ACS Measurement Science Au最新文献

Thermal cycling-based quantitative polymerase chain reaction (qPCR) represents the gold standard method for accurate and sensitive nucleic acid quantification in laboratory settings. However, its reliance on costly thermal cyclers limits the implementation of this technique for rapid point-of-care (POC) diagnostics. To address this, isothermal amplification techniques such as rolling circle amplification (RCA) have been developed, offering a simpler alternative that can operate without the need for sophisticated instrumentation. This study focuses on the development and optimization of toehold-mediated RCA (TRCA), which employs a conformationally switchable dumbbell DNA template for the sensitive and selective detection of cancer-associated miRNAs, specifically miR-21. In addition, we developed variants of hyperbranched TRCA (HTRCA), nicking-assisted TRCA (NTRCA), and hyperbranched NTRCA (HNTRCA) to facilitate exponential amplification by enhancing TRCA through the sequential incorporation of reverse primer (Pr) and nicking endonuclease (nE). By conducting a systematic kinetic analysis of the initial rate and end point signals for varying concentrations of key reaction components, we could identify optimal conditions that markedly enhanced the sensitivity and specificity of the TRCA variants. In particular, HNTRCA, which exploits the synergistic effect of Pr and nE, demonstrated an approximately 3000-fold improvement in the detection limit (260 fM) and a wider dynamic range of more than 4 log orders of magnitude compared to TRCA, thereby evidencing its superior performance. Also, we established a mechanistic model for TRCA that includes the roles of Pr and nE in different amplification processes. Model parameters were fitted to the experimental data, and additional simulations were conducted to compare the four amplification methods. Further tests with real biological samples revealed that this technique showed a good correlation with qPCR in quantifying miR-21 expression in various cell lines (0.9510 of Pearson's r), confirming its potential as a robust and rapid tool for nucleic acid detection. Therefore, the simplicity, high sensitivity, and potential for integration with POC diagnostic platforms make the HNTRCA system suitable for field deployment in resource-limited environments.

Thermal cycling-based quantitative polymerase chain reaction (qPCR) represents the gold standard method for accurate and sensitive nucleic acid quantification in laboratory settings. However, its reliance on costly thermal cyclers limits the implementation of this technique for rapid point-of-care (POC) diagnostics. To address this, isothermal amplification techniques such as rolling circle amplification (RCA) have been developed, offering a simpler alternative that can operate without the need for sophisticated instrumentation. This study focuses on the development and optimization of toehold-mediated RCA (TRCA), which employs a conformationally switchable dumbbell DNA template for the sensitive and selective detection of cancer-associated miRNAs, specifically miR-21. In addition, we developed variants of hyperbranched TRCA (HTRCA), nicking-assisted TRCA (NTRCA), and hyperbranched NTRCA (HNTRCA) to facilitate exponential amplification by enhancing TRCA through the sequential incorporation of reverse primer (Pr) and nicking endonuclease (nE). By conducting a systematic kinetic analysis of the initial rate and end point signals for varying concentrations of key reaction components, we could identify optimal conditions that markedly enhanced the sensitivity and specificity of the TRCA variants. In particular, HNTRCA, which exploits the synergistic effect of Pr and nE, demonstrated an approximately 3000-fold improvement in the detection limit (260 fM) and a wider dynamic range of more than 4 log orders of magnitude compared to TRCA, thereby evidencing its superior performance. Also, we established a mechanistic model for TRCA that includes the roles of Pr and nE in different amplification processes. Model parameters were fitted to the experimental data, and additional simulations were conducted to compare the four amplification methods. Further tests with real biological samples revealed that this technique showed a good correlation with qPCR in quantifying miR-21 expression in various cell lines (0.9510 of Pearson’s r), confirming its potential as a robust and rapid tool for nucleic acid detection. Therefore, the simplicity, high sensitivity, and potential for integration with POC diagnostic platforms make the HNTRCA system suitable for field deployment in resource-limited environments.

This research aims to develop a portable biosensor device for quickly detecting vWFA2, a biomarker for inflammatory conditions. This sensor could dramatically change detection methods and lead us to improve the sensitivity of our tests to overcome the limitations of conventional detection methods. Our label-free biomolecular assay is constructed on an Au-ZnO electrode surface and uses electrochemical impedance spectroscopy (EIS) to measure the capacitive change in impedance, revealing the binding effects of the target vWFA2, to the capture probe. Our developed biosensor platform exhibits greater sensitivity and specificity, covering a wide dynamic range of 750-24,000 pg/mL and showing a strong correlation with inflammatory conditions. This sensor exhibited a greater accuracy ranging from 86-110% for the known spiked concentrations in nondiluted or modified plasma samples. This electrochemical sensor has the potential to advance point-of-care diagnostic methods due to its high sensitivity and rapid response time. The vision behind this research is to develop an electrochemical sensor that can rapidly and accurately detect disease states, thus creating a pivotal prognostic tool in inflammatory state treatment and ultimately mitigating severe mortality and morbidity.

This research aims to develop a portable biosensor device for quickly detecting vWFA2, a biomarker for inflammatory conditions. This sensor could dramatically change detection methods and lead us to improve the sensitivity of our tests to overcome the limitations of conventional detection methods. Our label-free biomolecular assay is constructed on an Au-ZnO electrode surface and uses electrochemical impedance spectroscopy (EIS) to measure the capacitive change in impedance, revealing the binding effects of the target vWFA2, to the capture probe. Our developed biosensor platform exhibits greater sensitivity and specificity, covering a wide dynamic range of 750–24,000 pg/mL and showing a strong correlation with inflammatory conditions. This sensor exhibited a greater accuracy ranging from 86–110% for the known spiked concentrations in nondiluted or modified plasma samples. This electrochemical sensor has the potential to advance point-of-care diagnostic methods due to its high sensitivity and rapid response time. The vision behind this research is to develop an electrochemical sensor that can rapidly and accurately detect disease states, thus creating a pivotal prognostic tool in inflammatory state treatment and ultimately mitigating severe mortality and morbidity.

Per- and polyfluoroalkyl substances (PFAS) have become a major focus of research due to their widespread environmental presence and adverse health effects associated with human exposure. PFAS include legacy and emerging structures and are characterized by a range of functional groups and carbon-fluorine chains that vary in length (from fewer than 3 carbons to more than 7 carbons). Research has linked PFAS exposure to an array of health concerns, ranging from developmental and reproductive disorders to immune system impairments and an increased risk of certain cancers. In this new era of personalized health, measuring markers of PFAS exposure in human biospecimens is an important part of environmental public health surveillance. PFAS are typically measured in human blood and tissues using targeted approaches, which quantify individual PFAS structures using specific instrumentation. The diversity and complexity of PFAS, the limitations of the targeted approaches due to the sheer number of structures, and the absence of publicly available analytical standards pose significant challenges for measurement methodologies. This perspective aims to describe aggregate PFAS exposure measurements and their potential for use in precision medicine applications including a discussion of the limitations and potential benefits of these aggregate measurements. As public health organizations, healthcare professionals, and the public look for guidance regarding the safe use of and exposure to PFAS, in a pragmatic cost-effective manner, the dynamic field of measurement science is poised to respond with innovative technological solutions to an important public health need.

Per- and polyfluoroalkyl substances (PFAS) have become a major focus of research due to their widespread environmental presence and adverse health effects associated with human exposure. PFAS include legacy and emerging structures and are characterized by a range of functional groups and carbon–fluorine chains that vary in length (from fewer than 3 carbons to more than 7 carbons). Research has linked PFAS exposure to an array of health concerns, ranging from developmental and reproductive disorders to immune system impairments and an increased risk of certain cancers. In this new era of personalized health, measuring markers of PFAS exposure in human biospecimens is an important part of environmental public health surveillance. PFAS are typically measured in human blood and tissues using targeted approaches, which quantify individual PFAS structures using specific instrumentation. The diversity and complexity of PFAS, the limitations of the targeted approaches due to the sheer number of structures, and the absence of publicly available analytical standards pose significant challenges for measurement methodologies. This perspective aims to describe aggregate PFAS exposure measurements and their potential for use in precision medicine applications including a discussion of the limitations and potential benefits of these aggregate measurements. As public health organizations, healthcare professionals, and the public look for guidance regarding the safe use of and exposure to PFAS, in a pragmatic cost-effective manner, the dynamic field of measurement science is poised to respond with innovative technological solutions to an important public health need.

Ambient mass spectrometry (MS) technologies have been applied to spatial metabolomic profiling of various samples in an attempt to both increase analysis speed and reduce the length of sample preparation. Recent studies, however, have focused on improving the spatial resolution of ambient approaches. Finer resolution requires greater analysis times and commensurate computing power for more sophisticated data analysis algorithms and larger data sets. Higher resolution provides a more detailed molecular picture of the sample; however, for some applications, this is not required. A liquid microjunction surface sampling probe (LMJ-SSP) based MS platform combined with unsupervised multivariant analysis based hyperspectral visualization is demonstrated for the metabolomic analysis of marine bacteria from the genus Pseudoalteromonas to create a rapid and robust spatial profiling workflow for microbial natural product screening. In our study, metabolomic profiles of different Pseudoalteromonas species are quickly acquired without any sample preparation and distinguished by unsupervised multivariant analysis. Our robust platform is capable of automated direct sampling of microbes cultured on agar without clogging. Hyperspectral visualization-based rapid spatial profiling provides adequate spatial metabolite information on microbial samples through red–green–blue (RGB) color annotation. Both static and temporal metabolome differences can be visualized by straightforward color differences and differentiating m/z values identified afterward. Through this approach, novel analogues and their potential biosynthetic pathways are discovered by applying results from the spatial navigation to chromatography-based metabolome annotation. In this current research, LMJ-SSP is shown to be a robust and rapid spatial profiling method. Unsupervised multivariant analysis based hyperspectral visualization is proven straightforward for facile/rapid data interpretation. The combination of direct analysis and innovative data visualization forms a powerful tool to aid the identification/interpretation of interesting compounds from conventional metabolomics analysis.

Plasmon-enhanced infrared (IR) techniques have garnered significant interest for their ability to achieve greatly more sensitive IR detection than conventional surface enhanced IR techniques. However, the difficulty in electrically connecting antennas has limited their application in IR spectroelectrochemistry, a crucial field for catalysis, analysis, and energy storage. Recent technical advancements have enabled the successful application of electrochemical potentials to antennas, making plasmon-enhanced IR spectroelectrochemistry feasible. This perspective aims to summarize the latest strategies and offer insights into future improvements for better design of plasmon enhanced IR spectroelectrochemistry platforms and understanding of IR spectroelectrochemistry.

Ambient mass spectrometry (MS) technologies have been applied to spatial metabolomic profiling of various samples in an attempt to both increase analysis speed and reduce the length of sample preparation. Recent studies, however, have focused on improving the spatial resolution of ambient approaches. Finer resolution requires greater analysis times and commensurate computing power for more sophisticated data analysis algorithms and larger data sets. Higher resolution provides a more detailed molecular picture of the sample; however, for some applications, this is not required. A liquid microjunction surface sampling probe (LMJ-SSP) based MS platform combined with unsupervised multivariant analysis based hyperspectral visualization is demonstrated for the metabolomic analysis of marine bacteria from the genus Pseudoalteromonas to create a rapid and robust spatial profiling workflow for microbial natural product screening. In our study, metabolomic profiles of different Pseudoalteromonas species are quickly acquired without any sample preparation and distinguished by unsupervised multivariant analysis. Our robust platform is capable of automated direct sampling of microbes cultured on agar without clogging. Hyperspectral visualization-based rapid spatial profiling provides adequate spatial metabolite information on microbial samples through red-green-blue (RGB) color annotation. Both static and temporal metabolome differences can be visualized by straightforward color differences and differentiating m/z values identified afterward. Through this approach, novel analogues and their potential biosynthetic pathways are discovered by applying results from the spatial navigation to chromatography-based metabolome annotation. In this current research, LMJ-SSP is shown to be a robust and rapid spatial profiling method. Unsupervised multivariant analysis based hyperspectral visualization is proven straightforward for facile/rapid data interpretation. The combination of direct analysis and innovative data visualization forms a powerful tool to aid the identification/interpretation of interesting compounds from conventional metabolomics analysis.

Plasmon-enhanced infrared (IR) techniques have garnered significant interest for their ability to achieve greatly more sensitive IR detection than conventional surface enhanced IR techniques. However, the difficulty in electrically connecting antennas has limited their application in IR spectroelectrochemistry, a crucial field for catalysis, analysis, and energy storage. Recent technical advancements have enabled the successful application of electrochemical potentials to antennas, making plasmon-enhanced IR spectroelectrochemistry feasible. This perspective aims to summarize the latest strategies and offer insights into future improvements for better design of plasmon enhanced IR spectroelectrochemistry platforms and understanding of IR spectroelectrochemistry.