Analytical Methods最新文献_第5页

Advancements in gas chromatography-ion mobility spectrometry for analysing natural medicines 气相色谱-离子迁移谱法分析天然药物的研究进展。

IF 2.7 3区化学

Analytical Methods Pub Date : 2025-07-02 DOI: 10.1039/D5AY00439J

Yanan Xu, Ruien Li, Lequn Zhang, Xueyuan Bai and Wei Zhang

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Validated green ultra-fast UPLC-MS/MS method for the quantification of fedratinib in an HLM matrix: application to in vitro and in silico metabolic stability studies† 高效液相色谱-串联质谱（UPLC-MS/MS）绿色超快速定量分析法在体外和体内代谢稳定性研究中的应用

IF 2.7 3区化学

Analytical Methods Pub Date : 2025-07-01 DOI: 10.1039/D5AY00513B

Mohamed W. Attwa, Ali S. Abdelhameed and Adnan A. Kadi

{"title":"Validated green ultra-fast UPLC-MS/MS method for the quantification of fedratinib in an HLM matrix: application to in vitro and in silico metabolic stability studies†","authors":"Mohamed W. Attwa, Ali S. Abdelhameed and Adnan A. Kadi","doi":"10.1039/D5AY00513B","DOIUrl":"10.1039/D5AY00513B","url":null,"abstract":"Fedratinib (INREBIC®; FDB), an orally administered selective Janus kinase 2 (JAK-2) inhibitor, has been approved by the FDA for the treatment of intermediate-2 or high-risk primary or secondary myelofibrosis in adult patients. This study established a sensitive, fast, green, and dependable UPLC-MS/MS approach for quantifying FDB in human liver microsomes (HLMs); moreover, this approach was employed to assess the in vitro metabolic stability of FDB in HLMs. The validation steps of the UPLC-MS/MS approach adhered to the US-FDA principles for bioanalytical method validation. The StarDrop program, incorporating the DEREK and P450 modules, was employed to monitor the FDB chemical structure alerts and in silico metabolic lability, respectively. FDB and encorafenib (ENB as the IS) were analyzed using the isocratic mobile phase method on an Eclipse Plus C18 column. The developed UPLC-MS/MS method exhibited an ultra-fast (1 min), wide linearity range (1.0–3000 ng mL−1) with good separation of the target analytes and was accurate and reproducible in the absence of HLM matrix effects. The current study evaluated the precision and accuracy of the UPLC-MS/MS method for intra-day and inter-day assessments, varying from −5.33% to 5.56% and −9.00% to 6.67%, respectively. The intrinsic clearance (Clint) of FDB was measured at 34.86 mL min−1 kg−1, whereas the in vitro half-life (t1/2) was determined to be 23.26 min. In silico screening indicated that minor structural modifications to the pyrrolidine moiety in the process of drug design could increase metabolic stability and enhance safety relative to FDB. The assessment of in silico FDB ADME properties and metabolic stability is important for the progression of novel drug discovery aimed at improving metabolic stability.","PeriodicalId":64,"journal":{"name":"Analytical Methods","volume":" 27","pages":" 5714-5725"},"PeriodicalIF":2.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144525526","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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Deciphering the differences in aroma components of tobacco from different origins based on HS-GC-IMS and multivariate statistical analysis† 基于HS-GC-IMS和多元统计分析的不同产地烟草香气成分差异分析

IF 2.7 3区化学

Analytical Methods Pub Date : 2025-07-01 DOI: 10.1039/D5AY00531K

Suxuan Li, Ningyang Mao, Cong Chen, Hui Zhao, Xiaoyu Chen, Liusheng Wang, Fuyun Cui, Wenning Feng and Zhiyong Wu

{"title":"Deciphering the differences in aroma components of tobacco from different origins based on HS-GC-IMS and multivariate statistical analysis†","authors":"Suxuan Li, Ningyang Mao, Cong Chen, Hui Zhao, Xiaoyu Chen, Liusheng Wang, Fuyun Cui, Wenning Feng and Zhiyong Wu","doi":"10.1039/D5AY00531K","DOIUrl":"10.1039/D5AY00531K","url":null,"abstract":"This study employed headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) technology combined with multivariate statistical analysis methods to analyze the flavor compounds in flue-cured tobacco from five different regions in China: Henan, Hunan, Yunnan, Chongqing, and Fujian. A total of 98 volatile aroma compounds were identified through HS-GC-IMS analysis, including esters, ketones, aldehydes, acids, alcohols, heterocyclic compounds, sulfur-containing compounds, other types of compounds, and 8 uncharacterized compounds. Principal Component Analysis (PCA) and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) were utilized to conduct dimensionality reduction and distinguish the samples, effectively recognizing differences in volatile compounds among tobacco leaves from various origins. A Random Forest (RF) classification model was constructed, and its reliability was validated through ROC (Receiver Operating Characteristic) analysis, achieving an AUC (Area Under the Curve) value of 0.980, which demonstrates exceptional predictive performance. PCA revealed distinct separations of tobacco leaf samples from different regions on the PCA score plot, and OPLS-DA analysis further validated these differences and confirmed the model's validity through permutation testing. Twenty key aroma compounds with VIP > 1.0 were screened by integrating OPLS-DA with the Random Forest classification model. These compounds showed significant differences in content among different samples, suggesting their potential as chemical markers for distinguishing the origin of flue-cured tobacco. This study not only provides a new method for identifying volatile compounds in tobacco but also offers novel insights into the geographical identification of flue-cured tobacco.","PeriodicalId":64,"journal":{"name":"Analytical Methods","volume":" 27","pages":" 5736-5748"},"PeriodicalIF":2.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144525523","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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Molecularly imprinted polymer filter modified with natural polyphenols for extraction of levothyroxine from biological samples† 天然多酚修饰的分子印迹聚合物过滤器用于生物样品中左甲状腺素的提取。

IF 2.7 3区化学

Analytical Methods Pub Date : 2025-07-01 DOI: 10.1039/D5AY00617A

Fatemeh Yeksan and Tahere Khezeli

{"title":"Molecularly imprinted polymer filter modified with natural polyphenols for extraction of levothyroxine from biological samples†","authors":"Fatemeh Yeksan and Tahere Khezeli","doi":"10.1039/D5AY00617A","DOIUrl":"10.1039/D5AY00617A","url":null,"abstract":"In this study, a molecularly imprinted polymer (MIP) filter, modified with natural polyphenols extracted from green tea, was employed for the extraction of levothyroxine, followed by analysis via high-performance liquid chromatography with ultraviolet-visible detection (HPLC-UV). The filter's characteristics were comprehensively assessed using Fourier-transform infrared spectroscopy (FT-IR) to identify functional groups, scanning electron microscopy (SEM) to examine surface morphology, energy-dispersive spectroscopy (EDS) for elemental analysis, and X-ray diffraction (XRD) to elucidate crystalline structure. Following the passage of sample solutions through the filter, which was integrated with a solvent delivery system, and optimization of extraction parameters by response surface methodology (RSM), a linear range of 1 to 1000 μg L−1 was achieved for levothyroxine, with a coefficient of determination of 0.9999. The limit of detection and limit of quantification were 0.36 μg L−1 and 1.19 μg L−1, respectively. The method has an enrichment factor ranging from 245.0 to 250.5. Furthermore, the effect of the matrix on the extraction was insignificant. Applying this method to biological samples of blood serum and urine yielded recoveries exceeding 98.3%, with RSD below 6.1%.","PeriodicalId":64,"journal":{"name":"Analytical Methods","volume":" 28","pages":" 5951-5960"},"PeriodicalIF":2.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144574487","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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Quantification of four arsenic species in dried seafood via pressure tank-assisted extraction with HPLC-AFS† 压力罐辅助萃取-高效液相色谱法定量测定海产品中4种砷。

IF 2.7 3区化学

Analytical Methods Pub Date : 2025-07-01 DOI: 10.1039/D5AY00204D

Caijuan Ma, Peipei Ouyang, Qianqing Zheng and Fubao Qiu

{"title":"Quantification of four arsenic species in dried seafood via pressure tank-assisted extraction with HPLC-AFS†","authors":"Caijuan Ma, Peipei Ouyang, Qianqing Zheng and Fubao Qiu","doi":"10.1039/D5AY00204D","DOIUrl":"10.1039/D5AY00204D","url":null,"abstract":"A method for the rapid separation and detection of dimethylarsenate (DMA), arsenite [As(III)], monomethylarsenate (MMA), and arsenate [As(V)] was developed. This method combined high performance liquid chromatography with atomic fluorescence spectrometry (HPLC-AFS) via pressure tank-assisted extraction. Key parameters, including extraction temperature, extraction time, and extraction liquid concentration, were systematically investigated. Through orthogonal testing of the three factors at three levels, the optimal extraction conditions were identified as a nitric acid solution concentration of 1%, an extraction temperature of 150 °C, and an extraction time of 75 min. The results demonstrated that the four arsenic species could be completely separated within 6 min. Good linear relationships were observed in the concentration range of 1.00–100.0 μg L−1 for all species, with detection limits ranging from 0.21 to 0.85 μg L−1. The recoveries were between 88.6% and 103%, with relative standard deviations ranging from 1.4% to 4.8%. The method was successfully applied to detect the concentrations of arsenic species in dried seafood products, and it yielded satisfactory results. Moreover, the total arsenic concentration was quantified using atomic fluorescence spectrometry after wet digestion. The total concentration of arsenic in the samples was between 4.22 mg kg−1 and 24.4 mg kg−1, and the extraction efficiency, calculated as the percentage of the total arsenic species content extracted by the method to the total arsenic concentration, ranged from 1.35% to 13.5%. Notably, the inorganic arsenic levels in the analyzed samples were below the established safety limits.","PeriodicalId":64,"journal":{"name":"Analytical Methods","volume":" 27","pages":" 5726-5735"},"PeriodicalIF":2.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144525524","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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Correction: Real-time kinetic analysis and detection of glycated hemoglobin A1c using a quartz crystal microbalance-based aptasensor 校正：实时动态分析和检测糖化血红蛋白A1c使用石英晶体微天平为基础的适体传感器。

IF 2.7 3区化学

Analytical Methods Pub Date : 2025-06-30 DOI: 10.1039/D5AY90083B

Yossawadee Sriondee, Pasara Vijitvarasan, Arunothai Rattanachata, Hideki Nakajima, Sukunya Oaew and Sarawut Cheunkar

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Fast identification of influenza using label-free SERS combined with machine learning algorithms via clinical nasal swab samples† 通过临床鼻拭子样本使用无标记SERS结合机器学习算法快速识别流感。

IF 2.7 3区化学

Analytical Methods Pub Date : 2025-06-30 DOI: 10.1039/D5AY00374A

Shaohua He, Shibo Cao, Jiayi Yuan, Zhaoda Yu, Yi Liu, Yangmin Wu, Shuohong Weng, Ming Zong and Duo Lin

{"title":"Fast identification of influenza using label-free SERS combined with machine learning algorithms via clinical nasal swab samples†","authors":"Shaohua He, Shibo Cao, Jiayi Yuan, Zhaoda Yu, Yi Liu, Yangmin Wu, Shuohong Weng, Ming Zong and Duo Lin","doi":"10.1039/D5AY00374A","DOIUrl":"10.1039/D5AY00374A","url":null,"abstract":"Influenza virus outbreaks, which have become more frequent in recent years, have attracted global attention. Reverse transcription-polymerase chain reaction (RT-PCR) and enzyme-linked immunosorbent assay (ELISA), as the “gold standard” methods for virus detection, are not suitable for rapid diagnosis of the virus because of their long reaction time and sample preparation time. Therefore, a new method for influenza virus detection that is rapid, accurate and portable is needed. In this work, a label-free technology based on surface enhanced Raman spectroscopy was developed to directly analyse nasal swab samples in order to explore the molecular differences between influenza patients and normal people. Following that, machine learning algorithms based on Principal Component Analysis combined with Linear Discriminant Analysis (PCA-LDA) and Support Vector Machines (SVM) were used to extract and model the molecular features of nasal fluid to differentiate between influenza patients and normal people with an accuracy of 76.5%. With only 10 μL of sample and 5 seconds of testing time per sample, this label-free SERS combined with machine learning would provide a rapid and portable testing platform for influenza virus detection.","PeriodicalId":64,"journal":{"name":"Analytical Methods","volume":" 29","pages":" 6117-6123"},"PeriodicalIF":2.7,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144625021","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}

引用次数: 0

Rapid detection of colorants in black tea using mid- and short-wave near infrared spectroscopy† 中短波近红外光谱快速检测红茶中的着色剂。

IF 2.7 3区化学

Analytical Methods Pub Date : 2025-06-30 DOI: 10.1039/D5AY00480B

Zhengfei Luo, Yunfeng Chai, Guohua Zhao, Dongling Qiao, Fayin Ye, Lin Lei and Jia Chen

{"title":"Rapid detection of colorants in black tea using mid- and short-wave near infrared spectroscopy†","authors":"Zhengfei Luo, Yunfeng Chai, Guohua Zhao, Dongling Qiao, Fayin Ye, Lin Lei and Jia Chen","doi":"10.1039/D5AY00480B","DOIUrl":"10.1039/D5AY00480B","url":null,"abstract":"This study investigated the feasibility of using mid- and short-wave near-infrared (MS-NIR) spectroscopy for the rapid detection of colorants in black tea. A portable spectrometer was employed to acquire MS-NIR spectra from black tea samples. Support vector machine (SVM) and random forest (RF) models were developed for the discriminative detection of three colorants: tartrazine, sunset yellow, and ponceau 4R. The spectral preprocessing was optimized, and the predictive performance of the models was evaluated using validation data. The results indicated that, owing to the low concentration of colorants in black tea, the MS-NIR-based model was unsuitable for quantitative detection but effective for determining whether colorants were present. Overall, the discriminative capability of the SVM model surpassed that of the RF model. Following spectral preprocessing, the optimal SVM model achieved accuracy, precision, recall, and F1-score values of (97.50%, 96.15%, 100.00%, 0.9804), (95.00%, 96.00%, 96.00%, 0.9600), and (97.50%, 96.15%, 100.00%, 0.9804) for tartrazine, sunset yellow, and ponceau 4R, respectively. These findings demonstrate the feasibility of using MS-NIR for the rapid and discriminative identification of colorants in black tea. In practical applications, discriminative detection can serve as an initial rapid screening tool, followed by more precise quantitative detection methods to determine colorant concentrations.","PeriodicalId":64,"journal":{"name":"Analytical Methods","volume":" 28","pages":" 5897-5905"},"PeriodicalIF":2.7,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144558534","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}

引用次数: 0

Analysis of pyrolysis component variations in three azo compounds using headspace gas chromatography-mass spectrometry (HS-GC-MS)† 顶空气相色谱-质谱联用分析三种偶氮化合物热解组分的变化。

IF 2.7 3区化学

Analytical Methods Pub Date : 2025-06-30 DOI: 10.1039/D5AY00739A

Jinkun Liu, Zhanfang Liu, Jun Zhu, Guannan Zhang, Yajun Li, Zhenwen Sun, Hong Zhou, Zheng Zhou, Xianhe Deng, Dong Han and Yao Liu

{"title":"Analysis of pyrolysis component variations in three azo compounds using headspace gas chromatography-mass spectrometry (HS-GC-MS)†","authors":"Jinkun Liu, Zhanfang Liu, Jun Zhu, Guannan Zhang, Yajun Li, Zhenwen Sun, Hong Zhou, Zheng Zhou, Xianhe Deng, Dong Han and Yao Liu","doi":"10.1039/D5AY00739A","DOIUrl":"10.1039/D5AY00739A","url":null,"abstract":"As industrial explosive hazardous chemicals, 2,2′-azobis(2-methylpropionitrile) (AIBN), 2,2′-azodi(2-methylbutyronitrile) (AMBN) and 2,2′-azobis(2,4-dimethyl)valeronitrile (ABVN) have caused multiple explosion accidents. In this study, headspace gas chromatography-mass spectrometry (HS-GC-MS) was used to analyze the differences in pyrolysis products of these compounds under gradient temperatures from 60 to 150 °C and aerobic conditions, aiming to provide methodological support for microphysical evidence identification in forensic science. The results showed that with the increase of temperature, the chromatographic peak areas and numbers of the three compounds generally increased. Violent reactions occurred at 80–90 °C, and the reactions ended at approximately 150 °C. Through mass spectrometry matching, retention index (RI), and fragment ion verification, 40 pyrolysis products (including nitriles, ketones, etc.) were identified, among which some products appeared specifically in certain temperature intervals. Twelve differential components (VIP ≥ 1, p < 0.05) were screened out by principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA), and the Fisher discriminant model constructed based on these components achieved a 100% classification accuracy for unknown samples. This study reveals the temperature dependence and species specificity of the pyrolysis behavior of azo compounds, provides a novel pyrolysis product fingerprint-based analytical method for the forensic identification of trace evidence at explosion scenes, and is expected to improve the traceability accuracy of hazardous chemicals in complex scenarios.","PeriodicalId":64,"journal":{"name":"Analytical Methods","volume":" 28","pages":" 5849-5859"},"PeriodicalIF":2.7,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144558518","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}

引用次数: 0

A novel ATBH-modified gold nanoparticle for colorimetric detection and release monitoring of insulin across a wide concentration range 一种新型的atbh修饰金纳米颗粒，用于胰岛素在大浓度范围内的比色检测和释放监测。

IF 2.7 3区化学

Analytical Methods Pub Date : 2025-06-28 DOI: 10.1039/D5AY00648A

Xiaojie Dou, Wei Qiu and Xiang Chen

{"title":"A novel ATBH-modified gold nanoparticle for colorimetric detection and release monitoring of insulin across a wide concentration range","authors":"Xiaojie Dou, Wei Qiu and Xiang Chen","doi":"10.1039/D5AY00648A","DOIUrl":"10.1039/D5AY00648A","url":null,"abstract":"The visualization of insulin release can enhance patients' understanding of treatment progress and enable timely interventions, making it ideal for transdermal delivery systems. Current colorimetric methods for monitoring insulin are limited to ng mL−1 levels, insufficient for real-time release monitoring. This study proposes a novel small-molecule-modified gold nanoparticle (AuNP) using surface plasmon resonance for high-concentration insulin detection and monitoring. Molecular docking identified 2-amino-4-(trifluoromethyl)benzenethiol (ATBH), a high-affinity insulin binder (−4.8 kcal mol−1) featuring an amino group that reduces electrostatic repulsion between AuNPs and insulin, thereby enhancing insulin adsorption. ATBH-modified AuNPs (ATBH@AuNPs) were synthesized via Au–S bonds and characterized by SEM, TEM, UV-Vis spectroscopy, DLS, and insulin release assays. Experiments confirmed that ATBH@AuNP significantly broadens the insulin detection range from 0.35–1.4 μg mL−1 to 9.87–2510 μg mL−1, a 1792-fold improvement over unmodified AuNPs. A freeze-crosslinked polyvinyl alcohol (PVA) macrovesicle encapsulating ATBH@AuNP and insulin was developed, enabling real-time monitoring of insulin release through color changes caused by ATBH@AuNP aggregation.","PeriodicalId":64,"journal":{"name":"Analytical Methods","volume":" 27","pages":" 5759-5773"},"PeriodicalIF":2.7,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144537414","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}

引用次数: 0