Analytical science advances最新文献

{"title":"Multidimensional separations in top–down proteomics","authors":"Yanting Guo,&nbsp;Kellye A. Cupp-Sutton,&nbsp;Zhitao Zhao,&nbsp;Samin Anjum,&nbsp;Si Wu","doi":"10.1002/ansa.202300016","DOIUrl":"10.1002/ansa.202300016","url":null,"abstract":"<p>Top–down proteomics (TDP) identifies, quantifies, and characterises proteins at the intact proteoform level in complex biological samples to understand proteoform function and cellular mechanisms. However, analysing complex biological samples using TDP is still challenging due to high sample complexity and wide dynamic range. High-resolution separation methods are often applied prior to mass spectrometry (MS) analysis to decrease sample complexity and increase proteomics throughput. These separation methods, however, may not be efficient enough to characterise low abundance intact proteoforms in complex samples. As such, multidimensional separation techniques (combination of two or more separation methods with high orthogonality) have been developed and applied that demonstrate improved separation resolution and more comprehensive identification in TDP. A suite of multidimensional separation methods that couple various types of liquid chromatography (LC), capillary electrophoresis (CE), and/or gel electrophoresis-based separation approaches have been developed and applied in TDP to analyse complex biological samples. Here, we reviewed multidimensional separation strategies employed for TDP, summarised current applications, and discussed the gaps that may be addressed in the future.</p>","PeriodicalId":93411,"journal":{"name":"Analytical science advances","volume":"4 5-6","pages":"181-203"},"PeriodicalIF":0.0,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ansa.202300016","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42567902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Blood microsampling technologies: Innovations and applications in 2022","authors":"Manchu Umarani Thangavelu,&nbsp;Bert Wouters,&nbsp;Alida Kindt,&nbsp;Irwin K. M. Reiss,&nbsp;Thomas Hankemeier","doi":"10.1002/ansa.202300011","DOIUrl":"10.1002/ansa.202300011","url":null,"abstract":"<p>With the development of highly sensitive bioanalytical techniques, the volume of samples necessary for accurate analysis has reduced. Microsampling, the process of obtaining small amounts of blood, has thus gained popularity as it offers minimal-invasiveness, reduced logistical costs and biohazard risks while simultaneously showing increased sample stability and a potential for the decentralization of the approach and at-home self-sampling. Although the benefits of microsampling have been recognised, its adoption in clinical practice has been slow. Several microsampling technologies and devices are currently available and employed in research studies for various biomedical applications. This review provides an overview of the state-of-the-art in microsampling technology with a focus on the latest developments and advancements in the field of microsampling. Research published in the year 2022, including studies (i) developing strategies for the quantitation of analytes in microsamples and (ii) bridging and comparing the interchangeability between matrices and choice of technology for a given application, is reviewed to assess the advantages, challenges and limitations of the current state of microsampling. Successful implementation of microsampling in routine clinical care requires continued efforts for standardization and harmonization. Microsampling has been shown to facilitate data-rich studies and a patient-centric approach to healthcare and is foreseen to play a central role in the future digital revolution of healthcare through continuous monitoring to improve the quality of life.</p>","PeriodicalId":93411,"journal":{"name":"Analytical science advances","volume":"4 5-6","pages":"154-180"},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ansa.202300011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49646945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Anthocyanin-loaded bacterial cellulose nanofiber as a green sensor for monitoring the selective naked eye and visual detection of Al(III) Ions","authors":"Sima Arghavani,&nbsp;Fatemeh S. Mohseni-Shahri,&nbsp;Farid Moeinpour","doi":"10.1002/ansa.202300014","DOIUrl":"10.1002/ansa.202300014","url":null,"abstract":"<p>The present study developed a green metallochromic sensor that detects aluminium (Al(III)) ions in solution and solid state using anthocyanin extract from purple onion peels embedded in bacterial cellulose nanofibers (BCNFs). The CIE Lab colour parameters demonstrated that Al(III) binding causes a sensible change in colour. A variety of metal ions including K⁺, Mn²⁺, Cu²⁺, Hg²⁺, Cr²⁺, Pb²⁺ and Ni²⁺ were used to challenge the sensor to determine its selectivity. The findings demonstrated that the suggested sensor showed excellent selectivity toward Al(III) ion. Al(III) is quantitatively detected by the sensing method with detection limits in the range between 30–200 and 20–300 ppm in solution and solid state, respectively, and through observation with naked eye. The fabricated green metallochromic sensor is promising to be a simple, cheap, mobile and easily operable for real-time and on-site detection of Al(III) ions in food matrices.</p>","PeriodicalId":93411,"journal":{"name":"Analytical science advances","volume":"4 11-12","pages":"324-334"},"PeriodicalIF":0.0,"publicationDate":"2023-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://chemistry-europe.onlinelibrary.wiley.com/doi/epdf/10.1002/ansa.202300014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43406383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chewing the fat: How lipidomics is changing our understanding of human health and disease in 2022","authors":"Caroline Géhin,&nbsp;Stephen J. Fowler,&nbsp;Drupad K. Trivedi","doi":"10.1002/ansa.202300009","DOIUrl":"10.1002/ansa.202300009","url":null,"abstract":"<p>Lipids are biological molecules that play vital roles in all living organisms. They perform many cellular functions, such as 1) forming cellular and subcellular membranes, 2) storing and using energy, and 3) serving as chemical messengers during intra- and inter-cellular signal transduction. The large-scale study of the pathways and networks of cellular lipids in biological systems is called “lipidomics” and is one of the fastest-growing <i>omics</i> technologies of the last two decades. With state-of-the-art mass spectrometry instrumentation and sophisticated data handling, clinical studies show how human lipid composition changes in health and disease, thereby making it a valuable medium to collect for clinical applications, such as disease diagnostics, therapeutic decision-making, and drug development. This review gives a comprehensive overview of current workflows used in clinical research, from sample collection and preparation to data and clinical interpretations. This is followed by an appraisal of applications in 2022 and a perspective on the exciting future of clinical lipidomics.</p>","PeriodicalId":93411,"journal":{"name":"Analytical science advances","volume":"4 3-4","pages":"104-131"},"PeriodicalIF":0.0,"publicationDate":"2023-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ansa.202300009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48236915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Defect rate prediction and failure-cause diagnosis in a mass-production process for precision electric components","authors":"Hiromasa Kaneko","doi":"10.1002/ansa.202300019","DOIUrl":"10.1002/ansa.202300019","url":null,"abstract":"<p>Many defects occur during the mass production of precision electrical components. To control and manage them, process variables (PVs), such as the temperature, pressure, flow rate, and liquid level, are measured and time-series data analyzed. However, identification of point of defects is difficult as any operation can cause defects and multiple equipment units are used in parallel for some operations. This study considers the combination of unfavourable conditions between operations to predict the defect rate (DR) of products. A dataset measured in an actual mass-production process for precision electrical components is analysed to predict the DR of the products. Data analysis is performed on a dataset generated from an actual mass-production process for precision electrical components, and machine learning models. are constructed using ensemble learning methods, such as random forests, the gradient boosting decision tree, XGBoost, and LightGBM. Conventional univariate analyses only show a maximum correlation coefficient of 0.17 with a DR and process variables (PVs). In this study, we improved the correlation coefficient to 0.73 using a multivariate analysis, including the data of PVs that are not considered important in the process, and appropriately transformed PVs based on the domain knowledge of the process. Furthermore, PVs that were closely related to the DR could be diagnosed based on the feature importance of the constructed machine-learning models. This study confirms the importance of using domain knowledge to improve the prediction ability of machine learning models and the interpretation of constructed models.</p>","PeriodicalId":93411,"journal":{"name":"Analytical science advances","volume":"4 9-10","pages":"312-318"},"PeriodicalIF":0.0,"publicationDate":"2023-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ansa.202300019","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43884508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analytics for Grannies 002: Extractions","authors":"Tal Luzzatto Knaan","doi":"10.1002/ansa.202300900","DOIUrl":"10.1002/ansa.202300900","url":null,"abstract":"<p></p><p></p><p></p>","PeriodicalId":93411,"journal":{"name":"Analytical science advances","volume":"4 9-10","pages":"279-281"},"PeriodicalIF":0.0,"publicationDate":"2023-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ansa.202300900","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46045979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Applications of ambient ionization mass spectrometry in 2022: An annual review","authors":"Stephanie Rankin-Turner,&nbsp;Patrick Sears,&nbsp;Liam M Heaney","doi":"10.1002/ansa.202300004","DOIUrl":"https://doi.org/10.1002/ansa.202300004","url":null,"abstract":"<p>The development of ambient ionization mass spectrometry (AIMS) has transformed analytical science, providing the means of performing rapid analysis of samples in their native state, both in and out of the laboratory. The capacity to eliminate sample preparation and pre-MS separation techniques, leading to true real-time analysis, has led to AIMS naturally gaining a broad interest across the scientific community. Since the introduction of the first AIMS techniques in the mid-2000s, the field has exploded with dozens of novel ion sources, an array of intriguing applications, and an evident growing interest across diverse areas of study. As the field continues to surge forward each year, ambient ionization techniques are increasingly becoming commonplace in laboratories around the world. This annual review provides an overview of AIMS techniques and applications throughout 2022, with a specific focus on some of the major fields of research, including forensic science, disease diagnostics, pharmaceuticals and food sciences. New techniques and methods are introduced, demonstrating the unwavering drive of the analytical community to further advance this exciting field and push the boundaries of what analytical chemistry can achieve.</p>","PeriodicalId":93411,"journal":{"name":"Analytical science advances","volume":"4 5-6","pages":"133-153"},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ansa.202300004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50143857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Copper(II)/polyimide linked covalent organic framework as a powerful catalyst for the solvent-free microwave irradiation-based synthesis of 2,4,5-trisubstituted imidazoles","authors":"Mahnaz Sedaghat,&nbsp;Farid Moeinpour,&nbsp;Fatemeh S. Mohseni-Shahri","doi":"10.1002/ansa.202300012","DOIUrl":"10.1002/ansa.202300012","url":null,"abstract":"<p>Copper(II)/polyimide-linked covalent organic frameworks under solvent-free and microwave-assisted conditions have been used in an efficient one-pot protocol for the preparation of 2,4,5-trisubstituted imidazoles via benzil, aromatic aldehydes and ammonium acetate. By applying solvent-free conditions and microwave irradiation, three-component condensation provides safe operations, low pollution, quick access to products, and an easy set-up. As a result of its reusability, the catalyst can also be reutilized for many runs without missing any activity.</p>","PeriodicalId":93411,"journal":{"name":"Analytical science advances","volume":"4 9-10","pages":"302-311"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ansa.202300012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44051169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Overview of systematic toxicological analysis strategies and their coverage of substances in forensic toxicology","authors":"Karen Rygaard,&nbsp;Meiru Pan,&nbsp;Marie Katrine Klose Nielsen,&nbsp;Petur Weihe Dalsgaard,&nbsp;Brian Schou Rasmussen,&nbsp;Kristian Linnet","doi":"10.1002/ansa.202200062","DOIUrl":"10.1002/ansa.202200062","url":null,"abstract":"<p>Systematic toxicological analysis (STA) is the process of using an adequate analytical methodology to detect and identify as many potentially toxicologically relevant compounds as possible in biological samples. STA is an important part of everyday routine work within forensic toxicology, and several methods for STA have frequently been published and reviewed independently. However, the many drugs and other substances involved, as well as the constant emergence of new ones, may pose a major challenge in STA, which often demands a strategy involving multiple analytical methods in parallel. Such strategies have been published and evaluated less frequently despite their relevance in forensic toxicology. This mini-review briefly summarizes commonly applied methods for STA in forensic toxicology, including gas chromatography–mass spectrometry (GC–MS) and liquid chromatography–MS (LC–MS) methods, and highlights some of their potential pitfalls. Second, it provides an overview of previously reported strategies to conduct STA, including a presentation of the STA strategy applied in the authors’ laboratory. This involves broad drug screening by LC–high-resolution MS, supported by targeted screening and quantification using LC–tandem MS, headspace (HS)-GC–MS, HS-GC–flame ionization detector and other complementary methods. The STA strategy aims to cover as many potentially relevant drugs as possible and seeks to reduce potential pitfalls arising in forensic casework. The review underlines that not every substance can be identified in all circumstances even with a comprehensive STA strategy.</p>","PeriodicalId":93411,"journal":{"name":"Analytical science advances","volume":"4 3-4","pages":"96-103"},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ansa.202200062","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49282636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mass Sportrometry: An annual look back at applications of mass spectrometry in sport and exercise science","authors":"Marilyn LY Ong,&nbsp;Christopher G Green,&nbsp;Samantha N Rowland,&nbsp;Liam M Heaney","doi":"10.1002/ansa.202300003","DOIUrl":"10.1002/ansa.202300003","url":null,"abstract":"<p>Research in sport and exercise science (SES) is reliant on robust analyses of biomarker measurements to assist with the interpretation of physiological outcomes. Mass spectrometry (MS) is an analytical approach capable of highly sensitive, specific, precise, and accurate analyses of a range of biomolecules, many of which are of interest in SES including, but not limited to, endogenous metabolites, exogenously administered compounds (e.g. supplements), mineral ions, and circulating/tissue proteins. This annual review provides a summary of the applications of MS across studies investigating aspects related to sport or exercise in manuscripts published, or currently in press, in 2022. In total, 93 publications are included and categorized according to their methodologies including targeted analyses, metabolomics, lipidomics, proteomics, and isotope ratio/elemental MS. The advantageous analytical opportunities afforded by MS technologies are discussed across a selection of relevant articles. In addition, considerations for the future of MS in SES, including the need to improve the reporting of assay characteristics and validation data, are discussed, alongside the recommendation for selected current methods to be superseded by MS-based approaches where appropriate. The review identifies that a targeted, mostly quantitative, approach is the most commonly applied MS approach within SES, although there has also been a keen interest in the use of <i>‘omics’</i> to perform hypothesis-generating research studies. Nonetheless, MS is not commonplace in SES at this time, but its use to expand, and possibly improve, the analytical options should be continually considered to exploit the benefits of analytical chemistry in exercise/sports-based research. Overall, it is exciting to see the gradually increasing adoption of MS in SES and it is expected that the number, and quality, of MS-based assays in SES will increase over time, with the potential for 2023 to further establish this technique within the field.</p>","PeriodicalId":93411,"journal":{"name":"Analytical science advances","volume":"4 3-4","pages":"60-80"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ansa.202300003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49426533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}