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Biosensors
Volume 5
Issue 3
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Biosensors, Volume 5, Issue 3 (September 2015) – 12 articles , Pages 367-615

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1150 KiB  
Article
Smart Textile Based on Fiber Bragg Grating Sensors for Respiratory Monitoring: Design and Preliminary Trials
by Marco Ciocchetti, Carlo Massaroni, Paola Saccomandi, Michele A. Caponero, Andrea Polimadei, Domenico Formica and Emiliano Schena
Biosensors 2015, 5(3), 602-615; https://doi.org/10.3390/bios5030602 - 14 Sep 2015
Cited by 124 | Viewed by 10092
Abstract
Continuous respiratory monitoring is important to assess adequate ventilation. We present a fiber optic-based smart textile for respiratory monitoring able to work during Magnetic Resonance (MR) examinations. The system is based on the conversion of chest wall movements into strain of two fiber [...] Read more.
Continuous respiratory monitoring is important to assess adequate ventilation. We present a fiber optic-based smart textile for respiratory monitoring able to work during Magnetic Resonance (MR) examinations. The system is based on the conversion of chest wall movements into strain of two fiber Bragg grating (FBG) sensors, placed on the upper thorax (UT). FBGs are glued on the textile by an adhesive silicon rubber. To increase the system sensitivity, the FBGs positioning was led by preliminary experiments performed using an optoelectronic system: FBGs placed on the chest surface experienced the largest strain during breathing. System performances, in terms of respiratory period (TR), duration of inspiratory (TI) and expiratory (TE) phases, as well as left and right UT volumes, were assessed on four healthy volunteers. The comparison of results obtained by the proposed system and an optoelectronic plethysmography highlights the high accuracy in the estimation of TR, TI, and TE: Bland-Altman analysis shows mean of difference values lower than 0.045 s, 0.33 s, and 0.35 s for TR, TI, and TE, respectively. The mean difference of UT volumes between the two systems is about 8.3%. The promising results foster further development of the system to allow routine use during MR examinations.Continuous respiratory monitoring is important to assess adequate ventilation. We present a fiber optic-based smart textile for respiratory monitoring able to work during Magnetic Resonance (MR) examinations. The system is based on the conversion of chest wall movements into strain of two fiber Bragg grating (FBG) sensors, placed on the upper thorax (UT). FBGs are glued on the textile by an adhesive silicon rubber. To increase the system sensitivity, the FBGs positioning was led by preliminary experiments performed using an optoelectronic system: FBGs placed on the chest surface experienced the largest strain during breathing. System performances, in terms of respiratory period (TR), duration of inspiratory (TI) and expiratory (TE) phases, as well as left and right UT volumes, were assessed on four healthy volunteers. The comparison of results obtained by the proposed system and an optoelectronic plethysmography highlights the high accuracy in the estimation of TR, TI, and TE: Bland-Altman analysis shows mean of difference values lower than 0.045 s, 0.33 s, and 0.35 s for TR, TI, and TE, respectively. The mean difference of UT volumes between the two systems is about 8.3%. The promising results foster further development of the system to allow routine use during MR examinations. Full article
(This article belongs to the Special Issue Optical Sensors for Biomedical Applications)
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Figure 1

Figure 1
<p>(<b>a</b>) FBGs position and distance between the two FBGs. Blue lines and markers identify the upper thorax right compartment, red lines and markers identify the upper thorax left compartment, green lines and markers identify the line which separates the two compartments; (<b>b</b>) trend of FBG distance during quiet breathing of a healthy subject.</p> Full article ">Figure 2
<p>Picture of the experimental set-up.</p> Full article ">Figure 3
<p>(<b>a</b>) Trend of the data provided by the OEP; (<b>b</b>) Trend of the data provided by the two FBGs; (<b>c</b>) three different parameters investigated: Respiratory periods, calculated as the time interval between two consecutive peaks, inspiratory periods, calculated as the time interval that elapses between a maximum and the previous minimum of the signal, and expiratory periods, calculated as the time interval that elapses between a minimum and the previous maximum.</p> Full article ">Figure 4
<p>(<b>a</b>,<b>b</b>) Bland Altman plot comparing the respiratory period measured by OEP and by the smart textiles with the automatic method and the manual one, respectively; (<b>c</b>,<b>d</b>) Bland Altman plot comparing the inspiratory period measured by OEP and by the smart textiles with the automatic method and the manual one, respectively; (<b>e</b>,<b>f</b>) Bland Altman plot comparing the expiratory period measured by OEP and by the smart textiles with the automatic method and the manual one, respectively.</p> Full article ">Figure 5
<p>Correlation between the FBGs wavelength changes and UT volume considering both left and right side. The best fitting lines are also shown.</p> Full article ">Figure 6
<p>Comparison between the FBGs wavelength changes and UT volume considering both left and right side. The best fitting lines are also shown.</p> Full article ">
912 KiB  
Review
Point-of-Care Diagnostics in Low Resource Settings: Present Status and Future Role of Microfluidics
by Shikha Sharma, Julia Zapatero-Rodríguez, Pedro Estrela and Richard O'Kennedy
Biosensors 2015, 5(3), 577-601; https://doi.org/10.3390/bios5030577 - 13 Aug 2015
Cited by 272 | Viewed by 29768
Abstract
The inability to diagnose numerous diseases rapidly is a significant cause of the disparity of deaths resulting from both communicable and non-communicable diseases in the developing world in comparison to the developed world. Existing diagnostic instrumentation usually requires sophisticated infrastructure, stable electrical power, [...] Read more.
The inability to diagnose numerous diseases rapidly is a significant cause of the disparity of deaths resulting from both communicable and non-communicable diseases in the developing world in comparison to the developed world. Existing diagnostic instrumentation usually requires sophisticated infrastructure, stable electrical power, expensive reagents, long assay times, and highly trained personnel which is not often available in limited resource settings. This review will critically survey and analyse the current lateral flow-based point-of-care (POC) technologies, which have made a major impact on diagnostic testing in developing countries over the last 50 years. The future of POC technologies including the applications of microfluidics, which allows miniaturisation and integration of complex functions that facilitate their usage in limited resource settings, is discussed The advantages offered by such systems, including low cost, ruggedness and the capacity to generate accurate and reliable results rapidly, are well suited to the clinical and social settings of the developing world. Full article
(This article belongs to the Special Issue Low-Cost Biosensors for Developing Countries)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Schematic representation of the principle of sandwich format of a lateral flow immunoassay. (<b>A</b>) Labelled lateral flow test strip; (<b>B</b>) Migration of sample from sample pad to conjugate pad; if the desired antigen is present in the sample the conjugate will bind to it creating a complex (antigen-antibody-label); (<b>C</b>) The complex flows through the membrane towards the test line; (<b>D</b>) Immobilised Ab captures the complex and free labelled Ab and forms test and control lines, respectively; (<b>E</b>) Qualitative results-visual detection; (<b>F</b>) Quantitative detection, e.g., optical detection (depending on label used).</p> Full article ">Figure 2
<p>(<b>A</b>) Outline of manufacturing process for lateral flow tests; (<b>B</b>) Top view of a lateral flow immunoassay test cartridge.</p> Full article ">Figure 3
<p>Examples of microfluidic-based platforms. (<b>A</b>) Paper-based microfluidic device for simultaneous quantification of glucose and other analyte in urine. Taken from <a href="http://gmwgroup.harvard.edu" target="_blank">http://gmwgroup.harvard.edu</a> with permission from Prof. Whitesides; (<b>B</b>) Lab-on-a-chip platform developed by Alere for blood chemistry analysis. Reproduced with permission from Alere; (<b>C</b>) Lab-on-a-disc diagnostic device designed by Abaxis. Reproduced with permission from Abaxis.</p> Full article ">Figure 4
<p>ABORhCard summarised assay procedure. Buffer is manually added by the user to re-hydrate the antibodies and this process is confirmed by the visualisation of colours in the A, B, and D “verification windows”. Then, using the lancet provided, a fingerstick blood sample is collected and added into the “blood” well. Once the colour appears in the “verification window”, the blood and reagents mix and flow into the “results window” using the on-board Pump (P) and Vent (V). At the end of the procedure, agglutination occurs and results can be visualised. Images taken from <a href="http://www.micronics.net" target="_blank">www.micronics.net</a> with permission from Micronics.</p> Full article ">
479 KiB  
Article
The Detection of Helicobacter hepaticus Using Whispering-Gallery Mode Microcavity Optical Sensors
by Mark E. Anderson, Emily C. O'Brien, Emily N. Grayek, James K. Hermansen and Heather K. Hunt
Biosensors 2015, 5(3), 562-576; https://doi.org/10.3390/bios5030562 - 7 Aug 2015
Cited by 24 | Viewed by 7860
Abstract
Current bacterial detection techniques are relatively slow, require bulky instrumentation, and usually require some form of specialized training. The gold standard for bacterial detection is culture testing, which can take several days to receive a viable result. Therefore, simpler detection techniques that are [...] Read more.
Current bacterial detection techniques are relatively slow, require bulky instrumentation, and usually require some form of specialized training. The gold standard for bacterial detection is culture testing, which can take several days to receive a viable result. Therefore, simpler detection techniques that are both fast and sensitive could greatly improve bacterial detection and identification. Here, we present a new method for the detection of the bacteria Helicobacter hepaticus using whispering-gallery mode (WGM) optical microcavity-based sensors. Due to minimal reflection losses and low material adsorption, WGM-based sensors have ultra-high quality factors, resulting in high-sensitivity sensor devices. In this study, we have shown that bacteria can be non-specifically detected using WGM optical microcavity-based sensors. The minimum detection for the device was 1 × 104 cells/mL, and the minimum time of detection was found to be 750 s. Given that a cell density as low as 1 × 103 cells/mL for Helicobacter hepaticus can cause infection, the limit of detection shown here would be useful for most levels where Helicobacter hepaticus is biologically relevant. This study suggests a new approach for H. hepaticus detection using label-free optical sensors that is faster than, and potentially as sensitive as, standard techniques. Full article
(This article belongs to the Special Issue Optical Sensors for Biomedical Applications)
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<p>A model for WGM optical microcavity detection, based on [<a href="#B41-biosensors-05-00562" class="html-bibr">41</a>] (adapted with permission). In the top image, light (thick black line around the device) enters a WGM optical microcavity, where it experiences total internal reflection (TIR) and generates an evanescent field. The evanescent field is an optical field extending to the surrounding environment and decreasing exponentially with the distance away from the resonator’s interface. When an analyte (red sphere), such as bacteria, binds or adsorbs onto the surface of the microsphere, it changes the effective refractive index of the circulating optical field resonator, and it pulls part of the evanescent field to the outside of the resonator. The expansion of the optical field’s boundary causes the round-trip wavelength of light to increase about 2πΔl. The increase in the optical field’s wavelength results in a corresponding frequency shift in the transmission spectrum (bottom image).</p> Full article ">Figure 2
<p>Microscopic images of the tip of a single mode optical fiber before and after gravimetric melting with a CO<sub>2</sub> laser.</p> Full article ">Figure 3
<p>A model of the open-flow flow cell.</p> Full article ">Figure 4
<p>A representative resonance peak of the silica microspheres used as the WGM optical microcavities in the sensing experiments, showing a high quality factor device (black line—data, red line—Lorentzian fit) during testing in air.</p> Full article ">Figure 5
<p>An overlay of the wavelength shift over time for a single representative silica microsphere (sphere 4, referenced in <a href="#biosensors-05-00562-t001" class="html-table">Table 1</a> and <a href="#biosensors-05-00562-t002" class="html-table">Table 2</a>) used in the sensing experiments.</p> Full article ">
916 KiB  
Review
Current and Prospective Methods for Plant Disease Detection
by Yi Fang and Ramaraja P. Ramasamy
Biosensors 2015, 5(3), 537-561; https://doi.org/10.3390/bios5030537 - 6 Aug 2015
Cited by 508 | Viewed by 42423
Abstract
Food losses due to crop infections from pathogens such as bacteria, viruses and fungi are persistent issues in agriculture for centuries across the globe. In order to minimize the disease induced damage in crops during growth, harvest and postharvest processing, as well as [...] Read more.
Food losses due to crop infections from pathogens such as bacteria, viruses and fungi are persistent issues in agriculture for centuries across the globe. In order to minimize the disease induced damage in crops during growth, harvest and postharvest processing, as well as to maximize productivity and ensure agricultural sustainability, advanced disease detection and prevention in crops are imperative. This paper reviews the direct and indirect disease identification methods currently used in agriculture. Laboratory-based techniques such as polymerase chain reaction (PCR), immunofluorescence (IF), fluorescence in-situ hybridization (FISH), enzyme-linked immunosorbent assay (ELISA), flow cytometry (FCM) and gas chromatography-mass spectrometry (GC-MS) are some of the direct detection methods. Indirect methods include thermography, fluorescence imaging and hyperspectral techniques. Finally, the review also provides a comprehensive overview of biosensors based on highly selective bio-recognition elements such as enzyme, antibody, DNA/RNA and bacteriophage as a new tool for the early identification of crop diseases. Full article
(This article belongs to the Special Issue Biosensors in Agroecosystems)
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<p>Cyclic voltammetry of (a) AuNP-Screen printed carbon electrode (SPCE), (b) planar gold and (c) SPCE in presence of 1.7 mM methyl salicylate. (a') AuNP-SPCE, (b') planar gold and (c') SPCE in the absence of methyl salicylate. The responses of current to methyl salicylate and sensitivity are shown in the inset. Figure is adopted from Ref. [<a href="#B77-biosensors-05-00537" class="html-bibr">77</a>] with permission.</p> Full article ">Figure 2
<p>Cyclic voltammetry responses of (a and a') SnO<sub>2</sub>-Screen printed (SP) and (b and b') TiO<sub>2</sub>-SP (a and b) with and (a' and b') without the presence of 0.17 mM <span class="html-italic">p</span>-ethylguaiacol. Figure is adopted from Ref. [<a href="#B57-biosensors-05-00537" class="html-bibr">57</a>] with permission.</p> Full article ">Figure 3
<p>Schematic illustration of (<b>A</b>) antibody-based and (<b>B</b>) DNA/RNA-based biosensor for analyte detection. The specific combination of analyte and immobilized antibody (A) or DNA/RNA probe (B) produces a physicochemical change, such as mass, temperature, optical property or electrical potential. The change can be translated into a measurable signal for detection.</p> Full article ">Figure 4
<p>The fluorescence intensity of the four molecular beacons (CymMV RdRp, CymMV CP, ORSV RdRp and ORSV CP) with 0.01, 0.5, 1, 2, and 5 ng of purified viral RNA. The fluorescence intensity of all molecular beacons increased significantly and the limit of detection of purified viral RNA was estimated to be 0.5 ng. Figure has been adopted from Ref. [<a href="#B99-biosensors-05-00537" class="html-bibr">99</a>].</p> Full article ">Figure 5
<p>Sensitivity and specificity of (<b>A</b>) CymMV coat protein (CP) and (<b>B</b>) ORSV-CP QCM DNA biosensors upon incubation with increasing concentrations of viral RNA at different temperatures. Figure has been adopted from Ref. [<a href="#B100-biosensors-05-00537" class="html-bibr">100</a>].</p> Full article ">Figure 6
<p>Schematic illustration of enzymatic biosensor based on (<b>A</b>) mediated electron transfer and (<b>B</b>) direct electron transfer (DET).</p> Full article ">Figure 7
<p>Schematic illustration of (<b>A</b>) <span class="html-italic">P. cannabina</span> pv. <span class="html-italic">alisalensis</span> detection and (<b>B</b>) bioluminescent plagues with examination under light (left) and dark field (right) illumination. The bioluminescence at the plague periphery (phage/cell interface) indicates phage-infected pathogens. Figure has been adopted from Ref. [<a href="#B114-biosensors-05-00537" class="html-bibr">114</a>].</p> Full article ">
1052 KiB  
Article
Design and Characterization of a Sensorized Microfluidic Cell-Culture System with Electro-Thermal Micro-Pumps and Sensors for Cell Adhesion, Oxygen, and pH on a Glass Chip
by Sebastian M. Bonk, Marco Stubbe, Sebastian M. Buehler, Carsten Tautorat, Werner Baumann, Ernst-Dieter Klinkenberg and Jan Gimsa
Biosensors 2015, 5(3), 513-536; https://doi.org/10.3390/bios5030513 - 30 Jul 2015
Cited by 31 | Viewed by 9489
Abstract
We combined a multi-sensor glass-chip with a microfluidic channel grid for the characterization of cellular behavior. The grid was imprinted in poly-dimethyl-siloxane. Mouse-embryonal/fetal calvaria fibroblasts (MC3T3-E1) were used as a model system. Thin-film platinum (Pt) sensors for respiration (amperometric oxygen electrode), acidification (potentiometric [...] Read more.
We combined a multi-sensor glass-chip with a microfluidic channel grid for the characterization of cellular behavior. The grid was imprinted in poly-dimethyl-siloxane. Mouse-embryonal/fetal calvaria fibroblasts (MC3T3-E1) were used as a model system. Thin-film platinum (Pt) sensors for respiration (amperometric oxygen electrode), acidification (potentiometric pH electrodes) and cell adhesion (interdigitated-electrodes structures, IDES) allowed us to monitor cell-physiological parameters as well as the cell-spreading behavior. Two on-chip electro-thermal micro-pumps (ETμPs) permitted the induction of medium flow in the system, e.g., for medium mixing and drug delivery. The glass-wafer technology ensured the microscopic observability of the on-chip cell culture. Connecting Pt structures were passivated by a 1.2 μm layer of silicon nitride (Si3N4). Thin Si3N4 layers (20 nm or 60 nm) were used as the sensitive material of the pH electrodes. These electrodes showed a linear behavior in the pH range from 4 to 9, with a sensitivity of up to 39 mV per pH step. The oxygen sensors were circular Pt electrodes with a sensor area of 78.5 μm2. Their sensitivity was 100 pA per 1% oxygen increase in the range from 0% to 21% oxygen (air saturated). Two different IDES geometries with 30- and 50-μm finger spacings showed comparable sensitivities in detecting the proliferation rate of MC3T3 cells. These cells were cultured for 11 days in vitro to test the biocompatibility, microfluidics and electric sensors of our system under standard laboratory conditions. Full article
(This article belongs to the Special Issue Cell and Organ on Chip: Challenges and Advances)
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Figure 1
<p>Image of the sensorized cell-culture system. For better visibility, the microfluidic channels were filled with trypan-blue solution; (<b>A</b>) Top view. Two screws (silver in color) were used to fix the glass chip with the Pt sensor and ETµP structures in between the PMMA cover and ground plates and to seal the PDMS channels. For the photo, two of the four 1/4 inch 28 microfluidic connectors (top right, bottom left) were sealed with PDMS plugs. The other two connectors (blue) were disconnected for the photo. Flexible circuit-board connector (bottom, brown) was soldered to the chip pads. (<b>B</b>) Bottom view through the assembled system.</p> Full article ">Figure 2
<p>3D-COMSOL<sup>®</sup> simulations of the velocity distribution in the center plane of the microfluidic structure with sealed-off medium inlets and outlets (lower left and upper right circular structures). The velocity field was calculated assuming a volume force of 31.1 N·m<sup>−3</sup> induced in the ETµP volume, which was confined by the pump-field electrodes (see <a href="#biosensors-05-00513-f001" class="html-fig">Figure 1</a>B and <a href="#biosensors-05-00513-f003" class="html-fig">Figure 3</a>). Arrow: site of tracer-particle measurements in the flow-return path. Insert: Velocity profile in the center plane of the ETµP, 125 µm above the chip.</p> Full article ">Figure 3
<p>Scheme of the fluidic channels (blue) and location of the Pt-sensor structures (green) on the glass chip: (<b>A</b>) ETµP (1), eight common connectors for IDES with 30-µm (2; four connectors from left) and 50-µm (3; four connectors from right) finger widths, one oxygen (4) and two pH sensors with different sensor areas (5); (<b>B</b>) to-scale comparison of IDES (2, 3), directly heated ETµPs (1) and oxygen-electrode structures (4, top left: zoom of structure). The pumping force of the ETµP (1) is generated in the volume confined by the field electrode (lower horizontal stripe) and the common ground for the field electrode and the heating element (lower connector of the meander). Active surfaces of the oxygen sensor are marked in white (working electrode) and black (counter-electrode); finger widths and spacings were equal in each of the two IDES types. The outer boxes (30-µm structures: 1.4 × 0.5 mm<sup>2</sup>; 50-µm structures: 1.4 × 0.54 mm<sup>2</sup>) frame the passivation-free areas.</p> Full article ">Figure 4
<p>Pumping velocities induced in the flow-return path of the sensorized cell-culture system. Each data point represents the means of 10 tracer particles near the center of the path.</p> Full article ">Figure 5
<p>Microscopic images series of cells growing on 30-µm (<b>Top</b>) and 50-µm (<b>Bottom</b>) IDES in the center of the chip. The images were taken on days 1, 3, 5, 7, and 9 (compare to <a href="#biosensors-05-00513-f006" class="html-fig">Figure 6</a>).</p> Full article ">Figure 6
<p>(<b>A1</b>,<b>A2</b>): Typical examples for the frequency dependencies of the capacitance differences (−∆C) between the IDES capacitance during cell proliferation and the cell-free reference of five chips with four 30-µm IDES (<b>A1</b>) and four 50-µm IDES (<b>A</b>2) over 11 days of cell growth. (<b>B1</b>,<b>B2</b>): For each chip, the C<sub>PK</sub> values (<span class="html-italic">i.e.</span>, the –ΔC-peak values, see text) of the spectra were averaged for the four 30-µm (<b>B1</b>) and four 50-µm (<b>B2</b>) IDES. For comparison, curves for the highest (dashed line, circles) and lowest (dashed line, squares) averaged C<sub>PK</sub> values are shown, reflecting the limits of the cell-proliferation rates observed. From Verhulst-Pearl fits, the parameters in columns A of <a href="#biosensors-05-00513-t001" class="html-table">Table 1</a> were obtained when the data from all the chips were pooled for a certain IDES pitch (dotted lines). Parameters obtained from averaging the separately fitted parameters of each chip are given in columns B of <a href="#biosensors-05-00513-t001" class="html-table">Table 1</a> (solid lines). The experimental points for day 2 were not considered in the fits (see text).</p> Full article ">Figure 7
<p>Mean of 10 cyclic voltammograms of a 25-µm oxygen electrode in two-electrode configuration between −900 and 400 mV (step potential 10 mV, scan rate 10 mV/s) for air-saturated (solid lines) and oxygen-free media (dashed lines). Voltammetric scan directions are marked by arrows. Insert: zoom around −650 mV. Double arrows mark the current ranges swept during calibration of the electrode (−2.346 ± 0.038 nA (oxygen saturated); −0.073 ± 0.007 nA (oxygen depleted)) and during cell culture at −650 mV (<a href="#biosensors-05-00513-f008" class="html-fig">Figure 8</a>). Please note that the steep current increase for the oxygen-free medium above 100 mV is induced by the presence of 1% sodium sulphite.</p> Full article ">Figure 8
<p>Exemplary oxygen-sensor currents (left ordinate) measured in the microfluidic cell-culture system without cells (dotted lines, triangles) and in the presence of cells (solid lines, squares). The five-hourly current peaks correspond to the pumping cycles of medium exchange during cell culture. The abscissa data without cells was normalized to correspond to the measurements with cells. Measuring points in between the pump cycles were fitted by lines. The continuously increasing slopes in cell culture describe current rates which correspond to increasing oxygen-consumption rates of cells (right ordinate, open squares). The minimum and maximum of all lines with cells are plotted in the insert of <a href="#biosensors-05-00513-f007" class="html-fig">Figure 7</a>, marked by “cells”.</p> Full article ">Figure 9
<p>Cyclic potential measurements with a 20-nm (squares) and a 60 nm pH sensor (circles) between pH 6 and pH 8. The potentials were detected after 5 min before solution exchange and plotted over the reference pH. Sensitivities of −24.8 ± 0.8 mV (20 nm) and −25.6 ± 0.9 mV (60 nm) per pH step were obtained from linear fits.</p> Full article ">Figure 10
<p>Exemplary measurements with a 60-nm pH sensor in a cell-free chip (reference) and under cell culture conditions. As a reference, three measuring cycles were conducted with cell culture medium of pH 7.8 (dashed line). Medium exchange events can be recognized by glitches every five hours. Using a two-point calibration, a drifting pH scale (shown at 6.2 h) can be obtained from the drifting reference potential at pH 7.8 (see text). With cells a steady acidification was observed after each medium exchange (dotted line). Fits of single exponentials (Equation (3)) led to time constants decreasing for increasing cell numbers (squares, referring to right ordinate).</p> Full article ">
631 KiB  
Article
SPR Biosensor Probing the Interactions between TIMP-3 and Heparin/GAGs
by Fuming Zhang, Kyung Bok Lee and Robert J. Linhardt
Biosensors 2015, 5(3), 500-512; https://doi.org/10.3390/bios5030500 - 23 Jul 2015
Cited by 21 | Viewed by 7436
Abstract
Tissue inhibitor of metalloproteinases-3 (TIMP-3) belongs to a family of proteins that regulate the activity of matrix metalloproteinases (MMPs), which can process various bioactive molecules such as cell surface receptors, chemokines, and cytokines. Glycosaminoglycans (GAGs) interact with a number of proteins, thereby playing [...] Read more.
Tissue inhibitor of metalloproteinases-3 (TIMP-3) belongs to a family of proteins that regulate the activity of matrix metalloproteinases (MMPs), which can process various bioactive molecules such as cell surface receptors, chemokines, and cytokines. Glycosaminoglycans (GAGs) interact with a number of proteins, thereby playing an essential role in the regulation of many physiological/patho-physiological processes. Both GAGs and TIMP/MMPs play a major role in many cell biological processes, including cell proliferation, migration, differentiation, angiogenesis, apoptosis, and host defense. In this report, a heparin biosensor was used to map the interaction between TIMP-3 and heparin and other GAGs by surface plasmon resonance spectroscopy. These studies show that TIMP-3 is a heparin-binding protein with an affinity of ~59 nM. Competition surface plasmon resonance analysis indicates that the interaction between TIMP-3 and heparin is chain-length dependent, and N-sulfo and 6-O-sulfo groups (rather than the 2-O-sulfo groups) in heparin are important in the interaction of heparin with TIMP-3. Other GAGs (including chondroitin sulfate (CS) type E (CS-E)and CS type B (CS-B)demonstrated strong binding to TIMP-3, while heparan sulfate (HS), CS type A (CSA), CS type C (CSC), and CS type D (CSD) displayed only weak binding affinity. Full article
(This article belongs to the Special Issue Affinity Sensors)
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Figure 1

Figure 1
<p>Chemical structures of heparin, heparin-derived oligosaccharides, chemically modified heparins, and other GAGs.</p> Full article ">Figure 2
<p>Diagram of SPR solution competition study. The blue spheres represent TIMP-3 protein, the short red helices represent heparin or other GAGs. TIMP-3 protein (pre-mixed with 1000 nM heparin oligosaccharides or GAG) was injected over a chip containing immobilized heparin; only free protein can bind to the heparin on the chip.</p> Full article ">Figure 3
<p>SPR sensorgrams of the TIMP-3-heparin interaction. Concentrations of TIMP-3 (from top to bottom): 20, 10, 5, 2.5, and 1.25 nM, respectively. The black curves are the fitting curves using the 1:1 Langmuir binding model from BIAevaluate 4.0.1.</p> Full article ">Figure 4
<p>(<b>Top</b>): Sensorgrams of solution heparin oligosaccharides/surface heparin competition. TIMP-3 concentration was 10 nM, and concentrations of heparin oligosaccharides in solution were 1000 nM. (<b>Bottom</b>): Bar graphs (based on triplicate experiments with standard deviation) of normalized TIMP-3 binding preference to surface heparin by competing with different sizes of heparin oligosaccharides in solution.</p> Full article ">Figure 5
<p>(<b>Top</b>): Sensorgrams of solution GAGs/surface heparin competition. TIMP-3 concentration was 10 nM, and concentrations of GAGs in solution were 100 nM. (<b>Bottom</b>): Bar graphs (based on triplicate experiments with standard deviation) of normalized TIMP-3 binding preferences to surface heparin by competing with different GAGs.</p> Full article ">Figure 6
<p>(<b>Top</b>): Sensorgrams of solution competition SPR using chemically modified heparin. TIMP-3 concentration was 10 nM, and concentrations of chemically modified heparin in solution were 1000 nM. (<b>Bottom</b>): Bar graphs (based on triplicate experiments with standard deviation) of normalized TIMP-3 binding preferences to surface heparin by competing with different chemically modified heparin in solution.</p> Full article ">
885 KiB  
Review
Optical Microfibre Based Photonic Components and Their Applications in Label-Free Biosensing
by Pengfei Wang, Lin Bo, Yuliya Semenova, Gerald Farrell and Gilberto Brambilla
Biosensors 2015, 5(3), 471-499; https://doi.org/10.3390/bios5030471 - 22 Jul 2015
Cited by 34 | Viewed by 8478
Abstract
Optical microfibre photonic components offer a variety of enabling properties, including large evanescent fields, flexibility, configurability, high confinement, robustness and compactness. These unique features have been exploited in a range of applications such as telecommunication, sensing, optical manipulation and high Q resonators. Optical [...] Read more.
Optical microfibre photonic components offer a variety of enabling properties, including large evanescent fields, flexibility, configurability, high confinement, robustness and compactness. These unique features have been exploited in a range of applications such as telecommunication, sensing, optical manipulation and high Q resonators. Optical microfibre biosensors, as a class of fibre optic biosensors which rely on small geometries to expose the evanescent field to interact with samples, have been widely investigated. Due to their unique properties, such as fast response, functionalization, strong confinement, configurability, flexibility, compact size, low cost, robustness, ease of miniaturization, large evanescent field and label-free operation, optical microfibres based biosensors seem a promising alternative to traditional immunological methods for biomolecule measurements. Unlabeled DNA and protein targets can be detected by monitoring the changes of various optical transduction mechanisms, such as refractive index, absorption and surface plasmon resonance, since a target molecule is capable of binding to an immobilized optical microfibre. In this review, we critically summarize accomplishments of past optical microfibre label-free biosensors, identify areas for future research and provide a detailed account of the studies conducted to date for biomolecules detection using optical microfibres. Full article
(This article belongs to the Special Issue Optical Sensors for Biomedical Applications)
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<p>Illustration of typical structures of optical microfibre sensors: (<b>a</b>) straight microfibre biosensor; (<b>b</b>) microfibre tip biosensor; (<b>c</b>) evanescently coupled microfibre sensor; (<b>d</b>) heterogeneous resonant sensor.</p> Full article ">Figure 2
<p>Electric field distribution for a 1 μm diameter silica microfibre when the refractive index of the surrounding medium is (<b>a</b>) <span class="html-italic">RI</span> = 1; and (<b>b</b>) <span class="html-italic">RI</span> = 1.33. The black circle indicates the diameter of the microfibre.</p> Full article ">Figure 3
<p>Change of the fraction of the guided power in the microfibres with different microfibre diameters. The dashed line and the solid line correspond to microfibres with air cladding and water cladding, respectively.</p> Full article ">Figure 4
<p>Schematic diagram of the microfibre fabrication setup based on the microheater brushing technique.</p> Full article ">Figure 5
<p>Schematic diagram of a microheater in brushing motion to illustrate the effective heating zone <span class="html-italic">L <sub>ehz</sub></span>, microheater brushing length <span class="html-italic">L<sub>brush</sub></span>, and the total effective heating length <span class="html-italic">L</span>. Temperature distribution along the heating slot of the microheater is also shown.</p> Full article ">Figure 6
<p>Schematic of an optical microfibre tip sensor, light injected at the fibre pigtail pumps the functionalised coating, which emits fluorescent light that is collected when it is in proximity of the target compound.</p> Full article ">Figure 7
<p>Schematic diagram of an OMC consisting of two fused microfibres with a uniform waist region and two transition regions. Light launched into one input port can be coupled and split between two output ports due to the superposition between the even and odd modes.</p> Full article ">Figure 8
<p>(<b>a</b>) Immobilization and (<b>b</b>) anti-fibrinogen binding with the immobilized fibrinogen.</p> Full article ">Figure 9
<p>Schematic of a heterogeneous resonant sensor: an optical microfibre couples light into the resonant whispering gallery mode of a microsphere (dashed line), which is affected by the surrounding fluid.</p> Full article ">
363 KiB  
Review
Water Quality Monitoring in Developing Countries; Can Microbial Fuel Cells be the Answer?
by Jon Chouler and Mirella Di Lorenzo
Biosensors 2015, 5(3), 450-470; https://doi.org/10.3390/bios5030450 - 16 Jul 2015
Cited by 124 | Viewed by 22790
Abstract
The provision of safe water and adequate sanitation in developing countries is a must. A range of chemical and biological methods are currently used to ensure the safety of water for consumption. These methods however suffer from high costs, complexity of use and [...] Read more.
The provision of safe water and adequate sanitation in developing countries is a must. A range of chemical and biological methods are currently used to ensure the safety of water for consumption. These methods however suffer from high costs, complexity of use and inability to function onsite and in real time. The microbial fuel cell (MFC) technology has great potential for the rapid and simple testing of the quality of water sources. MFCs have the advantages of high simplicity and possibility for onsite and real time monitoring. Depending on the choice of manufacturing materials, this technology can also be highly cost effective. This review covers the state-of-the-art research on MFC sensors for water quality monitoring, and explores enabling factors for their use in developing countries. Full article
(This article belongs to the Special Issue Low-Cost Biosensors for Developing Countries)
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<p>Operating principles of a two-chamber microbial fuel cell (not to scale). The electroactive biofilm at the anode break down an organic substrate to produce electrons, protons and CO<sub>2</sub>. The electrons pass through an external load to be reduced at the cathode.</p> Full article ">Figure 2
<p>A schematic of three electron transfer mechanisms of microbes at the anode surface: (<b>a</b>) direct transfer by contact; (<b>b</b>) indirect electron transfer by redox shuttles (S <sub>RE</sub> = reduced electron shuttle, S <sub>OX</sub> = oxidized electron shuttle); (<b>c</b>) electron transfer by conductive nanowire matrix.</p> Full article ">Figure 3
<p>Basic principle of an MFC as a biosensor.</p> Full article ">
3736 KiB  
Article
Recent Improvement of Medical Optical Fibre Pressure and Temperature Sensors
by Sven Poeggel, Dineshbabu Duraibabu, Kyriacos Kalli, Gabriel Leen, Gerard Dooly, Elfed Lewis, Jimmy Kelly and Maria Munroe
Biosensors 2015, 5(3), 432-449; https://doi.org/10.3390/bios5030432 - 13 Jul 2015
Cited by 35 | Viewed by 10458
Abstract
This investigation describes a detailed analysis of the fabrication and testing of optical fibre pressure and temperature sensors (OFPTS). The optical sensor of this research is based on an extrinsic Fabry–Perot interferometer (EFPI) with integrated fibre Bragg grating (FBG) for simultaneous pressure and [...] Read more.
This investigation describes a detailed analysis of the fabrication and testing of optical fibre pressure and temperature sensors (OFPTS). The optical sensor of this research is based on an extrinsic Fabry–Perot interferometer (EFPI) with integrated fibre Bragg grating (FBG) for simultaneous pressure and temperature measurements. The sensor is fabricated exclusively in glass and with a small diameter of 0.2 mm, making it suitable for volume-restricted bio-medical applications. Diaphragm shrinking techniques based on polishing, hydrofluoric (HF) acid and femtosecond (FS) laser micro-machining are described and analysed. The presented sensors were examined carefully and demonstrated a pressure sensitivity in the range of \(s_p\) = 2–10 \(\frac{\text{nm}}{\text{kPa}}\) and a resolution of better than \(\Delta P\) = 10 Pa protect (0.1 cm H\(_2\)O). A static pressure test in 38 cmH\(_2\)O shows no drift of the sensor in a six-day period. Additionally, a dynamic pressure analysis demonstrated that the OFPTS never exceeded a drift of more than 130 Pa (1.3 cm H\(_2\)O) in a 12-h measurement, carried out in a cardiovascular simulator. The temperature sensitivity is given by \(k=10.7\) \(\frac{\text{pm}}{\text{K}}\), which results in a temperature resolution of better than \(\Delta T\) = 0.1 K. Since the temperature sensing element is placed close to the pressure sensing element, the pressure sensor is insensitive to temperature changes. Full article
(This article belongs to the Special Issue Optical Sensors for Biomedical Applications)
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<p>(<b>a</b>) Schematic of the optical fibre pressure and temperature sensors (OFPTS) system; (<b>b</b>) the hand-case-sized optical fibre system.</p> Full article ">Figure 2
<p>(<b>a</b>) Schematic of the optical fibre pressure and temperature sensor; (<b>b</b>) reflected optical spectrum of the OFPTS, with Fabry–Perot interferometer (FPI) and FBG.</p> Full article ">Figure 3
<p>(<b>a</b>) The acquired spectrum is split into the FPI and FBG part; (<b>b</b>) an acquired FPI spectrum (continuous line) with <math display="inline"> <mrow> <mn>1</mn> <mfrac> <mtext>nm</mtext> <mtext>pixel</mtext> </mfrac> </mrow> </math> and the continuous optical spectrum (dashed).</p> Full article ">Figure 4
<p>(<b>a</b>) FBG inscription into a photosensitive single-mode fibre (SMF) by using a phase mask and UV light; (<b>b</b>) FBG inscription by a femtosecond laser (FSL), which can be tailored to every optical wavelength.</p> Full article ">Figure 5
<p>The optical fibre pressure and temperature sensor assembly steps: (<b>a</b>) SMF, glass capillary (CAP) and multi-mode fibre (MMF); (<b>b</b>) the CAP is spliced to the MMF; (<b>c</b>) and the SMF is pushed into the CAP and fused together; (<b>d</b>) the MMF is polished to become the diaphragm; (<b>e</b>) <math display="inline"> <mrow> <mn>400</mn> <mo>×</mo> </mrow> </math> side view magnification of the OFPTS; (<b>f</b>) top view of the diaphragm, captured by a Vecco interferometer.</p> Full article ">Figure 6
<p>Top view of: (<b>a</b>) cut MMF without polishing; (<b>b</b>) MMF polished down to 12–20 <span class="html-italic">μ</span>m; (<b>c</b>) MMF polished down to 4–8 <span class="html-italic">μ</span>m, captured by a Zeiss microscope.</p> Full article ">Figure 7
<p>(<b>a</b>) Glass particles inside of the cavity; (<b>b</b>) broken diaphragm caused by over-polishing with: (1) a hole; (2) glass inside of the cavity; (3,4) deep scratches.</p> Full article ">Figure 8
<p>(<b>a</b>) FPI spectrum for different diaphragm thicknesses; (<b>b</b>) change of intensity during the etching process.</p> Full article ">Figure 9
<p>(<b>a</b>) OFPTS mounted vertically on the 3D-stage system; (<b>b</b>) FSL HighQ femtoREGENT 355 and equipment.</p> Full article ">Figure 10
<p>(<b>a</b>) Etching process by the FSL; (<b>b</b>) reflected FPI spectrum.</p> Full article ">Figure 11
<p>Top-view of: (<b>a</b>) a diaphragm with a big hole (1) caused by over-etching; (<b>b</b>) clean 2–3 <span class="html-italic">μ</span>m-thick diaphragm with: (1) CAP; (2) cavity and (3) SMF; (<b>c</b>) long-term used sensor, with small accumulated glass particles (1).</p> Full article ">Figure 12
<p>(<b>a</b>) Pressure chamber up to 10 bar; (<b>b</b>) FPI spectrum with stable FBG.</p> Full article ">Figure 13
<p>(<b>a</b>) Beaker with OFPTS, MPXV7002 reference sensor and scale; (<b>b</b>) increased pressure with successive 1-mm steps of water.</p> Full article ">Figure 14
<p>(<b>a</b>) Controlled temperature block; (<b>b</b>) FBG temperature shift.</p> Full article ">Figure 15
<p>(<b>a</b>) One hundred minutes with two heating and cooling phases; (<b>b</b>) temperature linearity.</p> Full article ">Figure 16
<p>(<b>a</b>) A 50-cm burette filled with water; (<b>b</b>) 20-min stability test of an OFPTS.</p> Full article ">Figure 17
<p>(<b>a</b>) A 72-h test with increased air pressure; (<b>b</b>) stability with compensated temperature.</p> Full article ">Figure 18
<p>Compared to a cent: (<b>a</b>) OFPTS (red illuminated) and 1-Fr tube; (<b>b</b>) 5-Fr NutriSafe catheter; (<b>c</b>) two sensors in a single 5-Fr catheter.</p> Full article ">Figure 19
<p>Mecoras CoroSim with Opsens and OMRON reference sensor.</p> Full article ">Figure 20
<p>(<b>a</b>) Pressure in the first minute; (<b>b</b>) pressure after 12 h of continuous measurement.</p> Full article ">
1713 KiB  
Article
Aluminum Nanoholes for Optical Biosensing
by Carlos Angulo Barrios, Víctor Canalejas-Tejero, Sonia Herranz, Javier Urraca, María Cruz Moreno-Bondi, Miquel Avella-Oliver, Ángel Maquieira and Rosa Puchades
Biosensors 2015, 5(3), 417-431; https://doi.org/10.3390/bios5030417 - 9 Jul 2015
Cited by 16 | Viewed by 8377
Abstract
Sub-wavelength diameter holes in thin metal layers can exhibit remarkable optical features that make them highly suitable for (bio)sensing applications. Either as efficient light scattering centers for surface plasmon excitation or metal-clad optical waveguides, they are able to form strongly localized optical fields [...] Read more.
Sub-wavelength diameter holes in thin metal layers can exhibit remarkable optical features that make them highly suitable for (bio)sensing applications. Either as efficient light scattering centers for surface plasmon excitation or metal-clad optical waveguides, they are able to form strongly localized optical fields that can effectively interact with biomolecules and/or nanoparticles on the nanoscale. As the metal of choice, aluminum exhibits good optical and electrical properties, is easy to manufacture and process and, unlike gold and silver, its low cost makes it very promising for commercial applications. However, aluminum has been scarcely used for biosensing purposes due to corrosion and pitting issues. In this short review, we show our recent achievements on aluminum nanohole platforms for (bio)sensing. These include a method to circumvent aluminum degradation—which has been successfully applied to the demonstration of aluminum nanohole array (NHA) immunosensors based on both, glass and polycarbonate compact discs supports—the use of aluminum nanoholes operating as optical waveguides for synthesizing submicron-sized molecularly imprinted polymers by local photopolymerization, and a technique for fabricating transferable aluminum NHAs onto flexible pressure-sensitive adhesive tapes, which could facilitate the development of a wearable technology based on aluminum NHAs. Full article
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<p>(<b>a</b>) Scanning electron microscope (SEM) photograph of a fabricated 500-nm-period Al NHA. Good surface and hole diameter uniformity is observed; (<b>b</b>) Measured spectral transmittances of a 500-nm-period Al NHA on glass immersed in different fluids. S-wavelength is related to the SPP resonance at the interface between the superstrate (air, liquids) and the metal: Its position redshifts from ~507 nm (air) to ~(670–750) nm (liquids) as the superstrate refractive index increases (bulk refractive index sensitivity = 487 nm/RIU). P- and Q-wavelengths are related to metal/substrate SPP resonances.</p> Full article ">Figure 2
<p>(<b>a</b>) A 500-nm-period Al NHA on a 1.2-mm-thick PC substrate illuminated through a microscope objective. Light diffraction is clearly observed; (<b>b</b>) SEM photograph of the nanopatterned Al surface revealing good hole diameter uniformity.</p> Full article ">Figure 3
<p>Experimental spectral transmittance of 500-nm-period Al NHAs on polycarbonate and glass substrates. The spectra exhibit three similar transmission minima: S-wavelength is associated to the superstrate (air)/metal interface SPP resonance, whereas P- and Q-wavelengths are related to substrate/metal SPP resonances.</p> Full article ">Figure 4
<p>Example of oxidized Al surfaces degradation, before (<b>a</b>) and after (<b>b</b>) interacting with PBS buffer.</p> Full article ">Figure 5
<p>Results of the biorecognition assay model system for BSA detection on oxidized Al, measured by scanner fluorescence. Experimental data fit to an exponential rise to max curve (<span class="html-italic">R</span><sup>2</sup> = 0.978).</p> Full article ">Figure 6
<p>Experimental transmission spectra of 620-nm-period (<b>a</b>) and 750-nm-period; (<b>b</b>) Al NHAs on PC supports for optical intensity interrogation at 650 nm (DVD) and 780 nm (CD) wavelength, respectively. Solid black dots indicate the operating points of the transducers while hollow dots show the expected operating points of the biosensors, that is, after biological receptor immobilization on the transducers surfaces.</p> Full article ">Figure 7
<p>Al NHAs on Scotch tape illustrating relevant features of these devices such as flexibility, adherence and optical diffraction. (<b>a</b>) A sample picked with two tweezers; (<b>b</b>) adhered onto a glass pipette; (<b>c</b>) SEM photograph of the Al NHA surface; (<b>d</b>) sample adhered onto a note.</p> Full article ">Figure 8
<p>Schematics of the synthesis of nanoMIPs in Al nanoholes by local photopolymerization. (<b>Left</b>) A prepolymerization MIP mixture, containing a photoinitiator for photopolymerization at 532 nm wavelength, is deposited on an array of nanoholes and green light is applied from the glass substrate side. This leads to highly localized optical fields in the nanoholes; (<b>Right</b>) NanoMIPs after removing the non-polymerized mixture.</p> Full article ">Figure 9
<p>(<b>a</b>) AFM image of a single nanoMIP synthesized in an Al nanohole by local photopolymerization; (<b>b</b>) Fluoresce image of a 5-µm-period array of nanoMIPs containing fluorescent R123.</p> Full article ">
735 KiB  
Article
Characterization of Lactate Sensors Based on Lactate Oxidase and Palladium Benzoporphyrin Immobilized in Hydrogels
by Liam P. Andrus, Rachel Unruh, Natalie A. Wisniewski and Michael J. McShane
Biosensors 2015, 5(3), 398-416; https://doi.org/10.3390/bios5030398 - 7 Jul 2015
Cited by 32 | Viewed by 10409
Abstract
An optical biosensor for lactate detection is described. By encapsulating enzyme-phosphor sensing molecules within permeable hydrogel materials, lactate-sensitive emission lifetimes were achieved. The relative amount of monomer was varied to compare three homo- and co-polymer materials: poly(2-hydroxyethyl methacrylate) (pHEMA) and two copolymers of [...] Read more.
An optical biosensor for lactate detection is described. By encapsulating enzyme-phosphor sensing molecules within permeable hydrogel materials, lactate-sensitive emission lifetimes were achieved. The relative amount of monomer was varied to compare three homo- and co-polymer materials: poly(2-hydroxyethyl methacrylate) (pHEMA) and two copolymers of pHEMA and poly(acrylamide) (pAam). Diffusion analysis demonstrated the ability to control lactate transport by varying the hydrogel composition, while having a minimal effect on oxygen diffusion. Sensors displayed the desired dose-variable response to lactate challenges, highlighting the tunable, diffusion-controlled nature of the sensing platform. Short-term repeated exposure tests revealed enhanced stability for sensors comprising hydrogels with acrylamide additives; after an initial “break-in” period, signal retention was 100% for 15 repeated cycles. Finally, because this study describes the modification of a previously developed glucose sensor for lactate analysis, it demonstrates the potential for mix-and-match enzyme-phosphor-hydrogel sensing for use in future multi-analyte sensors. Full article
(This article belongs to the Special Issue Fluorescence Based Sensing Technologies)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Flow through system schematic.</p> Full article ">Figure 2
<p>(<b>a</b>) Change of lactate concentration in permeate chamber over time for three sensor types; (<b>b</b>) Stern-Volmer plots for the same sensor types. Each set is an average of three compositionally identical sensors; errors bars denote 95% confidence intervals.</p> Full article ">Figure 3
<p>(<b>a</b>) 75:25 pHEMA:pAam lifetime response to lactate interrogation (<b>b</b>) calibration curves for three sensor types. Each calibration curve contains points representing the average phosphorescent lifetime; error bars denote the 95% confidence intervals for <span class="html-italic">n</span> = 3 sensors.</p> Full article ">Figure 4
<p>(<b>a</b>) 90:10 pHEMA:pAam signal retention over 20 cycles (<b>b</b>) % retention of first cycle signal (<b>c</b>) % retention of fifth cycle signal. Markers indicate average values, and error bars represent 95% confidence intervals between measured signal retention for <span class="html-italic">n</span> = 3 sensors.</p> Full article ">
5455 KiB  
Review
Use of Time-Resolved Fluorescence to Monitor Bioactive Compounds in Plant Based Foodstuffs
by M. Adília Lemos, Katarína Sárniková, Francesca Bot, Monica Anese and Graham Hungerford
Biosensors 2015, 5(3), 367-397; https://doi.org/10.3390/bios5030367 - 26 Jun 2015
Cited by 25 | Viewed by 8620
Abstract
The study of compounds that exhibit antioxidant activity has recently received much interest in the food industry because of their potential health benefits. Most of these compounds are plant based, such as polyphenolics and carotenoids, and there is a need to monitor them [...] Read more.
The study of compounds that exhibit antioxidant activity has recently received much interest in the food industry because of their potential health benefits. Most of these compounds are plant based, such as polyphenolics and carotenoids, and there is a need to monitor them from the field through processing and into the body. Ideally, a monitoring technique should be non-invasive with the potential for remote capabilities. The application of the phenomenon of fluorescence has proved to be well suited, as many plant associated compounds exhibit fluorescence. The photophysical behaviour of fluorescent molecules is also highly dependent on their microenvironment, making them suitable probes to monitor changes in pH, viscosity and polarity, for example. Time-resolved fluorescence techniques have recently come to the fore, as they offer the ability to obtain more information, coupled with the fact that the fluorescence lifetime is an absolute measure, while steady state just provides relative and average information. In this work, we will present illustrative time-resolved measurements, rather than a comprehensive review, to show the potential of time-resolved fluorescence applied to the study of bioactive substances. The aim is to help assess if any changes occur in their form, going from extraction via storage and cooking to the interaction with serum albumin, a principal blood transport protein. Full article
(This article belongs to the Special Issue Fluorescence Based Sensing Technologies)
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<p>Graphical depiction of time-resolved measurement methods and an indication of the information obtainable. (<b>a</b>) A modified Jablonski diagram, plus a relative indication of the wavelength positions of the absorption, fluorescence and phosphorescence spectra; (<b>b</b>) Representation of a decay (log intensity scale) and variation of lifetime (τ, indicated by gradient of decay) and intensity (I) on addition of a quencher ([Q]); (<b>c</b>) Time-resolved emission spectra (TRES) illustrating time slicing at two points and production of decay associated spectra; (<b>d</b>) Representation of fluorescence anisotropy, which can provide the initial anisotropy (r<sub>0</sub>), the limiting anisotropy (r<sub>∞</sub>) and the rotational correlation time (τ<sub>R</sub>).</p> Full article ">Figure 2
<p>(<b>a</b>) Microscopy image, via filters of chloroplast emission from a leaf (<span class="html-italic">Hedera—</span>inset); (<b>b</b>) outcome of a kinetic TCSPC measurement showing both the variation of fluorescence intensity and average lifetime for a whole leaf (<span class="html-italic">Ficus</span>—inset). The excitation was at 478 nm and the emission was selected using a filter for large spectral coverage. Three exponential analysis of the kinetic TCSPC measurement, showing (<b>c</b>) the lifetime values and (<b>d</b>) their normalised pre-exponential contribution. Adapted from [<a href="#B45-biosensors-05-00367" class="html-bibr">45</a>].</p> Full article ">Figure 3
<p>TRES measurement performed on a whole leaf (<span class="html-italic">Ficus</span>), showing (<b>a</b>) time-resolved emission spectra; (<b>b</b>) change in peak ratio of the principal emission bands with time after excitation and (<b>c</b>) decay associated spectra obtained via a global analysis of the TRES dataset. Adapted from [<a href="#B45-biosensors-05-00367" class="html-bibr">45</a>].</p> Full article ">Figure 4
<p>Fluorescence excitation-emission spectra (EEM’s) for the samples, showing excitation wavelength (<span class="html-italic">y</span>-axis) emission wavelength (<span class="html-italic">x</span>-axis) and the intensity as rainbow scale (red—high, blue—low). The lycopene EEM (LYC) has also been scaled (LYC zoom) to show the lower intensity emission at ~550 nm. The scattering positions relating to Rayleigh, Raman and second order are also indicated. Adapted from [<a href="#B48-biosensors-05-00367" class="html-bibr">48</a>].</p> Full article ">Figure 5
<p>Results of TRES measurements, showing (<b>a</b>) the equivalent steady state spectra and the decay associated spectra for (<b>b</b>) the untreated extract and (<b>c</b>) extract treated for 1 h. Excitation was at 378 nm. Adapted from [<a href="#B48-biosensors-05-00367" class="html-bibr">48</a>].</p> Full article ">Figure 6
<p>Representation of the decay of lycopene in hexane (red), also showing the IRF (of 36 ps—blue), fitted function (2 exponential green) and weighted residuals (green), close to the peak of the decay. The excitation wavelength was 409 nm (DD-405L) and the emission at 550 nm. Adapted from [<a href="#B48-biosensors-05-00367" class="html-bibr">48</a>].</p> Full article ">Figure 7
<p>(<b>a</b>) absorption spectrum for a freshly made solution of the sample stored for 41 days in (50:50, v:v) methanol: water; (<b>b</b>) effect of laser irradiation during the time-resolved measurements, either at 531 nm or 478 nm on the same sample.</p> Full article ">Figure 8
<p>Time-resolved decays for the beetroot samples stored for different times; (<b>a</b>) using 478 nm excitation; (<b>b</b>) with 531 nm excitation. The IRF in both cases is also shown (FWHM of 77 ps at 478 nm and 52 ps at 531 nm).</p> Full article ">Figure 9
<p>Fluorescence camera intensity images with white light illumination of a free hand slice of raw (<b>a</b>,<b>b</b>) and microwaved (<b>c</b>,<b>d</b>) <span class="html-italic">Purple Majesty</span>; (<b>a</b>,<b>c</b>) taken using a beam splitter, (<b>b</b>) R,B,G composite picture; (<b>d</b>) using blue filter cube. The bar (given in (a)) represents <span class="html-italic">ca</span>. 200 μm. Adapted from [<a href="#B47-biosensors-05-00367" class="html-bibr">47</a>].</p> Full article ">Figure 10
<p>Change in bioactive content in purple potato, relative to uncooked, seen using different cooking methods. TP—total phenolic compounds, TA—total anthocyanins and AOA—antioxidant activity. Adapted from [<a href="#B46-biosensors-05-00367" class="html-bibr">46</a>].</p> Full article ">Figure 11
<p>(<b>a</b>) TRES “time slices” measured from a sample of baked potato. The intensities are shown normalised. Excitation was at 510 nm (DD-510L); (<b>b</b>) Comparison of longer wavelength emission [<a href="#B46-biosensors-05-00367" class="html-bibr">46</a>] with relative (to uncooked) quantity of TA. Adapted from [<a href="#B46-biosensors-05-00367" class="html-bibr">46</a>].</p> Full article ">Figure 12
<p>Binding of turmeric extract with serum albumin; (<b>a</b>) outcome of a two exponential analysis from a kinetic TSCPC dataset. 10,000 decay histograms were collected, each with an acquisition time of 10 ms; (<b>b</b>) representative decay histograms at different times at the beginning of the binding process. Adapted from [<a href="#B44-biosensors-05-00367" class="html-bibr">44</a>].</p> Full article ">Figure 13
<p>Principal compounds that will be addressed here, showing their [<span class="html-italic">origin</span>] and main (sub type) along with the APPLICATION area in this work.</p> Full article ">Figure 14
<p>Relationship between the different anthocyanin (<b>AH<sup>+</sup></b>, <b>A</b>, <b>B</b>, <b>C</b><span class="html-italic">cis</span>, <b>C</b><span class="html-italic">trans</span>) forms adapted from [<a href="#B100-biosensors-05-00367" class="html-bibr">100</a>] and [colour] indications from [<a href="#B99-biosensors-05-00367" class="html-bibr">99</a>].</p> Full article ">
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