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Viruses Jan 2023Biosensor research is a swiftly growing field for developing rapid and precise analytical devices for biomedical, pharmaceutical, and industrial use and beyond. Herein,...
Biosensor research is a swiftly growing field for developing rapid and precise analytical devices for biomedical, pharmaceutical, and industrial use and beyond. Herein, we propose a phage-based biosensor method to develop a sensitive and specific system for biomedical detection. Our method is based on in vitro selected phages and their interaction with the targeted analytes as well as on optical properties that change according to the concentration of the model analyte. The green fluorescent protein (GFP) was chosen as our model analyte as it has its own well-known optical properties. Brilliant green was used as a reporter component for the sensor. Its presence enables a color intensity (absorbance) change when the analyte is present in the solution. Furthermore, the reporter dye functioned as a quencher for an additional lanthanide label in our assay. It mediated the specific phage-derived interference in the signal measured with the time-resolved luminescence. Most importantly, our results confirmed that the presented bifunctional phage with its liquid crystal properties enabled the measurement of GFP in a concentration-dependent, quantitative manner with a limit of detection of 0.24 µg/mL. In the future, our novel method to develop phage-based biosensors may provide highly sensitive and specific biosensors for biomedical or otherwise-relevant targets.
Topics: Bacteriophages; Biological Assay; Green Fluorescent Proteins; Luminescence
PubMed: 36851513
DOI: 10.3390/v15020299 -
The Analyst Aug 2021We introduce analyte-dependent exclusion of reporter reagents from restricted-access adsorbents as the basis of an isocratic reporter-exclusion immunoassay for viruses,...
We introduce analyte-dependent exclusion of reporter reagents from restricted-access adsorbents as the basis of an isocratic reporter-exclusion immunoassay for viruses, proteins, and other analytes. Capto™ Core 700 and related resins possess a noninteracting size-selective outer layer surrounding a high-capacity nonspecific mixed-mode capture adsorbent core. In the absence of analyte, antibody-enzyme reporter conjugates can enter the adsorbent and be captured, and their signal is lost. In the presence of large or artificially-expanded analytes, reporter reagents bind to analyte species to form complexes large enough to be excluded from the adsorbent core, allowing their signal to be observed. This assay principle is demonstrated using M13 bacteriophage virus and human chorionic gonadotropin as model analytes. The simple isocratic detection approach described here allows a rapid implementation of immunoassay for detection of a wide range of analytes and uses inexpensive, generally-applicable, and stable column materials instead of costly analyte-specific immunoaffinity adsorbents.
Topics: Bacteriophage M13; Chorionic Gonadotropin; Humans; Immunoassay; Indicators and Reagents
PubMed: 34198311
DOI: 10.1039/d1an00396h -
Risk Analysis : An Official Publication... Sep 2019The concept of "resilience analytics" has recently been proposed as a means to leverage the promise of big data to improve the resilience of interdependent critical...
The concept of "resilience analytics" has recently been proposed as a means to leverage the promise of big data to improve the resilience of interdependent critical infrastructure systems and the communities supported by them. Given recent advances in machine learning and other data-driven analytic techniques, as well as the prevalence of high-profile natural and man-made disasters, the temptation to pursue resilience analytics without question is almost overwhelming. Indeed, we find big data analytics capable to support resilience to rare, situational surprises captured in analytic models. Nonetheless, this article examines the efficacy of resilience analytics by answering a single motivating question: Can big data analytics help cyber-physical-social (CPS) systems adapt to surprise? This article explains the limitations of resilience analytics when critical infrastructure systems are challenged by fundamental surprises never conceived during model development. In these cases, adoption of resilience analytics may prove either useless for decision support or harmful by increasing dangers during unprecedented events. We demonstrate that these dangers are not limited to a single CPS context by highlighting the limits of analytic models during hurricanes, dam failures, blackouts, and stock market crashes. We conclude that resilience analytics alone are not able to adapt to the very events that motivate their use and may, ironically, make CPS systems more vulnerable. We present avenues for future research to address this deficiency, with emphasis on improvisation to adapt CPS systems to fundamental surprise.
PubMed: 31100198
DOI: 10.1111/risa.13328 -
Mikrochimica Acta Oct 2022The cornerstone of nanomaterial-based sensing systems is the synthesis of nanoparticles with appropriate surface functionalization that ensures their stability and... (Review)
Review
The cornerstone of nanomaterial-based sensing systems is the synthesis of nanoparticles with appropriate surface functionalization that ensures their stability and determines their reactivity with organic or inorganic analytes. To accomplish these requirements, various compounds are used as additives or growth factors to regulate the properties of the synthesized nanoparticles and their reactivity with the target analytes. A different rationale is to use the target analytes as additives or growth agents to control the formation and properties of nanoparticles. The main difference is that the analyte recognition event occurs before or during the formation of nanoparticles and it is based on the reactivity of the analytes with the precursor materials of the nanoparticles (e.g., metal ions, reducing agents, and coatings). The transition from the ionic (or molecular) state of the precursor materials to ordered nanostructured assemblies is used for sensing and signal transduction for the qualitative detection and the quantitative determination of the target analytes, respectively. This review focuses on assays that are based on analyte-mediated regulation of nanoparticles' formation and differentiate them from standard nanoparticle-based assays which rely on pre-synthesized nanoparticles. Firstly, the principles of analyte-mediated nanomaterial sensors are described and then they are discussed with emphasis on the sensing strategies, the signal transduction mechanisms, and their applications. Finally, the main advantages, as well as the limitations of this approach, are discussed and compared with assays that rely on pre-synthesized nanoparticles in order to highlight the major advances accomplished with this type of nano-sensors and elucidate challenges and opportunities for further evolving new nano-sensing strategies.
Topics: Biosensing Techniques; Nanoparticles; Nanostructures; Metals; Ions
PubMed: 36307660
DOI: 10.1007/s00604-022-05536-7 -
ACS Sensors Dec 2020The last two decades have seen great advancements in fundamental understanding and applications of metallic nanoparticles stabilized by mixed-ligand monolayers.... (Review)
Review
The last two decades have seen great advancements in fundamental understanding and applications of metallic nanoparticles stabilized by mixed-ligand monolayers. Identifying and controlling the organization of multiple ligands in the nanoparticle monolayer has been studied, and its effect on particle properties has been examined. Mixed-ligand protected particles have shown advantages over monoligand protected particles in fields such as catalysis, self-assembly, imaging, and drug delivery. In this Review, the use of mixed-ligand monolayer protected nanoparticles for sensing applications will be examined. This is the first time this subject is examined as a whole. Mixed-ligand nanoparticle-based sensors are revealed to be divided into four groups, each of which will be discussed. The first group consists of ligands that work cooperatively to improve the sensors' properties. In the second group, multiple ligands are utilized for sensing multiple analytes. The third group combines ligands used for analyte recognition and signal production. In the final group, a sensitive, but unstable, functional ligand is combined with a stabilizing ligand. The Review will conclude by discussing future challenges and potential research directions for this promising subject.
Topics: Catalysis; Ligands; Metal Nanoparticles
PubMed: 33241680
DOI: 10.1021/acssensors.0c02124 -
Analytical Chemistry Jul 2019Isolation of substances by liquid-phase microextraction (LPME) or electromembrane extraction (EME) is becoming more and more important in analytical chemistry. However,...
Isolation of substances by liquid-phase microextraction (LPME) or electromembrane extraction (EME) is becoming more and more important in analytical chemistry. However, the understanding of the mass transfer in LPME and EME is limited, especially for highly concentrated samples. In this work, the mass transfer in LPME and EME from aqueous samples (0.5-200 mg L) was studied in terms of recovery, equilibrium time, flux, and mass transfer capacity. In both EME and LPME, high recoveries were achieved at low analyte concentration, and the recoveries decreased at high analyte concentration. For EME, the loss in recovery was partly compensated by increasing the extraction voltage (from 50 to 200 V), while the LPME recovery at high analyte concentration was improved by increasing the extraction time (from 30 to 180 min). EME was superior in terms of equilibrium time and flux, while LPME provided much higher mass transfer capacity especially for highly concentrated samples. Moreover, the recovery was much more sensitive to high analyte concentrations in EME than in LPME, and the EME recovery decreased significantly above 50 mg L, indicating that LPME could be used to isolate analytes in a wider concentration range than EME. We believe that this fundamental study will be of great importance for the selection of a suitable membrane-based microextraction technique.
PubMed: 31141346
DOI: 10.1021/acs.analchem.9b00946 -
Bioanalysis Aug 2023Microextraction techniques have attracted the attention of many researchers working in the field of bioanalysis due to their unique advantages, mainly in downsizing the... (Review)
Review
Microextraction techniques have attracted the attention of many researchers working in the field of bioanalysis due to their unique advantages, mainly in downsizing the scale of sample preparation steps. In parallel, analytical derivatization offers a powerful combination in terms of additional sensitivity, selectivity and compatibility with modern separation techniques. The aim of this review is to discuss the most recent advances in bioanalytical sample preparation based on the combination of microextraction and analytical derivatization. Both innovative fundamental reports and analyte-targeted applications are included and discussed. Dispersive liquid-liquid extraction and solid-phase microextraction are the most common techniques that typically combined with derivatization, while the development of novel and greener protocols is receiving substantial consideration in the field of analytical chemistry.
Topics: Humans; Chemistry, Analytic; Liquid-Liquid Extraction; Research Personnel; Solid Phase Microextraction; Specimen Handling
PubMed: 37638635
DOI: 10.4155/bio-2023-0121 -
Critical Reviews in Analytical Chemistry 2023Accurate quantification of biomarkers has always been a challenge for many bioanalytical scientists due to their endogenous nature and low concentration in biological... (Review)
Review
Accurate quantification of biomarkers has always been a challenge for many bioanalytical scientists due to their endogenous nature and low concentration in biological matrices. Different analytical approaches have been developed for quantifying biomarkers including enzyme-linked immunosorbent assay, immunohistochemistry, western blotting, and chromatographic techniques assisted with mass spectrometry. Liquid chromatography-tandem mass spectrometry-based quantification of biomarkers has gained more attention over other traditional techniques due to its higher sensitivity and selectivity. However, the primary challenge lies with this technique includes the unavailability of a blank matrix for method development. To overcome this challenge, different analytical approaches are being developed including surrogate analyte and surrogate matrix approach. Such approaches include quantification of biomarkers in a surrogate matrix or quantification of an isotopically labeled surrogate analyte in an authentic matrix. To demonstrate the authenticity of the surrogate approach, it is mandatory to establish quantitative parallelism through validation employing respective surrogate analytes and surrogate matrices. In this review, different bioanalytical approaches for biomarker quantification and recent advancements in the field aiming for improvement in the specificity of the techniques have been discussed. Liquid chromatography-tandem mass spectrometry-based surrogate approaches for biomarker quantification and significance of parallelism establishment in both surrogate matrix and surrogate analyte-based approaches have been critically discussed. In addition, different methods for demonstrating parallelism in the surrogate method have been explained.
Topics: Tandem Mass Spectrometry; Chromatography, Liquid; Biomarkers
PubMed: 35138951
DOI: 10.1080/10408347.2022.2035210 -
Annual Review of Analytical Chemistry... Jul 2021Field-flow fractionation (FFF) is a family of techniques that was created especially for separating and characterizing macromolecules, nanoparticles, and...
Field-flow fractionation (FFF) is a family of techniques that was created especially for separating and characterizing macromolecules, nanoparticles, and micrometer-sized analytes. It is coming of age as new nanomaterials, polymers, composites, and biohybrids with remarkable properties are introduced and new analytical challenges arise due to synthesis heterogeneities and the motivation to correlate analyte properties with observed performance. Appreciation of the complexity of biological, pharmaceutical, and food systems and the need to monitor multiple components across many size scales have also contributed to FFF's growth. This review highlights recent advances in FFF capabilities, instrumentation, and applications that feature the unique characteristics of different FFF techniques in determining a variety of information, such as averages and distributions in size, composition, shape, architecture, and microstructure and in investigating transformations and function.
PubMed: 33770457
DOI: 10.1146/annurev-anchem-091520-052742 -
Frontiers in Medicine 2021A main goal of Precision Medicine is that of incorporating and integrating the vast corpora on different databases about the molecular and environmental origins of... (Review)
Review
A main goal of Precision Medicine is that of incorporating and integrating the vast corpora on different databases about the molecular and environmental origins of disease, into analytic frameworks, allowing the development of individualized, context-dependent diagnostics, and therapeutic approaches. In this regard, artificial intelligence and machine learning approaches can be used to build analytical models of complex disease aimed at prediction of personalized health conditions and outcomes. Such models must handle the wide heterogeneity of individuals in both their genetic predisposition and their social and environmental determinants. Computational approaches to medicine need to be able to efficiently manage, visualize and integrate, large datasets combining structure, and unstructured formats. This needs to be done while constrained by different levels of confidentiality, ideally doing so within a unified analytical architecture. Efficient data integration and management is key to the successful application of computational intelligence approaches to medicine. A number of challenges arise in the design of successful designs to medical data analytics under currently demanding conditions of performance in personalized medicine, while also subject to time, computational power, and bioethical constraints. Here, we will review some of these constraints and discuss possible avenues to overcome current challenges.
PubMed: 35145977
DOI: 10.3389/fmed.2021.784455