In this study, the ability of the Capillary-attached conductive gas sensor (CGS) in real-time gas identification was investigated. The structure of the prototype fabricated CGS is presented. Portions were selected from the beginning of the CGS transient response including the first 11 samples to the first 100 samples. Different feature extraction and classification methods were applied on the selected portions. Validation of methods was evaluated to study the ability of an early portion of the CGS transient response in target gas (TG) identification. Experimental results proved that applying extracted features from an early part of the CGS transient response along with a classifier can distinguish short-chain alcohols from each other perfectly. Decreasing time of exposition in the interaction between target gas and sensing element improved the reliability of the sensor. Classification rate was also improved and time of identification was decreased. Moreover, the results indicated the optimum interval of the early transient response of the CGS for selecting portions to achieve the best classification rates.
This paper presents a comparison between data from single modality and fusion methods to classify Tualang honey as pure or adulterated using Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) statistical classification approaches. Ten different brands of certified pure Tualang honey were obtained throughout peninsular Malaysia and Sumatera, Indonesia. Various concentrations of two types of sugar solution (beet and cane sugar) were used in this investigation to create honey samples of 20%, 40%, 60% and 80% adulteration concentrations. Honey data extracted from an electronic nose (e-nose) and Fourier Transform Infrared Spectroscopy (FTIR) were gathered, analyzed and compared based on fusion methods. Visual observation of classification plots revealed that the PCA approach able to distinct pure and adulterated honey samples better than the LDA technique. Overall, the validated classification results based on FTIR data (88.0%) gave higher classification accuracy than e-nose data (76.5%) using the LDA technique. Honey classification based on normalized low-level and intermediate-level FTIR and e-nose fusion data scored classification accuracies of 92.2% and 88.7%, respectively using the Stepwise LDA method. The results suggested that pure and adulterated honey samples were better classified using FTIR and e-nose fusion data than single modality data.
Human chorionic gonadotropin (hCG), a glycoprotein hormone secreted from the placenta, is a key molecule that indicates pregnancy. Here, we have designed a cost-effective, label-free, in situ point-of-care (POC) immunosensor to estimate hCG using a cuneated 25 nm polysilicon nanogap electrode. A tiny chip with the dimensions of 20.5 × 12.5 mm was fabricated using conventional lithography and size expansion techniques. Furthermore, the sensing surface was functionalized by (3-aminopropyl)triethoxysilane and quantitatively measured the variations in hCG levels from clinically obtained human urine samples. The dielectric properties of the present sensor are shown with a capacitance above 40 nF for samples from pregnant women; it was lower with samples from non-pregnant women. Furthermore, it has been proven that our sensor has a wide linear range of detection, as a sensitivity of 835.88 μA mIU(-1) ml(-2) cm(-2) was attained, and the detection limit was 0.28 mIU/ml (27.78 pg/ml). The dissociation constant Kd of the specific antigen binding to the anti-hCG was calculated as 2.23 ± 0.66 mIU, and the maximum number of binding sites per antigen was Bmax = 22.54 ± 1.46 mIU. The sensing system shown here, with a narrow nanogap, is suitable for high-throughput POC diagnosis, and a single injection can obtain triplicate data or parallel analyses of different targets.
The discovery of Systematic Evolution of Ligands by Exponential Enrichment (SELEX) assay has led to the generation of aptamers from libraries of nucleic acids. Concomitantly, aptamer-target recognition and its potential biomedical applications have become a major research endeavour. Aptamers possess unique properties that make them superior biological receptors to antibodies with a plethora of target molecules. Some specific areas of opportunities explored for aptamer-target interactions include biochemical analysis, cell signalling and targeting, biomolecular purification processes, pathogen detection and, clinical diagnosis and therapy. Most of these potential applications rely on the effective immobilisation of aptamers on support systems to probe target species. Hence, recent research focus is geared towards immobilising aptamers as oligosorbents for biodetection and bioscreening. This article seeks to review advances in immobilised aptameric binding with associated successful milestones and respective limitations. A proposal for high throughput bioscreening using continuous polymeric adsorbents is also presented.
The pragmatic outcome of a lung cancer diagnosis is closely interrelated in reducing the number of fatal death caused by the world's top cancerous disease. Regardless of the advancement made in understanding lung tumor, and its multimodal treatment, in general the percentage of survival remain low. Late diagnosis of a cancerous cell in patients is the major hurdle for the above circumstances. In the new era of a lung cancer diagnosis with low cost, portable and non-invasive clinical sampling, nanotechnology is at its inflection point where current researches focus on the implementation of biosensor conjugated nanomaterials for the generation of the ideal sensing. The present review encloses the superiority of nanomaterials from zero to three-dimensional nanostructures in its discrete and nanocomposites nanotopography on sensing lung cancer biomarkers. Recent researches conducted on definitive nanomaterials and nanocomposites at multiple dimension with distinctive physiochemical property were focused to subside the cases associated with lung cancer through the development of novel biosensors. The hurdles encountered in the recent research and future preference with prognostic clinical lung cancer diagnosis using multidimensional nanomaterials and its composites are presented.
A fluorogenic probe has been developed for determination of telomerase activity using chimeric DNA-templated silver nanoclusters (AgNCs). The formation of AgNCs was investigated before (route A) and after (route B) telomerase elongation reaction. Both routes caused selective quenching of the yellow emission of the AgNCs (best measured at excitation/emission wavelength of 470/557 nm) in telomerase-positive samples. The quenching mechanism was studied using synthetically elongated DNA to mimic the telomerase-catalyzed elongation. The findings show that quenching is due to the formation of parallel G-quadruplexes with a -TTA- loop in the telomerase elongated products. The assay was validated using different cancer cell extracts, with intra- and interassay coefficients of variations of <9.8%. The limits of detection for MCF7, RPMI 2650 and HT29 cell lines are 15, 22 and 39 cells/μL. This represents a distinct improvement over the existing telomeric repeat amplification protocol (TRAP) assay in terms of time, sensitivity and cost. Graphical Abstract A method was developed using chimeric DNA-templated silver nanoclusters to detect telomerase activity directly in cell extracts. The sensitivity of this new method outperforms the traditional TRAP assay, and without the need for amplification.
In purine metabolism, the xanthine oxidoreductase enzyme converts hypoxanthine (HXN) to xanthine (XN) and XN to uric acid (UA). This leads to the deposition of UA crystals in several parts of the body and the serum UA level might be associated with various multifunctional disorders. The dietary intake of caffeine (CF) and ascorbic acid (AA) decreases the UA level in the serum, which leads to cellular damage. Hence, it is highly needed to monitor the UA level in the presence of AA, XN, HXN, and CF and vice versa. Considering this sequence of complications, the present paper reports the fabrication of an electrochemical sensor using low-cost N-doped carbon dots (CDs) for the selective and simultaneous determination of UA in the presence of AA, XN, HXN, and CF at the physiological pH. The colloidal solution of CDs was prepared by the pyrolysis of asparagine and fabricated on a GC electrode by cycling the potential from -0.20 to +1.2 V in a solution containing CDs and 0.01 M H2SO4. Here, the surface -NH2 functionalities of CDs were used to make a thin film of CDs on the GC electrode. FT-IR spectroscopy confirmed the involvement of the -NH2 group in the formation of the CD film. HR-TEM analysis depicts that the formed CDs showed spherical particles with a size of 1.67 nm and SEM analysis exhibits the 89 nm CD film on the GC electrode surface. The fabricated CD film was successfully used for the sensitive and selective determination of UA. The determination of UA was achieved selectively in a mixture consisting of AA, XN, HXN, and CF with 50-fold high concentration. The CDs-film fabricated electrode has several benefits over the bare electrode: (i) well-resolved oxidation peaks for five analytes, (ii) boosted sensitivity, (iii) shifted oxidation as well as on-set potentials toward less positive potentials, and (iv) high stability. The practical utility of the present sensor was tested by simultaneously determining the multifactorial disorders-causing agents in human fluids. The electrocatalyst developed in the present study is sustainable and can be used for multiple analyses; besides, the electrochemical method used for the fabrication of the CD film is environmentally benign.
Cardiovascular disease is a major global health issue. In particular, acute myocardial infarction (AMI) requires urgent attention and early diagnosis. The use of point-of-care diagnostics has resulted in the improved management of cardiovascular disease, but a major drawback is that the performance of POC devices does not rival that of central laboratory tests. Recently, many studies and advances have been made in the field of surface-enhanced Raman scattering (SERS), including the development of POC biosensors that utilize this detection method. Here, we present a review of the strengths and limitations of these emerging SERS-based biosensors for AMI diagnosis. The ability of SERS to multiplex sensing against existing POC detection methods are compared and discussed. Furthermore, SERS calibration-free methods that have recently been explored to minimize the inconvenience and eliminate the limitations caused by the limited linear range and interassay differences found in the calibration curves are outlined. In addition, the incorporation of artificial intelligence (AI) in SERS techniques to promote multivariate analysis and enhance diagnostic accuracy are discussed. The future prospects for SERS-based POC devices that include wearable POC SERS devices toward predictive, personalized medicine following the Fourth Industrial Revolution are proposed.
While the printed circuit board (PCB) has been widely considered as the building block of integrated electronics, the world is switching to pursue new ways of merging integrated electronic circuits with textiles to create flexible and wearable devices. Herein, as an alternative for PCB, we described a non-printed integrated-circuit textile (NIT) for biomedical and theranostic application via a weaving method. All the devices are built as fibers or interlaced nodes and woven into a deformable textile integrated circuit. Built on an electrochemical gating principle, the fiber-woven-type transistors exhibit superior bending or stretching robustness, and were woven as a textile logical computing module to distinguish different emergencies. A fiber-type sweat sensor was woven with strain and light sensors fibers for simultaneously monitoring body health and the environment. With a photo-rechargeable energy textile based on a detailed power consumption analysis, the woven circuit textile is completely self-powered and capable of both wireless biomedical monitoring and early warning. The NIT could be used as a 24/7 private AI "nurse" for routine healthcare, diabetes monitoring, or emergencies such as hypoglycemia, metabolic alkalosis, and even COVID-19 patient care, a potential future on-body AI hardware and possibly a forerunner to fabric-like computers.
Two-dimensional (2D) layered nanomaterials have triggered an intensive interest due to the fascinating physiochemical properties with the exceptional physical, optical and electrical characteristics that transpired from the quantum size effect of their ultra-thin structure. Among the family of 2D nanomaterials, molybdenum disulfide (MoS2) features distinct characteristics related to the existence of direct energy bandgap, which significantly lowers the leakage current and surpasses other 2D materials. In this overview, we expatiate the novel strategies to synthesize MoS2 that cover techniques such as liquid exfoliation, chemical vapour deposition, mechanical exfoliation, hydrothermal reaction, and Van Der Waal epitaxial growth on the substrate. We extend the discussion on the recent progress in biosensing applications of the produced MoS2, highlighting the important surface-to-volume of ultrathin MoS2 structure, which enhances the overall performance of the devices. Further, envisioned the missing piece with the current MoS2-based biosensors towards developing the future strategies.
A biosensor formed by a combination of silicon (Si) micropore and graphene nanohole technology is expected to act as a promising device structure to interrogate single molecule biopolymers, such as deoxyribonucleic acid (DNA). This paper reports a novel technique of using a focused ion beam (FIB) as a tool for direct fabrication of both conical-shaped micropore in Si3N4/Si and a nanohole in graphene to act as a fluidic channel and sensing membrane, respectively. The thinning of thick Si substrate down to 50 µm has been performed prior to a multi-step milling of the conical-shaped micropore with final pore size of 3 µm. A transfer of graphene onto the fabricated conical-shaped micropore with little or no defect was successfully achieved using a newly developed all-dry transfer method. A circular shape graphene nanohole with diameter of about 30 nm was successfully obtained at beam exposure time of 0.1 s. This study opens a breakthrough in fabricating an integrated graphene nanohole and conical-shaped Si micropore structure for biosensor applications.
Reduced graphene oxide (rGO) has emerged as a promising nanomaterial for reliable detection of pathogenic bacteria due to its exceptional properties such as ultrahigh electron transfer ability, large surface to volume ratio, biocompatibility, and its unique interactions with DNA bases of the aptamer. In this study, rGO-azophloxine (AP) nanocomposite aptasensor was developed for a sensitive, rapid, and robust detection of foodborne pathogens. Besides providing an excellent conductive and soluble rGO nanocomposite, the AP dye also acts as an electroactive indicator for redox reactions. The interaction of the label-free single-stranded deoxyribonucleic acid (ssDNA) aptamer with the test organism, Salmonella enterica serovar Typhimurium (S. Typhimurium), was monitored by differential pulse voltammetry analysis, and this aptasensor showed high sensitivity and selectivity for whole-cell bacteria detection. Under optimum conditions, this aptasensor exhibited a linear range of detection from 108 to 101 cfu mL-1 with good linearity (R 2 = 0.98) and a detection limit of 101 cfu mL-1. Furthermore, the developed aptasensor was evaluated with non-Salmonella bacteria and artificially spiked chicken food sample with S. Typhimurium. The results demonstrated that the rGO-AP aptasensor possesses high potential to be adapted for the effective and rapid detection of a specific foodborne pathogen by an electrochemical approach. Graphical abstract Fabrication of graphene-based nanocomposite aptasensor for detection of foodborne pathogen.
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 response of trilayer graphene nanoribbon (TGN)-based ion-sensitive field-effect transistor (ISFET) to different pH solutions and adsorption effect on the sensing parameters are analytically studied in this research. The authors propose a TGN-based sensor to electrochemically detect pH. To this end, absorption effect on the sensing area in the form of carrier concentration, carrier velocity, and conductance variations are investigated. Also, the caused electrical response on TGN as a detection element is analytically proposed, in which significant current decrease of the sensor is observed after exposure to high pH values. In order to verify the accuracy of the model, it is compared with recent reports on pH sensors. The TGN-based pH sensor exposes higher current compared to that of carbon nanotube (CNT) counterpart for analogous ambient conditions. While, the comparative results demonstrate that the conductance of proposed model is lower than that of monolayer graphene-counterpart for equivalent pH values. The results confirm that the conductance of the sensor is decreased and Vg-min is obviously right-shifted by increasing value of pH. The authors demonstrate that although there is not the experimental evidence reported in the part of literature for TGN sensor, but the model can assist in comprehending experiments involving nanoscale pH sensors.
Biosensors research is a fast growing field in which tens of thousands of papers have been published over the years, and the industry is now worth billions of dollars. The biosensor products have found their applications in numerous industries including food and beverages, agricultural, environmental, medical diagnostics, and pharmaceutical industries and many more. Even though numerous biosensors have been developed for detection of proteins, peptides, enzymes, and numerous other biomolecules for diverse applications, their applications in tissue engineering have remained limited. In recent years, there has been a growing interest in application of novel biosensors in cell culture and tissue engineering, for example, real-time detection of small molecules such as glucose, lactose, and H2O2 as well as serum proteins of large molecular size, such as albumin and alpha-fetoprotein, and inflammatory cytokines, such as IFN-g and TNF-α. In this review, we provide an overview of the recent advancements in biosensors for tissue engineering applications.
Bioimpedance analysis is a noninvasive, low cost and a commonly used approach for body composition measurements and assessment of clinical condition. There are a variety of methods applied for interpretation of measured bioimpedance data and a wide range of utilizations of bioimpedance in body composition estimation and evaluation of clinical status. This paper reviews the main concepts of bioimpedance measurement techniques including the frequency based, the allocation based, bioimpedance vector analysis and the real time bioimpedance analysis systems. Commonly used prediction equations for body composition assessment and influence of anthropometric measurements, gender, ethnic groups, postures, measurements protocols and electrode artifacts in estimated values are also discussed. In addition, this paper also contributes to the deliberations of bioimpedance analysis assessment of abnormal loss in lean body mass and unbalanced shift in body fluids and to the summary of diagnostic usage in different kinds of conditions such as cardiac, pulmonary, renal, and neural and infection diseases.
Sensing applications can be used to report biomolecular interactions in order to elucidate the functions of molecules. The use of an analyte and a ligand is a common set-up in sensor development. For several decades, antibodies have been considered to be potential analytes or ligands for development of so-called "immunosensors." In an immunosensor, formation of the complex between antibody and antigen transduces the signal, which is measurable in various ways (e.g., both labeled and label-free based detection). Success of an immunosensor depends on various factors, including surface functionalization, antibody orientation, density of the antibody on the sensor platform, and configuration of the immunosensor. Careful optimization of these factors can generate clear-cut results for any immunosensor. Herein, current aspects, involved in the generated immunosensors, are discussed.
Lung cancer is one of the most serious threats to human where 85% of lethal death caused by non-small cell lung cancer (NSCLC) induced by epidermal growth factor receptor (EGFR) mutation. The present research focuses in the development of efficient and effortless EGFR mutant detection strategy through high-performance and sensitive genosensor. The current amplified through 250 µm sized fingers between 100 µm aluminium electrodes indicates the voltammetry signal generated by means of the mutant DNA sequence hybridization. To enhance the DNA immobilization and hybridization, ∼25 nm sized aluminosilicate nanocomposite synthesized from the disposed joss fly ash was deposited on the gaps between aluminium electrodes. The probe, mutant (complementary), and wild (single-base pair mismatch) targets were designed precisely from the genomic sequences denote the detection of EGFR mutation. Fourier-transform Infrared Spectroscopy analysis was performed at every step of surface functionalization evidences the relevant chemical bonding of biomolecules on the genosensor as duplex DNA with peak response at 1150 cm-1 to 1650 cm-1. Genosensor depicts a sensitive EGFR mutation as it is able to detect apparently at 100 aM mutant against 1 µM DNA probe. The insignificant voltammetry signal generated with wild type strand emphasizes the specificity of genosensor in the detection of single base pair mismatch. The inefficiency of genosensor in detecting EGFR mutation in the absence of aluminosilicate nanocomposite implies the insensitivity of genosensing DNA hybridization and accentuates the significance of aluminosilicate. Based on the slope of the calibration curve, the attained sensitivity of aluminosilicate modified genosensor was 3.02E-4 A M-1. The detection limit of genosensor computed based on 3σ calculation, relative to the change of current proportional to the logarithm of mutant concentration is at 100 aM.
Electrochemical biosensors for phenolic compound determination were developed by immobilization of tyrosinase enzyme in a series of methacrylic-acrylic based biosensor membranes deposited directly using a photocuring method. By modifying the hydrophilicity of the membranes using different proportions of 2-hydroxyethyl methacrylate (HEMA) and butyl acrylate (nBA), we developed biosensor membranes of different hydrophilic characters. The differences in hydrophilicity of these membranes led to changes in the sensitivity of the biosensors towards different phenolic compounds. In general biosensors constructed from the methacrylic-acrylic based membranes showed the poorest response to catechol relative to other phenolic compounds, which is in contrast to many other biosensors based on tyrosinase. The decrease in hydrophilicity of the membrane also allowed better selectivity towards chlorophenols. However, phenol biosensors constructed from the more hydrophilic membrane materials demonstrated better analytical performance towards phenol compared with those made from less hydrophilic ones. For the detection of phenols, these biosensors with different membranes gave detection limits of 0.13-0.25 microM and linear response range from 6.2-54.2 microM phenol. The phenol biosensors also showed good phenol recovery from landfill leachate samples (82-117%).
Food recalls due to undeclared allergens or contamination are costly to the food manufacturing industry worldwide. As the industry strives for better manufacturing efficiencies over a diverse range of food products, there is a need for the development of new analytical techniques to improve monitoring of the presence of unintended food allergens during the food manufacturing process. In particular, the monitoring of wash samples from cleaning in place systems (CIP), used in the cleaning of food processing equipment, would allow for the effective removal of allergen containing ingredients in between food batches. Casein proteins constitute the biggest group of proteins in milk and hence are the most common milk protein allergen in food ingredients. As such, these proteins could present an ideal analyte for cleaning validation. In this work, molecularly imprinted polymer nanoparticles (nanoMIPs) with high affinity toward bovine α-casein were synthesized using a solid-phase imprinting method. The nanoMIPs were then characterized and incorporated into label free surface plasmon resonance (SPR) based sensor. The nanoMIPs demonstrated good binding affinity and selectivity toward α-casein (KD ∼ 10 × 10-9 M). This simple affinity sensor demonstrated the quantitative detection of α-casein achieving a detection limit of 127 ± 97.6 ng mL-1 (0.127 ppm) which is far superior to existing commercially available ELISA kits. Recoveries from spiked CIP wastewater samples were within the acceptable range (87-120%). The reported sensor could allow food manufacturers to adequately monitor and manage food allergen risk in food processing environments while ensuring that the food produced is safe for the consumer.