Pub Date : 2025-06-02DOI: 10.1016/j.pnmrs.2025.101574
Shaoying Huang , José Miguel Algarín , Joseba Alonso , R Anieyrudh , Jose Borreguero , Fabian Bschorr , Paul Cassidy , Wei Ming Choo , David Corcos , Teresa Guallart-Naval , Heng Jing Han , Kay Chioma Igwe , Jacob Kang , Joe Li , Sebastian Littin , Jie Liu , Gonzalo Gabriel Rodriguez , Eddy Solomon , Li-Kuo Tan , Rui Tian , Bernhard Blümich
Nuclear magnetic resonance instruments are becoming available to the do-it-yourself community, and there is increasing interest in the practical aspects of building a magnetic resonance imaging instrument from scratch. This review is focused on the different steps involved in such an endeavour, the challenges encountered and their solutions; it is based on experience gained at a four-day “hackathon” (named “ezyMRI”) at Singapore University of Technology and Design in spring 2024. One day of this event was devoted to educational lectures and three days to system construction and testing; seventy young researchers from all parts of the world formed six teams focusing respectively on magnet, gradient coil, RF coil, console, system integration, and design, which together produced a working MRI instrument in three days.
{"title":"Experience of how to build an MRI machine from scratch","authors":"Shaoying Huang , José Miguel Algarín , Joseba Alonso , R Anieyrudh , Jose Borreguero , Fabian Bschorr , Paul Cassidy , Wei Ming Choo , David Corcos , Teresa Guallart-Naval , Heng Jing Han , Kay Chioma Igwe , Jacob Kang , Joe Li , Sebastian Littin , Jie Liu , Gonzalo Gabriel Rodriguez , Eddy Solomon , Li-Kuo Tan , Rui Tian , Bernhard Blümich","doi":"10.1016/j.pnmrs.2025.101574","DOIUrl":"10.1016/j.pnmrs.2025.101574","url":null,"abstract":"<div><div>Nuclear magnetic resonance instruments are becoming available to the do-it-yourself community, and there is increasing interest in the practical aspects of building a magnetic resonance imaging instrument from scratch. This review is focused on the different steps involved in such an endeavour, the challenges encountered and their solutions; it is based on experience gained at a four-day “hackathon” (named “ezyMRI”) at Singapore University of Technology and Design in spring 2024. One day of this event was devoted to educational lectures and three days to system construction and testing; seventy young researchers from all parts of the world formed six teams focusing respectively on magnet, gradient coil, RF coil, console, system integration, and design, which together produced a working MRI instrument in three days.</div></div>","PeriodicalId":20740,"journal":{"name":"Progress in Nuclear Magnetic Resonance Spectroscopy","volume":"150 ","pages":"Article 101574"},"PeriodicalIF":7.3,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144587743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-02DOI: 10.1016/j.pnmrs.2025.101573
Frédéric A. Perras , Marek Pruski
This review provides an up-to-date account of the development of two solid-state (SS)NMR methods for enhancing resolution and sensitivity, fast magic angle spinning (MAS) and dynamic nuclear polarization (DNP), and the resulting progress in surface science. We demonstrate the high resolution and efficiency that can be achieved by using two-dimensional homo- and heteronuclear correlation experiments with small rotors capable of MAS at rates exceeding 100 kHz. DNP has offered significant enhancements in signal sensitivity and allowed access to nuclei and experiments that are beyond the limits of conventional SSNMR. The continuing progress in fast MAS and DNP methodologies in recent years generated an unprecedented shift in SSNMR’s capabilities in the studies of surface and interface regions of solids, especially mesoporous supports and catalysts. We give numerous examples of recent applications and discuss the prospects for further improvements of both methods.
{"title":"Advances in solid-state NMR for the studies of mesoporous solids: fast magic spinning and dynamic nuclear polarization","authors":"Frédéric A. Perras , Marek Pruski","doi":"10.1016/j.pnmrs.2025.101573","DOIUrl":"10.1016/j.pnmrs.2025.101573","url":null,"abstract":"<div><div>This review provides an up-to-date account of the development of two solid-state (SS)NMR methods for enhancing resolution and sensitivity, fast magic angle spinning (MAS) and dynamic nuclear polarization (DNP), and the resulting progress in surface science. We demonstrate the high resolution and efficiency that can be achieved by using two-dimensional homo- and heteronuclear correlation experiments with small rotors capable of MAS at rates exceeding 100 kHz. DNP has offered significant enhancements in signal sensitivity and allowed access to nuclei and experiments that are beyond the limits of conventional SSNMR. The continuing progress in fast MAS and DNP methodologies in recent years generated an unprecedented shift in SSNMR’s capabilities in the studies of surface and interface regions of solids, especially mesoporous supports and catalysts. We give numerous examples of recent applications and discuss the prospects for further improvements of both methods.</div></div>","PeriodicalId":20740,"journal":{"name":"Progress in Nuclear Magnetic Resonance Spectroscopy","volume":"150 ","pages":"Article 101573"},"PeriodicalIF":7.3,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-29DOI: 10.1016/j.pnmrs.2025.101564
G.A. Nagana Gowda , Wentao Zhu , Daniel Raftery
The fast-growing field of metabolomics focuses on the analyses of complicated mixtures of small molecules present in biological samples. To date, metabolomics has provided a wealth of information on biological systems and impacted numerous areas of basic and life sciences. A major focus of metabolomics has been on biomedicine with the goal of biomarker discovery, drug discovery and improved mechanistic understanding of the pathogenesis of many human diseases. Analytical methods play a pivotal role in metabolomics, with the two most widely used platforms being nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS). Among their many complementary capabilities, NMR is generally more reproducible and quantitative, whereas MS is more sensitive. Recent technological advances in NMR have resulted in multifaceted developments, including improvements in sensitivity, resolution and speed, along with expanded metabolite identification and quantitation, which together provide exciting potential for future studies. In addition to NMR developments, the combination of NMR with MS provides numerous benefits that are becoming more evident over time. Hence, the metabolomics field has witnessed an increased number of studies and applications that combine NMR with MS in numerous areas, including new methods development for unknown identification, metabolite quantitation, disease biomarker discovery, mechanistic understanding of disease pathogenesis, and dietary risk factors of diseases among others. This report describes the current status of state-of-the-art methods in NMR-based metabolomics, along with recent advances and future prospects, with an emphasis on the benefits of combining NMR with MS.
{"title":"NMR-based metabolomics: Where are we now and where are we going?","authors":"G.A. Nagana Gowda , Wentao Zhu , Daniel Raftery","doi":"10.1016/j.pnmrs.2025.101564","DOIUrl":"10.1016/j.pnmrs.2025.101564","url":null,"abstract":"<div><div>The fast-growing field of metabolomics focuses on the analyses of complicated mixtures of small molecules present in biological samples. To date, metabolomics has provided a wealth of information on biological systems and impacted numerous areas of basic and life sciences. A major focus of metabolomics has been on biomedicine with the goal of biomarker discovery, drug discovery and improved mechanistic understanding of the pathogenesis of many human diseases. Analytical methods play a pivotal role in metabolomics, with the two most widely used platforms being nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS). Among their many complementary capabilities, NMR is generally more reproducible and quantitative, whereas MS is more sensitive. Recent technological advances in NMR have resulted in multifaceted developments, including improvements in sensitivity, resolution and speed, along with expanded metabolite identification and quantitation, which together provide exciting potential for future studies. In addition to NMR developments, the combination of NMR with MS provides numerous benefits that are becoming more evident over time. Hence, the metabolomics field has witnessed an increased number of studies and applications that combine NMR with MS in numerous areas, including new methods development for unknown identification, metabolite quantitation, disease biomarker discovery, mechanistic understanding of disease pathogenesis, and dietary risk factors of diseases among others. This report describes the current status of state-of-the-art methods in NMR-based metabolomics, along with recent advances and future prospects, with an emphasis on the benefits of combining NMR with MS.</div></div>","PeriodicalId":20740,"journal":{"name":"Progress in Nuclear Magnetic Resonance Spectroscopy","volume":"150 ","pages":"Article 101564"},"PeriodicalIF":7.3,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144125325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-27DOI: 10.1016/j.pnmrs.2025.101563
Jose L. Uribe , Annie V. McAllister , Rachel W. Martin
Three-dimensional (3D) printing has emerged as a transformative technology for nuclear magnetic resonance (NMR) instrumentation, offering flexibility in the design and fabrication of custom tools that enhance experimental capabilities. Additive manufacturing has made it possible for many NMR labs to build their own magic angle spinning assemblies, sample handling devices, and other critical components. We summarize common 3D printing techniques, such as fused deposition modeling (FDM) and stereolithography (SLA) for polymers, along with metal printing methods like selective laser melting. By facilitating rapid prototyping, 3D printing accelerates the development and optimization of NMR systems, as well as bypassing traditional manufacturing constraints. This review also discusses perspectives on the future of 3D printing in NMR and related methods, providing cost-effective, in-house solutions that increase participation, allow for sharing and remixing of innovations, and broaden applications across chemical, biological, and materials research.
{"title":"Additive fabrication for NMR probe builders","authors":"Jose L. Uribe , Annie V. McAllister , Rachel W. Martin","doi":"10.1016/j.pnmrs.2025.101563","DOIUrl":"10.1016/j.pnmrs.2025.101563","url":null,"abstract":"<div><div>Three-dimensional (3D) printing has emerged as a transformative technology for nuclear magnetic resonance (NMR) instrumentation, offering flexibility in the design and fabrication of custom tools that enhance experimental capabilities. Additive manufacturing has made it possible for many NMR labs to build their own magic angle spinning assemblies, sample handling devices, and other critical components. We summarize common 3D printing techniques, such as fused deposition modeling (FDM) and stereolithography (SLA) for polymers, along with metal printing methods like selective laser melting. By facilitating rapid prototyping, 3D printing accelerates the development and optimization of NMR systems, as well as bypassing traditional manufacturing constraints. This review also discusses perspectives on the future of 3D printing in NMR and related methods, providing cost-effective, in-house solutions that increase participation, allow for sharing and remixing of innovations, and broaden applications across chemical, biological, and materials research.</div></div>","PeriodicalId":20740,"journal":{"name":"Progress in Nuclear Magnetic Resonance Spectroscopy","volume":"150 ","pages":"Article 101563"},"PeriodicalIF":7.3,"publicationDate":"2025-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143906256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Food metabolomics has emerged as a powerful tool for characterizing complex food systems, offering a non-targeted highly discriminative approach for detecting authenticity, assessing quality, and ensuring safety across an array of food matrices. By capturing the complete spectral signature of a sample and reducing it to manageable variables, this technique provides an extensive metabolite snapshot that encompasses everything from minor compounds to major constituents.
A key advantage lies in the reproducibility and robustness of NMR spectroscopy, allowing the comparison of spectra even across different instruments and laboratories. Such comparability fosters collaborative efforts and facilitates the establishment of large, community-built datasets, which are critical for advancing reliable classification models and enabling wide-scale deployment of non-targeted protocols. Rigor in each step, ranging from selecting representative authentic samples to optimizing acquisition parameters, data processing, and classification algorithms, proves essential for achieving consistent, high-quality metabolomics data.
As validation and standardization practices become more widely accepted, NMR-based non-targeted approaches will accelerate innovations in food product monitoring and labeling, reduce analytical uncertainties, and address emerging challenges in food fraud detection. Ultimately, by combining best-in-class protocols, collaborative networks, and open-access data repositories, non-targeted NMR metabolomics has the potential to revolutionize traceability and foster global consumer confidence in the authenticity and quality of the food supply chain.
{"title":"Advances in food metabolomics: Validating NMR-based non-targeted methods and fostering collaborative NMR applications","authors":"Biagia Musio , Antonino Rizzuti , Piero Mastrorilli , Vito Gallo","doi":"10.1016/j.pnmrs.2025.101562","DOIUrl":"10.1016/j.pnmrs.2025.101562","url":null,"abstract":"<div><div>Food metabolomics has emerged as a powerful tool for characterizing complex food systems, offering a non-targeted highly discriminative approach for detecting authenticity, assessing quality, and ensuring safety across an array of food matrices. By capturing the complete spectral signature of a sample and reducing it to manageable variables, this technique provides an extensive metabolite snapshot that encompasses everything from minor compounds to major constituents.</div><div>A key advantage lies in the reproducibility and robustness of NMR spectroscopy, allowing the comparison of spectra even across different instruments and laboratories. Such comparability fosters collaborative efforts and facilitates the establishment of large, community-built datasets, which are critical for advancing reliable classification models and enabling wide-scale deployment of non-targeted protocols. Rigor in each step, ranging from selecting representative authentic samples to optimizing acquisition parameters, data processing, and classification algorithms, proves essential for achieving consistent, high-quality metabolomics data.</div><div>As validation and standardization practices become more widely accepted, NMR-based non-targeted approaches will accelerate innovations in food product monitoring and labeling, reduce analytical uncertainties, and address emerging challenges in food fraud detection. Ultimately, by combining best-in-class protocols, collaborative networks, and open-access data repositories, non-targeted NMR metabolomics has the potential to revolutionize traceability and foster global consumer confidence in the authenticity and quality of the food supply chain.</div></div>","PeriodicalId":20740,"journal":{"name":"Progress in Nuclear Magnetic Resonance Spectroscopy","volume":"150 ","pages":"Article 101562"},"PeriodicalIF":7.3,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143899416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-24DOI: 10.1016/j.pnmrs.2025.101560
Silvie Foldynova-Trantirkova , Jakub Harnos , Jan Rynes , Vladimira Zlinska , Lukas Trantirek
In-cell NMR spectroscopy has recently emerged as a unique source of atomically resolved information on the structure, dynamics, and interactions of nucleic acids (NAs) within the intracellular space of living cells. Its recent applications have helped reveal fundamental differences in the behaviour of NAs in cells compared to the in vitro conditions commonly used for their study, as well as in physiologically distinct cellular states. This review covers the fundamental principles and practical aspects of acquiring in-cell NMR data in currently established eukaryotic cellular models, Xenopus laevis oocytes, and human cells. The primary purpose of this review is to present and discuss the technical and conceptual aspects of in-cell NMR sample preparations and their manipulations during in-cell NMR data acquisition, as understanding these aspects is vital for comprehending the physiological significance of in-cell NMR data and the information they provide. Considerations on the planning of in-cell NMR experiments and the presentation of in-cell NMR data on nucleic acids are discussed. We hope this will enable readers to navigate through the ever-growing pool of in-cell NMR literature and gain the knowledge needed to assess and comprehend published data independently. Additionally, we hope it will inspire some readers to actively participate in this rapidly expanding and fascinating field of cellular structural biology.
{"title":"In-cell NMR spectroscopy of nucleic acids: Basic concepts, practical aspects, and applications","authors":"Silvie Foldynova-Trantirkova , Jakub Harnos , Jan Rynes , Vladimira Zlinska , Lukas Trantirek","doi":"10.1016/j.pnmrs.2025.101560","DOIUrl":"10.1016/j.pnmrs.2025.101560","url":null,"abstract":"<div><div>In-cell NMR spectroscopy has recently emerged as a unique source of atomically resolved information on the structure, dynamics, and interactions of nucleic acids (NAs) within the intracellular space of living cells. Its recent applications have helped reveal fundamental differences in the behaviour of NAs in cells compared to the in vitro conditions commonly used for their study, as well as in physiologically distinct cellular states. This review covers the fundamental principles and practical aspects of acquiring in-cell NMR data in currently established eukaryotic cellular models, <em>Xenopus laevis</em> oocytes, and human cells. The primary purpose of this review is to present and discuss the technical and conceptual aspects of in-cell NMR sample preparations and their manipulations during in-cell NMR data acquisition, as understanding these aspects is vital for comprehending the physiological significance of in-cell NMR data and the information they provide. Considerations on the planning of in-cell NMR experiments and the presentation of in-cell NMR data on nucleic acids are discussed. We hope this will enable readers to navigate through the ever-growing pool of in-cell NMR literature and gain the knowledge needed to assess and comprehend published data independently. Additionally, we hope it will inspire some readers to actively participate in this rapidly expanding and fascinating field of cellular structural biology.</div></div>","PeriodicalId":20740,"journal":{"name":"Progress in Nuclear Magnetic Resonance Spectroscopy","volume":"148 ","pages":"Article 101560"},"PeriodicalIF":7.3,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143551675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-24DOI: 10.1016/j.pnmrs.2025.101561
Dongyue Si , Simon J. Littlewood , Michael G. Crabb , Andrew Phair , Claudia Prieto , René M. Botnar
Cardiovascular magnetic resonance (CMR) imaging is an established non-invasive tool for the assessment of cardiovascular diseases, which are the leading cause of death globally. CMR provides dynamic and static multi-contrast and multi-parametric images, including cine for functional evaluation, contrast-enhanced imaging and parametric mapping for tissue characterization, and MR angiography for the assessment of the aortic, coronary and pulmonary circulation. However, clinical CMR imaging sequences still have some limitations such as the requirement for multiple breath-holds, incomplete spatial coverage, complex planning and acquisition, low scan efficiency and long scan times. To address these challenges, novel techniques have been developed during the last two decades, focusing on automated planning and acquisition timing, improved respiratory and cardiac motion handling strategies, image acceleration algorithms employing undersampled reconstruction, all-in-one imaging techniques that can acquire multiple contrast/parameters in a single scan, deep learning based methods applied along the entire CMR imaging pipeline, as well as imaging at high- and low-field strengths. In this article, we aim to provide a comprehensive review of CMR imaging, covering both established and emerging techniques, to give an overview of the present and future applications of CMR.
{"title":"Cardiovascular magnetic resonance imaging: Principles and advanced techniques","authors":"Dongyue Si , Simon J. Littlewood , Michael G. Crabb , Andrew Phair , Claudia Prieto , René M. Botnar","doi":"10.1016/j.pnmrs.2025.101561","DOIUrl":"10.1016/j.pnmrs.2025.101561","url":null,"abstract":"<div><div>Cardiovascular magnetic resonance (CMR) imaging is an established non-invasive tool for the assessment of cardiovascular diseases, which are the leading cause of death globally. CMR provides dynamic and static multi-contrast and multi-parametric images, including cine for functional evaluation, contrast-enhanced imaging and parametric mapping for tissue characterization, and MR angiography for the assessment of the aortic, coronary and pulmonary circulation. However, clinical CMR imaging sequences still have some limitations such as the requirement for multiple breath-holds, incomplete spatial coverage, complex planning and acquisition, low scan efficiency and long scan times. To address these challenges, novel techniques have been developed during the last two decades, focusing on automated planning and acquisition timing, improved respiratory and cardiac motion handling strategies, image acceleration algorithms employing undersampled reconstruction, all-in-one imaging techniques that can acquire multiple contrast/parameters in a single scan, deep learning based methods applied along the entire CMR imaging pipeline, as well as imaging at high- and low-field strengths. In this article, we aim to provide a comprehensive review of CMR imaging, covering both established and emerging techniques, to give an overview of the present and future applications of CMR.</div></div>","PeriodicalId":20740,"journal":{"name":"Progress in Nuclear Magnetic Resonance Spectroscopy","volume":"148 ","pages":"Article 101561"},"PeriodicalIF":7.3,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143526544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-15DOI: 10.1016/j.pnmrs.2025.101558
Danila A. Barskiy , John W. Blanchard , Dmitry Budker , James Eills , Szymon Pustelny , Kirill F. Sheberstov , Michael C.D. Tayler , Andreas H. Trabesinger
Zero and ultralow-field nuclear magnetic resonance (ZULF NMR) is an NMR modality where experiments are performed in fields at which spin–spin interactions within molecules and materials are stronger than Zeeman interactions. This typically occurs at external fields of microtesla strength or below, considerably smaller than Earth’s field. In ZULF NMR, the measurement of spin–spin couplings and spin relaxation rates provides a nondestructive means for identifying chemicals and chemical fragments, and for conducting sample or process analyses. The absence of the symmetry imposed by a strong external magnetic field enables experiments that exploit terms in the nuclear spin Hamiltonian that are suppressed in high-field NMR, which in turn opens up new capabilities in a broad range of fields, from the search for dark matter to the preparation of hyperpolarized contrast agents for clinical imaging. Furthermore, as in ZULF NMR the Larmor frequencies are typically in the audio band, the nuclear spins can be manipulated with d.c. magnetic field pulses, and highly sensitive magnetometers are used for detection. In contrast to high-field NMR, the low-frequency signals readily pass through conductive materials such as metals, and heterogeneous samples do not lead to resonance line broadening, meaning that high-resolution spectroscopy is possible. Notable practical advantages of ZULF NMR spectroscopy are the low cost and relative simplicity and portability of the spectrometer system. In recent years ZULF NMR has become more accessible, thanks to improvements in magnetometer sensitivity and commercial availability, and the development of hyperpolarization methods that provide a simple means to boost signal strengths by several orders of magnitude. These topics are reviewed and a perspective on potential future avenues of ZULF-NMR research is presented.
{"title":"Zero- to ultralow-field nuclear magnetic resonance","authors":"Danila A. Barskiy , John W. Blanchard , Dmitry Budker , James Eills , Szymon Pustelny , Kirill F. Sheberstov , Michael C.D. Tayler , Andreas H. Trabesinger","doi":"10.1016/j.pnmrs.2025.101558","DOIUrl":"10.1016/j.pnmrs.2025.101558","url":null,"abstract":"<div><div>Zero and ultralow-field nuclear magnetic resonance (ZULF NMR) is an NMR modality where experiments are performed in fields at which spin–spin interactions within molecules and materials are stronger than Zeeman interactions. This typically occurs at external fields of microtesla strength or below, considerably smaller than Earth’s field. In ZULF NMR, the measurement of spin–spin couplings and spin relaxation rates provides a nondestructive means for identifying chemicals and chemical fragments, and for conducting sample or process analyses. The absence of the symmetry imposed by a strong external magnetic field enables experiments that exploit terms in the nuclear spin Hamiltonian that are suppressed in high-field NMR, which in turn opens up new capabilities in a broad range of fields, from the search for dark matter to the preparation of hyperpolarized contrast agents for clinical imaging. Furthermore, as in ZULF NMR the Larmor frequencies are typically in the audio band, the nuclear spins can be manipulated with d.c. magnetic field pulses, and highly sensitive magnetometers are used for detection. In contrast to high-field NMR, the low-frequency signals readily pass through conductive materials such as metals, and heterogeneous samples do not lead to resonance line broadening, meaning that high-resolution spectroscopy is possible. Notable practical advantages of ZULF NMR spectroscopy are the low cost and relative simplicity and portability of the spectrometer system. In recent years ZULF NMR has become more accessible, thanks to improvements in magnetometer sensitivity and commercial availability, and the development of hyperpolarization methods that provide a simple means to boost signal strengths by several orders of magnitude. These topics are reviewed and a perspective on potential future avenues of ZULF-NMR research is presented.</div></div>","PeriodicalId":20740,"journal":{"name":"Progress in Nuclear Magnetic Resonance Spectroscopy","volume":"148 ","pages":"Article 101558"},"PeriodicalIF":7.3,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143521127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-13DOI: 10.1016/j.pnmrs.2025.101559
Mārtiņš Otikovs , Zhiyong Zhang , Lucio Frydman
Magnetic resonance imaging (MRI) is an indispensable tool used in both the lab and the clinic. Part of the strength of MRI comes from its ability to deliver anatomical information highlighted with different types of contrasts, including functional and diffusion-oriented acquisitions that are often incompatible with normal, multi-shot scans. For these problems, Nobel-award-winning techniques such as Echo Planar Imaging (EPI) have been essential in opening a manifold of new applications. EPI, however, has challenges when dealing with sharp changes in magnetic susceptibility, including those arising in the presence of air/tissue or air/fat interfaces, from non-ferromagnetic metal implants, as well when the main magnetic field cannot be shimmed to achieve the desired degree of homogeneity, as often is the case in systems built using permanent magnets. Among the techniques being proposed to deal with this kind of problem is spatiotemporally-encoded (SPEN) MRI. The present review focuses on the principles of this technique, with an emphasis on: i) explaining SPEN's resilience to field inhomogeneities, on the basis of expanded bandwidth considerations vis-à-vis EPI; ii) “the good, the bad and the ugly” associated with the undersampling that SPEN usually has to carry out when employing expanded bandwidths; iii) recent developments in data processing algorithms seeking to alleviate the “bad and the ugly” part of these experiments by formulating SPEN image reconstruction as an optimization problem, and then relying on compressed sensing and parallel imaging concepts to achieve improved image quality; and iv) the incorporation of experimental improvements including scan interleaving, simultaneous multi-banding and multi-echo elements, to keep in line with advancements in other areas of fast MRI. The strengths and weaknesses of these data sampling and processing strategies are assessed, and examples of their leverage in functional, but foremost diffusion-weighted, imaging applications, are presented.
{"title":"Principles and Progress in ultrafast 2D spatiotemporally encoded MRI","authors":"Mārtiņš Otikovs , Zhiyong Zhang , Lucio Frydman","doi":"10.1016/j.pnmrs.2025.101559","DOIUrl":"10.1016/j.pnmrs.2025.101559","url":null,"abstract":"<div><div>Magnetic resonance imaging (MRI) is an indispensable tool used in both the lab and the clinic. Part of the strength of MRI comes from its ability to deliver anatomical information highlighted with different types of contrasts, including functional and diffusion-oriented acquisitions that are often incompatible with normal, multi-shot scans. For these problems, Nobel-award-winning techniques such as Echo Planar Imaging (EPI) have been essential in opening a manifold of new applications. EPI, however, has challenges when dealing with sharp changes in magnetic susceptibility, including those arising in the presence of air/tissue or air/fat interfaces, from non-ferromagnetic metal implants, as well when the main magnetic field cannot be shimmed to achieve the desired degree of homogeneity, as often is the case in systems built using permanent magnets. Among the techniques being proposed to deal with this kind of problem is spatiotemporally-encoded (SPEN) MRI. The present review focuses on the principles of this technique, with an emphasis on: i) explaining SPEN's resilience to field inhomogeneities, on the basis of expanded bandwidth considerations vis-à-vis EPI; ii) “the good, the bad and the ugly” associated with the undersampling that SPEN usually has to carry out when employing expanded bandwidths; iii) recent developments in data processing algorithms seeking to alleviate the “bad and the ugly” part of these experiments by formulating SPEN image reconstruction as an optimization problem, and then relying on compressed sensing and parallel imaging concepts to achieve improved image quality; and iv) the incorporation of experimental improvements including scan interleaving, simultaneous multi-banding and multi-echo elements, to keep in line with advancements in other areas of fast MRI. The strengths and weaknesses of these data sampling and processing strategies are assessed, and examples of their leverage in functional, but foremost diffusion-weighted, imaging applications, are presented.</div></div>","PeriodicalId":20740,"journal":{"name":"Progress in Nuclear Magnetic Resonance Spectroscopy","volume":"146 ","pages":"Article 101559"},"PeriodicalIF":7.3,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143528652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-17DOI: 10.1016/j.pnmrs.2024.101556
Yao Luo, Xiaoxu Zheng, Mengjie Qiu, Yaoping Gou, Zhengxian Yang, Xiaobo Qu, Zhong Chen, Yanqin Lin
Nuclear Magnetic Resonance (NMR), as an advanced technology, has widespread applications in various fields like chemistry, biology, and medicine. However, issues such as long acquisition times for multidimensional spectra and low sensitivity limit the broader application of NMR. Traditional algorithms aim to address these issues but have limitations in speed and accuracy. Deep Learning (DL), a branch of Artificial Intelligence (AI) technology, has shown remarkable success in many fields including NMR. This paper presents an overview of the basics of DL and current applications of DL in NMR, highlights existing challenges, and suggests potential directions for improvement.
{"title":"Deep learning and its applications in nuclear magnetic resonance spectroscopy","authors":"Yao Luo, Xiaoxu Zheng, Mengjie Qiu, Yaoping Gou, Zhengxian Yang, Xiaobo Qu, Zhong Chen, Yanqin Lin","doi":"10.1016/j.pnmrs.2024.101556","DOIUrl":"10.1016/j.pnmrs.2024.101556","url":null,"abstract":"<div><div>Nuclear Magnetic Resonance (NMR), as an advanced technology, has widespread applications in various fields like chemistry, biology, and medicine. However, issues such as long acquisition times for multidimensional spectra and low sensitivity limit the broader application of NMR. Traditional algorithms aim to address these issues but have limitations in speed and accuracy. Deep Learning (DL), a branch of Artificial Intelligence (AI) technology, has shown remarkable success in many fields including NMR. This paper presents an overview of the basics of DL and current applications of DL in NMR, highlights existing challenges, and suggests potential directions for improvement.</div></div>","PeriodicalId":20740,"journal":{"name":"Progress in Nuclear Magnetic Resonance Spectroscopy","volume":"146 ","pages":"Article 101556"},"PeriodicalIF":7.3,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142989368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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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