Epileptic seizures are caused by abnormal electrical activity in the brain. Although many underlying disease mechanisms may lead to epilepsy, the cause of the disease remains unknown in about 50% of patients worldwide. Given the complex interactions involving multiple signaling molecules in the course of epilepsy, relying solely on a single molecule for detection may lead to false positive results. Therefore, developing fluorescent probes capable of simultaneously detecting multiple signal molecules is the key to improving the accuracy of epilepsy diagnosis. This study developed a fluorescent probe WSC for simultaneously responding to hypochlorite (ClO-) and viscosity. In the presence of ClO- and viscosity, the probe exhibited fluorescence turn-on responses at 653 nm and 757 nm, respectively. Cell experiments further confirmed that the progression of epilepsy is related to ferroptosis. Furthermore, the probe facilitated non-invasive, multiparameter in vivo imaging in epileptic mouse brains, an approach that could enhance diagnostic accuracy and thereby offer a scientific basis for early intervention and personalized medicine.
{"title":"Dual-channel fluorescence imaging revealing epilepsy-mediated ferroptosis processes in the mouse brain.","authors":"Qian Pang, Weijie Zhang, Fangjun Huo, Caixia Yin","doi":"10.1039/d6an01177b","DOIUrl":"https://doi.org/10.1039/d6an01177b","url":null,"abstract":"<p><p>Epileptic seizures are caused by abnormal electrical activity in the brain. Although many underlying disease mechanisms may lead to epilepsy, the cause of the disease remains unknown in about 50% of patients worldwide. Given the complex interactions involving multiple signaling molecules in the course of epilepsy, relying solely on a single molecule for detection may lead to false positive results. Therefore, developing fluorescent probes capable of simultaneously detecting multiple signal molecules is the key to improving the accuracy of epilepsy diagnosis. This study developed a fluorescent probe WSC for simultaneously responding to hypochlorite (ClO<sup>-</sup>) and viscosity. In the presence of ClO<sup>-</sup> and viscosity, the probe exhibited fluorescence turn-on responses at 653 nm and 757 nm, respectively. Cell experiments further confirmed that the progression of epilepsy is related to ferroptosis. Furthermore, the probe facilitated non-invasive, multiparameter <i>in vivo</i> imaging in epileptic mouse brains, an approach that could enhance diagnostic accuracy and thereby offer a scientific basis for early intervention and personalized medicine.</p>","PeriodicalId":63,"journal":{"name":"Analyst","volume":" ","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149259599","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}
Powder-based colorimetric test kits enable rapid reagent dissolution but are prone to spillage, reagent loss, and dispersed waste during field use, whereas conventional compressed tablets provide cleaner handling but often dissolve slowly and require manual shaking. Here, an effervescent ‘drop-and-detect’ sensing tablet is reported that combines tablet-grade handling robustness with rapid, autonomous reagent release for shake-free copper detection in water. By integrating sensing reagents, stabilizing excipients, and effervescent agents into a single solid-dose platform via powder compression, the system eliminates the need for manual mixing, vortexing, or complex sample handling. The physical properties of the tablets, including weight, hardness, friability, disintegration time, and content uniformity, were evaluated. In addition, dissolution and effervescence kinetics were investigated. Upon contact with water, the autonomous effervescence facilitates complete dissolution and initiates a specific colorimetric reaction. In this mechanism, sodium ascorbate reduces cupric ions (Cu2+) to cuprous ions (Cu+), which then react with 2,2′-biquinoline-4,4′-dicarboxylic acid (BCA) to form a stable, lavender-colored [Cu(BCA)2]3− coordination complex. Compared with a conventional non-effervescent tablet, the effervescent formulation reduced the assay time from 15 min to 2 min while maintaining suitable mechanical integrity for handling and storage. The sensor exhibited a linear response over the 0.3–2.0 mg L−1 copper range (R2 = 0.98) with an LOD of 0.03 mg L−1 and an LOQ of 0.09 mg L−1. Good selectivity was observed in the presence of potentially interfering species, and validation using tap, canal, pond, and river water samples supported copper quantification in complex matrices. For Lachine Canal water spiked with 1.0 mg L−1 Cu, the tablet sensor showed 92.4% agreement with ICP-MS. By bridging the gap between powder reagents and compressed tablets, this effervescent sensing format enables portable, laboratory-free water monitoring while providing a practical route toward solid-dose analytical sensing.
{"title":"Effervescent sensing tablets for clean handling and shake-free, rapid copper detection in water","authors":"Mohsen Ghiasi Tarzi,Maryam Mansouri,Seyed Hamid Safiabadi Tali,Zubi Sadiq,Sana Jahanshahi-Anbuhi","doi":"10.1039/d6an00753h","DOIUrl":"https://doi.org/10.1039/d6an00753h","url":null,"abstract":"Powder-based colorimetric test kits enable rapid reagent dissolution but are prone to spillage, reagent loss, and dispersed waste during field use, whereas conventional compressed tablets provide cleaner handling but often dissolve slowly and require manual shaking. Here, an effervescent ‘drop-and-detect’ sensing tablet is reported that combines tablet-grade handling robustness with rapid, autonomous reagent release for shake-free copper detection in water. By integrating sensing reagents, stabilizing excipients, and effervescent agents into a single solid-dose platform via powder compression, the system eliminates the need for manual mixing, vortexing, or complex sample handling. The physical properties of the tablets, including weight, hardness, friability, disintegration time, and content uniformity, were evaluated. In addition, dissolution and effervescence kinetics were investigated. Upon contact with water, the autonomous effervescence facilitates complete dissolution and initiates a specific colorimetric reaction. In this mechanism, sodium ascorbate reduces cupric ions (Cu2+) to cuprous ions (Cu+), which then react with 2,2′-biquinoline-4,4′-dicarboxylic acid (BCA) to form a stable, lavender-colored [Cu(BCA)2]3− coordination complex. Compared with a conventional non-effervescent tablet, the effervescent formulation reduced the assay time from 15 min to 2 min while maintaining suitable mechanical integrity for handling and storage. The sensor exhibited a linear response over the 0.3–2.0 mg L−1 copper range (R2 = 0.98) with an LOD of 0.03 mg L−1 and an LOQ of 0.09 mg L−1. Good selectivity was observed in the presence of potentially interfering species, and validation using tap, canal, pond, and river water samples supported copper quantification in complex matrices. For Lachine Canal water spiked with 1.0 mg L−1 Cu, the tablet sensor showed 92.4% agreement with ICP-MS. By bridging the gap between powder reagents and compressed tablets, this effervescent sensing format enables portable, laboratory-free water monitoring while providing a practical route toward solid-dose analytical sensing.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"96 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149248490","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 non-destructive identification of black gel pen inks and their writing age is crucial in forensic document examination, particularly for legal and financial paperwork. This study proposes an intelligent framework integrating hyperspectral imaging (HSI) with a novel deep learning model, PG-BCANet, for objective ink characterization. Hyperspectral data were collected from diverse ink samples on standard A4 paper, representing different pen models and chronological ages. After noise suppression and baseline drift correction using Savitzky-Golay (SG) smoothing and Standard Normal Variate (SNV) normalization, three feature selection algorithms, including Principal Component Analysis (PCA), Interval Random Forest (iRF), and Successive Projections Algorithm (SPA), were comparatively evaluated. For classification, the proposed PG-BCANet, constructed on a 1-D Convolutional Neural Network (1DCNN), incorporates a Band-Gate mechanism, Efficient Channel Attention (ECA), and residual connections to optimize feature extraction from high-dimensional spectral data. Experimental results demonstrate that PG-BCANet outperforms traditional models, achieving superior accuracies of 96.6% for model identification and up to 89.2% for writing time differentiation. These results significantly surpass both KNN (91.2%, 82.9%) and SVM-based models (94.7%, 84.7%), confirming the efficacy of the Band-Gate and attention modules in capturing subtle spectral variances. This research provides a robust, non-invasive, and high-precision methodology for questioned document examination and expands the application of deep learningenhanced HSI in forensic science.
{"title":"Non-destructive Discrimination of Black Gel Pen Inks via Physics-Guided Band-Gate Attention Network and Hyperspectral Imaging","authors":"Qian Qian,Yan Li,Xinri Zhang,Xinrui Xie,Lu Yin","doi":"10.1039/d6an00923a","DOIUrl":"https://doi.org/10.1039/d6an00923a","url":null,"abstract":"The non-destructive identification of black gel pen inks and their writing age is crucial in forensic document examination, particularly for legal and financial paperwork. This study proposes an intelligent framework integrating hyperspectral imaging (HSI) with a novel deep learning model, PG-BCANet, for objective ink characterization. Hyperspectral data were collected from diverse ink samples on standard A4 paper, representing different pen models and chronological ages. After noise suppression and baseline drift correction using Savitzky-Golay (SG) smoothing and Standard Normal Variate (SNV) normalization, three feature selection algorithms, including Principal Component Analysis (PCA), Interval Random Forest (iRF), and Successive Projections Algorithm (SPA), were comparatively evaluated. For classification, the proposed PG-BCANet, constructed on a 1-D Convolutional Neural Network (1DCNN), incorporates a Band-Gate mechanism, Efficient Channel Attention (ECA), and residual connections to optimize feature extraction from high-dimensional spectral data. Experimental results demonstrate that PG-BCANet outperforms traditional models, achieving superior accuracies of 96.6% for model identification and up to 89.2% for writing time differentiation. These results significantly surpass both KNN (91.2%, 82.9%) and SVM-based models (94.7%, 84.7%), confirming the efficacy of the Band-Gate and attention modules in capturing subtle spectral variances. This research provides a robust, non-invasive, and high-precision methodology for questioned document examination and expands the application of deep learningenhanced HSI in forensic science.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"23 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149241310","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}
Matrine-type alkaloids (MTAs) occur naturally in Sophora plants and frequently contaminate honey, creating regulatory friction between China and the EU owing to their toxicity and divergent maximum residue limits. Existing analytical tools either rely on laboratory-based instrumentation or target single analytes. We developed a colloidal gold immunochromatographic strip (GICA) that simultaneously detects four MTAs-oxymatrine, matrine, sophocarpine and sophoridine-in honey. A broad-specificity monoclonal antibody (mAb 1C1) was raised via computationally guided hapten design, integrating conformational overlay, Mulliken charge and electrostatic potential mapping. The antibody showed high affinity (Kₐ = 3.85 × 10¹⁰ L/mol) and half-maximal inhibitory concentrations of 1. 73, 3.84, 3.77 and 22.43 ng/mL for the four alkaloids, respectively. Under optimised conditions, the strip achieved visual cut-offs of 2-50 mg/kg and calculated LODs of 0.03-0.42 mg/kg, with spike recoveries of 87.2-107.0% in honey. Results agreed well with LC-MS/MS and the total assay time was 15 min. This work provides a simple, low-cost, field-ready platform for multi-alkaloid screening, directly addressing the compliance needs of honey export monitoring.
{"title":"Development of a Gold Immunochromatographic Strip with Broad-Specificity Monoclonal Antibodies for Rapid Detection of Matrine-Type Alkaloids in Honey","authors":"Shufen Si,Xueqing Wang,Liqiang Liu,aihong wu,Chuanlai Xu","doi":"10.1039/d6an01015f","DOIUrl":"https://doi.org/10.1039/d6an01015f","url":null,"abstract":"Matrine-type alkaloids (MTAs) occur naturally in Sophora plants and frequently contaminate honey, creating regulatory friction between China and the EU owing to their toxicity and divergent maximum residue limits. Existing analytical tools either rely on laboratory-based instrumentation or target single analytes. We developed a colloidal gold immunochromatographic strip (GICA) that simultaneously detects four MTAs-oxymatrine, matrine, sophocarpine and sophoridine-in honey. A broad-specificity monoclonal antibody (mAb 1C1) was raised via computationally guided hapten design, integrating conformational overlay, Mulliken charge and electrostatic potential mapping. The antibody showed high affinity (Kₐ = 3.85 × 10¹⁰ L/mol) and half-maximal inhibitory concentrations of 1. 73, 3.84, 3.77 and 22.43 ng/mL for the four alkaloids, respectively. Under optimised conditions, the strip achieved visual cut-offs of 2-50 mg/kg and calculated LODs of 0.03-0.42 mg/kg, with spike recoveries of 87.2-107.0% in honey. Results agreed well with LC-MS/MS and the total assay time was 15 min. This work provides a simple, low-cost, field-ready platform for multi-alkaloid screening, directly addressing the compliance needs of honey export monitoring.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"4 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149241312","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}
Aulia Ratri Hapsari,Noura Said Alkiyumi,Nicholas J. Goddard,Ruchi Gupta
Sustainable polymers such as chitosan are gaining popularity for diverse applications including sensing. Electrochemical sensors with chitosan-nanocomposite electrodes have been reported, but the use of undoped chitosan can reduce the cost of sensors. Chitosan films deposited on glass substrates can serve as optical label-free leaky waveguide (LW) sensors, providing high sensitivity at low cost compared to other optical sensors. Here, for the first time, we report chitosan LW biosensors for sequence-specific quantification of ∼7.9 kDa target DNA. The target DNA sequence selected in this work is strongly associated with low-grade, non-muscle-invasive bladder cancer. The chitosan LW biosensor offered a limit of detection (LOD) of 1.4 nM for the target DNA in buffer without amplification and an analysis time of 30 min. In comparison, the LOD for the target DNA in 50% and 100% synthetic urine was 18.7 and 33.2 nM, respectively.
{"title":"A chitosan leaky waveguide biosensor for measurement of DNA biomarkers","authors":"Aulia Ratri Hapsari,Noura Said Alkiyumi,Nicholas J. Goddard,Ruchi Gupta","doi":"10.1039/d6an01137c","DOIUrl":"https://doi.org/10.1039/d6an01137c","url":null,"abstract":"Sustainable polymers such as chitosan are gaining popularity for diverse applications including sensing. Electrochemical sensors with chitosan-nanocomposite electrodes have been reported, but the use of undoped chitosan can reduce the cost of sensors. Chitosan films deposited on glass substrates can serve as optical label-free leaky waveguide (LW) sensors, providing high sensitivity at low cost compared to other optical sensors. Here, for the first time, we report chitosan LW biosensors for sequence-specific quantification of ∼7.9 kDa target DNA. The target DNA sequence selected in this work is strongly associated with low-grade, non-muscle-invasive bladder cancer. The chitosan LW biosensor offered a limit of detection (LOD) of 1.4 nM for the target DNA in buffer without amplification and an analysis time of 30 min. In comparison, the LOD for the target DNA in 50% and 100% synthetic urine was 18.7 and 33.2 nM, respectively.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"10 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149241311","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}
Food-safety decisions require rapid screening of adulteration, origin fraud, elemental contamination and freshness loss. Laser-induced breakdown spectroscopy (LIBS) provides direct multi-element fingerprints with short acquisition times and little reagent consumption. Its performance in foods, however, depends on a coupled analytical chain: sample presentation controls laser coupling and mass removal; plasma evolution and acquisition govern emission; calibration and modelling determine interpretation; and validation establishes reliability beyond the development dataset. This critical review uses that chain to assess food-related LIBS workflows. It examines powders, moist tissues, fatty materials, liquids and spatially heterogeneous samples, then considers plasma-aware acquisition, preprocessing, chemometrics, deep learning and multimodal fusion. Task-specific comparisons with ICP-based methods, near-infrared spectroscopy, Raman spectroscopy and hyperspectral imaging clarify where LIBS adds value. Pelletization provides a reproducible baseline for many powders, whereas moist, fatty and liquid matrices often require flattening, phase control, immobilization or enrichment. Readiness is strongest for selected mineral-related authenticity screens and elemental warning at concentrations clearly above a decision threshold, provided that independent validation and quality control are available. Closed-set provenance and portable sorting are generally less mature, while regulatory trace confirmation, cross-instrument transfer and realistic microbial analysis require stronger evidence. Progress depends on end-to-end timing, threshold-focused validation, interpretable models, drift monitoring and selective confirmation with complementary techniques.
{"title":"Laser-induced breakdown spectroscopy for food safety analysis: sample presentation, data interpretation, and application readiness","authors":"Yikang Hou,Zhuoxi Li,Jie Lian","doi":"10.1039/d6an00368k","DOIUrl":"https://doi.org/10.1039/d6an00368k","url":null,"abstract":"Food-safety decisions require rapid screening of adulteration, origin fraud, elemental contamination and freshness loss. Laser-induced breakdown spectroscopy (LIBS) provides direct multi-element fingerprints with short acquisition times and little reagent consumption. Its performance in foods, however, depends on a coupled analytical chain: sample presentation controls laser coupling and mass removal; plasma evolution and acquisition govern emission; calibration and modelling determine interpretation; and validation establishes reliability beyond the development dataset. This critical review uses that chain to assess food-related LIBS workflows. It examines powders, moist tissues, fatty materials, liquids and spatially heterogeneous samples, then considers plasma-aware acquisition, preprocessing, chemometrics, deep learning and multimodal fusion. Task-specific comparisons with ICP-based methods, near-infrared spectroscopy, Raman spectroscopy and hyperspectral imaging clarify where LIBS adds value. Pelletization provides a reproducible baseline for many powders, whereas moist, fatty and liquid matrices often require flattening, phase control, immobilization or enrichment. Readiness is strongest for selected mineral-related authenticity screens and elemental warning at concentrations clearly above a decision threshold, provided that independent validation and quality control are available. Closed-set provenance and portable sorting are generally less mature, while regulatory trace confirmation, cross-instrument transfer and realistic microbial analysis require stronger evidence. Progress depends on end-to-end timing, threshold-focused validation, interpretable models, drift monitoring and selective confirmation with complementary techniques.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"9 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149230136","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}
In anticancer drug discovery, there is a clear need to determine how much of a drug enters the cell and its concentration in different cellular compartments (e.g., the nucleus or cytoplasm). This information helps assess therapeutic efficacy and optimise drug design and in vivo dosage. Compared with other analytical techniques, Raman spectroscopy provides many advantages that make it well suited to this application. It is non-destructive, preserving the structural and chemical integrity of the sample. It also eliminates the need for complex sample preparation and is suitable for live-cell experiments. Moreover, Raman spectra are largely unaffected by water interference, making the technique ideal for analysing living cells. Label-free detection is one of its most distinctive advantages. This study requires quantitative analysis without any fluorescent labels or other biological markers, while Raman measurements can rely solely on the inherent Raman properties of the anticancer drug itself, eliminating potential interference from labels on biological activity. Overall, this paper provides a comprehensive investigation into the application of Raman spectroscopy for quantifying anticancer drug concentrations in living cells, combined with machine learning-based analysis. It advances beyond imaging analysis of drug distribution by determining drug concentrations and membrane permeability coefficients using Raman signals. For drugs administered at a concentration of 0.3%, accuracies of 0.01-0.1% were determined for a variety of anticancer drugs in different cell lines within a measurement window of 5 minutes.
{"title":"Quantification of drug concentrations in individual living cancer cells using Raman spectroscopy and machine learning","authors":"Jiaming Li,Jan Cerski,Andrew Downes","doi":"10.1039/d6an00870d","DOIUrl":"https://doi.org/10.1039/d6an00870d","url":null,"abstract":"In anticancer drug discovery, there is a clear need to determine how much of a drug enters the cell and its concentration in different cellular compartments (e.g., the nucleus or cytoplasm). This information helps assess therapeutic efficacy and optimise drug design and in vivo dosage. Compared with other analytical techniques, Raman spectroscopy provides many advantages that make it well suited to this application. It is non-destructive, preserving the structural and chemical integrity of the sample. It also eliminates the need for complex sample preparation and is suitable for live-cell experiments. Moreover, Raman spectra are largely unaffected by water interference, making the technique ideal for analysing living cells. Label-free detection is one of its most distinctive advantages. This study requires quantitative analysis without any fluorescent labels or other biological markers, while Raman measurements can rely solely on the inherent Raman properties of the anticancer drug itself, eliminating potential interference from labels on biological activity. Overall, this paper provides a comprehensive investigation into the application of Raman spectroscopy for quantifying anticancer drug concentrations in living cells, combined with machine learning-based analysis. It advances beyond imaging analysis of drug distribution by determining drug concentrations and membrane permeability coefficients using Raman signals. For drugs administered at a concentration of 0.3%, accuracies of 0.01-0.1% were determined for a variety of anticancer drugs in different cell lines within a measurement window of 5 minutes.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"1 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149230137","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}
A molecularly imprinted polymer (MIP) composed of 2-vinylpyridine and 1-vinyl-3-ethylimidazolium acetate (FMs) imprinted with homophthalic acid (pseudo-template (T) was fabricated directly on a stainless-steel substrate for selective adsorption of mono- and dicarboxylic acid metabolites of light aromatic components of petrogenic oil from complex aqueous samples. The analytical method features multiplexed sample processing, which yeilds high-throughput extraction and desorption (≥ 45 samples in 2.7 h or <4 min/sample), combined with a fast (8 min) UHPLC-MS/MS method for analysis of metabolites associated with microbially influenced corrosion (MIC) and bioremediation. Notable parameters that influence extraction efficiency, such as ratios of polymer components, extraction time, desorption time, desorption volume, and desorption solvent, were optimized. Polymer morphology, porosity and surface area were determined using scanning electron microscopy (SEM) and nitrogen adsorption porosimetry (Brunauer Emmett-Teller, BET), respectively. The method achieved limits of detection (LOD) ranging from 0.05-0.2 ng mL-1 and limits of quantitation (LOQ) from 0.1-0.5 ng mL-1 with excellent linearity (R2 > 0.998) over 2-3 orders of magnitude for monocarboxylic acids (e.g., 0.1-500 ng mL-1 for salicylic acid, 0.5-1000 ng mL-1 for o, p, m-toluic acid) and for dicarboxylic metabolites (e.g., 0.5-500 ng mL-1 for phenylsuccinic acid and 0.1-500 ng mL-1 for benzylsuccinic acid). The accuracies from spiked samples ranged from 84-4-108% with %RSD of 1.6-13% for seawater and 83.6-114% with %RSD of 1.3-10.5% for produced water.
在不锈钢底物上制备了一种由2-乙烯基吡啶和1-乙烯基-3-乙基咪唑醋酸酯（FMs）分子印迹聚合物（MIP），用于选择性吸附复杂含水样品中轻芳香烃组分的一羧酸代谢物和二羧酸代谢物。该分析方法具有多重样品处理的特点，对单羧酸（例如水杨酸0.1-500 ng mL-1, o, p， m-甲酸0.5-1000 ng mL-1）和二羧酸代谢物（例如苯琥珀酸0.5-500 ng mL-1和苯琥珀酸0.1-500 ng mL-1）产生高通量的提取和解吸（2.7 h或0.998样品≥45个），超过2-3个数量级。海水加样的准确度为84-4-108%，RSD为1.6-13%；采出水加样的准确度为83.6-114%，RSD为1.3-10.5%。
{"title":"Molecularly imprinted polymer thin film solid phase microextraction for biomarkers of anaerobic metabolism of BTEX by microorganisms involved in bioremediation and in microbially influenced corrosion","authors":"Temitope Odunayo Nwachukwu,Reza Akhoondi,Christina Sheila Bottaro","doi":"10.1039/d6an00943c","DOIUrl":"https://doi.org/10.1039/d6an00943c","url":null,"abstract":"A molecularly imprinted polymer (MIP) composed of 2-vinylpyridine and 1-vinyl-3-ethylimidazolium acetate (FMs) imprinted with homophthalic acid (pseudo-template (T) was fabricated directly on a stainless-steel substrate for selective adsorption of mono- and dicarboxylic acid metabolites of light aromatic components of petrogenic oil from complex aqueous samples. The analytical method features multiplexed sample processing, which yeilds high-throughput extraction and desorption (≥ 45 samples in 2.7 h or <4 min/sample), combined with a fast (8 min) UHPLC-MS/MS method for analysis of metabolites associated with microbially influenced corrosion (MIC) and bioremediation. Notable parameters that influence extraction efficiency, such as ratios of polymer components, extraction time, desorption time, desorption volume, and desorption solvent, were optimized. Polymer morphology, porosity and surface area were determined using scanning electron microscopy (SEM) and nitrogen adsorption porosimetry (Brunauer Emmett-Teller, BET), respectively. The method achieved limits of detection (LOD) ranging from 0.05-0.2 ng mL-1 and limits of quantitation (LOQ) from 0.1-0.5 ng mL-1 with excellent linearity (R2 > 0.998) over 2-3 orders of magnitude for monocarboxylic acids (e.g., 0.1-500 ng mL-1 for salicylic acid, 0.5-1000 ng mL-1 for o, p, m-toluic acid) and for dicarboxylic metabolites (e.g., 0.5-500 ng mL-1 for phenylsuccinic acid and 0.1-500 ng mL-1 for benzylsuccinic acid). The accuracies from spiked samples ranged from 84-4-108% with %RSD of 1.6-13% for seawater and 83.6-114% with %RSD of 1.3-10.5% for produced water.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"44 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149230138","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}
Decentralised point-of-care testing (POCT) is driving a paradigm shift towards non-invasive and minimally invasive continuous health monitoring. While alternative biofluids, such as saliva, sweat, tears, exhaled breath condensate, and interstitial fluid (ISF) offer a patient-centric window into systemic physiology, their clinical utility remains constrained by ultra-low biomarker concentrations, severe matrix complexity, high analytical noise, and ambiguous correlations with established blood reference ranges. This review examines how micro-total analysis systems (µTAS), augmented by advanced functional materials and artificial intelligence (AI), systematically overcome these analytical bottlenecks. We evaluate wearable, implantable, and handheld microfluidic architectures, focusing on how passive fluidic logic and on-chip pre-concentration matrices (e.g., cellulose nanofibers and hydrogels) minimise biofouling and sample attenuation. Furthermore, we assess next-generation transduction modalities, spanning low-power electrochemical arrays, optical colorimetric assays, and vibrational spectroscopy (IR and Raman), amplified by functional porous nanomaterials, including MXenes, metal-organic frameworks (MOFs), and covalent organic frameworks (COFs). Crucially, we detail the pivotal shift from conventional linear calibration models to machine learning (ML)-driven multivariate deconvolution. We review the deployment of computational frameworks-including supervised/unsupervised learning, convolutional neural networks (CNNs), and long short-term memory (LSTM) networks for direct microfluidic signal denoising, dynamic sensor calibration, drift compensation, and multiplexed pattern decoding. Finally, we address the technical, ethical, and regulatory hurdles to clinical translation, highlighting emerging frontiers such as Edge AI and federated learning. Synergistically unifying precision bio-interface fluidics with intelligent data pipelines could help move microfluidic POCT platforms from qualitative screening tools towards quantitative, predictive diagnostics, although most reported systems remain at the prototype or pilot stage and still require prospective clinical validation.
{"title":"Intelligent diagnostics: AI-augmented microfluidic devices for non-invasive and minimally invasive disease biomarker monitoring.","authors":"Akkapol Suea-Ngam, Supacha Wirojsaengthong, Pumidech Puthongkham, Nadnudda Rodthongkum","doi":"10.1039/d6an00751a","DOIUrl":"https://doi.org/10.1039/d6an00751a","url":null,"abstract":"<p><p>Decentralised point-of-care testing (POCT) is driving a paradigm shift towards non-invasive and minimally invasive continuous health monitoring. While alternative biofluids, such as saliva, sweat, tears, exhaled breath condensate, and interstitial fluid (ISF) offer a patient-centric window into systemic physiology, their clinical utility remains constrained by ultra-low biomarker concentrations, severe matrix complexity, high analytical noise, and ambiguous correlations with established blood reference ranges. This review examines how micro-total analysis systems (µTAS), augmented by advanced functional materials and artificial intelligence (AI), systematically overcome these analytical bottlenecks. We evaluate wearable, implantable, and handheld microfluidic architectures, focusing on how passive fluidic logic and on-chip pre-concentration matrices (<i>e.g.</i>, cellulose nanofibers and hydrogels) minimise biofouling and sample attenuation. Furthermore, we assess next-generation transduction modalities, spanning low-power electrochemical arrays, optical colorimetric assays, and vibrational spectroscopy (IR and Raman), amplified by functional porous nanomaterials, including MXenes, metal-organic frameworks (MOFs), and covalent organic frameworks (COFs). Crucially, we detail the pivotal shift from conventional linear calibration models to machine learning (ML)-driven multivariate deconvolution. We review the deployment of computational frameworks-including supervised/unsupervised learning, convolutional neural networks (CNNs), and long short-term memory (LSTM) networks for direct microfluidic signal denoising, dynamic sensor calibration, drift compensation, and multiplexed pattern decoding. Finally, we address the technical, ethical, and regulatory hurdles to clinical translation, highlighting emerging frontiers such as Edge AI and federated learning. Synergistically unifying precision bio-interface fluidics with intelligent data pipelines could help move microfluidic POCT platforms from qualitative screening tools towards quantitative, predictive diagnostics, although most reported systems remain at the prototype or pilot stage and still require prospective clinical validation.</p>","PeriodicalId":63,"journal":{"name":"Analyst","volume":" ","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149230912","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}
Dide Su Demirel,Naci Polat,Hakan Eligul,Zeynep Yegin,Barbaros Cetin,Veli Cengiz Ozalp,Elif Esra Altuner,Ali Dogan Dursun,Gunes Kibar
Saliva is a promising non-invasive specimen for respiratory virus diagnostics but its biochemical complexity challenges direct interfacing with affinity-based biosensors. We report a dual-aptamer magnetic-capture electrochemical assay for detection of influenza B virus (IBV) and human respiratory syncytial virus (hRSV) in artificial saliva. For each target virus, two sequence-distinct DNA aptamers are used: an amino-modified capture aptamer (IBV1 or RSV1) covalently coupled to ~5 µm polydopamine-coated magnetic microparticles by direct Schiff-base reaction with the polydopamine quinone/catechol surface, and a thiol-modified detection aptamer (IBV2 or RSV2) self-assembled on screen-printed gold electrodes via thiol–gold chemistry. After a single multiplexed batch capture step with both aptamer–magnetic-particle types, the pellet is split and analysed in parallel on the two aptamer-modified electrodes by square-wave voltammetry (SWV). Langmuir analysis of the SWV calibration curves yielded apparent dissociation constants of Kd = 177 ± 62 PFU mL⁻¹ (IBV) and 226 ± 85 PFU mL⁻¹ (hRSV), with detection limits of 15 and 11 PFU mL⁻¹, respectively. Log-linear calibration spanned 10¹–10⁴ PFU mL⁻¹ on both channels (n = 4 concentrations, R² = 0.995 and 0.990) with sensitivities of 8.58 and 6.61 µA per decade, so that each virus-specific assay covers three orders of magnitude of viral load. The sequence-orthogonal dual-aptamer geometry — capture and detection recognitions targeting non-identical epitopes — is proposed as the structural mitigation. This proof-of-concept establishes a programmable, saliva-compatible architecture reconfigurable for emerging respiratory pathogens by aptamer substitution alone.
{"title":"Dual-Aptamer Magnetic Capture and Electrochemical Detection of Influenza B and Respiratory Syncytial Viruses in Artificial Saliva","authors":"Dide Su Demirel,Naci Polat,Hakan Eligul,Zeynep Yegin,Barbaros Cetin,Veli Cengiz Ozalp,Elif Esra Altuner,Ali Dogan Dursun,Gunes Kibar","doi":"10.1039/d6an01053a","DOIUrl":"https://doi.org/10.1039/d6an01053a","url":null,"abstract":"Saliva is a promising non-invasive specimen for respiratory virus diagnostics but its biochemical complexity challenges direct interfacing with affinity-based biosensors. We report a dual-aptamer magnetic-capture electrochemical assay for detection of influenza B virus (IBV) and human respiratory syncytial virus (hRSV) in artificial saliva. For each target virus, two sequence-distinct DNA aptamers are used: an amino-modified capture aptamer (IBV1 or RSV1) covalently coupled to ~5 µm polydopamine-coated magnetic microparticles by direct Schiff-base reaction with the polydopamine quinone/catechol surface, and a thiol-modified detection aptamer (IBV2 or RSV2) self-assembled on screen-printed gold electrodes via thiol–gold chemistry. After a single multiplexed batch capture step with both aptamer–magnetic-particle types, the pellet is split and analysed in parallel on the two aptamer-modified electrodes by square-wave voltammetry (SWV). Langmuir analysis of the SWV calibration curves yielded apparent dissociation constants of Kd = 177 ± 62 PFU mL⁻¹ (IBV) and 226 ± 85 PFU mL⁻¹ (hRSV), with detection limits of 15 and 11 PFU mL⁻¹, respectively. Log-linear calibration spanned 10¹–10⁴ PFU mL⁻¹ on both channels (n = 4 concentrations, R² = 0.995 and 0.990) with sensitivities of 8.58 and 6.61 µA per decade, so that each virus-specific assay covers three orders of magnitude of viral load. The sequence-orthogonal dual-aptamer geometry — capture and detection recognitions targeting non-identical epitopes — is proposed as the structural mitigation. This proof-of-concept establishes a programmable, saliva-compatible architecture reconfigurable for emerging respiratory pathogens by aptamer substitution alone.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"8 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149225962","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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