Clenbuterol (CLB) is an antibiotic and illegal growth promoter drug that has a long half-life and easily remains as residue and contaminates the animal-based food product that leads to various health problems. In this work, electrochemical immunosensor based on poly(3,4-ethylenedioxythiophene)/graphene oxide (PEDOT/GO) modified screen-printed carbon electrode (SPCE) for CLB detection was developed for antibiotic monitoring in a food product. The modification of SPCE with PEDOT/GO as a sensor platform was performed through electropolymerization, while the electrochemical assay was accomplished while using direct competitive format in which the free CLB and clenbuterol-horseradish peroxidase (CLB-HRP) in the solution will compete to form binding with the polyclonal anti-clenbuterol antibody (Ab) immobilized onto the modified electrode surface. A linear standard CLB calibration curve with R² = 0.9619 and low limit of detection (0.196 ng mL-1) was reported. Analysis of milk samples indicated that this immunosensor was able to detect CLB in real samples and the results that were obtained were comparable with enzyme-linked immunosorbent assays (ELISA).
Peptide cross-linked poly(ethylene glycol) hydrogel has been widely used for drug delivery and tissue engineering. However, the use of this material as a biosensor for the detection of collagenase has not been explored. Proteases play a key role in the pathology of diseases such as rheumatoid arthritis and osteoarthritis. The detection of this class of enzyme using the degradable hydrogel film format is promising as a point-of-care device for disease monitoring. In this study, a protease biosensor was developed based on the degradation of a peptide cross-linked poly(ethylene glycol) hydrogel film and demonstrated for the detection of collagenase. The hydrogel was deposited on gold-coated quartz crystals, and their degradation in the presence of collagenase was monitored using a quartz crystal microbalance (QCM). The biosensor was shown to respond to concentrations between 2 and 2000 nM in less than 10 min with a lower detection limit of 2 nM.
The emergence of highly pathogenic and deadly human coronaviruses, namely SARS-CoV and MERS-CoV within the past two decades and currently SARS-CoV-2, have resulted in millions of human death across the world. In addition, other human viral diseases, such as mosquito borne-viral diseases and blood-borne viruses, also contribute to a higher risk of death in severe cases. To date, there is no specific drug or medicine available to cure these human viral diseases. Therefore, the early and rapid detection without compromising the test accuracy is required in order to provide a suitable treatment for the containment of the diseases. Recently, nanomaterials-based biosensors have attracted enormous interest due to their biological activities and unique sensing properties, which enable the detection of analytes such as nucleic acid (DNA or RNA), aptamers, and proteins in clinical samples. In addition, the advances of nanotechnologies also enable the development of miniaturized detection systems for point-of-care (POC) biosensors, which could be a new strategy for detecting human viral diseases. The detection of virus-specific genes by using single-stranded DNA (ssDNA) probes has become a particular interest due to their higher sensitivity and specificity compared to immunological methods based on antibody or antigen for early diagnosis of viral infection. Hence, this review has been developed to provide an overview of the current development of nanoparticles-based biosensors that target pathogenic RNA viruses, toward a robust and effective detection strategy of the existing or newly emerging human viral diseases such as SARS-CoV-2. This review emphasizes the nanoparticles-based biosensors developed using noble metals such as gold (Au) and silver (Ag) by virtue of their powerful characteristics as a signal amplifier or enhancer in the detection of nucleic acid. In addition, this review provides a broad knowledge with respect to several analytical methods involved in the development of nanoparticles-based biosensors for the detection of viral nucleic acid using both optical and electrochemical techniques.
Sweat analysis offers non-invasive real-time on-body measurement for wearable sensors. However, there are still gaps in current developed sweat-sensing devices (SSDs) regarding the concerns of mixing fresh and old sweat and real-time measurement, which are the requirements to ensure accurate the measurement of wearable devices. This review paper discusses these limitations by aiding model designs, features, performance, and the device operation for exploring the SSDs used in different sweat collection tools, focusing on continuous and non-continuous flow sweat analysis. In addition, the paper also comprehensively presents various sweat biomarkers that have been explored by earlier works in order to broaden the use of non-invasive sweat samples in healthcare and related applications. This work also discusses the target analyte's response mechanism for different sweat compositions, categories of sweat collection devices, and recent advances in SSDs regarding optimal design, functionality, and performance.
Timely detection and diagnosis are essentially needed to guide outbreak measures and infection control. It is vital to improve healthcare quality in public places, markets, schools and airports and provide useful insights into the technological environment and help researchers acknowledge the choices and gaps available in this field. In this narrative review, the detection of coronavirus disease 2019 (COVID-19) technologies is summarized and discussed with a comparison between them from several aspects to arrive at an accurate decision on the feasibility of applying the best of these techniques in the biosensors that operate using laser detection technology. The collection of data in this analysis was done by using six reliable academic databases, namely, Science Direct, IEEE Xplore, Scopus, Web of Science, Google Scholar and PubMed. This review includes an analysis review of three highlights: evaluating the hazard of pandemic COVID-19 transmission styles and comparing them with Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) to identify the main causes of the virus spreading, a critical analysis to diagnose coronavirus disease 2019 (COVID-19) based on artificial intelligence using CT scans and CXR images and types of biosensors. Finally, we select the best methods that can potentially stop the propagation of the coronavirus pandemic.
Matched MeSH terms: Biosensing Techniques/methods*; Biosensing Techniques/statistics & numerical data
The race towards the development of user-friendly, portable, fast-detection, and low-cost devices for healthcare systems has become the focus of effective screening efforts since the pandemic attack in December 2019, which is known as the coronavirus disease 2019 (COVID-19) pandemic. Currently existing techniques such as RT-PCR, antigen-antibody-based detection, and CT scans are prompt solutions for diagnosing infected patients. However, the limitations of currently available indicators have enticed researchers to search for adjunct or additional solutions for COVID-19 diagnosis. Meanwhile, identifying biomarkers or indicators is necessary for understanding the severity of the disease and aids in developing efficient drugs and vaccines. Therefore, clinical studies on infected patients revealed that infection-mediated clinical biomarkers, especially pro-inflammatory cytokines and acute phase proteins, are highly associated with COVID-19. These biomarkers are undermined or overlooked in the context of diagnosis and prognosis evaluation of infected patients. Hence, this review discusses the potential implementation of these biomarkers for COVID-19 electrical biosensing platforms. The secretion range for each biomarker is reviewed based on clinical studies. Currently available electrical biosensors comprising electrochemical and electronic biosensors associated with these biomarkers are discussed, and insights into the use of infection-mediated clinical biomarkers as prognostic and adjunct diagnostic indicators in developing an electrical-based COVID-19 biosensor are provided.
Nowadays, several neurological disorders and neurocrine tumours are associated with dopamine (DA) concentrations in various biological fluids. Highly accurate and ultrasensitive detection of DA levels in different biological samples in real-time can change and improve the quality of a patient's life in addition to reducing the treatment cost. Therefore, the design and development of diagnostic tool for in vivo and in vitro monitoring of DA is of considerable clinical and pharmacological importance. In recent decades, a large number of techniques have been established for DA detection, including chromatography coupled to mass spectrometry, spectroscopic approaches, and electrochemical (EC) methods. These methods are effective, but most of them still have some drawbacks such as consuming time, effort, and money. Added to that, sometimes they need complex procedures to obtain good sensitivity and suffer from low selectivity due to interference from other biological species such as uric acid (UA) and ascorbic acid (AA). Advanced materials can offer remarkable opportunities to overcome drawbacks in conventional DA sensors. This review aims to explain challenges related to DA detection using different techniques, and to summarize and highlight recent advancements in materials used and approaches applied for several sensor surface modification for the monitoring of DA. Also, it focuses on the analytical features of the EC and optical-based sensing techniques available.
A novel label-free electrochemical DNA biosensor was constructed for the determination of Escherichia coli bacteria in environmental water samples. The aminated DNA probe was immobilized onto hollow silica microspheres (HSMs) functionalized with 3-aminopropyltriethoxysilane and deposited onto a screen-printed electrode (SPE) carbon paste with supported gold nanoparticles (AuNPs). The biosensor was optimized for higher specificity and sensitivity. The label-free E. coli DNA biosensor exhibited a dynamic linear response range of 1 × 10-10 µM to 1 × 10-5 µM (R2 = 0.982), with a limit of detection at 1.95 × 10-15 µM, without a redox mediator. The sensitivity of the developed DNA biosensor was comparable to the non-complementary and single-base mismatched DNA. The DNA biosensor demonstrated a stable response up to 21 days of storage at 4 ℃ and pH 7. The DNA biosensor response was regenerable over three successive regeneration and rehybridization cycles.
Life was once normal before the first announcement of COVID-19's first case in Wuhan, China, and what was slowly spreading became an overnight worldwide pandemic. Ever since the virus spread at the end of 2019, it has been morphing and rapidly adapting to human nature changes which cause difficult conundrums in the efforts of fighting it. Thus, researchers were steered to investigate the virus in order to contain the outbreak considering its novelty and there being no known cure. In contribution to that, this paper extensively reviewed, compared, and analyzed two main points; SARS-CoV-2 virus transmission in humans and detection methods of COVID-19 in the human body. SARS-CoV-2 human exchange transmission methods reviewed four modes of transmission which are Respiratory Transmission, Fecal-Oral Transmission, Ocular transmission, and Vertical Transmission. The latter point particularly sheds light on the latest discoveries and advancements in the aim of COVID-19 diagnosis and detection of SARS-CoV-2 virus associated with this disease in the human body. The methods in this review paper were classified into two categories which are RNA-based detection including RT-PCR, LAMP, CRISPR, and NGS and secondly, biosensors detection including, electrochemical biosensors, electronic biosensors, piezoelectric biosensors, and optical biosensors.
The concept of optical antennas in physical optics is still evolving. Like the antennas used in the radio frequency (RF) regime, the aspiration of optical antennas is to localize the free propagating radiation energy, and vice versa. For this purpose, optical antennas utilize the distinctive properties of metal nanostructures, which are strong plasmonic coupling elements at the optical regime. The concept of optical antennas is being advanced technologically and they are projected to be substitute devices for detection in the millimeter, infrared, and visible regimes. At present, their potential benefits in light detection, which include polarization dependency, tunability, and quick response times have been successfully demonstrated. Optical antennas also can be seen as directionally responsive elements for point detectors. This review provides an overview of the historical background of the topic, along with the basic concepts and parameters of optical antennas. One of the major parts of this review covers the use of optical antennas in biosensing, presenting biosensing applications with a broad description using different types of data. We have also mentioned the basic challenges in the path of the universal use of optical biosensors, where we have also discussed some legal matters.
In this article a luminescence fiber optic biosensor for the microdetection of heavy metal toxicity in waters based on the marine bacterium Aliivibrio fischeri (A. fischeri) encapsulated in alginate microspheres is described. Cu(II), Cd(II), Pb(II), Zn(II), Cr(VI), Co(II), Ni(II), Ag(I) and Fe(II) were selected as sample toxic heavy metal ions for evaluation of the performance of this toxicity microbiosensor. The loss of bioluminescence response from immobilized A. fischeri bacterial cells corresponds to changes in the toxicity levels. The inhibition of the luminescent biosensor response collected at excitation and emission wavelengths of 287 ± 2 nm and 487 ± 2 nm, respectively, was found to be reproducible and repeatable within the relative standard deviation (RSD) range of 2.4-5.7% (n = 8). The toxicity biosensor based on alginate micropsheres exhibited a lower limit of detection (LOD) for Cu(II) (6.40 μg/L), Cd(II) (1.56 μg/L), Pb(II) (47 μg/L), Ag(I) (18 μg/L) than Zn(II) (320 μg/L), Cr(VI) (1,000 μg/L), Co(II) (1700 μg/L), Ni(II) (2800 μg/L), and Fe(III) (3100 μg/L). Such LOD values are lower when compared with other previous reported whole cell toxicity biosensors using agar gel, agarose gel and cellulose membrane biomatrices used for the immobilization of bacterial cells. The A. fischeri bacteria microencapsulated in alginate biopolymer could maintain their metabolic activity for a prolonged period of up to six weeks without any noticeable changes in the bioluminescence response. The bioluminescent biosensor could also be used for the determination of antagonistic toxicity levels for toxicant mixtures. A comparison of the results obtained by atomic absorption spectroscopy (AAS) and using the proposed luminescent A. fischeri-based biosensor suggests that the optical toxicity biosensor can be used for quantitative microdetermination of heavy metal toxicity in environmental water samples.
Optical chemical sensors have promoted escalating interest in the determination of various pollutants in the environment, which are creating toxicity and may cause serious health problems. This review paper focuses particularly on the recent progress and developments in this field; the working principles and basic classes of optical chemical sensors have been briefly described.
Animal senses cover a broad range of signal types and signal bandwidths and have inspired various sensors and bioinstrumentation devices for biological and medical applications. Insects, such as desert ants and honeybees, for example, utilize polarized skylight pattern-based information in their navigation activities. They reliably return to their nests and hives from places many kilometers away. The insect navigation system involves the dorsal rim area in their compound eyes and the corresponding polarization sensitive neurons in the brain. The dorsal rim area is equipped with photoreceptors, which have orthogonally arranged small hair-like structures termed microvilli. These are the specialized sensors for the detection of polarized skylight patterns (e-vector orientation). Various research groups have been working on the development of novel navigation systems inspired by polarized skylight-based navigation in animals. Their major contributions are critically reviewed. One focus of current research activities is on imitating the integration path mechanism in desert ants. The potential for simple, high performance miniaturized bioinstrumentation that can assist people in navigation will be explored.
Microfluidics-based lab-on-chip (LOC) systems are an active research area that is revolutionising high-throughput sequencing for the fast, sensitive and accurate detection of a variety of pathogens. LOCs also serve as portable diagnostic tools. The devices provide optimum control of nanolitre volumes of fluids and integrate various bioassay operations that allow the devices to rapidly sense pathogenic threat agents for environmental monitoring. LOC systems, such as microfluidic biochips, offer advantages compared to conventional identification procedures that are tedious, expensive and time consuming. This paper aims to provide a broad overview of the need for devices that are easy to operate, sensitive, fast, portable and sufficiently reliable to be used as complementary tools for the control of pathogenic agents that damage the environment.
Increasing interest in analyzing human gait using various wearable sensors, which is known as Human Activity Recognition (HAR), can be found in recent research. Sensors such as accelerometers and gyroscopes are widely used in HAR. Recently, high interest has been shown in the use of wearable sensors in numerous applications such as rehabilitation, computer games, animation, filmmaking, and biomechanics. In this paper, classification of human daily activities using Ensemble Methods based on data acquired from smartphone inertial sensors involving about 30 subjects with six different activities is discussed. The six daily activities are walking, walking upstairs, walking downstairs, sitting, standing and lying. It involved three stages of activity recognition; namely, data signal processing (filtering and segmentation), feature extraction and classification. Five types of ensemble classifiers utilized are Bagging, Adaboost, Rotation forest, Ensembles of nested dichotomies (END) and Random subspace. These ensemble classifiers employed Support vector machine (SVM) and Random forest (RF) as the base learners of the ensemble classifiers. The data classification is evaluated with the holdout and 10-fold cross-validation evaluation methods. The performance of each human daily activity was measured in terms of precision, recall, F-measure, and receiver operating characteristic (ROC) curve. In addition, the performance is also measured based on the comparison of overall accuracy rate of classification between different ensemble classifiers and base learners. It was observed that overall, SVM produced better accuracy rate with 99.22% compared to RF with 97.91% based on a random subspace ensemble classifier.
Toxins are believed to play a crucial role in Burkholderia pseudomallei pathogenicity, however to date, only a few have been identified. The discovery of additional toxic molecules is limited by the lack of a sensitive indicator of B. pseudomallei toxicity. Previously, from a whole genome transcriptome analysis of B. pseudomallei-infected Caenorhabditis elegans, we noted significant overexpression of a number of worm genes encoding detoxification enzymes, indicating the host's attempt to clear bacterial toxic molecules. One of these genes, ugt-29, a family member of UDP-glucuronosyltransferases, was the most robustly induced phase II detoxification gene. In this study, we show that strong induction of ugt-29 is restricted to infections by the most virulent species among the pathogens tested. We also noted that ugt-29 is activated upon disruption of host protein synthesis. Hence, we propose that UGT-29 could be a promising biosensor to detect B. pseudomallei toxins that compromise host protein synthesis. The identification of bactobolin, a polyketide-peptide hybrid molecule, as a toxic molecule of B. pseudomallei further verifies the utilization of this surveillance system to search for bacterial toxins. Hence, a ugt-29 based reporter should be useful in screening for other molecules that inhibit host protein synthesis.
N-acylhomoserine lactone (AHL)-based quorum sensing (QS) is important for the regulation of proteobacterial virulence determinants. Thus, the inhibition of AHL synthases offers non-antibiotics-based therapeutic potentials against QS-mediated bacterial infections. In this work, functional AHL synthases of Pseudomonas aeruginosa LasI and RhlI were heterologously expressed in an AHL-negative Escherichia coli followed by assessments on their AHLs production using AHL biosensors and high resolution liquid chromatography-mass spectrometry (LCMS). These AHL-producing E. coli served as tools for screening AHL synthase inhibitors. Based on a campaign of screening synthetic molecules and natural products using our approach, three strongest inhibitors namely are salicylic acid, tannic acid and trans-cinnamaldehyde have been identified. LCMS analysis further confirmed tannic acid and trans-cinnemaldehyde efficiently inhibited AHL production by RhlI. We further demonstrated the application of trans-cinnemaldehyde inhibiting Rhl QS system regulated pyocyanin production in P. aeruginosa up to 42.06%. Molecular docking analysis suggested that trans-cinnemaldehyde binds to the LasI and EsaI with known structures mainly interacting with their substrate binding sites. Our data suggested a new class of QS-inhibiting agents from natural products targeting AHL synthase and provided a potential approach for facilitating the discovery of anti-QS signal synthesis as basis of novel anti-infective approach.
Surface plasmon resonance (SPR) is a medical diagnosis technique with high sensitivity and specificity. In this research, a new method based on SPR is proposed for rapid, 10-minute detection of the anti-dengue virus in human serum samples. This novel technique, known as rapid immunoglobulin M (IgM)-based dengue diagnostic test, can be utilized quickly and easily at the point of care. Four dengue virus serotypes were used as ligands on a biochip. According to the results, a serum volume of only 1 μl from a dengue patient (as a minimized volume) is required to indicate SPR angle variation to determine the ratio of each dengue serotype in samples with 83-93% sensitivity and 100% specificity.
Antibody labelling to reporter molecules is gaining popularity due to its many potential applications for diagnostics and therapeutics. However, non-directional bioconjugation methods which are commonly used often results in the loss of target binding capabilities. Therefore, a site-specific enzymatic based bioconjugation such as sortase-mediated transpeptidation allows for a more rapid and efficient method of antibody conjugation for diagnostic applications. Here we describe the utilization of sortase A bioconjugation to conjugate a single chain fragment variable (scFv) to the extracellular invertase (invB) from Zymomonas mobilis with the aim of developing an invertase based immunoassay. In addition, conjugation to enhanced green fluorescent protein (eGFP) was also validated to show the flexibility of the method. The invertase conjugated complex was successfully applied for the detection of antibody-antigen interaction using a personal glucose meter (PGM) for assay readout. The setup was used in both a direct and competitive assay highlighting the robustness of the conjugate for assay development. The method provides an alternative conjugation process to allow easy exchange of antibodies to facilitate rapid development of diagnostic assays for various diseases on the PGM platform.
Hybrid gold nanostructures seeded into nanotextured zinc oxide (ZnO) nanoflowers (NFs) were created for novel biosensing applications. The selected 'spotted NFs' had a 30-nm-thick gold nanoparticle (AuNP) layer, chosen from a range of AuNP thicknesses, sputtered onto the surface. The generated nanohybrids, characterized by morphological, physical and structural analyses, were uniformly AuNP-seeded onto the ZnO NFs with an average length of 2-3 μm. Selective capture of molecular probes onto the seeded AuNPs was evidence for the specific interaction with DNA from pathogenic Leptospirosis-causing strains via hybridization and mis-match analyses. The attained detection limit was 100 fM as determined via impedance spectroscopy. High levels of stability, reproducibility and regeneration of the sensor were obtained. Selective DNA immobilization and hybridization were confirmed by nitrogen and phosphorus peaks in an X-ray photoelectron spectroscopy analysis. The created nanostructure hybrids illuminate the mechanism of generating multiple-target, high-performance detection on a single NF platform, which opens a new avenue for array-based medical diagnostics.