Azita HassanMazandarani, John M. Masterson, William Querido, Andrzej Steplewski, Yi Zhang, Carissa Huynh, Maurice M. Garcia, Andrzej Fertala, Nancy Pleshko
Microplastics (MPs) are environmental contaminants with sizes of the order of less than 5 mm that can enter the human body through inhalation and ingestion. Studies have shown that MPs can pose a threat to human health, and thus evaluation of the presence and potential adverse effects of MPs in tissues is critical. Typical MP studies include enzymatic or chemical tissue digestion that can lead to the loss of some MPs. Moreover, digestion does not allow mapping the location of the contaminant within the tissue architecture. This study aimed to develop a method to evaluate the presence of MPs in histological (thin) sections of tissues without digestion using optical photothermal infrared (O-PTIR) microspectroscopy at sub-micron (500 nm) spatial resolution. Tissue phantoms containing specific amounts and types of MPs and biological tissues were evaluated using polarized light microscopy (PLM) and O-PTIR, and several data analysis approaches were employed to detect MPs in non-digested samples. MPs of sizes from 3 to 85 µm were detected and characterized in tissue phantoms. Furthermore, we detected MPs related to the breakdown products of nylon and cellulose particles in thin sections of biological tissues and discussed obstacles related to the use of database spectra for comparison with O-PTIR spectra, demonstrating the potential of this novel approach and the associated challenges.
{"title":"Optical photothermal infrared spectroscopic assessment of microplastics in tissue models and non-digested human tissue sections","authors":"Azita HassanMazandarani, John M. Masterson, William Querido, Andrzej Steplewski, Yi Zhang, Carissa Huynh, Maurice M. Garcia, Andrzej Fertala, Nancy Pleshko","doi":"10.1039/d5an00241a","DOIUrl":"https://doi.org/10.1039/d5an00241a","url":null,"abstract":"Microplastics (MPs) are environmental contaminants with sizes of the order of less than 5 mm that can enter the human body through inhalation and ingestion. Studies have shown that MPs can pose a threat to human health, and thus evaluation of the presence and potential adverse effects of MPs in tissues is critical. Typical MP studies include enzymatic or chemical tissue digestion that can lead to the loss of some MPs. Moreover, digestion does not allow mapping the location of the contaminant within the tissue architecture. This study aimed to develop a method to evaluate the presence of MPs in histological (thin) sections of tissues without digestion using optical photothermal infrared (O-PTIR) microspectroscopy at sub-micron (500 nm) spatial resolution. Tissue phantoms containing specific amounts and types of MPs and biological tissues were evaluated using polarized light microscopy (PLM) and O-PTIR, and several data analysis approaches were employed to detect MPs in non-digested samples. MPs of sizes from 3 to 85 µm were detected and characterized in tissue phantoms. Furthermore, we detected MPs related to the breakdown products of nylon and cellulose particles in thin sections of biological tissues and discussed obstacles related to the use of database spectra for comparison with O-PTIR spectra, demonstrating the potential of this novel approach and the associated challenges.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"8 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146208826","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}
Megan Wilson, Dhiya Al-Jumeily, Jason Birkett, Iftikhar Khan, Ismail Abbas, Matthew Harper, Sulaf Assi
Cardiovascular diseases (CVDs) and diabetes mellitus (DM) are significant conditions that impact lives around the globe. Frequently employed methods for detecting CVDs and/or DM such as blood work and cardiac catheterisation are often invasive, intrusive and can cause the patient additional physical and psychological harm. Vibrational spectroscopic methods including near-infrared (NIR) spectroscopy have emerged as novel methods for detecting medical conditions and diseases including amyotrophic lateral sclerosis, cancer, DM and periodontitis. NIR spectroscopy's ability to perform rapid and cost-effective analysis saves diagnostic waiting times, providing relief for strained healthcare systems. Moreover, their non-invasive, non-intrusive and non-destructive nature allow application to alternative biological matrices such as hair, fingernails and saliva. Therefore, this work explored the feasibility of NIR spectroscopy paired with machine learning (ML) for detecting CVDs and/or DM in fingernails. NIR spectroscopy successful characterised disease-related spectral features including key NIR regions related to the presence of advanced glycated end-products (AGEs), glycated proteins and DM. To further assess the detective capabilities of NIR spectroscopy, classification models were trained. Cubic and quadratic support vector machine (SVM) models demonstrated accuracy in terms of the classification of healthy, CVD and diabetic fingernails. Accuracy was further improved through binary classification models, which allowed the independent classification of CVD and DM spectra against healthy spectra. In summary, NIR spectroscopy combined with ML provided accurate detection for CVDs and DM in fingernails.
{"title":"Exploring the feasibility of near-infrared spectroscopy and machine learning for detecting cardiovascular diseases and diabetes mellitus in fingernails","authors":"Megan Wilson, Dhiya Al-Jumeily, Jason Birkett, Iftikhar Khan, Ismail Abbas, Matthew Harper, Sulaf Assi","doi":"10.1039/d5an01061f","DOIUrl":"https://doi.org/10.1039/d5an01061f","url":null,"abstract":"Cardiovascular diseases (CVDs) and diabetes mellitus (DM) are significant conditions that impact lives around the globe. Frequently employed methods for detecting CVDs and/or DM such as blood work and cardiac catheterisation are often invasive, intrusive and can cause the patient additional physical and psychological harm. Vibrational spectroscopic methods including near-infrared (NIR) spectroscopy have emerged as novel methods for detecting medical conditions and diseases including amyotrophic lateral sclerosis, cancer, DM and periodontitis. NIR spectroscopy's ability to perform rapid and cost-effective analysis saves diagnostic waiting times, providing relief for strained healthcare systems. Moreover, their non-invasive, non-intrusive and non-destructive nature allow application to alternative biological matrices such as hair, fingernails and saliva. Therefore, this work explored the feasibility of NIR spectroscopy paired with machine learning (ML) for detecting CVDs and/or DM in fingernails. NIR spectroscopy successful characterised disease-related spectral features including key NIR regions related to the presence of advanced glycated end-products (AGEs), glycated proteins and DM. To further assess the detective capabilities of NIR spectroscopy, classification models were trained. Cubic and quadratic support vector machine (SVM) models demonstrated accuracy in terms of the classification of healthy, CVD and diabetic fingernails. Accuracy was further improved through binary classification models, which allowed the independent classification of CVD and DM spectra against healthy spectra. In summary, NIR spectroscopy combined with ML provided accurate detection for CVDs and DM in fingernails.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"4 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146205657","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}
Erick G. Báez Bolívar, Jessica S. Fortin, Taiwo A. Ademoye, Scott A. McLuckey
Native mass spectrometry implemented with theta emitters was used to demonstrate differences in conformational states of wild-type, A53T mutant, and truncated α-synuclein dissolved at physiologically relevant pH and Na+ concentrations compared to aqueous solutions of ammonium acetate. Specifically, 150 mM NaCl at pH 7.4, 20 mM NaCl at pH 4.5, and 15 mM NaCl at pH 7.2 were used to reflect, to some extent, the extracellular environment, lysosome, and cytosol, respectively. Analysis of charge state distributions obtained from physiologically relevant solutions vs. their ammonium acetate counterparts allows the comparison of α-synuclein conformational states. The protein shows relatively high conformational flexibility at 150 mM NaCl and pH 7.4, while it shows at least two different conformational states at 20 mM NaCl and pH 4.5. We observed a trend towards the adoption of less compact conformations at acidic pH, where Na+ appears to play a distinctive role in the adoption of different conformational states. Early-stage oligomers (dimer, pentamer, hexamer and heptamer) were also detected. Since oligomer formation was protein-specific, wild-type α-synuclein formed dimers while truncated α-synuclein formed pentamers, hexamers and heptamers, their abundances are consistent with kinetics of aggregation reported in the literature.
采用theta发射器进行的原生质谱分析显示，与醋酸铵水溶液相比，野生型、A53T突变型和截断型α-突触核蛋白在生理相关的pH和Na+浓度下溶解的构象状态存在差异。具体来说，在pH 7.4时使用150 mM NaCl，在pH 4.5时使用20 mM NaCl，在pH 7.2时使用15 mM NaCl在一定程度上分别反映细胞外环境、溶酶体和细胞质。从生理相关溶液和相应的乙酸铵溶液中获得的电荷态分布分析允许比较α-突触核蛋白构象状态。该蛋白在150 mM NaCl和pH 7.4条件下表现出较高的构象柔韧性，而在20 mM NaCl和pH 4.5条件下表现出至少两种不同的构象状态。我们观察到在酸性pH下采用不致密构象的趋势，其中Na+似乎在采用不同构象状态中起着独特的作用。早期低聚物（二聚体、五聚体、六聚体和七聚体）也被检测到。由于低聚物的形成是蛋白质特异性的，野生型α-突触核蛋白形成二聚体，而截断的α-突触核蛋白形成五聚体、六聚体和七聚体，因此它们的丰度与文献报道的聚集动力学一致。
{"title":"Differences in α-synuclein conformational states in physiologically relevant pH/Na+ concentrations and ammonium acetate solutions unveiled by native mass spectrometry","authors":"Erick G. Báez Bolívar, Jessica S. Fortin, Taiwo A. Ademoye, Scott A. McLuckey","doi":"10.1039/d5an01336d","DOIUrl":"https://doi.org/10.1039/d5an01336d","url":null,"abstract":"Native mass spectrometry implemented with theta emitters was used to demonstrate differences in conformational states of wild-type, A53T mutant, and truncated α-synuclein dissolved at physiologically relevant pH and Na<small><sup>+</sup></small> concentrations compared to aqueous solutions of ammonium acetate. Specifically, 150 mM NaCl at pH 7.4, 20 mM NaCl at pH 4.5, and 15 mM NaCl at pH 7.2 were used to reflect, to some extent, the extracellular environment, lysosome, and cytosol, respectively. Analysis of charge state distributions obtained from physiologically relevant solutions <em>vs.</em> their ammonium acetate counterparts allows the comparison of α-synuclein conformational states. The protein shows relatively high conformational flexibility at 150 mM NaCl and pH 7.4, while it shows at least two different conformational states at 20 mM NaCl and pH 4.5. We observed a trend towards the adoption of less compact conformations at acidic pH, where Na<small><sup>+</sup></small> appears to play a distinctive role in the adoption of different conformational states. Early-stage oligomers (dimer, pentamer, hexamer and heptamer) were also detected. Since oligomer formation was protein-specific, wild-type α-synuclein formed dimers while truncated α-synuclein formed pentamers, hexamers and heptamers, their abundances are consistent with kinetics of aggregation reported in the literature.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"18 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146205656","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}
Mônica Duarte da Silva, Ruth Speidel, Ayesha Seth, Hianka J.C. de Carvalho, Maria Miglino, Abraham K. Badu-Tawiah
Long COVID is characterized by persistent symptoms, including fatigue, cognitive impairment, and respiratory issues, affecting a considerable number of individuals post-infection. The underlying mechanism is not fully understood, but it has been proposed to involve the reactivation of virus, which subsequently induces immune dysregulation. In this proof-of-concept study, we developed a paper-based immunoassay for the detection of the nucleocapsid (N) protein, which due to its stability and low mutation rate, is a valuable biomarker for detecting residual viral presence. By utilizing reporter antibodies conjugated to cleavable ionic probes through dendrimer chemistry, we were able to analyze the immunoassay results with ambient mass spectrometry using on-chip paper spray ionization. The used dendrimer enhanced mass spectrometry sensitivity by enabling the attachment of multiple ionic probes to a single reporter antibody. The method presented here achieved a limit of detection of 2.4 pM for N protein detection from paper. Unlike traditional sensitive COVID tests that are only accessible to hospitalized individuals, our paper-based assay has potential to enable long COVID to be detected under resource-limited settings. Our method was applied to analyze 20 human plasma samples, including 10 from individuals with long COVID and 10 from healthy controls with no history of SARS-CoV-2 infection. We observed a significantly higher MS signal—up to two orders of magnitude—for samples collected from long COVID patients compared to controls. The ability to use the paper device in remote locations tested by evaluating the stability of the assay, which showed that after 30 days of storage at room temperature, the device retained sufficient analytical performance. Given this robustness, we believe our platform will be suitable for direct-to-consumer testing, enabling individuals with low viral loads to be screened in a timely fashion.
{"title":"Paper-Based Immunoassay with Signal Amplification for Sensitive Detection of Nucleocapsid Protein Toward the Diagnosis of Long COVID","authors":"Mônica Duarte da Silva, Ruth Speidel, Ayesha Seth, Hianka J.C. de Carvalho, Maria Miglino, Abraham K. Badu-Tawiah","doi":"10.1039/d5an01267h","DOIUrl":"https://doi.org/10.1039/d5an01267h","url":null,"abstract":"Long COVID is characterized by persistent symptoms, including fatigue, cognitive impairment, and respiratory issues, affecting a considerable number of individuals post-infection. The underlying mechanism is not fully understood, but it has been proposed to involve the reactivation of virus, which subsequently induces immune dysregulation. In this proof-of-concept study, we developed a paper-based immunoassay for the detection of the nucleocapsid (N) protein, which due to its stability and low mutation rate, is a valuable biomarker for detecting residual viral presence. By utilizing reporter antibodies conjugated to cleavable ionic probes through dendrimer chemistry, we were able to analyze the immunoassay results with ambient mass spectrometry using on-chip paper spray ionization. The used dendrimer enhanced mass spectrometry sensitivity by enabling the attachment of multiple ionic probes to a single reporter antibody. The method presented here achieved a limit of detection of 2.4 pM for N protein detection from paper. Unlike traditional sensitive COVID tests that are only accessible to hospitalized individuals, our paper-based assay has potential to enable long COVID to be detected under resource-limited settings. Our method was applied to analyze 20 human plasma samples, including 10 from individuals with long COVID and 10 from healthy controls with no history of SARS-CoV-2 infection. We observed a significantly higher MS signal—up to two orders of magnitude—for samples collected from long COVID patients compared to controls. The ability to use the paper device in remote locations tested by evaluating the stability of the assay, which showed that after 30 days of storage at room temperature, the device retained sufficient analytical performance. Given this robustness, we believe our platform will be suitable for direct-to-consumer testing, enabling individuals with low viral loads to be screened in a timely fashion.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"45 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146205670","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}
This review provides a systematic integration of deep eutectic solvents (DESs) into molecular imprinting, establishing DES-based molecularly imprinted polymers (DES-MIPs) as an emerging class of green affinity materials. The present review emphasizes the diverse functional roles of DESs in the synthesis of MIPs, as well as the reaction mechanisms of their components, hydrogen bond acceptors (HBAs) and hydrogen bond donors (HBDs). It systematically covers the fundamental principles of molecular imprinting, highlighting the advantages and mechanisms of DES-based imprinting over traditional MIP approaches, such as the ability of DESs to act as functional monomers for polymerization, templates to guide imprint site formation, porogens for the regulation of polymer pore structure, and eluents for the efficient removal of templates. Furthermore, the specific applications of DES-based MIPs in food safety, environmental monitoring, and biomedical analysis are described, and future perspectives for this field are discussed.
{"title":"Deep Eutectic Solvents in Molecularly Imprinted Materials: A Comprehensive Review of Functional Roles and Recent Advances","authors":"Dongdong Cheng, Xin Wang, Jia Li, Yongquan Dai, Pen Jin, Yi Li, Lina Lu, Xingping Luo, Jun Lin, Zegen Wang, Binlian Jiang, Xiaodong Wei, Zhijun Wang, Shuo Feng","doi":"10.1039/d5an01278c","DOIUrl":"https://doi.org/10.1039/d5an01278c","url":null,"abstract":"This review provides a systematic integration of deep eutectic solvents (DESs) into molecular imprinting, establishing DES-based molecularly imprinted polymers (DES-MIPs) as an emerging class of green affinity materials. The present review emphasizes the diverse functional roles of DESs in the synthesis of MIPs, as well as the reaction mechanisms of their components, hydrogen bond acceptors (HBAs) and hydrogen bond donors (HBDs). It systematically covers the fundamental principles of molecular imprinting, highlighting the advantages and mechanisms of DES-based imprinting over traditional MIP approaches, such as the ability of DESs to act as functional monomers for polymerization, templates to guide imprint site formation, porogens for the regulation of polymer pore structure, and eluents for the efficient removal of templates. Furthermore, the specific applications of DES-based MIPs in food safety, environmental monitoring, and biomedical analysis are described, and future perspectives for this field are discussed.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"32 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146205671","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}
Jiani Wang, Fuxian Ge, Jing Wang, Di Zhang, Miran Tang
MicroRNAs (miRNAs) are highly promising biomarkers, especially in the diagnosis, prognosis and therapeutic monitoring of diseases such as cancer. DNA as a unique nanostructure makes it particularly useful in biosensing. Catalytic hairpin assembly (CHA) is a promising enzyme-free and efficient isothermal amplification method. However, its performance and application value are limited by background signals. This study presented shielded loop-mediated catalytic hairpin assembly (SL-CHA). Complementary nucleic acids were introduced into the hairpin loop to inhibit the activity of single-stranded bases, and CHA exhibited lower background signal with the same signal amplification ability. SL-CHA showed better performance in miRNA-224-5p detection in serum, demonstrating its good potential for the clinical detection of miRNAs.
{"title":"Shielded loop-mediated catalytic hairpin assembly for the specific detection of microRNA","authors":"Jiani Wang, Fuxian Ge, Jing Wang, Di Zhang, Miran Tang","doi":"10.1039/d5an00955c","DOIUrl":"https://doi.org/10.1039/d5an00955c","url":null,"abstract":"MicroRNAs (miRNAs) are highly promising biomarkers, especially in the diagnosis, prognosis and therapeutic monitoring of diseases such as cancer. DNA as a unique nanostructure makes it particularly useful in biosensing. Catalytic hairpin assembly (CHA) is a promising enzyme-free and efficient isothermal amplification method. However, its performance and application value are limited by background signals. This study presented shielded loop-mediated catalytic hairpin assembly (SL-CHA). Complementary nucleic acids were introduced into the hairpin loop to inhibit the activity of single-stranded bases, and CHA exhibited lower background signal with the same signal amplification ability. SL-CHA showed better performance in miRNA-224-5p detection in serum, demonstrating its good potential for the clinical detection of miRNAs.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"99 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146184509","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}
We report fluorescent digital pH probes based on a polymeric design comprising thermoresponsive, proton-binding and environment-sensitive fluorescent units. At selected temperatures, fluorescence switching was nearly complete, with a slight pH variation of <1 unit. The fluorescence-switching mechanism involved a proton-induced three-dimensional structural change in the polymer, which altered local hydrophobicity near the environment-sensitive fluorescent units. Based on the change in local hydrophobicity during operation, extremely sharp responses were produced because of the variation in proton-binding abilities of the probes. The polymeric design ensured functional flexibility, including a pH-responsive region and a direction of fluorescence switching. As an application of fluorescent digital pH probes, intracellular logic operations were performed by varying the pH and temperature. By distinguishing the minute pH and temperature difference inside mammalian cells, a specific condition — high pH and temperature — generated strong fluorescence with an extended fluorescence lifetime, as confirmed via fluorescence-lifetime imaging microscopy.
{"title":"Digital Fluorescent pH Probes: Polymer-Based Design, Fluorescence Response, Mechanism, Functional Tuning and Application to Logic Operation in Live Cells","authors":"Seiichi Uchiyama, Eiko Hamada, Masaharu Takarada, Kohki Okabe","doi":"10.1039/d5an01187f","DOIUrl":"https://doi.org/10.1039/d5an01187f","url":null,"abstract":"We report fluorescent digital pH probes based on a polymeric design comprising thermoresponsive, proton-binding and environment-sensitive fluorescent units. At selected temperatures, fluorescence switching was nearly complete, with a slight pH variation of <1 unit. The fluorescence-switching mechanism involved a proton-induced three-dimensional structural change in the polymer, which altered local hydrophobicity near the environment-sensitive fluorescent units. Based on the change in local hydrophobicity during operation, extremely sharp responses were produced because of the variation in proton-binding abilities of the probes. The polymeric design ensured functional flexibility, including a pH-responsive region and a direction of fluorescence switching. As an application of fluorescent digital pH probes, intracellular logic operations were performed by varying the pH and temperature. By distinguishing the minute pH and temperature difference inside mammalian cells, a specific condition — high pH and temperature — generated strong fluorescence with an extended fluorescence lifetime, as confirmed via fluorescence-lifetime imaging microscopy.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"11 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146184411","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 this study, classification models based on Laser-induced breakdown spectroscopy (LIBS) technology, combined with machine learning (ML) and deep learning (DL) algorithms, were proposed to enable the rapid and high-precision classification of small specimen uranium ores. LIBS spectral data from 12 types of uranium ore samples were collected and subsequently subjected to standard normal variate (SNV) preprocessing before model construction. The classification models were constructed using the random forest (RF) algorithm and three DL algorithms—feedforward neural network (FNN), cconvolutional neural network (CNN), and long short-term memory (LSTM)—incorporating two feature extraction methods: least absolute shrinkage and selection operator (LASSO) and principal component analysis (PCA). The classification performance and generalization ability of the different models and feature extraction strategies were systematically evaluated. It was found that the RF model exhibited significant overfitting when the training set size was small, and its performance improvement required an increase in training set proportion. When LASSO feature selection was incorporated, the DL models outperformed the RF model, although some misclassifications were still observed. In contrast, PCA, which utilized only the first five principal components, effectively retained the global discriminative information of the spectra. All DL models based on PCA features achieved 100% classification accuracy for both the training and testing sets. This study demonstrates that PCA can effectively extract global spectral information, overcoming the limitations posed by small specimens in LIBS classification tasks for uranium ores. When combined with DL models, PCA significantly improves classification performance and generalization ability, offering a reliable technical pathway for the rapid and accurate identification of small specimen uranium ores.
{"title":"Classification of small specimen uranium ores using LIBS combined with machine learning and deep learning algorithms","authors":"Jingrong Li, Xiaoliang Liu, Ming Zhang, Xiangting Meng, Hua Rong, Shaohua Sun, Zuoye Liu, Chunyan Zou, Xiaoyang Guo","doi":"10.1039/d5an01326g","DOIUrl":"https://doi.org/10.1039/d5an01326g","url":null,"abstract":"In this study, classification models based on Laser-induced breakdown spectroscopy (LIBS) technology, combined with machine learning (ML) and deep learning (DL) algorithms, were proposed to enable the rapid and high-precision classification of small specimen uranium ores. LIBS spectral data from 12 types of uranium ore samples were collected and subsequently subjected to standard normal variate (SNV) preprocessing before model construction. The classification models were constructed using the random forest (RF) algorithm and three DL algorithms—feedforward neural network (FNN), cconvolutional neural network (CNN), and long short-term memory (LSTM)—incorporating two feature extraction methods: least absolute shrinkage and selection operator (LASSO) and principal component analysis (PCA). The classification performance and generalization ability of the different models and feature extraction strategies were systematically evaluated. It was found that the RF model exhibited significant overfitting when the training set size was small, and its performance improvement required an increase in training set proportion. When LASSO feature selection was incorporated, the DL models outperformed the RF model, although some misclassifications were still observed. In contrast, PCA, which utilized only the first five principal components, effectively retained the global discriminative information of the spectra. All DL models based on PCA features achieved 100% classification accuracy for both the training and testing sets. This study demonstrates that PCA can effectively extract global spectral information, overcoming the limitations posed by small specimens in LIBS classification tasks for uranium ores. When combined with DL models, PCA significantly improves classification performance and generalization ability, offering a reliable technical pathway for the rapid and accurate identification of small specimen uranium ores.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"46 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146160608","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}
Lipidomics has emerged as a vital discipline for understanding cellular metabolism and disease pathology. However, the immense structural diversity, wide dynamic range, and varying ionization efficiencies of lipids present significant analytical challenges. MS analysis workflow often falls short in detecting low abundance species and resolving complex structural isomers. To address these limitations, chemical derivatization has been widely adopted to manipulate the chemical properties of lipids prior to analysis. This review summarizes the significant progress in chemical derivatization-enabled lipidomics over the past decades, highlighting its pivotal role in bridging the gap between analytical capability and biological complexity. We critically discuss three core dimensions of improvement: (1) enhancement of detection sensitivity through derivatization strategies that increase ionization efficiency of lipids; (2) refinement of structural elucidation, specifically using selective reactions to pinpoint carbon-carbon double bond locations and differentiate isomers; and (3) advancement of spectrometric specificity and quantification via mass-shift profiling, which enables precise quantification or high-throughput multiplex analysis. Finally, we discuss how these chemical tools are facilitating the discovery of novel lipid biomarkers and providing deeper insights into lipid metabolism in biomedical research.
{"title":"Chemical Reaction-Enabled Lipidomics: From Sensitive Structural Analysis to Biomedical Applications","authors":"Qirui Yu, Xiaoxiao Ma","doi":"10.1039/d5an01334h","DOIUrl":"https://doi.org/10.1039/d5an01334h","url":null,"abstract":"Lipidomics has emerged as a vital discipline for understanding cellular metabolism and disease pathology. However, the immense structural diversity, wide dynamic range, and varying ionization efficiencies of lipids present significant analytical challenges. MS analysis workflow often falls short in detecting low abundance species and resolving complex structural isomers. To address these limitations, chemical derivatization has been widely adopted to manipulate the chemical properties of lipids prior to analysis. This review summarizes the significant progress in chemical derivatization-enabled lipidomics over the past decades, highlighting its pivotal role in bridging the gap between analytical capability and biological complexity. We critically discuss three core dimensions of improvement: (1) enhancement of detection sensitivity through derivatization strategies that increase ionization efficiency of lipids; (2) refinement of structural elucidation, specifically using selective reactions to pinpoint carbon-carbon double bond locations and differentiate isomers; and (3) advancement of spectrometric specificity and quantification via mass-shift profiling, which enables precise quantification or high-throughput multiplex analysis. Finally, we discuss how these chemical tools are facilitating the discovery of novel lipid biomarkers and providing deeper insights into lipid metabolism in biomedical research.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"24 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146160611","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}
Hydrogen sulfide (H2S) has emerged as a key neuromodulator in the central nervous system, yet its accurate quantification in the complex brain system remains challenging due to strong interference from endogenous thiols and other sulfur-containing species. Here, we report an excited-state intramolecular proton transfer (ESIPT)-based fluorescent probe designed for selective and sensitive detection of H2S. The probe incorporates a cyano-substituted carbamate unit that suppresses ESIPT, producing a distinct turn-on fluorescence response at 594 nm upon H2S-induced cleavage. Probe exhibits a substantial linear fluorescence enhancement in the range of 2-50 μM (R2 = 0.997) with a low detection limit of 0.206 μM. The reaction product displays excellent fluorescence stability over several hours, minimal sensitivity to pH variations under physiological conditions, and outstanding selectivity against biologically abundant ions, reactive species, thiols, and amino acids. Importantly, Probe enabled reliable quantification of endogenous H2S in hippocampal microdialysates from normal and Parkinson’s disease (PD) mice. These findings demonstrate the potential of Probe as a robust analytical tool for studying H2S dynamics in neurochemical processes.
{"title":"Selective Fluorescent Detection of Hydrogen Sulfide in the Brain microdialysate Using an ESIPT-Activated Probe","authors":"Qian Wang, Cong Luo, Jingyi Tang, Zhaolun Duan, Hui Pan, Huihui Wang, Haoyue Xiang, Hui Gu","doi":"10.1039/d5an01258a","DOIUrl":"https://doi.org/10.1039/d5an01258a","url":null,"abstract":"Hydrogen sulfide (H2S) has emerged as a key neuromodulator in the central nervous system, yet its accurate quantification in the complex brain system remains challenging due to strong interference from endogenous thiols and other sulfur-containing species. Here, we report an excited-state intramolecular proton transfer (ESIPT)-based fluorescent probe designed for selective and sensitive detection of H2S. The probe incorporates a cyano-substituted carbamate unit that suppresses ESIPT, producing a distinct turn-on fluorescence response at 594 nm upon H2S-induced cleavage. Probe exhibits a substantial linear fluorescence enhancement in the range of 2-50 μM (R2 = 0.997) with a low detection limit of 0.206 μM. The reaction product displays excellent fluorescence stability over several hours, minimal sensitivity to pH variations under physiological conditions, and outstanding selectivity against biologically abundant ions, reactive species, thiols, and amino acids. Importantly, Probe enabled reliable quantification of endogenous H2S in hippocampal microdialysates from normal and Parkinson’s disease (PD) mice. These findings demonstrate the potential of Probe as a robust analytical tool for studying H2S dynamics in neurochemical processes.","PeriodicalId":63,"journal":{"name":"Analyst","volume":"96 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146153508","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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