Analyst最新文献

{"title":"A novel cataluminescence sensor for rapid detection of methanol at low working temperature based on Ni/CeO2 catalyst","authors":"Shufang Luo, Fangyuan Yuan, Zhenhua Qin, Yuxiu Yang, Xu Teng, Chao Lu","doi":"10.1039/d5an00626k","DOIUrl":"https://doi.org/10.1039/d5an00626k","url":null,"abstract":"Cataluminescence (CTL) is an attractive chemiluminescence phenomenon that occurs at the gas-solid catalytic interface, and there is a strong anticipation for highly efficient CTL. Herein, Ni/CeO2 catalyst was successfully developed by using the in-situ doping method. In comparison with the CeO2 nanoparticles and NiO nanoparticles, Ni/CeO2 catalyst exhibited superior CTL performance toward methanol. Based on the outstanding catalytic performance of Ni/CeO2, a novel CTL sensor with excellent sensitivity, good selectivity, and satisfactory stability was fabricated for the detection of methanol at low working temperature. Notably, the reaction time and recovery time of the proposed CTL sensor for methanol detection were as short as 7 s and 6 s, respectively. The proposed CTL sensor was successfully applied to detect methanol in commercial white wine samples with recoveries of 107.86-113.09%. The relative standard deviation for the detection of methanol in commercial white wine samples was less than 7%. Accordingly, the proposed CTL sensor with the advantage of fast response and reliable characteristics provided a promising choice for rapid detection of methanol. This work provided a new direction for the development of CTL sensors with high performance and low working temperature.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"51 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144630126","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}

{"title":"A minimal sampling, in-line spectroscopic calibration method for unstable components during ammoniation of fatty acids","authors":"C. M. Raffel, J. Meekes, H.-J. van Manen, A. J. B. ten Kate, A. Chaudhuri, J. van der Schaaf","doi":"10.1039/d4an01051e","DOIUrl":"https://doi.org/10.1039/d4an01051e","url":null,"abstract":"The ammoniation of fatty acid produces fatty amide, as well as unstable ammonium salt, whose composition profile can vary with off-line sampling. This makes the analysis and determination of reaction kinetics challenging. In-line FT-IR spectroscopy removes the need for sampling, but requires calibration of the reacting system at reaction conditions, which is complicated by the near-instant formation of ammonium salt. In this work, we demonstrate the development of a calibration method which overcomes the complexities posed by both off-line and in-line analysis. This is achieved by taking only eight off-line samples for determination of the more stable components and formulating mass balances of the reactive system for each in-line acquired FT-IR spectrum. This allows for the determination of the rapidly fluctuating salt content. The essential assumptions underlying the mass balances and the resulting calibration are based on a qualitative examination of the reaction system through principal component analysis. Put together, this enables in-line calibration of the system at reaction conditions, achieving relative errors below 10% using partial least squares regression.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"199 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144629999","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}

{"title":"Characterizing ssRNA and dsRNA electrophoretic behavior: empirical insights with neural network-aided predictions","authors":"Nina Sheng Li, Adriana Coll De Peña, Matei Vaduva, Somdatta Goswami, Anubhav Tripathi","doi":"10.1039/d5an00381d","DOIUrl":"https://doi.org/10.1039/d5an00381d","url":null,"abstract":"RNA-based therapeutics are currently at the forefront of the biopharmaceutical industry because of their safety, efficacy, and shortened time from disease discovery to therapy development. Microfluidic electrophoresis provides a great analytical platform to analyze nucleic acids in unprecedented detail. However, while DNA has been studied extensively within microfluidic systems, there is limited data available for RNA, particularly of chemically modified molecules, such as those used in the COVID-19 mRNA vaccines, and for long double-stranded RNA molecules, which may accompany, intentionally or as a by-product, RNA therapeutics. To this end, this study focused on the empirical microfluidic electrophoretic analysis of double- and single-stranded RNA, non-modified and pseudouridine-modified, at varying gel concentrations. It then compared the findings to the electrophoretic mobility models in the literature. This work was then complemented with data-driven and physics-informed neural networks that successfully predicted the migration time and length of different RNA molecules with an average error of 12.34% for the data-driven model and 0.77% for the physics-informed model. The low error in the physics-informed neural networks opens the doors to the electrophoretic characterization of molecules, even beyond RNA, without the need for extensive experimental data.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"15 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144630123","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}

{"title":"Colourimetric Detection of Bisphenol A in Water: A Smartphone-Based Sensor Using Inverse Opal Molecularly Imprinted Photonic Crystal Hydrogel","authors":"Sree Sanker SS, Subin Thomas, Dhanya P Jacob, V S Suniya, Savitha Nalini, Madhusoodanan Kottarathil Naduvil","doi":"10.1039/d4an01426j","DOIUrl":"https://doi.org/10.1039/d4an01426j","url":null,"abstract":"Molecularly imprinted photonic crystal hydrogel (MIPCH) serves as a highly effective platform for the sensitive and selective detection of various analyte molecules. In this study, we present a smartphone-based inverse opal MIPCH (IOMIPCH) sensor designed for the sensitive and selective detection of bisphenol A (BPA) in water samples. The sensor is prepared by photopolymerizing the hydrogel precursor solution within the voids of a polystyrene (PS) photonic crystal (PC) opal film. This is followed by the etching of BPA molecules and the removal of PS spheres forming inverse opal structure with binding sites for analyte BPA. The sensor displays a vibrant structural colour that experiences a redshift upon rebinding of the BPA molecules. The structural colour change provides a visually observable indication of the sensor response. The IOMIPCH-BPA sensor demonstrates a low limit of detection (LoD) of 0.69 fM and a rapid response time of 4 minutes with the ability to selectively detect BPA even in complex sample matrices. Additionally, it is reusable and maintains its performance for up to one month. We used the sensor response images to train a deep learning-based regression model on the smartphone, enabling quantitative predictions of BPA concentration. This integration creates an accurate, portable smart sensor platform capable of real-time BPA sensing.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"279 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144622727","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}

{"title":"Differentiation of lactose sample batches from surface impurities by OrbiSIMS","authors":"Bin Yan, Junting Zhang, Eleonora Paladino, Mark Nicholas, Paulina Rakowska, Anthony W.T. Bristow, Ian Gilmore","doi":"10.1039/d5an00364d","DOIUrl":"https://doi.org/10.1039/d5an00364d","url":null,"abstract":"Impurities present on the surface of pharmaceutical formulations for drug delivery significantly impact their stability and efficacy. Hence, the characterization of impurities on the surface is essential to ensure efficacy, quality, and safety. Secondary ion mass spectrometry (SIMS) is gaining increasing popularity for surface analysis in the pharmaceutical industry, due to its high sensitivity and spatial resolution. Time-of-Flight (ToF) SIMS instruments have been successfully used. However, their application has been limited since the mass resolving power and mass accuracy are too low to separate complex peaks and give identification with confidence. The OrbiSIMS instrument overcomes this issue owing to its Orbitrap analyzer with a mass resolving power of > 240,000 at m/z 200 and a mass accuracy of < 2 p.p.m. We use the OrbiSIMS in combination with multivariate analysis to differentiate notionally identical batches of lactose from different suppliers using the detection of small differences in surface impurities.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"9 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144622728","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}

{"title":"High-sensitivity Detection of Brilliant Blue by Disposable chitosan-biochar Electrochemical Sensors","authors":"junbin cao, chengcheng xu, Jianwei Zhao, wenmei tao","doi":"10.1039/d5an00585j","DOIUrl":"https://doi.org/10.1039/d5an00585j","url":null,"abstract":"This research created a disposable electrochemical sensor utilizing a chitosan-biochar (CS-H500) composite-modified glassy carbon electrode (GCE) for the very sensitive detection of brilliant blue (BB) in food products. The CS-H500 composite dispersion was synthesized using the ultrasonic dispersion method, while quantum chemical simulations clarified the adsorption mechanism of BB molecules on the electrode surface via π-π conjugation and electrostatic interactions. Optimized experimental settings comprised: 16 μL of CS-H500 dispersion modification, 300 seconds of accumulation period, and a pH 7.0 phosphate buffer. The results indicated that chitosan (CS) markedly enhanced the dispersibility of biochar, augmenting the effective surface area of the modified electrode by 2.53 times (0.179 cm<small>²</small>) in comparison to the bare GCE. The sensor demonstrated a linear detection range of 1.0×10<small>^-6</small> to 1.0×10<small>^-4</small> mol/L for BB, with a detection limit of 1.0×10<small>^-7</small> mol/L (S/N=3), acceptable recoveries (91.49%-102.18%), and commendable reproducibility (RSD=8.01%). Interference studies validated significant selectivity against citric acid, glucose, prevalent metal ions, and proficient differentiation from mixed pigments such as sunset yellow (SY) and fluorescein sodium (FS). The analysis of practical beverage samples confirmed its reliability. This disposable electrode design streamlines operations, prevents cross-contamination, and offers an effective option for on-site monitoring of food additives.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"14 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144611323","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}

{"title":"High-throughput DeepPRM-Stellar proteomics coupled with machine learning enables precise quantification of atherosclerosis-stroke progression biomarkers and risk prediction","authors":"Ye Liu, Ouyang Hu, Jingyi Wang, Yijie Qiu, Jin Xiao, Xin Cheng, Pengyuan Yang, Ning-Shao Xia, Yueting Xiong, Quan Yuan","doi":"10.1039/d5an00396b","DOIUrl":"https://doi.org/10.1039/d5an00396b","url":null,"abstract":"Predicting the progression of asymptomatic large-artery atherosclerosis (LAA) to acute ischemic stroke (AIS) remains a significant challenge when relying solely on anatomical stenosis. To address this clinical gap, we integrated discovery-phase serum proteomics with machine-learning techniques to identify circulating biomarkers capable of predicting atherosclerotic progression. Utilizing a dual-cohort design (Cohort I: discovery stage, n = 43; Cohort II: validation stage, n = 39), we established a Serum Protein Candidate Biomarker Bank (SPCBB) encompassing 1,484 proteins by harmonizing literature-derived evidence (1369 proteins) with 222 differentially expressed proteins (DEPs) identified through mass spectrometry analysis. Global proteomics revealed that LAA-associated proteins were enriched in cholesterol metabolism, whereas AIS was characterized by the activation of complement/coagulation cascades. We performed targeted validation of 171 peptides (corresponding to 156 proteins) using DeepPRM on the Stellar platform, thereby facilitating machine learning-based optimization of the biomarker panel. The XGBoost algorithm identified two diagnostic signatures: a three-protein panel (RNASE4, HBA1, ATF6B) that differentiates AIS from LAA, with an area under the curve (AUC) of 0.917 and specificity of 80.0%; and a six-protein panel (MRC1, HBA1, GUC2A, HBD, CLEC3B, FLNA) that distinguishes AIS/LAA from healthy controls, achieving an AUC of 0.971 and specificity of 86.0%. To further validate key candidates, we performed ELISA assays for GUCA2A and FLNA, which confirmed their significant elevation in patients with AIS and LAA (p &lt; 0.01), consistent with the proteomics findings. Both internal and external validations confirmed robust performance across cohorts. These validated biomarker panels establish a proteomics-driven framework for serum-based, dynamic monitoring of LAA progression, thereby supporting clinical decision-making aimed at optimizing early stroke prevention in asymptomatic individuals.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"109 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144611255","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}

{"title":"CeMM-WormTracker: Long-term, single-worm level tracking and phenotyping of C. elegans cultivated in CeMM on an integrated and enclosed microfluidic device","authors":"Qianqian Yang, Runtao Zhong, Mengyu Wang, Wenbo Chang, Kexin Chen, Yeqing Sun","doi":"10.1039/d5an00394f","DOIUrl":"https://doi.org/10.1039/d5an00394f","url":null,"abstract":"Caenorhabditis elegans (C. elegans) is a typical model organism that has predominantly relied on growth using a bacterial diet, presenting limitations for automated experimentations (mainly due to the requirement of periodic transfer to new plates), and accuracy of results (because of possible interference by bacterial metabolism in liquid media), which makes flexible manipulation and long-term tracking difficult. C. elegans Maintenance Medium (CeMM), a chemically defined sterile liquid medium, holds the potential to solve these problems. Population-level studies of C. elegans cultured in CeMM have shown that nematode development slows, fecundity declines, lifespan increases, lipid and protein stores decrease, and gene expression changes relative to that on a bacterial diet. However, automated cultivation of C. elegans in CeMM, long-term tracking and phenotyping at single-worm level remains challenging. Here, we developed a chamber-array chip (WormChip-1.8) and an integrated and enclosed microfluidic device, CeMM-WormTracker, with the capability of automating fluid control and worm manipulation for single-worm level tracking and phenotyping of C. elegans grown in CeMM. By using a microscope, the CeMM-WormTracker allows for observation of C. elegans development, motility, reproduction, and survival for a long period of time. Our data demonstrate that it is possible to longitudinally track and phenotype the growth and development of nematodes at single-worm level for at least 75 days within the device, enabling comprehensive monitoring of the whole reproductive period and lifespan in sterile liquid culture, which is difficult for well plate-based experiments. Comparing with the results from 96-well plates, the development, activity, and reproduction of nematodes in the microfluidic device seems more stable. Thus, the CeMM-WormTracker provides feasible solutions for automated and high-throughput experimentations in studies of C. elegans, both on the ground and in orbit.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"22 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144603752","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}

{"title":"Comparative Performance Evaluation of Triple Quadrupole Tandem Mass Spectrometry and Orbitrap High-Resolution Mass Spectrometry for Analysis of Antibiotics in Creek Water Impacted by CETP Discharge","authors":"Arhama Arhama Ansari, Ayush Ransingh, Soumyo Mukherji, Andrew S Hursthouse, Fiona Henriquez, John Connolly, Suparna Mukherji","doi":"10.1039/d5an00482a","DOIUrl":"https://doi.org/10.1039/d5an00482a","url":null,"abstract":"The widespread detection of antibiotics in aquatic environments, particularly in effluent-receiving surface waters, poses significant ecological and public health concerns due to their role in promoting antimicrobial resistance. Accurate trace-level antibiotic measurement is essential for environmental risk assessment and improving wastewater treatment strategies. This study presents the development, optimization, and validation of two complementary liquid chromatography-mass spectrometry (LC-MS) workflows for the simultaneous quantification of nine antibiotics across five therapeutic classes in creek water impacted by a Common Effluent Treatment Plant (CETP). The performance of a triple quadrupole LC-MS/MS system (LC-QqQ-MS) was compared to that of a high-resolution Orbitrap mass spectrometer (LC-Orbitrap-HRMS). Both instruments demonstrated excellent linearity (R² &gt; 0.99) and satisfactory recoveries (70–90%) across a wide concentration range. The method detection limits ranged from 0.11 to 0.23 ng L⁻¹ for LC-QqQ-MS and from 0.02 to 0.13 ng L⁻¹ for LC-Orbitrap-HRMS, confirming the superior sensitivity of the high-resolution system approach. Application to real-world creek water samples revealed the ubiquitous presence of multiple antibiotics, with azithromycin and enrofloxacin dominating the detected concentrations, particularly near the CETP discharge point and a nearby waste dumping site. A three-way ANOVA confirmed that antibiotic concentrations were significantly affected by instrument type, sampling site, and antibiotic class along with their interactions. Additionally, non-target screening performed using LC-Orbitrap-HRMS enabled the detection of additional antibiotics belonging to quinolones, sulfonamides and aminoglycosides, further demonstrating the broader analytical scope of high-resolution mass spectrometry. The study highlights the necessity of using advanced analytical tools for the accurate quantification of antibiotics in complex matrices and underscores the environmental risks posed by pharmaceutical pollution in industrial discharge-impacted water bodies.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"37 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144594835","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}

{"title":"Predicting the retention time of microparticles in electrokinetic migration.","authors":"Alaleh Vaghef-Koodehi,Victor H Perez-Gonzalez,Blanca H Lapizco-Encinas","doi":"10.1039/d5an00515a","DOIUrl":"https://doi.org/10.1039/d5an00515a","url":null,"abstract":"Insulator based electrokinetic (iEK) devices have emerged as powerful tools for analyzing both nano- and microparticles due to their simplicity, robustness, and ability to integrate linear and nonlinear electrokinetic (EK) effects into a single platform. Recent studies emphasize the importance of nonlinear electrophoresis (EPNL) in particle analysis, for performing separations based on size, shape, and charge differences. Despite these advancements, the development of an empirical equation for predicting particle retention times in iEK-based systems that incorporates EPNL remains limited. This study presents a method for predicting particle retention time in iEK systems in scenarios where the linear EK regime allows for particles migration, while also incorporating EPNL and accounting for particle characteristics, applied electric fields, and microdevice features. Experiments were conducted using eight reference microparticles, grouped into four pairs with similar sizes (3.6 μm to 11.7 μm) but distinct zeta potentials (∼-20 mV and ∼-30 mV), across three distinct iEK microdevices: one with asymmetrical oval-diamond posts, one with symmetrical oval posts, and one postless design. Experimental retention times (tR,e) were measured at applied voltages ranging from 400 V to 1450 V. Using the collected tR,e data, three empirical equations were developed to describe particle velocity, incorporating both linear and nonlinear velocities. Validation with two control particles demonstrated prediction errors below 24% in all devices. These findings underscore the potential of the empirical equations in predicting particle behavior in iEK systems.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"92 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144594215","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}