Low-field nuclear magnetic resonance (NMR) has three general modalities: spectroscopy, imaging, and relaxometry. In the last twelve years, the modality of spectroscopy, also known as benchtop NMR, compact NMR, or just low-field NMR, has undergone instrumental development due to new permanent magnetic materials and design. As a result, benchtop NMR has emerged as a powerful analytical tool for use in process analytical control (PAC). Nevertheless, the successful application of NMR devices as an analytical tool in several areas is intrinsically linked to its coupling with different chemometric methods. This review focuses on the evolution of benchtop NMR and chemometrics in chemical analysis, including applications in fuels, foods, pharmaceuticals, biochemicals, drugs, metabolomics, and polymers. The review also presents different low-resolution NMR methods for spectrum acquisition and chemometric techniques for calibration, classification, discrimination, data fusion, calibration transfer, multi-block and multi-way.

Lipid analysis is an integral part of food authentication and quality control which provides consumers with the necessary information to make an informed decision about their lipid intake. Recent advancement in lipid analysis and lipidome scope represents great opportunities for food science. In this review we provide a comprehensive overview of available tools for extraction, analysis and interpretation of data related to dietary fats analyses. Different analytical platforms are discussed including GC, MS, NMR, IR and UV with emphasis on their merits and limitations alongside complementary tools such as chemometric models and lipid-targeted online databases. Applications presented here include quality control, authentication of organic and delicacy food, tracing dietary fat source and investigating the effect of heat/storage on lipids. A multitude of analytical methods with different sensitivity, affordability, reproducibility and ease of operation are now available to comprehensively analyze dietary fats. Application of these methods range from studies which favor the use of large data generating platforms such as MS-based methods, to routine quality control which demands easy to use affordable equipment as TLC and IR. Hence, this review provides a navigation tool for food scientists to help develop an optimal protocol for their future lipid analysis quest.

Nuclear magnetic resonance (NMR) spectroscopy is one of the principal analytical techniques for metabolomics. It has the advantages of minimal sample preparation and high reproducibility, making it an ideal technique for generating large amounts of metabolomics data for biobanks and large-scale studies. Metabolomics is a popular \"omics\" technology and has established itself as a comprehensive exploratory biomarker tool; however, it has yet to reach its collaborative potential in data collation due to the lack of standardisation of the metabolomics workflow seen across small-scale studies. This systematic review compiles the different NMR metabolomics methods used for serum, plasma, and urine studies, from sample collection to data analysis, that were most popularly employed over a two-year period in 2019 and 2020. It also outlines how these methods influence the raw data and the downstream interpretations, and the importance of reporting for reproducibility and result validation. This review can act as a valuable summary of NMR metabolomic workflows that are actively used in human biofluid research and will help guide the workflow choice for future research.

SARS-CoV-2 is the coronavirus causing the ongoing pandemic with > 460 millions of infections and > 6 millions of deaths. SARS-CoV-2 nucleocapsid (N) is the only structural protein which plays essential roles in almost all key steps of the viral life cycle with its diverse functions depending on liquid-liquid phase separation (LLPS) driven by interacting with various nucleic acids. The 419-residue N protein is highly conserved in all variants including delta and omicron, and composed of both folded N-/C-terminal domains (NTD/CTD) as well as three long intrinsically disordered regions (IDRs). Recent results have suggested that its CTD and IDRs are also cryptic nucleic acid-binding domains. In this context, any small molecules capable of interfering in its interaction with nucleic acids are anticipated to modulate its LLPS and associated functions. Indeed, ATP, the energy currency existing at very high concentrations (2-12 mM) in all living cells but absent in viruses, modulates LLPS of N protein, and consequently appears to be evolutionarily hijacked by SARS-CoV-2 to promote its life cycle. Hydroxychloroquine (HCQ) has been also shown to specifically bind NTD and CTD to inhibit their interactions with nucleic acids, as well as to disrupt LLPS. Particularly, the unique structure of the HCQ-CTD complex offers a promising strategy for further design of anti-SARS-CoV-2 drugs with better affinity and specificity. The finding may indicate that LLPS is indeed druggable by small molecules, thus opening up a promising direction for drug discovery/design by targeting LLPS in general.

Nuclear magnetic resonance (NMR) spectroscopy is a robust method, which can rapidly analyze mixtures at the molecular level without requiring separation and/or purification steps, making it ideal for applications in food science. Despite its increasing popularity among food scientists, NMR is still an underutilized methodology in this area, mainly due to its high cost, relatively low sensitivity, and the lack of NMR expertise by many food scientists. The aim of this review is to help bridge the knowledge gap that may exist when attempting to apply NMR methodologies to the field of food science. We begin by covering the basic principles required to apply NMR to the study of foods and nutrients. A description of the discipline of chemometrics is provided, as the combination of NMR with multivariate statistical analysis is a powerful approach for addressing modern challenges in food science. Furthermore, a comprehensive overview of recent and key applications in the areas of compositional analysis, food authentication, quality control, and human nutrition is provided. In addition to standard NMR techniques, more sophisticated NMR applications are also presented, although limitations, gaps, and potentials are discussed. We hope this review will help scientists gain some of the knowledge required to apply the powerful methodology of NMR to the rich and diverse field of food science.

Nuclear magnetic resonance (NMR) spectroscopy is an important analytical tool in chemistry, biology, and life science, but it suffers from relatively low sensitivity and long acquisition time. Thus, improving the apparent signal-to-noise ratio and accelerating data acquisition became indispensable. In this review, we summarize the recent progress on low-rank Hankel matrix and tensor methods, which exploit the exponential property of free-induction decay signals, to enable effective denoising and spectra reconstruction. We also outline future developments that are likely to make NMR spectroscopy a far more powerful technique.

Metabolomics involvement in the study of foods is steadily growing. Such a rise is a consequence of the increasing demand in the food sector to address challenges regarding the issues of food safety, quality, and authenticity in a more comprehensive way. Virgin olive oil (VOO) is a key product of the Mediterranean diet, with a globalized consumer interest as it may be associated with various nutritional and health benefits. Despite the strict legislation to protect this high added-value agricultural commodity and offer guarantees to consumers and honest producers, there are still analytical issues needing to be further addressed. Thus, this review aims to present the efforts made using targeted and untargeted metabolomics approaches, namely nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry-based techniques (mainly LC/GC-MS) combined with multivariate statistical analysis. Case-studies focusing on geographical/varietal classification and detection of adulteration are discussed with regards to the identification of possible markers. The advantages and limitations of each of the aforementioned techniques applied to VOO analysis are also highlighted.

Since the concept of deep learning (DL) was formally proposed in 2006, it has had a major impact on academic research and industry. Nowadays, DL provides an unprecedented way to analyze and process data with demonstrated great results in computer vision, medical imaging, natural language processing, and so forth. Herein, applications of DL in NMR spectroscopy are summarized, and a perspective for DL as an entirely new approach that is likely to transform NMR spectroscopy into a much more efficient and powerful technique in chemistry and life sciences is outlined.

Unravelling the relationship between food and health requires a more in-depth knowledge of the various changes occurring in the gastrointestinal tract during digestion and which may ultimately affect the nutritional quality and safety of ingested food lipids before absorption into the bloodstream. In this context, this review deals with the oxidation process of food lipids under digestive conditions and the studies carried out on this topic using different digestion models: in vitro, in vivo or ex vivo, static or dynamic, and including one, two and/or three digestive phases (oral, gastric and duodenal). These studies have contributed to clarifying the occurrence and extent of lipid degradation under such a particular environment, many of them also highlighting the factors affecting the advance or delay of the oxidation of dietary lipids during digestion, like: food lipid content, unsaturation degree and initial oxidative status; the presence in the food bolus of compounds showing antioxidant activity (polyphenols, tocopherols…) either added or naturally present; the presence in the food bolus of proteins (including iron or not); food technological or culinary processings (salting, smoking, cooking…), among others. Likewise, the methodologies employed to study lipid oxidation under digestive conditions are also summarized and future research perspectives are discussed.

Fatty acids are important nutritional substances and metabolites in living organisms. These acids are abundant in Chinese herbs, such as Brucea javanica, Notopterygium forbesii, Isatis tinctoria, Astragalus membranaceus, and Aconitum szechenyianum. This review illustrates the types of fatty acids and their significant roles in the human body. Many analytical methods are used for the qualitative and quantitative evaluation of fatty acids. Some of the methods used to analyze fatty acids in more than 30 kinds of plants, drugs, and other samples are presented in this paper. These analytical methods include gas chromatography, liquid chromatography, near-infrared spectroscopy, and NMR spectroscopy. The advantages and disadvantages of these techniques are described and compared. This review provides a valuable reference for establishing methods for fatty acid determination.