite, for this “Sensors for Biomedical, Environmental and Food Monitoring Applications” Special Issue, manuscripts dealing with different detection methods-based sensors for application fields mentioned above, while not being limited to those, which will be or not presented in the frame of the International Conference “IC-ANMBES 2016, Brasov, Romania” (http://sciforum.net/conference/icanmbes). Both original research and review articles are welcome. Original research papers that describe the development, characterization/evaluation, simulations and utilization of platforms for detection of biological active or toxic compounds in complex samples with potential applications in medical analysis and diagnosis, environmental or food monitoring are of interest. Reviews should provide an up-to-date and critical overview of state-of-the-art of platforms and detection mechanisms, especially those used for sensing. The manuscripts can deal with microfluidics and point-of-care microdevices, optical fibers, novel materials electrodes and surface functionalization strategies for the detection of specific (bio)molecules in complex samples or new concepts and fundamental studies with potential relevance to sensory detection. Please feel free to contact us and send us your suggestions that you would like to discuss beforehand. We look forward to and welcome your participation in this Special Issue.

Prof. Dr. Monica Florescu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Sensors
  • Microfluidics
  • Point-of-care microdevices
  • Novel materials
  • Surface functionalization

Published Papers (10 papers)

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Research

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Open AccessArticle Graphene-Ag Hybrids on Laser-Textured Si Surface for SERS Detection
Sensors 2017, 17(7), 1462; doi:10.3390/s17071462
Received: 7 May 2017 / Revised: 12 June 2017 / Accepted: 14 June 2017 / Published: 22 June 2017
Cited by 1 | PDF Full-text (10770 KB) | HTML Full-text | XML Full-text
Abstract
Surface-enhanced Raman scattering (SERS) has been extensively investigated as an effective approach for trace species detection. Silver nanostructures are high-sensitivity SERS substrates in common use, but their poor chemical stability impedes practical applications. Herein, a stable and sensitive SERS substrate based on the
[...] Read more.
Surface-enhanced Raman scattering (SERS) has been extensively investigated as an effective approach for trace species detection. Silver nanostructures are high-sensitivity SERS substrates in common use, but their poor chemical stability impedes practical applications. Herein, a stable and sensitive SERS substrate based on the hybrid structures of graphene/silver film/laser-textured Si (G/Ag/LTSi) was developed, and a simple, rapid, and low-cost fabrication approach was explored. Abundant nanoparticles were directly created and deposited on the Si surface via laser ablation. These aggregated nanoparticles functioned as hotspots after a 30 nm Ag film coating. A monolayer graphene was transferred to the Ag film surface to prevent the Ag from oxidation. The SERS behavior was investigated by detecting R6G and 4-MBT molecules. The experimental results indicate that the maximum enhancement factor achieved by the G/Ag/LTSi substrate is over 107 and less than 23% SERS signals lost when the substrate was exposed to ambient conditions for 50 days. The covering graphene layer played crucial roles in both the Raman signals enhancement and the Ag nanostructure protection. The stable and sensitive SERS performance of G/Ag/LTSi substrate evince that the present strategy is a useful and convenient route to fabricate large-area graphene-silver plasmonic hybrids for SERS applications. Full article
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Open AccessArticle Tyrosinase-Based Biosensors for Selective Dopamine Detection
Sensors 2017, 17(6), 1314; doi:10.3390/s17061314
Received: 3 May 2017 / Revised: 30 May 2017 / Accepted: 1 June 2017 / Published: 7 June 2017
PDF Full-text (3617 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
A novel tyrosinase-based biosensor was developed for the detection of dopamine (DA). For increased selectivity, gold electrodes were previously modified with cobalt (II)-porphyrin (CoP) film with electrocatalytic activity, to act both as an electrochemical mediator and an enzyme support, upon which the enzyme
[...] Read more.
A novel tyrosinase-based biosensor was developed for the detection of dopamine (DA). For increased selectivity, gold electrodes were previously modified with cobalt (II)-porphyrin (CoP) film with electrocatalytic activity, to act both as an electrochemical mediator and an enzyme support, upon which the enzyme tyrosinase (Tyr) was cross-linked. Differential pulse voltammetry was used for electrochemical detection and the reduction current of dopamine-quinone was measured as a function of dopamine concentration. Our experiments demonstrated that the presence of CoP improves the selectivity of the electrode towards dopamine in the presence of ascorbic acid (AA), with a linear trend of concentration dependence in the range of 2–30 µM. By optimizing the conditioning parameters, a separation of 130 mV between the peak potentials for ascorbic acid AA and DA was obtained, allowing the selective detection of DA. The biosensor had a sensitivity of 1.22 ± 0.02 µA·cm−2·µM−1 and a detection limit of 0.43 µM. Biosensor performances were tested in the presence of dopamine medication, with satisfactory results in terms of recovery (96%), and relative standard deviation values below 5%. These results confirmed the applicability of the biosensors in real samples such as human urine and blood serum. Full article
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Open AccessArticle Hybrid-Aware Model for Senior Wellness Service in Smart Home
Sensors 2017, 17(5), 1182; doi:10.3390/s17051182
Received: 31 March 2017 / Revised: 30 April 2017 / Accepted: 17 May 2017 / Published: 22 May 2017
PDF Full-text (2930 KB) | HTML Full-text | XML Full-text
Abstract
Smart home technology with situation-awareness is important for seniors to improve safety and security. With the development of context-aware computing, wearable sensor technology, and ubiquitous computing, it is easier for seniors to manage their health problem in smart home environment. For monitoring senior
[...] Read more.
Smart home technology with situation-awareness is important for seniors to improve safety and security. With the development of context-aware computing, wearable sensor technology, and ubiquitous computing, it is easier for seniors to manage their health problem in smart home environment. For monitoring senior activity in smart home, wearable, and motion sensors—such as respiration rate (RR), electrocardiography (ECG), body temperature, and blood pressure (BP)—were used for monitoring movements of seniors. For context-awareness, environmental sensors—such as gas, fire, smoke, dust, temperature, and light sensors—were used for senior location data collection. Based on senior activity, senior health status can be classified into positive and negative. Based on senior location and time, senior safety is classified into safe and emergency. In this paper, we propose a hybrid inspection service middleware for monitoring elderly health risk based on senior activity and location. This hybrid-aware model for the detection of abnormal status of seniors has four steps as follows: (1) data collection from biosensors and environmental sensors; (2) monitoring senior location and time of stay in each location using environmental sensors; (3) monitoring senior activity using biometric data; finally, (4) expectation-maximization based decision-making step recommending proper treatment based on a senior health risk ratio. Full article
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Open AccessArticle Detection of Soil Nitrogen Using Near Infrared Sensors Based on Soil Pretreatment and Algorithms
Sensors 2017, 17(5), 1102; doi:10.3390/s17051102
Received: 1 March 2017 / Revised: 1 May 2017 / Accepted: 4 May 2017 / Published: 11 May 2017
Cited by 1 | PDF Full-text (1418 KB) | HTML Full-text | XML Full-text
Abstract
Soil nitrogen content is one of the important growth nutrient parameters of crops. It is a prerequisite for scientific fertilization to accurately grasp soil nutrient information in precision agriculture. The information about nutrients such as nitrogen in the soil can be obtained quickly
[...] Read more.
Soil nitrogen content is one of the important growth nutrient parameters of crops. It is a prerequisite for scientific fertilization to accurately grasp soil nutrient information in precision agriculture. The information about nutrients such as nitrogen in the soil can be obtained quickly by using a near-infrared sensor. The data can be analyzed in the detection process, which is nondestructive and non-polluting. In order to investigate the effect of soil pretreatment on nitrogen content by near infrared sensor, 16 nitrogen concentrations were mixed with soil and the soil samples were divided into three groups with different pretreatment. The first group of soil samples with strict pretreatment were dried, ground, sieved and pressed. The second group of soil samples were dried and ground. The third group of soil samples were simply dried. Three linear different modeling methods are used to analyze the spectrum, including partial least squares (PLS), uninformative variable elimination (UVE), competitive adaptive reweighted algorithm (CARS). The model of nonlinear partial least squares which supports vector machine (LS-SVM) is also used to analyze the soil reflectance spectrum. The results show that the soil samples with strict pretreatment have the best accuracy in predicting nitrogen content by near-infrared sensor, and the pretreatment method is suitable for practical application. Full article
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Open AccessArticle Direct Electrochemical Detection of Bisphenol A Using a Highly Conductive Graphite Nanoparticle Film Electrode
Sensors 2017, 17(4), 836; doi:10.3390/s17040836
Received: 27 February 2017 / Revised: 22 March 2017 / Accepted: 5 April 2017 / Published: 11 April 2017
PDF Full-text (1937 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
We developed an accurate and sensitive sensor for electrochemical detection of bisphenol A (BPA) with a high-conductivity graphite nanoparticle (GN) film electrode. The GNs consisted of several stacked graphene sheets and showed a homogenous spherical shape, high conductivity, large surface area and good
[...] Read more.
We developed an accurate and sensitive sensor for electrochemical detection of bisphenol A (BPA) with a high-conductivity graphite nanoparticle (GN) film electrode. The GNs consisted of several stacked graphene sheets and showed a homogenous spherical shape, high conductivity, large surface area and good adsorption properties to BPA. The constructed GN film electrode exhibited improved amperometric current responses such as decreased impedance and lowered BPA oxidation potential compared with those of a pristine electrode, and also possessed a large surface area to allow fast electron transfer and BPA accumulation. A pre-accumulation process with BPA adsorption resulted in considerable current signal enhancement during BPA detection. The loading amount of GNs on the film electrode and the time for target BPA enrichment were optimized. The GN film electrode-based sensor showed high reproducibility and high selectivity for BPA over other reagents. Differential pulse voltammetry experiments revealed that the concentrations of BPA were linearly correlated with the current changes, and the lowest limit of detection of the sensor was 35 nM. Furthermore, the sensor showed great accuracy and reliability, as confirmed by high-performance liquid chromatography measurements. The sensor was also successfully used for BPA determination in groundwater samples, demonstrating its potential for real environmental analysis. Full article
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Open AccessArticle An Improved Label-Free Indirect Competitive SPR Immunosensor and Its Comparison with Conventional ELISA for Ractopamine Detection in Swine Urine
Sensors 2017, 17(3), 604; doi:10.3390/s17030604
Received: 13 January 2017 / Revised: 8 February 2017 / Accepted: 22 February 2017 / Published: 16 March 2017
PDF Full-text (1870 KB) | HTML Full-text | XML Full-text
Abstract
Ractopamine (RCT) is banned for use in animals in many countries, and it is urgent to develop efficient methods for specific and sensitive RCT detection. A label-free indirect competitive surface plasmon resonance (SPR) immunosensor was first developed with a primary antibody herein and
[...] Read more.
Ractopamine (RCT) is banned for use in animals in many countries, and it is urgent to develop efficient methods for specific and sensitive RCT detection. A label-free indirect competitive surface plasmon resonance (SPR) immunosensor was first developed with a primary antibody herein and then improved by a secondary antibody for the detection of RCT residue in swine urine. Meanwhile, a pre-incubation process of RCT and the primary antibody was performed to further improve the sensitivity. With all the key parameters optimized, the improved immunosenor can attain a linear range of 0.3–32 ng/mL and a limit of detection (LOD) of 0.09 ng/mL for RCT detection with high specificity. Furthermore, the improved label-free SPR immunosenor was compared thoroughly with a conventional enzyme-linked immunosorbent assay (ELISA). The SPR immunosensor showed advantages over the ELISA in terms of LOD, reagent consumption, analysis time, experiment automation, and so on. The SPR immunosensor can be used as potential method for real-time monitoring and screening of RCT residue in swine urine or other samples. In addition, the design using antibody pairs for biosensor development can be further referred to for other small molecule detection. Full article
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Open AccessArticle Bent Fiber Sensor for Preservative Detection in Milk
Sensors 2016, 16(12), 2094; doi:10.3390/s16122094
Received: 24 October 2016 / Revised: 29 November 2016 / Accepted: 6 December 2016 / Published: 9 December 2016
PDF Full-text (1992 KB) | HTML Full-text | XML Full-text
Abstract
A fiber optic sensor sensitive to refractive index changes of the outer region of the fiber cladding is presented. The sensor uses bent plastic optical fibers in different bending lengths to increase sensitivity. Measurements were made for low-fat milk, the refractive index of
[...] Read more.
A fiber optic sensor sensitive to refractive index changes of the outer region of the fiber cladding is presented. The sensor uses bent plastic optical fibers in different bending lengths to increase sensitivity. Measurements were made for low-fat milk, the refractive index of which is altered by some preservatives such as formaldehyde, hydrogen peroxide, and sodium carbonate. Concentrations of the preservatives in the milk were changed between 0% and 14.3% while the refractive indices occurred between 1.34550 and 1.35093 for the minimum (0%) and maximum (14.286%) concentrations of sodium carbonate, respectively. Due to bending-induced sensitivity, the sensor is able to detect refractive index changes less of than 0.4%. The results show that there is excellent linearity between the concentration and normalized response of the sensor. Full article
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Open AccessArticle Predicting Gilthead Sea Bream (Sparus aurata) Freshness by a Novel Combined Technique of 3D Imaging and SW-NIR Spectral Analysis
Sensors 2016, 16(10), 1735; doi:10.3390/s16101735
Received: 7 July 2016 / Revised: 29 September 2016 / Accepted: 13 October 2016 / Published: 19 October 2016
Cited by 1 | PDF Full-text (2676 KB) | HTML Full-text | XML Full-text
Abstract
A technique that combines the spatial resolution of a 3D structured-light (SL) imaging system with the spectral analysis of a hyperspectral short-wave near infrared system was developed for freshness predictions of gilthead sea bream on the first storage days (Days 0–6). This novel
[...] Read more.
A technique that combines the spatial resolution of a 3D structured-light (SL) imaging system with the spectral analysis of a hyperspectral short-wave near infrared system was developed for freshness predictions of gilthead sea bream on the first storage days (Days 0–6). This novel approach allows the hyperspectral analysis of very specific fish areas, which provides more information for freshness estimations. The SL system obtains a 3D reconstruction of fish, and an automatic method locates gilthead’s pupils and irises. Once these regions are positioned, the hyperspectral camera acquires spectral information and a multivariate statistical study is done. The best region is the pupil with an R2 of 0.92 and an RMSE of 0.651 for predictions. We conclude that the combination of 3D technology with the hyperspectral analysis offers plenty of potential and is a very promising technique to non destructively predict gilthead freshness. Full article
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Open AccessArticle Utility of Ochrobactrum anthropi YC152 in a Microbial Fuel Cell as an Early Warning Device for Hexavalent Chromium Determination
Sensors 2016, 16(8), 1272; doi:10.3390/s16081272
Received: 29 May 2016 / Revised: 15 July 2016 / Accepted: 8 August 2016 / Published: 16 August 2016
Cited by 2 | PDF Full-text (947 KB) | HTML Full-text | XML Full-text
Abstract
Fast hexavalent chromium (Cr(VI)) determination is important for environmental risk and health-related considerations. We used a microbial fuel cell-based biosensor inoculated with a facultatively anaerobic, Cr(VI)-reducing, and exoelectrogenic Ochrobactrum anthropi YC152 to determine the Cr(VI) concentration in water. The results indicated that O.
[...] Read more.
Fast hexavalent chromium (Cr(VI)) determination is important for environmental risk and health-related considerations. We used a microbial fuel cell-based biosensor inoculated with a facultatively anaerobic, Cr(VI)-reducing, and exoelectrogenic Ochrobactrum anthropi YC152 to determine the Cr(VI) concentration in water. The results indicated that O. anthropi YC152 exhibited high adaptability to pH, temperature, salinity, and water quality under anaerobic conditions. The stable performance of the microbial fuel cell (MFC)-based biosensor indicated its potential as a reliable biosensor system. The MFC voltage decreased as the Cr(VI) concentration in the MFC increased. Two satisfactory linear relationships were observed between the Cr(VI) concentration and voltage output for various Cr(VI) concentration ranges (0.0125–0.3 mg/L and 0.3–5 mg/L). The MFC biosensor is a simple device that can accurately measure Cr(VI) concentrations in drinking water, groundwater, and electroplating wastewater in 45 min with low deviations (<10%). The use of the biosensor can help in preventing the violation of effluent regulations and the maximum allowable concentration of Cr(VI) in water. Thus, the developed MFC biosensor has potential as an early warning detection device for Cr(VI) determination even if O. anthropi YC152 is a possible opportunistic pathogen. Full article
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Review

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Open AccessReview Smartphone-Based Food Diagnostic Technologies: A Review
Sensors 2017, 17(6), 1453; doi:10.3390/s17061453
Received: 31 March 2017 / Revised: 5 June 2017 / Accepted: 14 June 2017 / Published: 20 June 2017
PDF Full-text (4063 KB) | HTML Full-text | XML Full-text
Abstract
A new generation of mobile sensing approaches offers significant advantages over traditional platforms in terms of test speed, control, low cost, ease-of-operation, and data management, and requires minimal equipment and user involvement. The marriage of novel sensing technologies with cellphones enables the development
[...] Read more.
A new generation of mobile sensing approaches offers significant advantages over traditional platforms in terms of test speed, control, low cost, ease-of-operation, and data management, and requires minimal equipment and user involvement. The marriage of novel sensing technologies with cellphones enables the development of powerful lab-on-smartphone platforms for many important applications including medical diagnosis, environmental monitoring, and food safety analysis. This paper reviews the recent advancements and developments in the field of smartphone-based food diagnostic technologies, with an emphasis on custom modules to enhance smartphone sensing capabilities. These devices typically comprise multiple components such as detectors, sample processors, disposable chips, batteries and software, which are integrated with a commercial smartphone. One of the most important aspects of developing these systems is the integration of these components onto a compact and lightweight platform that requires minimal power. To date, researchers have demonstrated several promising approaches employing various sensing techniques and device configurations. We aim to provide a systematic classification according to the detection strategy, providing a critical discussion of strengths and weaknesses. We have also extended the analysis to the food scanning devices that are increasingly populating the Internet of Things (IoT) market, demonstrating how this field is indeed promising, as the research outputs are quickly capitalized on new start-up companies. Full article
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