Showing papers in "Analyst in 2020"

Optical biosensors: an exhaustive and comprehensive review.

Abstract: Optical biosensors have exhibited worthwhile performance in detecting biological systems and promoting significant advances in clinical diagnostics, drug discovery, food process control, and environmental monitoring. Without complexity in their pretreatment and probable influence on the nature of target molecules, these biosensors have additional advantages such as high sensitivity, robustness, reliability, and potential to be integrated on a single chip. In this review, the state of the art optical biosensor technologies, including those based on surface plasmon resonance (SPR), optical waveguides, optical resonators, photonic crystals, and optical fibers, are presented. The principles for each type of biosensor are concisely introduced and particular emphasis has been placed on recent achievements. The strengths and weaknesses of each type of biosensor have been outlined as well. Concluding remarks regarding the perspectives of future developments are discussed.

Fundamentals of fast-scan cyclic voltammetry for dopamine detection

Abstract: Fast-scan cyclic voltammetry (FSCV) is used with carbon-fiber microelectrodes for the real-time detection of neurotransmitters on the subsecond time scale. With FSCV, the potential is ramped up from a holding potential to a switching potential and back, usually at a 400 V s−1 scan rate and a frequency of 10 Hz. The plot of current vs. applied potential, the cyclic voltammogram (CV), has a very different shape for FSCV than for traditional cyclic voltammetry collected at scan rates which are 1000-fold slower. Here, we explore the theory of FSCV, with a focus on dopamine detection. First, we examine the shape of the CVs. Background currents, which are 100-fold higher than faradaic currents, are subtracted out. Peak separation is primarily due to slow electron transfer kinetics, while the symmetrical peak shape is due to exhaustive electrolysis of all the adsorbed neurotransmitters. Second, we explain the origins of the dopamine waveform, and the factors that limit the holding potential (oxygen reduction), switching potential (water oxidation), scan rate (electrode instability), and repetition rate (adsorption). Third, we discuss data analysis, from data visualization with color plots, to the automated algorithms like principal components regression that distinguish dopamine from pH changes. Finally, newer applications are discussed, including optimization of waveforms for analyte selectivity, carbon nanomaterial electrodes that trap dopamine, and basal level measurements that facilitate neurotransmitter measurements on a longer time scale. FSCV theory is complex, but understanding it enables better development of new techniques to monitor neurotransmitters in vivo.

Antifouling strategies in advanced electrochemical sensors and biosensors.

Abstract: Electrochemical biosensors have been applied in a broad range of clinical applications for pathogen biomarker detection and medical applications and diagnosis due to the sensitivity of electrochemical methods and the bioselectivity of the components. The complexity of clinical conditions with various biofoulants (proteins, cells, polysaccharides and lipids) severely influences the reliability and stability of sensors for direct detection or immersion under changing conditions. Therefore, designing an antifouling sensing platform that can effectively reduce undesired binding to maintain biosensor performance in optimized analysis is necessary. For this purpose, the fundamental mechanisms of fouling materials and commonly used biocompatible antifouling components have been discussed, and the relevant effective modification strategies are introduced in this review. Recent advances in these strategies are demonstrated in examples with analysis of essential modification methods for reliable sensing in non-specific binding solutions or complex biofluids. The challenges and future perspectives of modification strategies for current clinical application are also discussed in this review.

Development of a lateral flow immunoassay strip for rapid detection of IgG antibody against SARS-CoV-2 virus.

Abstract: The ongoing worldwide SARS-CoV-2 epidemic clearly has a tremendous influence on public health. Molecular detection based on oral swabs was used for confirmation of SARS-CoV-2 infection. However, high false negative rates were reported. We describe here the development of a point-of-care (POC) serological assay for the detection of IgG antibody against SARS-CoV-2. The principle of a lateral flow immunoassay strip (LFIAs) consists of fixing SARS-CoV-2 nucleocapsid protein to the surface of the strip and coupling anti-human IgG with colloidal gold nanoparticles (Au NPs). A series of parameters of this method were optimized, including the concentration of coating antigen, BSA blocking concentration and pH value for conjugation. The entire detection process took 15-20 min with a volume of 80 μL of the analyte solution containing 10 μL of serum and 70 μL sample diluent. The performance of the established assay was evaluated using serum samples of the clinically diagnosed cases of Coronavirus Disease 2019 (COVID-19). Our results indicated that the LFIAs for SARS-CoV-2 had satisfactory stability and reproducibility. As a result, our fast and easy LFIAs could provide a preliminary test result for physicians to make the correct diagnosis of SARS-CoV-2 infections along with alternative testing methods and clinical findings, as well as seroprevalence determination, especially in low-resource countries.

Are plasmonic optical biosensors ready for use in point-of-need applications?

Abstract: Plasmonics has drawn significant attention in the area of biosensors for decades due to the unique optical properties of plasmonic resonant nanostructures. While the sensitivity and specificity of molecular detection relies significantly on the resonance conditions, significant attention has been dedicated to the design, fabrication, and optimization of plasmonic substrates. The adequate choice of materials, structures, and functionality goes hand in hand with a fundamental understanding of plasmonics to enable the development of practical biosensors that can be deployed in real life situations. Here we provide a brief review of plasmonic biosensors detailing most recent developments and applications. Besides metals, novel plasmonic materials such as graphene are highlighted. Sensors based on Surface Plasmon Resonance (SPR), Localized Surface Plasmon Resonance (LSPR), and Surface Enhanced Raman Spectroscopy (SERS) are presented and classified based on their materials and structure. In addition, most recent applications to environment monitoring, health diagnosis, and food safety are presented. Potential problems related to the implementation in such applications are discussed and an outlook is presented.

Recent advances in fast-scan cyclic voltammetry

Abstract: Fast-scan cyclic voltammetry (FSCV) at carbon-fiber microelectrodes (CFMEs) is a versatile electrochemical technique to probe neurochemical dynamics in vivo. Progress in FSCV methodology continues to address analytical challenges arising from biological needs to measure low concentrations of neurotransmitters at specific sites. This review summarizes recent advances in FSCV method development in three areas: (1) waveform optimization, (2) electrode development, and (3) data analysis. First, FSCV waveform parameters such as holding potential, switching potential, and scan rate have been optimized to monitor new neurochemicals. The new waveform shapes introduce better selectivity toward specific molecules such as serotonin, histamine, hydrogen peroxide, octopamine, adenosine, guanosine, and neuropeptides. Second, CFMEs have been modified with nanomaterials such as carbon nanotubes or replaced with conducting polymers to enhance sensitivity, selectivity, and antifouling properties. Different geometries can be obtained by 3D-printing, manufacturing arrays, or fabricating carbon nanopipettes. Third, data analysis is important to sort through the thousands of CVs obtained. Recent developments in data analysis include preprocessing by digital filtering, principal components analysis for distinguishing analytes, and developing automated algorithms to detect peaks. Future challenges include multisite measurements, machine learning, and integration with other techniques. Advances in FSCV will accelerate research in neurochemistry to answer new biological questions about dynamics of signaling in the brain.

Portable and field-deployed surface plasmon resonance and plasmonic sensors

Abstract: Plasmonic sensors are ideally suited for the design of small, integrated, and portable devices that can be employed in situ for the detection of analytes relevant to environmental sciences, clinical diagnostics, infectious diseases, food, and industrial applications. To successfully deploy plasmonic sensors, scaled-down analytical devices based on surface plasmon resonance (SPR) and localized surface plasmon resonance (LSPR) must integrate optics, plasmonic materials, surface chemistry, fluidics, detectors and data processing in a functional instrument with a small footprint. The field has significantly progressed from the implementation of the various components in specifically designed prism-based instruments to the use of nanomaterials, optical fibers and smartphones to yield increasingly portable devices, which have been shown for a number of applications in the laboratory and deployed on site for environmental, biomedical/clinical, and food applications. A roadmap to deploy plasmonic sensors is provided by reviewing the current successes and by laying out the directions the field is currently taking to increase the use of field-deployed plasmonic sensors at the point-of-care, in the environment and in industries.

Comparison of activation processes for 3D printed PLA-graphene electrodes: electrochemical properties and application for sensing of dopamine

Abstract: This paper reports the comparison of the electrochemical properties of 3D PLA-graphene electrodes (PLA-G) under different activation conditions and through different processes. In this work, the performance of the electrodes was evaluated after polishing, electrochemical and chemical treatments and a combination of them. The best results were obtained with hydroxide activation using 1.0 mol L-1 NaOH for 30 min of immersion, which promoted the saponification of PLA exposing the graphene nanoribbon structures. The improvement was more evident also after electrochemical activation, which led to a great increase in surface area, defects, electron transfer rate and amount of edge sites. The analytical performance of the proposed PLA-GNaOH-30-EC electrode was evaluated in the presence of dopamine (DA) by three electrochemical techniques, presenting a broad linear range, and limits of detection of 3.49, 2.17 and 1.67 μmol L-1 were obtained by cyclic voltammetry (CV), differential pulse voltammetry (DPV) and square wave voltammetry (SWV), respectively. The separation and quantification of DA in the presence of AA and UA was also reported. The sensor showed good repeatability and reproducibility and was successfully applied to DA determination in synthetic urine and human serum, showing good recovery, from 88.8 to 98.4%. Therefore, the activation methods were essential for the improvement in the 3D PLA-G electrode properties, allowing graphene surface alteration and electrochemical enhancement in the sensing of molecular targets.

Nanozyme-based electrochemical biosensors for disease biomarker detection.

Abstract: In recent years, a new group of nanomaterials named nanozymes that exhibit enzyme-mimicking catalytic activity has emerged as a promising alternative to natural enzymes. Nanozymes can address some of the intrinsic limitations of natural enzymes such as high cost, low stability, difficulty in storage, and specific working conditions (i.e., narrow substrate, temperature and pH ranges). Thus, synthesis and applications of hybrid and stimuli-responsive advanced nanozymes could revolutionize the current practice in life sciences and biosensor applications. On the other hand, electrochemical biosensors have long been used as an efficient way for quantitative detection of analytes (biomarkers) of interest. As such, the use of nanozymes in electrochemical biosensors is particularly important to achieve low cost and stable biosensors for prognostics, diagnostics, and therapeutic monitoring of diseases. Herein, we summarize the recent advances in the synthesis and classification of common nanozymes and their application in electrochemical biosensor development. After briefly overviewing the applications of nanozymes in non-electrochemical-based biomolecular sensing systems, we thoroughly discuss the state-of-the-art advances in nanozyme-based electrochemical biosensors, including genosensors, immunosensors, cytosensors and aptasensors. The applications of nanozymes in microfluidic-based assays are also discussed separately. We also highlight the challenges of nanozyme-based electrochemical biosensors and provide some possible strategies to address these limitations. Finally, future perspectives on the development of nanozyme-based electrochemical biosensors for disease biomarker detection are presented. We envisage that standardization of nanozymes and their fabrication process may bring a paradigm shift in biomolecular sensing by fabricating highly specific, multi-enzyme mimicking nanozymes for highly sensitive, selective, and low-biofouling electrochemical biosensors.

Current developments in LC-MS for pharmaceutical analysis.

Abstract: Liquid chromatography (LC) based techniques in combination with mass spectrometry (MS) detection have had a large impact on the development of new pharmaceuticals in the past decades. Continuous improvements in mass spectrometry and interface technologies, combined with advanced liquid chromatographic techniques for high-throughput qualitative and quantitative analysis, have resulted in a wider scope of applications in the pharmaceutical field. LC-MS tools are increasingly used to analyze pharmaceuticals across a variety of stages in their discovery and development. These stages include drug discovery, product characterization, metabolism studies (in vitro and in vivo) and the identification of impurities and degradation products. The increase in LC-MS applications has been enormous, with retention times and molecular weights (and related fragmentation patterns) emerging as crucial analytical features in the drug development process. The goal of this review is to give an overview of the main developments in LC-MS based techniques for the analysis of small pharmaceutical molecules in the last decade and give a perspective on future trends in LC-MS in the pharmaceutical field.

Multiplexed detection of biomarkers in lateral-flow immunoassays

Abstract: Multiplexed detection of biomarkers, i.e., simultaneous detection of multiple biomarkers in a single assay, is a process of great advantages including enhanced diagnostic precision, improved diagnostic efficiency, reduced diagnostic cost, and alleviated pain of patients. A typical lateral-flow immunoassay (LFIA) is a widely used paper-based immunochromatographic test strip designed to detect a target biomarker through two common formats: sandwich assay and competitive assay. In order to obtain qualitative or quantitative results, a probe with unique optical or magnetic properties is usually employed to characterize the concentration of the target biomarker. The typical LFIA is suitable for point-of-care testing due to its simplicity, portability, cost-effectiveness, and rapid detection of a target biomarker. However, detection of a single biomarker in the typical LFIA is not favorable for high throughput analysis. Therefore, multiplexed detection of biomarkers in LFIAs has been extensively studied in recent years for high throughput analysis. To accomplish multiplexed detection of biomarkers in LFIAs, the most frequently used structure is a test strip with multiple test lines (TLs), where each TL can detect a specific biomarker. An alternative structure, i.e., a multi-channel structure with multiple test strips, where each test strip has one TL for detecting a specific biomarker, is employed for multiplexed detection of biomarkers. Sometimes, a single test strip with only one TL containing different receptors, where each detection receptor corresponds to a specific biomarker, is another structure applied for multiplexed detection of biomarkers. This paper reviews three common structures for multiplexed detection of biomarkers in LFIAs, i.e., a test strip with multiple TLs, a multi-channel structure with multiple test strips, and a test strip with a single TL. Based on the three common structures, different signal detection strategies that include colorimetric detection, fluorescence detection, surface-enhanced Raman scattering detection, and magnetic detection, along with performance and perspectives are discussed.

Rapid and accurate detection of Escherichia coli O157:H7 in beef using microfluidic wax-printed paper-based ELISA

Abstract: Escherichia coli O157:H7 is a severe foodborne pathogen that causes lots of life-threatening diseases. In the search for a rapid, sensitive, portable and low-cost method to detect this pathogen, we developed a wax-printed paper-based enzyme-linked immunosorbent assay (P-ELISA) based on microfluidic paper-based analytical devices (μPADs), with the whole operation time being less than 3 h and only needing 5 μl samples for detection. The limit of detection (LOD) of E. coli O157:H7 reached 104 CFU ml-1, which is an order of magnitude higher than that of conventional ELISA (C-ELISA). The LOD in artificially contaminated beef samples is 1 CFU per 25 g after enriching the culture for 8 h. This method is superior to the molecular biology method in detection sensitivity and superior to C-ELISA and the national standard method in detection time and cost. Thus, the established P-ELISA method has good sensitivity, specificity and repeatability. It can be suitable for point-of-care testing without expensive and bulky instruments and can also provide a platform for detecting other pathogens, especially in areas that lack advanced clinical equipment.

A rapid dual-channel readout approach for sensing carbendazim with 4-aminobenzenethiol-functionalized core–shell Au@Ag nanoparticles

Abstract: In this study, a 4-aminobenzenethiol-functionalized core-shell silver-coated gold nanoparticle (Au@Ag-4ABT NP) system was designed for the rapid sensing of carbendazim (CBZ) using a combination of naked-eye colorimetry and surface-enhanced Raman spectroscopy (SERS) dual-channel approach. Under alkaline conditions, the deprotonated CBZ species could interact with Ag surfaces via the N-Ag-O and N-Ag-N bonds. As a result, the neighboring Au@Ag-4ABT NPs would come closer through π-π interactions inducing the aggregation of Au@Ag-4ABT NPs. The aggregation of nanoparticles caused changes in the optical properties of the colloidal system, allowing observation with naked eyes, while the generation of more localized surface plasmon resonance "hotspots" between the adjacent Au@Ag nanoparticles permitted monitoring by the SERS technique. The proposed method showed effective sensitivity toward CBZ with limit of detection and limit of quantitation values of 37 and 122 ppb, respectively. In addition, the proposed dual-channel assay could serve as a simple and rapid method for sensing CBZ in tap water, cauliflower, and pear juice within 30 min.

Deep learning networks for the recognition and quantitation of surface-enhanced Raman spectroscopy

Abstract: Surface-enhanced Raman spectroscopy (SERS) based on machine learning methods has been applied in material analysis, biological detection, food safety, and intelligent analysis. However, machine learning methods generally require extra preprocessing or feature engineering, and handling large-scale data using these methods is challenging. In this study, deep learning networks were used as fully connected networks, convolutional neural networks (CNN), fully convolutional networks (FCN), and principal component analysis networks (PCANet) to determine their abilities to recognise drugs in human urine and measure pirimiphos-methyl in wheat extract in the two input forms of a one-dimensional vector or a two-dimensional matrix. The best recognition result for drugs in urine with an accuracy of 98.05% in the prediction set was obtained using CNN with spectra as input in the matrix form. The optimal quantitation for pirimiphos-methyl was obtained using FCN with spectra in the matrix form, and the analysis was accomplished with a determination coefficient of 0.9997 and a root mean square error of 0.1574 in the prediction set. These networks performed better than the common machine learning methods. Overall, the deep learning networks provide feasible alternatives for the recognition and quantitation of SERS.

Recent developments of nanoenzyme-based colorimetric sensors for heavy metal detection and the interaction mechanism

Abstract: Heavy metal contamination has posed a great threat to human survival and social development. For this, a series of nanoenzyme-based colorimetric sensors, e.g., metal nanoparticles, metal oxides, metal sulfides, graphene-based nanomaterials, G-quadruplex and so on, were developed for the rapid and efficient detection of toxic heavy metal ions, whose detection limit for heavy metal ions could be as low as the nmol L-1 level. The recognition mechanism was based on the catalysis and signal amplification of nanozymes, a new type of nanomaterial possessing specific catalytic activity towards certain chemical reactions such as the oxidation of colorless TMB to blue oxTMB. In this work, we are trying to present readers with a better understanding of this important colorimetric sensing material by illustrating its application in the detection of heavy metal ions using metal nanoparticles, metal oxides, metal sulfides, graphene-based nanomaterials, G-quadruplex, etc. respectively.

Multiple and sensitive SERS detection of cancer-related exosomes based on gold–silver bimetallic nanotrepangs

Abstract: Exosomes are endogenous vesicles of cells, and can be used as important biomarkers for cancers. In this work, we developed a sensitive and reliable SERS sensor for simultaneous detection of multiple cancer-related exosomes. The SERS detection probes were made of bimetallic SERS-active nanotags, gold-silver-silver core-shell-shell nanotrepangs (GSSNTs), which were composed of bumpy surface nanorod (gold nanotrepang, GNT) cores and bilayer silver shells, and decorated with linker DNAs, which were complementary to the aptamer targeting exosomes. Three kinds of SERS detection probes were designed via the adoption of different Raman reporter molecules and linker DNAs. The capture probes were prepared by modifying specific aptamers of the target exosomes on magnetic beads (MBs). In the absence of target exosomes, SERS detection probes were coupled with MBs via specific DNA hybridization for use as aptamer-based SERS sensors. In the presence of target exosomes, the aptamer specifically recognized and captured the exosomes, and GSSNTs were subsequently released into the supernatant. Therefore, attenuated SERS signals were detected on the MBs, indicating the presence of target exosomes. The proposed aptamer-based SERS sensor is expected to be a facile and sensitive method for the multiplex detection of cancer biomarkers and has potential future applications in clinical diagnosis.

Detection of the SARS-CoV-2 humanized antibody with paper-based ELISA

Abstract: This work reports the development of a rapid, simple and inexpensive colorimetric paper-based assay for the detection of the severe acute respiratory symptom coronavirus 2 (SARS-CoV-2) humanized antibody. The paper device was prepared with lamination for easy sample handling and coated with the recombinant SARS-CoV-2 nucleocapsid antigen. This assay employed a colorimetric reaction, which is followed by horseradish peroxidase (HRP) conjugated detecting antibody in the presence of the 3,3′,5,5′-tetramethylbenzidine (TMB) substrate. The colorimetric readout was evaluated and quantified for specificity and sensitivity. The characterization of this assay includes determining the linear regression curve, the limit of detection (LOD), the repeatability, and testing complex biological samples. We found that the LOD of the assay was 9.00 ng μL−1 (0.112 IU mL−1). The relative standard deviation was approximately 10% for a sample number of n = 3. We believe that our proof-of-concept assay has the potential to be developed for clinical screening of the SARS-CoV-2 humanized antibody as a tool to confirm infected active cases or to confirm SARS-CoV-2 immune cases during the process of vaccine development.

NMR-based metabolomics and fluxomics: developments and future prospects.

Abstract: NMR spectroscopy is an essential analytical technique in metabolomics and fluxomics workflows, owing to its high structural elucidation capabilities combined with its intrinsic quantitative nature. However, routine NMR "omic" analytical methods suffer from several drawbacks that may have limited their use as a method of choice, in particular when compared to another widely used technique, mass spectrometry. This review describes, in a critical and perspective discussion, how some of the most recent developments emerging from the NMR community could act as real game changers for metabolomics and fluxomics in the near future. Advanced developments to make NMR metabolomics more resolutive, more sensitive and more accessible are described, as well as new approaches to improve the identification of biomarkers. We hope that this review will convince a broad end-user community of the increasing role of NMR in the "omic" world at the beginning of the 2020s.

Enhanced paper-based ELISA for simultaneous EVs/exosome isolation and detection using streptavidin agarose-based immobilization

Abstract: EVs/exosomes are considered as the next generation of biomarkers, including for liquid biopsies. Consequently, the quantification of EVs/exosomes is crucial for facilitating EV/exosome research and applications. Paper-based enzyme-linked immunosorbent assay (p-ELISA) is a portable diagnostic system with low cost that is simple and easy to use; however, it shows low sensitivity and linearity. In this study, we develop p-ELISA for targeting EVs/exosomes by using streptavidin agarose resin-based immobilization (SARBI). This method reduces assay preparation times, provides strong binding, and retains good sensitivity and linearity. The time required for the total assay, including preparation steps and surface immobilization, was shortened to ∼2 h. We evaluated SARBI p-ELISA systems with/without CD63 capture Ab and then with fetal bovine serum (FBS) and EVs/exosome-depleted fetal bovine serum (dFBS). The results provide evidence supporting the selective capture ability of SARBI p-ELISA. We obtain semiquantitative p-ELISA results using an exosome standard (ES) and human serum (HS), with R2 values of 0.95 and 0.92, respectively.

Aptamers vs. antibodies as capture probes in optical porous silicon biosensors

Abstract: Over the past decade aptamers have emerged as a promising class of bioreceptors for biosensing applications with significant advantages over conventional antibodies. However, experimental studies comparing aptasensors and immunosensors, under equivalent conditions, are limited and the results are inconclusive, in terms of benefits and limitations of each bioreceptor type. In the present work, the performance of aptamer and antibody bioreceptors for the detection of a his-tagged protein, used as a model target, is compared. The bioreceptors are immobilized onto a nanostructured porous silicon (PSi) thin film, used as the optical transducer, and the target protein is detected in a real-time and label-free format by reflective interferometric Fourier transform spectroscopy. For the antibodies, random-oriented immobilization onto the PSi nanostructure results in a poor biosensing performance. Contrary, Fc-oriented immobilization of the antibodies shows a similar biosensing performance to that exhibited by the aptamer-based biosensor, in terms of binding rate, dynamic detection range, limit of detection and selectivity. The aptasensor outperforms in terms of its reusability and storability, while the immunosensor could not be regenerated for subsequent experiments.

Label-free electrochemical immunosensor based on biocompatible nanoporous Fe3O4 and biotin-streptavidin system for sensitive detection of zearalenone.

Abstract: In this study, a sensitive label-free electrochemical immunosensor was designed based on nanoporous Fe3O4 and a biotin-streptavidin system to specifically detect zearalenone (ZEN). Herein, nanoporous Fe3O4 was employed to carry streptavidin to prepare the highly sensitive immunosensor. The application of nanoporous Fe3O4 and the biotin-streptavidin reaction provided large amounts of antibodies on each conjugate, thus amplifying the detected signal. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) were conducted to characterize the modification with ZEN. Factors which might influence the properties of the immunosensor, including concentration of nanoporous Fe3O4, pH of the buffer, incubation time and temperature were studied. Under the best conditions, the immunosensor displayed a highly sensitive response toward ZEN, ranging in concentration from 10.0 pg mL-1 to 3.00 ng mL-1 and 3.00 ng mL-1 to 12.0 ng mL-1, with a low detection limit of 3.7 pg mL-1. The results for analysis of human urine samples were satisfactory. Furthermore, this proposed method may find promising applications in the detection of other mycotoxins.

Identification of methicillin-resistant Staphylococcus aureus bacteria using surface-enhanced Raman spectroscopy and machine learning techniques

Abstract: To combat antibiotic resistance, it is extremely important to select the right antibiotic by performing rapid diagnosis of pathogens. Traditional techniques require complicated sample preparation and time-consuming processes which are not suitable for rapid diagnosis. To address this problem, we used surface-enhanced Raman spectroscopy combined with machine learning techniques for rapid identification of methicillin-resistant and methicillin-sensitive Gram-positive Staphylococcus aureus strains and Gram-negative Legionella pneumophila (control group). A total of 10 methicillin-resistant S. aureus (MRSA), 3 methicillin-sensitive S. aureus (MSSA) and 6 L. pneumophila isolates were used. The obtained spectra indicated high reproducibility and repeatability with a high signal to noise ratio. Principal component analysis (PCA), hierarchical cluster analysis (HCA), and various supervised classification algorithms were used to discriminate both S. aureus strains and L. pneumophila. Although there were no noteworthy differences between MRSA and MSSA spectra when viewed with the naked eye, some peak intensity ratios such as 732/958, 732/1333, and 732/1450 proved that there could be a significant indicator showing the difference between them. The k-nearest neighbors (kNN) classification algorithm showed superior classification performance with 97.8% accuracy among the traditional classifiers including support vector machine (SVM), decision tree (DT), and naive Bayes (NB). Our results indicate that SERS combined with machine learning can be used for the detection of antibiotic-resistant and susceptible bacteria and this technique is a very promising tool for clinical applications.

Label-free detection of nosocomial bacteria using a nanophotonic interferometric biosensor

Abstract: Nosocomial infections are a major concern at the worldwide level. Early and accurate identification of nosocomial pathogens is crucial to provide timely and adequate treatment. A prompt response also prevents the progression of the infection to life-threatening conditions, such as septicemia or generalized bloodstream infection. We have implemented two highly sensitive methodologies using an ultrasensitive photonic biosensor based on a bimodal waveguide interferometer (BiMW) for the fast detection of Pseudomonas aeruginosa and methicillin-resistant Staphylococcus aureus (MRSA), two of the most prevalent bacteria associated with nosocomial infections. For that, we have developed a biofunctionalization strategy based on the use of a PEGylated silane (silane-PEG-COOH) which provides a highly resistant and bacteria-repelling surface, which is crucial to specifically detect each bacterium. Two different biosensor assays have been set under standard buffer conditions: one based on a specific direct immunoassay employing polyclonal antibodies for the detection of P. aeruginosa and another one employing aptamers for the direct detection of MRSA. The biosensor immunoassay for P. aeruginosa is fast (it only takes 12 min) and specific and has experimentally detected concentrations down to 800 cfu mL-1 (cfu: colony forming unit). The second one relies on the use of an aptamer that specifically detects penicillin-binding protein 2a (PBP2a), a protein only expressed in the MRSA mutant, providing a photonic biosensor with the ability to identify the resistant pathogen MRSA and differentiate it from methicillin-susceptible S. aureus (MSSA). Direct, label-free, and selective detection of whole MRSA bacteria has been achieved, making possible the direct detection of also 800 cfu mL-1. According to the signal-to-noise (S/N) ratio of the device, a theoretical limit of detection (LOD) of around 49 and 29 cfu mL-1 was estimated for P. aeruginosa and MRSA, respectively. Both results obtained under standard conditions reveal the great potential this interferometric biosensor device has as a versatile and specific tool for bacterial detection and quantification, providing a rapid method for the identification of nosocomial pathogens within the clinical requirements of sensitivity for the diagnosis of infections.

Detection of breast cancer-derived exosomes using the horseradish peroxidase-mimicking DNAzyme as an aptasensor

Abstract: Exosomes are membrane-enclosed phospholipid extracellular vesicles with a variety of tumor antigens which can be applied in the diagnosis and treatment of cancer due to the high secretion on the surface of cancer cells. Until now, many research studies on exosomes have been reported, but convenient and low-cost detection methods still need to be developed. Recently, we have developed a sensitive, simple and low-cost colorimetric aptasensor by designing a hairpin-like structure, which combined the highly specific MUC1 aptamer with a hemin/G-quadruplex for the detection of breast cancer exosomes. The hemin/G-quadruplex toward H2O2 reduction was used to generate an evidently strong colorimetric response owing to acting as a HRP-mimicking DNAzyme. The aptasensor is regarded as an “on–off” type switch, which strictly controls the process of reaction responding to the existence or not of exosomes. In our study, associated exosome detection limits are 3.94 × 105 particles per mL, which showed a higher sensitivity compared to commercial ELISA. Our method not only exhibited the advantages of being convenient and time-saving, with few instruments used, but also the signal generated using this method can be easily observed by the naked eye. Furthermore, the proposed strategy can well differentiate breast cancer patients from healthy individuals, demonstrating potential application in the analysis of clinical specimens.

Light-responsive nanozymes for biosensing

Abstract: Using light as an external stimulus plays a key role not only in modulating activities of nanozymes, but also in constructing efficient biosensing systems. This mini-review highlights recent advances in light-responsive nanozyme-based biosensing systems. First, we introduce the light stimulation for regulating nanozymes' activities. Then, several strategies are presented to construct efficient photo-responsive nanozyme-based detection systems by using metal-based nanozymes, carbon-based nanozymes, and MOF-based nanozymes, respectively. Moreover, the detection mechanisms of current biosensors are discussed. Finally, we discuss the current challenges and future perspectives of this research area.

Visualization of the in situ distribution of contents and hydrogen bonding states of cellular level water in apple tissues by confocal Raman microscopy

Abstract: Raman spectroscopy has been employed for studying the hydrogen bonding states of water molecules for decades, however, Raman imaging data contain thousands of spectra, making it challenging to obtain information on water with different hydrogen bonds. In the current study, a novel method combining confocal Raman microscopy (CRM) imaging with the iterative curve fitting algorithms was developed to determine the distribution of water contents at the cellular level and water states with different hydrogen bonds in apple tissues. Raman imaging data ranging from 2700 to 3800 cm-1 were acquired from whole cells in the apple tissue, which were then decomposed into seven sub-peaks using the fixed-position Gaussian iterative curve fitting (FPGICF) algorithm. The content and hydrogen bonding states of cellular water were calculated as the area sum of the OH stretching vibration and the area ratio of DA-OH over DDAA-OH stretching vibration or the number of hydrogen bonds of each water molecule, respectively. Finally, the area of each sub-peak, the area sum of the OH stretching vibration, and the area ratio of DA-OH over DDAA-OH stretching vibration were used to visualize the distribution of each sub-peak, water contents and water states with different hydrogen bonds, respectively. In addition, it was found that the number of hydrogen bonds of each water molecule could also be considered as a criterion to describe the hydrogen bond states of water in apple tissues. The availability of such information should provide new insights for future study of cellular water in other food materials.

Spectroelectrochemistry, the future of visualizing electrode processes by hyphenating electrochemistry with spectroscopic techniques

Abstract: The combination of electrochemistry and spectroscopy, known as spectroelectrochemistry (SEC), is an already established approach. By combining these two techniques, the relevance of the data obtained is greater than what it would be when using them independently. A number of review papers have been published on this subject, mostly written for experts in the field and focused on recent advances. In this review, written for both the novice in the field and the more experienced reader, the focus is not on the past but on the future. The scope is narrowed down to four techniques the authors claim to have the most potential for the future, namely: infrared spectroelectrochemistry (IR-SEC), Raman spectroelectrochemistry (Raman-SEC), nuclear magnetic resonance spectroelectrochemistry (NMR-SEC) and, perhaps slightly more controversial but certainly promising, electrochemistry mass-spectrometry (EC-MS).

Glutamate sensing in biofluids: recent advances and research challenges of electrochemical sensors

Abstract: Glutamate is a nonessential amino acid and a putative neurotransmitter. When its consumption exceeds its synthesis, it becomes necessary to monitor its levels. Hence, a low-cost, sensitive and real-time monitoring of glutamate to quantify pain and detect neurodegenerative diseases is imperative to improve pharmacotherapy and early diagnosis for health care. While enzymatic electrochemical sensors are promising to address issues in lab-based detection techniques, non-enzymatic sensors are better due to their higher stability and lower cost. In this review, we aim to discuss the recent advances and remaining challenges of sensing glutamate in biofluids. First, we discuss the metabolic routes of glutamate, followed by its transmission processes to the biofluids. Second, we identify the connection of glutamate to pathologies as a potential biomarker. Third, we emphasize electrochemical sensors instantaneously detect glutamate in biofluids in real-time, quantifying pain and monitoring neurodegenerative diseases. The literature shows the concentration of glutamate in biofluids, such as plasma, cerebral spinal fluid, urine, and saliva are in the range of 5–100 μM, 0.5–2 μM, 8.5 (3.3–18.4) μM mM−1 creatinine, and 0.232 ± 0.177 μM respectively. While these concentration levels are sometimes lower than the detection limit of electrochemical sensors, functionalization of the nanomaterials currently being used such as NiO and Co3O4 with carbon nanotubes or beta-cyclodextrin may improve the sensing performance. Another key challenge in the research is to develop relationships between glutamate and biofluids. Finally, we have to advance electrochemical sensors that are compatible to detect glutamate in physiological conditions for long durations of time.

Plasmonic tweezers for optical manipulation and biomedical applications.

Abstract: Plasmonic tweezers are an emerging research topic because of their breakthrough in the conventional diffraction limit and precise manipulation at the nanoscale. Notably, their compatibility with analytical techniques (e.g. fluorescence, surface-enhanced Raman scattering (SERS), and laser desorption/ionization mass spectrometry (LDI MS)) opens up opportunities in optical manipulation and biomedical applications. Herein, we first introduce the structures and trapping forces, followed by a summary of the properties of plasmonic tweezers. The optical trapping of biosamples by plasmonic tweezers are then reviewed, including microorganisms and biomolecules. Finally, we highlight the integration of plasmonic tweezers with analytical techniques towards bioanalytical applications. We conclude with perspectives on the future directions for this topic. We foresee the upcoming era of biological detection by plasmonic tweezing in both academy and industry, which calls for the interest and efforts of scientists from diverse fields.

Electrochemical biosensors based on antibody, nucleic acid and enzyme functionalized graphene for the detection of disease-related biomolecules.

Abstract: The unique physical structure and chemical and electrical properties of graphene make it an ideal choice for sensor materials. The sensing platform of biomolecule functionalized graphene has received extensive attention due to its high sensitivity and selectivity, especially the biosensors constructed by combining antibodies, nucleic acids and enzymes that efficiently recognize specific targets with graphene having a large specific surface area and a fast electron transfer rate, which has become a significant research direction. In this paper, electrochemical biosensors based on graphene materials developed in recent years are summarized. The methods of functional modification of graphene, graphene oxide and reduced graphene oxide with antibodies, nucleic acids and enzymes are briefly described. In addition, the advantages and disadvantages of the constructed electrochemical biosensors in detecting pathogens and disease markers are also reviewed. Finally, we are optimistic about this prospect for the development direction and application prospects of such electrochemical biosensors.