G. Thomas Knecht,Maxwell J. Unger,Alison R. H. Narayan,Robert T. Kennedy
Droplet microfluidics has become a versatile tool for high-throughput phenotypic analysis of cells, employed in enzyme engineering, drug screening, and antibiotic assays. An important metric in such bioanalyses is the optical density (OD600) of the culture, but current methods for measuring OD600 within cultured droplets are limited. Herein, we present a machine-vision method for the measurement of OD600 between 0.1 and 4.3 in flowing microdroplets from 0.5–50 nL in volume. This system can make real-time decisions based on cell density and volume measurements and was demonstrated to remove vacant droplets from an emulsion by dielectrophoretic sorting at up to 10 droplets per s based on cell density with an error rate below 10%. We show that droplets can also be subjected to subsequent on-line analysis such as mass spectrometry (MS) and their growth levels correlated to metabolite abundances. We show that growth level is correlated with lysine abundance in droplets incubated with engineered E. coli cells.
{"title":"Machine vision-enabled OD measurement and mass spectrometric determination of metabolites of microbial cell-containing microfluidic droplets in real-time","authors":"G. Thomas Knecht,Maxwell J. Unger,Alison R. H. Narayan,Robert T. Kennedy","doi":"10.1039/d6an00623j","DOIUrl":"https://doi.org/10.1039/d6an00623j","url":null,"abstract":"Droplet microfluidics has become a versatile tool for high-throughput phenotypic analysis of cells, employed in enzyme engineering, drug screening, and antibiotic assays. An important metric in such bioanalyses is the optical density (OD600) of the culture, but current methods for measuring OD600 within cultured droplets are limited. Herein, we present a machine-vision method for the measurement of OD600 between 0.1 and 4.3 in flowing microdroplets from 0.5–50 nL in volume. This system can make real-time decisions based on cell density and volume measurements and was demonstrated to remove vacant droplets from an emulsion by dielectrophoretic sorting at up to 10 droplets per s based on cell density with an error rate below 10%. We show that droplets can also be subjected to subsequent on-line analysis such as mass spectrometry (MS) and their growth levels correlated to metabolite abundances. We show that growth level is correlated with lysine abundance in droplets incubated with engineered E. coli cells.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"101 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149027590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Polypropylene glycol 1000 (PPG1000) is a hydrophilic polymer widely used in pharmaceuticals and industry, but quantifying it in complex biological samples remains challenging. This study develops and validates a sensitive UPLC-MS/MS method for PPG1000 measurement in zebrafish tissues. The method combines micro-solid-phase extraction (μ-SPE) cleanup with a 2.5 min chromatographic run and MS³ detection for PPG1000-equivalent quantification in zebrafish tissues. We systematically compared three mass spectrometric acquisition modes: multiple reaction monitoring (MRM), MS³, and in-source collision-induced dissociation (CID). The ammonium adduct [M+NH₄]⁺ of the 15-mer oligomer (m/z 906.6) served as the precursor ion. MS³ using a linear ion trap (m/z 906.6 → 175.1 → 117.1) delivered the highest signal intensity (3.6×10⁶ cps), approximately 3.3-fold and 40-fold higher than MRM and CID respectively. Integrating μ-SPE further improved method performance over conventional protein precipitation. The method showed excellent linearity (100 to 10000 ng/mL, r > 0.997) and was applied to zebrafish tissue distribution after aqueous exposure to 200 μg/mL PPG1000. All three tissues (gill, liver, brain) exhibited increasing concentrations from 2 to 4 h, with gill showing the highest accumulation. Detectable brain levels suggest partial blood brain barrier penetration. This work provides the first systematic comparison of MRM, MS³, and in-source CID for PPG quantification, establishing a sensitive analytical platform with complementary greenness and practical applicability assessments using AGREE, AGSA, CACI, and GEMAM, for polymer bioanalysis in complex matrices.
{"title":"MS³ acquisition and μ-SPE cleanup enable sensitive quantification of PPG1000 in zebrafish tissues: Systematic comparison with MRM and in-source CID strategies","authors":"Jiarui Zhang,Zichang Tian,Jinqing Wu,Jiale Liu,Xinyue Zhou,Yue Deng,Shuang Feng,Jing Peng,Lei Yin,Linquan Li","doi":"10.1039/d6an00734a","DOIUrl":"https://doi.org/10.1039/d6an00734a","url":null,"abstract":"Polypropylene glycol 1000 (PPG1000) is a hydrophilic polymer widely used in pharmaceuticals and industry, but quantifying it in complex biological samples remains challenging. This study develops and validates a sensitive UPLC-MS/MS method for PPG1000 measurement in zebrafish tissues. The method combines micro-solid-phase extraction (μ-SPE) cleanup with a 2.5 min chromatographic run and MS³ detection for PPG1000-equivalent quantification in zebrafish tissues. We systematically compared three mass spectrometric acquisition modes: multiple reaction monitoring (MRM), MS³, and in-source collision-induced dissociation (CID). The ammonium adduct [M+NH₄]⁺ of the 15-mer oligomer (m/z 906.6) served as the precursor ion. MS³ using a linear ion trap (m/z 906.6 → 175.1 → 117.1) delivered the highest signal intensity (3.6×10⁶ cps), approximately 3.3-fold and 40-fold higher than MRM and CID respectively. Integrating μ-SPE further improved method performance over conventional protein precipitation. The method showed excellent linearity (100 to 10000 ng/mL, r > 0.997) and was applied to zebrafish tissue distribution after aqueous exposure to 200 μg/mL PPG1000. All three tissues (gill, liver, brain) exhibited increasing concentrations from 2 to 4 h, with gill showing the highest accumulation. Detectable brain levels suggest partial blood brain barrier penetration. This work provides the first systematic comparison of MRM, MS³, and in-source CID for PPG quantification, establishing a sensitive analytical platform with complementary greenness and practical applicability assessments using AGREE, AGSA, CACI, and GEMAM, for polymer bioanalysis in complex matrices.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"226 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149027586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bacteraemia is a life-threatening infection associated with substantial morbidity and mortality. Current diagnosis relies on blood culture followed by culture-based identification and antimicrobial susceptibility testing, which remain the clinical gold standard but require prolonged turnaround times. Isothermal amplification technologies such as loop-mediated isothermal amplification (LAMP) offer a rapid, cost-effective, and accessible alternative for pathogen identification and antimicrobial resistance detection directly from positive blood cultures, particularly in resource-limited settings. However, their widespread implementation remains constrained by sample preparation requirements and limited multiplexing capabilities. To address these challenges, we developed ALADIM (Accessible and integrated LAMP Analysis for multiplex Detection of Infectious agents in Microfluidics), an integrated microfluidic platform combining bacterial DNA extraction, multiplex on-chip LAMP amplification, and instrument-free amplicon detection by lateral flow immunoassay (LFIA). The complete workflow can be performed in less than two hours, compared with the 24-48 h typically required for conventional diagnostic methods. As a proof of concept, the system was designed to detect E. coli, the most frequently reported pathogen in bacteraemia, together with two clinically relevant antimicrobial resistance determinants, blaCTX-M-15 and blaOXA-48, as well as an internal positive control. The multiplex assay was first evaluated using 14 bacterial strains cultured in LB medium. Performance of the on-chip workflow was comparable to that of the reference method consisting of conventional tube-based LAMP followed by LFIA detection, achieving 100% sensitivity and >84% specificity for malF and blaOXA-48, and 68% sensitivity with 83% specificity for blaCTX-M-15. The complete ALADIM workflow was subsequently assessed using overnight positive blood cultures generated from 15 PCR-characterised strains, corresponding to 61 independent experiments encompassing sample preparation, DNA amplification, and LFIA readout. In this more challenging matrix, specificity remained above 77% for all targets. Sensitivity exceeded 94% for malF and blaOXA-48, whereas detection of blaCTX-M-15 showed lower sensitivity (56%). A comparable reduction in sensitivity was also observed with the reference in-tube method (>68%), underscoring the analytical challenges associated with direct analysis of blood culture-derived samples. Overall, this study demonstrates the feasibility of integrating sample preparation, multiplex nucleic acid amplification, microfluidic handling, and lateral-flow-based detection within a single user-friendly platform. While further optimization is required to improve performance in complex matrices, increase analytical sensitivity, and expand multiplexing capabilities, ALADIM provides a promising foundation for the development of accessible molecular diagnostics for bloodstream infect
{"title":"Simplified bacterial identification and antimicrobial resistance detection in bacteraemia by on-chip multiplexed LAMP from blood cultures","authors":"Capucine Treille,Lilas Pommiès,Xenia Garcia Velasquez,Hervé Volland,Karla Perez-Toralla,Hervé Boutal","doi":"10.1039/d5an01310k","DOIUrl":"https://doi.org/10.1039/d5an01310k","url":null,"abstract":"Bacteraemia is a life-threatening infection associated with substantial morbidity and mortality. Current diagnosis relies on blood culture followed by culture-based identification and antimicrobial susceptibility testing, which remain the clinical gold standard but require prolonged turnaround times. Isothermal amplification technologies such as loop-mediated isothermal amplification (LAMP) offer a rapid, cost-effective, and accessible alternative for pathogen identification and antimicrobial resistance detection directly from positive blood cultures, particularly in resource-limited settings. However, their widespread implementation remains constrained by sample preparation requirements and limited multiplexing capabilities. To address these challenges, we developed ALADIM (Accessible and integrated LAMP Analysis for multiplex Detection of Infectious agents in Microfluidics), an integrated microfluidic platform combining bacterial DNA extraction, multiplex on-chip LAMP amplification, and instrument-free amplicon detection by lateral flow immunoassay (LFIA). The complete workflow can be performed in less than two hours, compared with the 24-48 h typically required for conventional diagnostic methods. As a proof of concept, the system was designed to detect E. coli, the most frequently reported pathogen in bacteraemia, together with two clinically relevant antimicrobial resistance determinants, blaCTX-M-15 and blaOXA-48, as well as an internal positive control. The multiplex assay was first evaluated using 14 bacterial strains cultured in LB medium. Performance of the on-chip workflow was comparable to that of the reference method consisting of conventional tube-based LAMP followed by LFIA detection, achieving 100% sensitivity and >84% specificity for malF and blaOXA-48, and 68% sensitivity with 83% specificity for blaCTX-M-15. The complete ALADIM workflow was subsequently assessed using overnight positive blood cultures generated from 15 PCR-characterised strains, corresponding to 61 independent experiments encompassing sample preparation, DNA amplification, and LFIA readout. In this more challenging matrix, specificity remained above 77% for all targets. Sensitivity exceeded 94% for malF and blaOXA-48, whereas detection of blaCTX-M-15 showed lower sensitivity (56%). A comparable reduction in sensitivity was also observed with the reference in-tube method (>68%), underscoring the analytical challenges associated with direct analysis of blood culture-derived samples. Overall, this study demonstrates the feasibility of integrating sample preparation, multiplex nucleic acid amplification, microfluidic handling, and lateral-flow-based detection within a single user-friendly platform. While further optimization is required to improve performance in complex matrices, increase analytical sensitivity, and expand multiplexing capabilities, ALADIM provides a promising foundation for the development of accessible molecular diagnostics for bloodstream infect","PeriodicalId":63,"journal":{"name":"Analyst","volume":"7 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149013577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kana Matsuoka,Masahiro Ando,Takuji Nakashima,Haruko Takeyama
Liquid chromatography (LC) has been the gold standard for analyzing complex biological samples, yet conventional detection methods present analytical challenges. Mass spectrometry requires expensive instrumentation and struggles with structural isomers. UV and fluorescence detection necessitate derivatization for compounds lacking chromophores, extending analysis time and potentially altering labile compounds or masking structural modifications. Raman spectroscopy offers fundamentally different detection principles that could address these challenges by directly probing molecular vibrations to provide structural information independent of UV absorption. However, the primary obstacle to LC-Raman implementation has been Raman spectroscopy's inherently weak scattering signal. This study addresses these fundamental challenges through a simple yet effective approach using a newly developed system combining post-column spotting with solvent evaporation. By transforming dilute liquid samples into concentrated solid deposits, this method dramatically enhances Raman signals while simultaneously eliminating solvent interference. The approach was applied to comprehensive amino acid analysis, which is essential for evaluating complex biological matrices. The LC-Raman system achieved remarkable sensitivity with signal-to-noise ratios above 10 at 20 ng injection level, demonstrating that solvent evaporation and solid-state concentration effectively overcome traditional sensitivity limitations. All 20 proteinogenic amino acids were detected without derivatization regardless of chromophore presence. Beyond sensitivity improvements, the system provides direct structural identification through vibrational spectroscopy. Lysine and its post-translational modifications (Nε-acetyl-lysine and Nε,Nε,Nε-trimethyllysine) were clearly discriminated through diagnostic vibrational bands. This demonstrates a distinct advantage of the Raman-based approach: direct molecular identification through intrinsic vibrational fingerprints without requiring fragmentation or derivatization, providing complementary information to existing methods. Analysis of DMEM cell culture medium identified eight major amino acids, and multivariate curve resolution successfully extracted pure component spectra for co-eluting leucine, isoleucine, and glucose, adding a chemical dimension to chromatographic separation. Furthermore, phenylalanine and glutamine in the cell culture medium were determined via LC-Raman spectroscopy. This study establishes LC-Raman spectroscopy as a powerful analytical tool that successfully addresses historical sensitivity limitations while preserving unique molecular identification capabilities. The approach's applicability extends beyond amino acids to any LC-amenable compounds with sufficient Raman activity, opening new possibilities for pharmaceutical, clinical, and biotechnology applications where structural specificity and label-free analysis are essential.
{"title":"Sensitive and derivatization-free amino acid analysis using liquid chromatography-Raman spectroscopy","authors":"Kana Matsuoka,Masahiro Ando,Takuji Nakashima,Haruko Takeyama","doi":"10.1039/d6an00841k","DOIUrl":"https://doi.org/10.1039/d6an00841k","url":null,"abstract":" Liquid chromatography (LC) has been the gold standard for analyzing complex biological samples, yet conventional detection methods present analytical challenges. Mass spectrometry requires expensive instrumentation and struggles with structural isomers. UV and fluorescence detection necessitate derivatization for compounds lacking chromophores, extending analysis time and potentially altering labile compounds or masking structural modifications. Raman spectroscopy offers fundamentally different detection principles that could address these challenges by directly probing molecular vibrations to provide structural information independent of UV absorption. However, the primary obstacle to LC-Raman implementation has been Raman spectroscopy's inherently weak scattering signal. This study addresses these fundamental challenges through a simple yet effective approach using a newly developed system combining post-column spotting with solvent evaporation. By transforming dilute liquid samples into concentrated solid deposits, this method dramatically enhances Raman signals while simultaneously eliminating solvent interference. The approach was applied to comprehensive amino acid analysis, which is essential for evaluating complex biological matrices. The LC-Raman system achieved remarkable sensitivity with signal-to-noise ratios above 10 at 20 ng injection level, demonstrating that solvent evaporation and solid-state concentration effectively overcome traditional sensitivity limitations. All 20 proteinogenic amino acids were detected without derivatization regardless of chromophore presence. Beyond sensitivity improvements, the system provides direct structural identification through vibrational spectroscopy. Lysine and its post-translational modifications (Nε-acetyl-lysine and Nε,Nε,Nε-trimethyllysine) were clearly discriminated through diagnostic vibrational bands. This demonstrates a distinct advantage of the Raman-based approach: direct molecular identification through intrinsic vibrational fingerprints without requiring fragmentation or derivatization, providing complementary information to existing methods. Analysis of DMEM cell culture medium identified eight major amino acids, and multivariate curve resolution successfully extracted pure component spectra for co-eluting leucine, isoleucine, and glucose, adding a chemical dimension to chromatographic separation. Furthermore, phenylalanine and glutamine in the cell culture medium were determined via LC-Raman spectroscopy. This study establishes LC-Raman spectroscopy as a powerful analytical tool that successfully addresses historical sensitivity limitations while preserving unique molecular identification capabilities. The approach's applicability extends beyond amino acids to any LC-amenable compounds with sufficient Raman activity, opening new possibilities for pharmaceutical, clinical, and biotechnology applications where structural specificity and label-free analysis are essential.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"47 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149013578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Meng Deng,Hao Guo,Zeyun Yang,Ruixue Yan,Jianpeng Ma,Wenting Niu,Yujiao Kang,Mingyue Wang,Wu Yang
Rutin (RT), a crucial flavonoid compound, exhibits significant physiological activities and medicinal value through its anti-tumor, anti-oxidation, and anti-inflammation effects, and cardiovascular protection. It is of great significance to develop an efficient and sensitive detection method for rutin. To achieve sensitive and rapid detection of rutin, this study constructs a novel composite-material electrochemical sensing platform based on a highly crystalline covalent organic framework (A-COF). The A-COF@NH2-MWCNT/GCE electrochemical sensor was successfully fabricated by preparing an in situ grown A-COF@NH2-MWCNT composite material to modify a glassy carbon electrode (GCE). Under the optimized experimental conditions, the electrochemical response of the sensor to rutin was investigated using the CV method and the DPV method. The results indicate that the constructed sensor exhibits satisfactory electrochemical characteristics, with a detection limit of 0.01 μM (S/N = 3) and a linear range of 0.2–170 μM. It also demonstrates good repeatability, reproducibility, stability, and anti-interference ability. The sensor was applied to detect rutin content in actual samples (human serum, urine, rutin tablets and buckwheat), and the results were accurate and reliable, with high recovery rates. This study offers a novel, simple and efficient electrochemical detection method for the trace analysis of rutin.
{"title":"A novel electrochemical sensing platform based on highly crystalline covalent organic frameworks for the sensitive detection of rutin","authors":"Meng Deng,Hao Guo,Zeyun Yang,Ruixue Yan,Jianpeng Ma,Wenting Niu,Yujiao Kang,Mingyue Wang,Wu Yang","doi":"10.1039/d6an00698a","DOIUrl":"https://doi.org/10.1039/d6an00698a","url":null,"abstract":"Rutin (RT), a crucial flavonoid compound, exhibits significant physiological activities and medicinal value through its anti-tumor, anti-oxidation, and anti-inflammation effects, and cardiovascular protection. It is of great significance to develop an efficient and sensitive detection method for rutin. To achieve sensitive and rapid detection of rutin, this study constructs a novel composite-material electrochemical sensing platform based on a highly crystalline covalent organic framework (A-COF). The A-COF@NH2-MWCNT/GCE electrochemical sensor was successfully fabricated by preparing an in situ grown A-COF@NH2-MWCNT composite material to modify a glassy carbon electrode (GCE). Under the optimized experimental conditions, the electrochemical response of the sensor to rutin was investigated using the CV method and the DPV method. The results indicate that the constructed sensor exhibits satisfactory electrochemical characteristics, with a detection limit of 0.01 μM (S/N = 3) and a linear range of 0.2–170 μM. It also demonstrates good repeatability, reproducibility, stability, and anti-interference ability. The sensor was applied to detect rutin content in actual samples (human serum, urine, rutin tablets and buckwheat), and the results were accurate and reliable, with high recovery rates. This study offers a novel, simple and efficient electrochemical detection method for the trace analysis of rutin.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"32 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149010187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Liu Zhao,Haiyun Yang,Xin Zhu,Wenhong Che,Qiuyu Meng,Lu Yang,Chunmei Yang
Computed tomography (CT) represents one of the most widely utilized and clinically effective imaging techniques for gastrointestinal diseases. Specifically, spectral CT, as an advanced evolution of conventional CT, has significantly improved diagnostic accuracy. The creation of high-performance and biocompatible contrast agents is essential for achieving superior visualization of the gastrointestinal tract and facilitating accurate disease identification. Recent studies reveal that small molecule- and nanoparticle-based contrast agents with high atomic number elements demonstrate significant promise in gastrointestinal diagnostics via spectral CT imaging. Therefore, this review systematically discusses the synthesis, characteristics and advantages of small molecule- and nanoparticle-based contrast agents, with emphasis on their utility in gastrointestinal imaging, disease diagnosis, and therapeutic interventions. Furthermore, the limitations and future directions of current contrast agents are also evaluated, offering a foundation for the design of novel gastrointestinal spectral CT contrast agents.
{"title":"Recent advances in spectral CT contrast agents for gastrointestinal tract imaging","authors":"Liu Zhao,Haiyun Yang,Xin Zhu,Wenhong Che,Qiuyu Meng,Lu Yang,Chunmei Yang","doi":"10.1039/d6an00572a","DOIUrl":"https://doi.org/10.1039/d6an00572a","url":null,"abstract":"Computed tomography (CT) represents one of the most widely utilized and clinically effective imaging techniques for gastrointestinal diseases. Specifically, spectral CT, as an advanced evolution of conventional CT, has significantly improved diagnostic accuracy. The creation of high-performance and biocompatible contrast agents is essential for achieving superior visualization of the gastrointestinal tract and facilitating accurate disease identification. Recent studies reveal that small molecule- and nanoparticle-based contrast agents with high atomic number elements demonstrate significant promise in gastrointestinal diagnostics via spectral CT imaging. Therefore, this review systematically discusses the synthesis, characteristics and advantages of small molecule- and nanoparticle-based contrast agents, with emphasis on their utility in gastrointestinal imaging, disease diagnosis, and therapeutic interventions. Furthermore, the limitations and future directions of current contrast agents are also evaluated, offering a foundation for the design of novel gastrointestinal spectral CT contrast agents.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"15 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149010188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Patricia Gimenez Barrera,Anne Michelin,Aurélie Tournié,Kaoutar El Haloui,Tsveta Miteva,Emeline Pouyet
Neural networks are increasingly used in conservation science to exploit hyperspectral imaging (HSI) datasets. The literature includes a wide range of models with different architectures and hyperparameters available to the community. Yet, defining the optimal configurations of such parameters for new datasets is not straightforward. This work focuses on state-of-the-art optimization strategies to ensure that the best performance of the models is achieved, offering new opportunities for improving the predictive capacity of the model on unseen data. In particular, a synthetic mixture dataset is designed to train two widely-used neural network models: a 1D-CNN and a fully connected deep neural network (FC-DNN). The two models with architecture and hyperparameters taken directly from the literature are compared with optimized models using Bayesian approaches that combine Neural Architecture Search (NAS) and hyperparameter optimization (HPO). Full optimization of both the architecture and the hyperparameters of the neural network have proven to improve significantly the pigment classification accuracy, enabling more reliable pigment mapping from reflectance imaging spectroscopy (RIS) data. Optimized 1D-CNN and FC-DNN present similar capabilities for multilabel pigment classification of artistic materials, as shown through a representative case study on medieval illumination mock-ups.
{"title":"Deep neural network optimization for pigment classification: a case study on representative medieval illumination mock-ups","authors":"Patricia Gimenez Barrera,Anne Michelin,Aurélie Tournié,Kaoutar El Haloui,Tsveta Miteva,Emeline Pouyet","doi":"10.1039/d6an00787b","DOIUrl":"https://doi.org/10.1039/d6an00787b","url":null,"abstract":"Neural networks are increasingly used in conservation science to exploit hyperspectral imaging (HSI) datasets. The literature includes a wide range of models with different architectures and hyperparameters available to the community. Yet, defining the optimal configurations of such parameters for new datasets is not straightforward. This work focuses on state-of-the-art optimization strategies to ensure that the best performance of the models is achieved, offering new opportunities for improving the predictive capacity of the model on unseen data. In particular, a synthetic mixture dataset is designed to train two widely-used neural network models: a 1D-CNN and a fully connected deep neural network (FC-DNN). The two models with architecture and hyperparameters taken directly from the literature are compared with optimized models using Bayesian approaches that combine Neural Architecture Search (NAS) and hyperparameter optimization (HPO). Full optimization of both the architecture and the hyperparameters of the neural network have proven to improve significantly the pigment classification accuracy, enabling more reliable pigment mapping from reflectance imaging spectroscopy (RIS) data. Optimized 1D-CNN and FC-DNN present similar capabilities for multilabel pigment classification of artistic materials, as shown through a representative case study on medieval illumination mock-ups.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"13 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148993853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The typical off-flavor compound 2-methylisoborneol (2-MIB) is widely present in water bodies which induces unpleasant odors in water even at extremely low concentrations. It is urgent to develop a simplified laboratory-based electrochemical screening workflow for trace 2-MIB quantification since the traditional detection techniques are time-consuming and require complex pretreatment procedures. This study developed an innovative molecularly imprinted electrochemical sensor by using multi-walled carbon nanotubes (MWCNTs), molecularly imprinted polymers (MIPs), and a glassy carbon electrode (GCE) to detect trace 2-MIB in water. The sensor enabled highly specific capture of 2-MIB relying on the distinctive recognition cavities of MIPs. The theoretical saturated adsorption capacity extrapolated via the Langmuir model was calculated to be 6742 μg g−1. Systematic optimization was performed to achieve the best detection performance. The sensor exhibited a good linear response toward 2-MIB in the range of 25–200 ng L−1 under optimal conditions with a regression equation of ΔI (μA) = 0.34C + 2.1 and a correlation coefficient R2 = 0.9972. The method detection limit for 2-MIB reached 1.6 ng L−1, providing a screening strategy for trace 2-MIB in environmental water samples. The MWCNTs@DMIPs/GCE sensor showed good selectivity, reproducibility, and stability with satisfactory recoveries of 2-MIB ranging from 92.1% to 100.4% in different water samples. These findings of this study provide a feasible electrochemical screening technique for trace off-flavor substance detection.
典型的恶臭化合物2-甲基异冰片醇（2-MIB）广泛存在于水体中，即使在极低浓度下也会引起水中的难闻气味。由于传统的检测技术耗时且需要复杂的预处理程序，因此迫切需要开发一种简化的基于实验室的痕量2-MIB定量电化学筛选工作流程。本研究利用多壁碳纳米管（MWCNTs）、分子印迹聚合物（MIPs）和玻璃碳电极（GCE）开发了一种创新的分子印迹电化学传感器，用于检测水中痕量的2-MIB。该传感器依靠MIPs的独特识别空腔实现了对2-MIB的高度特异性捕获。通过Langmuir模型外推的理论饱和吸附容量为6742 μg−1。为了达到最佳的检测性能，进行了系统优化。在最优条件下，传感器对2-MIB在25 ~ 200 ng L−1范围内具有良好的线性响应，回归方程为ΔI (μA) = 0.34C + 2.1，相关系数R2 = 0.9972。该方法对2-MIB的检出限达到1.6 ng L−1，为环境水样中痕量2-MIB的筛选提供了一种策略。MWCNTs@DMIPs/GCE传感器在不同水样中具有良好的选择性、重复性和稳定性，2-MIB的回收率在92.1% ~ 100.4%之间。本研究结果为痕量异味物质的电化学筛选提供了一种可行的方法。
{"title":"An MWCNT-based dummy-template molecularly imprinted electrochemical sensor for detecting 2-methylisoborneol in water","authors":"Haowen Hong,Jun Wu,Jian Lu","doi":"10.1039/d6an00668j","DOIUrl":"https://doi.org/10.1039/d6an00668j","url":null,"abstract":"The typical off-flavor compound 2-methylisoborneol (2-MIB) is widely present in water bodies which induces unpleasant odors in water even at extremely low concentrations. It is urgent to develop a simplified laboratory-based electrochemical screening workflow for trace 2-MIB quantification since the traditional detection techniques are time-consuming and require complex pretreatment procedures. This study developed an innovative molecularly imprinted electrochemical sensor by using multi-walled carbon nanotubes (MWCNTs), molecularly imprinted polymers (MIPs), and a glassy carbon electrode (GCE) to detect trace 2-MIB in water. The sensor enabled highly specific capture of 2-MIB relying on the distinctive recognition cavities of MIPs. The theoretical saturated adsorption capacity extrapolated via the Langmuir model was calculated to be 6742 μg g−1. Systematic optimization was performed to achieve the best detection performance. The sensor exhibited a good linear response toward 2-MIB in the range of 25–200 ng L−1 under optimal conditions with a regression equation of ΔI (μA) = 0.34C + 2.1 and a correlation coefficient R2 = 0.9972. The method detection limit for 2-MIB reached 1.6 ng L−1, providing a screening strategy for trace 2-MIB in environmental water samples. The MWCNTs@DMIPs/GCE sensor showed good selectivity, reproducibility, and stability with satisfactory recoveries of 2-MIB ranging from 92.1% to 100.4% in different water samples. These findings of this study provide a feasible electrochemical screening technique for trace off-flavor substance detection.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"16 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148993854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chi Zhang,Seohee Ma,Mingmin Zhou,Laura L Lukov,Nikta Zafarjafarzadeh
Optical methods enable minimally invasive analysis of chemical distributions and dynamics in biological specimens. Many optical imaging modalities have been developed to generate chemical contrast based on intrinsic molecular signatures or highly specific labeling. Coherent Raman scattering (CRS) microscopy has emerged as a powerful label-free technique for imaging biomolecules or exogenous compounds in biological samples. Most CRS imaging studies have focused on extracting chemical distribution, composition, and abundance in samples, and work in these areas has been extensively reviewed. However, an important aspect of chemical processes—the dynamics of chemical changes over time—has received less emphasis in CRS microscopy. Many critical insights into chemical processes lie in the spatiotemporal evolution of molecular species in live samples. Such information can only be obtained through live-cell imaging, and more importantly, longitudinal imaging of the same sample over time. In this review, we focus on key parameters related to longitudinal live-cell CRS microscopy and major recent studies. We first discuss three primary factors that must be considered for longitudinal CRS imaging: limit of detection, chemical selectivity, and phototoxicity. Limit of detection and chemical selectivity determine what CRS can measure, whereas phototoxicity dictates whether longitudinal imaging can capture meaningful cellular chemical dynamics with minimal perturbation to biological functions. In these discussions, we also provide critical comparisons between CRS microscopy and fluorescence microscopy. We then review recent developments and achievements in longitudinal CRS microscopy. Finally, we provide perspectives on future directions and areas where longitudinal CRS microscopy can make contributions to advancing our understanding of biological processes.
{"title":"Longitudinal Live-Cell Chemical Imaging Using Coherent Raman Scattering Microscopy","authors":"Chi Zhang,Seohee Ma,Mingmin Zhou,Laura L Lukov,Nikta Zafarjafarzadeh","doi":"10.1039/d6an00802j","DOIUrl":"https://doi.org/10.1039/d6an00802j","url":null,"abstract":"Optical methods enable minimally invasive analysis of chemical distributions and dynamics in biological specimens. Many optical imaging modalities have been developed to generate chemical contrast based on intrinsic molecular signatures or highly specific labeling. Coherent Raman scattering (CRS) microscopy has emerged as a powerful label-free technique for imaging biomolecules or exogenous compounds in biological samples. Most CRS imaging studies have focused on extracting chemical distribution, composition, and abundance in samples, and work in these areas has been extensively reviewed. However, an important aspect of chemical processes—the dynamics of chemical changes over time—has received less emphasis in CRS microscopy. Many critical insights into chemical processes lie in the spatiotemporal evolution of molecular species in live samples. Such information can only be obtained through live-cell imaging, and more importantly, longitudinal imaging of the same sample over time. In this review, we focus on key parameters related to longitudinal live-cell CRS microscopy and major recent studies. We first discuss three primary factors that must be considered for longitudinal CRS imaging: limit of detection, chemical selectivity, and phototoxicity. Limit of detection and chemical selectivity determine what CRS can measure, whereas phototoxicity dictates whether longitudinal imaging can capture meaningful cellular chemical dynamics with minimal perturbation to biological functions. In these discussions, we also provide critical comparisons between CRS microscopy and fluorescence microscopy. We then review recent developments and achievements in longitudinal CRS microscopy. Finally, we provide perspectives on future directions and areas where longitudinal CRS microscopy can make contributions to advancing our understanding of biological processes.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"58 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148980639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bakr Ahmed Taha,Ali J. Addie,Khalid Hassan Ibnouf,Majid S. Jabir,Omar Talal Mahmood,R. Apsari,Norhana Arsad
Continuous physiological monitoring is a prerequisite in medicine that enables early disease detection, long-term health monitoring, and individualized therapeutic interventions. Although wearable optical biosensors have evolved significantly, their long-term clinical deployment remains limited by mechanical degradation, signal drift, biofouling, energy constraints, and poor integration with intelligent healthcare infrastructure. These issues are especially acute in the aged and disabled, when constant, dependable, and tailored monitoring is critical for proactive disease treatment. As a result, next-generation sensing technologies must progress beyond passive data collection toward self-adaptive systems capable of maintaining analytical accuracy while supporting patient-specific clinical interpretation and clinician-supervised decision-making. This perspective presents an overview of self-adaptive nanophotonic metasurfaces as the sensing foundation for Living Digital Twins (LDTs) in personalized healthcare. To create an intelligent sensing ecosystem, the proposed framework combines flexible plasmonic, localized surface plasmon resonance (LSPR), surface-enhanced Raman scattering (SERS), artificial intelligence, internet of nano things (IoNT) connectivity, and individualized digital twin analytics. The proposed framework combines continuous multimodal biomarker sensing with patient-specific physiological modelling to support longitudinal updating of digital representations. Edge intelligence enables low-latency signal processing, while adaptive analytics may improve sensing stability, calibration, and patient-specific interpretation. The integration of adaptive nanophotonic sensing with digital twins therefore represents a prospective approach for supporting early identification of physiological deterioration, individualized risk assessment, and clinician-supervised treatment planning in aging and disabled populations.
{"title":"Self-Adaptive Nanophotonic Metasurfaces Enabling Digital Twins: Toward Continuous Personalized Healthcare in Aging and Disability","authors":"Bakr Ahmed Taha,Ali J. Addie,Khalid Hassan Ibnouf,Majid S. Jabir,Omar Talal Mahmood,R. Apsari,Norhana Arsad","doi":"10.1039/d6an00888g","DOIUrl":"https://doi.org/10.1039/d6an00888g","url":null,"abstract":"Continuous physiological monitoring is a prerequisite in medicine that enables early disease detection, long-term health monitoring, and individualized therapeutic interventions. Although wearable optical biosensors have evolved significantly, their long-term clinical deployment remains limited by mechanical degradation, signal drift, biofouling, energy constraints, and poor integration with intelligent healthcare infrastructure. These issues are especially acute in the aged and disabled, when constant, dependable, and tailored monitoring is critical for proactive disease treatment. As a result, next-generation sensing technologies must progress beyond passive data collection toward self-adaptive systems capable of maintaining analytical accuracy while supporting patient-specific clinical interpretation and clinician-supervised decision-making. This perspective presents an overview of self-adaptive nanophotonic metasurfaces as the sensing foundation for Living Digital Twins (LDTs) in personalized healthcare. To create an intelligent sensing ecosystem, the proposed framework combines flexible plasmonic, localized surface plasmon resonance (LSPR), surface-enhanced Raman scattering (SERS), artificial intelligence, internet of nano things (IoNT) connectivity, and individualized digital twin analytics. The proposed framework combines continuous multimodal biomarker sensing with patient-specific physiological modelling to support longitudinal updating of digital representations. Edge intelligence enables low-latency signal processing, while adaptive analytics may improve sensing stability, calibration, and patient-specific interpretation. The integration of adaptive nanophotonic sensing with digital twins therefore represents a prospective approach for supporting early identification of physiological deterioration, individualized risk assessment, and clinician-supervised treatment planning in aging and disabled populations.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"76 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148980640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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