Potential Of Nuclear Magnetic Resonance Research Articles

Unexpected temperature dependence of 1H paramagnetic shift in MAS NMR of nickelocene

This work revisits the temperature dependence of 1H paramagnetic shift in nickelocene as a potential nuclear magnetic resonance (NMR) thermometer under fast magic angle spinning (MAS) rate. Surprisingly, an abnormal temperature dependence of 1H paramagnetic shift has been observed. In addition to a 1/T dependence term, a 1/T2 dependence term must be included to correctly describe the curvature behavior of the δ1H-T correlation under fast MAS rate.

Identification and quantification of polystyrene microplastics in marine sediments facing a river mouth through NMR spectroscopy

Accurate identification and quantification of microplastic pollution in marine sediments are crucial for assessing their ecological impact. In this study, we explored the potential of Nuclear Magnetic Resonance (NMR) spectroscopy as an analytical tool for the analysis of microplastics in complex environmental matrices such as marine sediments. Two common plastic polymers, polystyrene (PS) and acrylonitrile butadiene styrene (ABS), were investigated. The marine sediments facing the Tiber River mouth (Italy) were collected according to a bathymetric gradient. Results demonstrated the successful detection and quantification of PS in all sediment samples (within a range of 12.3–64.6 μg/L), while no ABS significant signals were found. An increment trend with depth was observed in the PS signal, relatable to its physicochemical properties and the Tiber River plume hydrodynamic characteristics. The NMR's non-destructive nature and minimal sample preparation represent a promising avenue for standardizing protocols to assess the microplastic distribution and impact in marine sediments.

Potential of nuclear magnetic resonance for the determination of organochlorine in edible oils

Chloride contaminants are the culprit for the formation of harmful compounds such as the 3-monochloropropane-1,2-diol esters (3-MCPDE) and 2-monochlororpropane-1,3-diol esters (2-MCPDE) during edible oil processing. Understanding the source of these chloride’s donor is important for steps to be taken to mitigate the formation of undesirable chloropropanols in refined edible oils. Nuclear magnetic resonance (NMR) was used to differentiate between the inorganic chloride and organochlorine present in crude palm oil, palm superolein, refined olive oil and refined sunflower oil. A quantitative NMR (qNMR) method was developed to analyse the amount of organochlorine present in the aforementioned edible oils. Excellent regression coefficient (R ≥ 0.9995) and LOQ (0.45 ppm) showed that the method is linear and feasible. Recoveries of the method spanned between 90 % and 94 % for the four types of oils analysed. This showed the potential of qNMR for the determination of organochlorine in edible oils.

Metabolomic profiles predict individual multidisease outcomes

Risk stratification is critical for the early identification of high-risk individuals and disease prevention. Here we explored the potential of nuclear magnetic resonance (NMR) spectroscopy-derived metabolomic profiles to inform on multidisease risk beyond conventional clinical predictors for the onset of 24 common conditions, including metabolic, vascular, respiratory, musculoskeletal and neurological diseases and cancers. Specifically, we trained a neural network to learn disease-specific metabolomic states from 168 circulating metabolic markers measured in 117,981 participants with ~1.4 million person-years of follow-up from the UK Biobank and validated the model in four independent cohorts. We found metabolomic states to be associated with incident event rates in all the investigated conditions, except breast cancer. For 10-year outcome prediction for 15 endpoints, with and without established metabolic contribution, a combination of age and sex and the metabolomic state equaled or outperformed established predictors. Moreover, metabolomic state added predictive information over comprehensive clinical variables for eight common diseases, including type 2 diabetes, dementia and heart failure. Decision curve analyses showed that predictive improvements translated into clinical utility for a wide range of potential decision thresholds. Taken together, our study demonstrates both the potential and limitations of NMR-derived metabolomic profiles as a multidisease assay to inform on the risk of many common diseases simultaneously.

Unlocking the Full Potential of NMR Using Machine Learning: A Case Study of a Gas Field With an Oil Problem

This paper describes the application of machine-learning techniques for unlocking the full potential of nuclear magnetic resonance (NMR), using a case study from the Seven Heads gas field. This field has long been recognized but was not developed due to a variety of technical challenges, including the thin-bedded nature of the sediments and the presence of both mobile and immobile viscous residual oil. The oil is a highly viscous liquid which, if produced, could block production tubing due to the shallow depth of the reservoir and associated low pressures. To produce dry gas successfully, identification of both oil and gas zones was necessary to enable gas zones to be perforated and oil zones to be excluded. During the development drilling campaign, the reservoir was appraised using a formation evaluation program specifically designed to address the presence of oil within the thinly bedded reservoir. In conjunction with core data and high-resolution electric logs, NMR logs were used to identify and avoid perforating zones with higher oil saturations. Formation fluid types were derived from the NMR using a pattern recognition technique that analyzes the entire shape of the T1 and T2 distributions to derive the volumes of gas, oil, and water. This machine-learning technique was calibrated using Dean and Stark fluid analysis data and enabled the prediction of continuous water, gas, and oil saturation curves. The results were used to ensure that the perforation strategy avoided oil-bearing sands. This paper describes how the NMR, together with machine learning, has enabled a complex tight gas field to be developed.

Formulation and Characterization of Atorvastatin Nanocystal Tablet

The aim of the present study was to investigate the effect of Soluplus on the solubility of atorvastatin and to develop a nanocrystals formulation that can improve the oral bioavailability of atorvastatin. We demonstrated that Soluplus increases the aqueous solubility of atorvastatin. Several nanocrystals formulations of atorvastatin with Soluplus were prepared at using drug: carrier ratio of 1: 1, 1: 1.1, 1: 1.2, 1: 1.3, 1: 1.4, 1: 1.5, 1: 1.6, 1: 1.7, 1: 1.8, 1: 1.9 and 1: 2 by anti-solvent precipitation. Physicochemical analysis demonstrated that atorvastatin is crystalline in each nanocrystals and the 1: 1 drug: carrier ratio provided the highest degree of sustained atorvastatin super saturation. The prepared nanocrystals were characterized by Fourier Transform Infrared Spectroscopy, Differential Scanning Calorimeter, X-ray Diffraction Study, Zeta potential Nuclear magnetic resonance and Scanning Electron Microscopy. Solubility and dissolution study was performed to check the enhanced properties of nanocrystals of atorvastatin. It was observed that, nanocrystals tablet containing nanocrystals exhibited significantly faster solubility and drug dissolution as compared with conventional and marketed tablet of a drug. Amongst all nanocrystals formulations with drug polymer ratio 1: 1 shows highest solubility that is 2.5027±0.77 as compared to pure drug 0.4918±0.51 mg/ml. This increase solubility and dissolution due to increased surface area and characteristics of nanocrystals and soluplus.

Potential of Nuclear Magnetic Resonance for a Discriminant Characterization of PDO VOOs

Interest in virgin olive oil (VOO) is growing among consumers and industry due to its well‐received sensorial attributes and to its higher oxidative stability, as well as to its positive health effects. Furthermore, attention is being increasingly paid to other quality attributes of VOO, such as sustainability and geographical origin. For these reasons, this oil has an important added value and is exposed to fraudulent practices. In order to guarantee its origin, the European Union (EU) has developed the Protected Designation of Origin (PDO) quality scheme that links the characteristics of a VOO to its geographical origin. In recent years attempts to develop tools that enable the authentication of PDO‐labeled VOOs are carried out. In this regard, studies using Nuclear Magnetic Resonance (NMR) to this aim are here reviewed.Practical Applications: Due to the added value of PDO VOOs, their authentication is of great importance for administration, consumers and producers. The studies in which NMR spectroscopy has been used to this aim are analyzed here. In this context, this review provides a view of the state of the art that can be of practical interest not only for the researchers of the subject but also for the aforementioned groups.Approaches based on NMR spectroscopic data combined with different statistical analysis are used to develop predictive models with the aim of discriminating PDO VOOs from non‐PDO oils, or even to discriminate a VOO from a certain PDO from other different PDO oils.

Molecular diffusion and mobility characterization in ionomer/catalyst dispersions using nuclear magnetic resonance spectroscopy-imaging combined technique

Electrochemical reactions of polymer electrolyte fuel cells occur in catalyst layers, and microscale structure of the catalyst layer is essential for the efficient transport of gas, electron, and proton. Catalyst inks as the dispersion of catalyst/carbon particles and ionomers are used to fabricate catalyst layers, and the preparation process of catalyst inks have an impact on their characteristics and eventually affects the structures of catalyst layers. Herein, we investigated the potential of nuclear magnetic resonance (NMR) spectroscopy and magnetic resonance imaging (MRI) as tools to characterize catalyst inks. We developed an NMR-MRI combined technique to determine the self-diffusion coefficient of solvent molecules at a local region of samples selected from an MRI image. In addition, we used 19F NMR spectroscopy to examine the mobility of main and side chains of the ionomer in various compositions of water–n-propanol mixture solvent. It was found that the ionomer side-chain mobility increased by adding n-propanol to water. Furthermore, we showed that MRI was useful to observe the inhomogeneous particle concentration in the catalyst ink, which was not accessible via optical methods. The characterization techniques presented here are expected to promote fundamental understandings for preparing catalyst inks.

Potential role of nuclear magnetic resonance spectroscopy to identify salivary metabolite alterations in patients with head and neck cancer.

The analysis of the salivary metabolomic profile may offer an early phase approach to assess the changes associated with a wide range of diseases including head and neck cancer. The aim of the present study was to investigate the potential of nuclear magnetic resonance (NMR) spectroscopy for detecting the salivary metabolic changes associated with head and neck squamous cell carcinoma (HNSCC). Unstimulated whole-mouth saliva samples collected from HNSCC patients (primary tumour was located either in the larynx or in the oral cavity) and healthy controls were analysed by 1H-NMR spectroscopy. Reliably identified salivary metabolites were quantified and the determined concentration values were compared group-wise using a Mann-Whitney U-test. Multivariate discrimination function analysis (DFA) was conducted to identify such a combination of metabolites, when considered together, that gives maximum discrimination between the groups. HNSCC patients exhibited significantly increased concentrations of 1,2-propanediol (P=0.032) and fucose (P=0.003), while proline levels were significantly decreased (P=0.043). In the DFA model, the most powerful discrimination was achieved when fucose, glycine, methanol and proline were considered as combined biomarkers, resulting in a correct classification rate of 92.1%, sensitivity of 87.5% and specificity of 93.3%. To conclude, NMR spectrometric analysis was revealed to be a feasible approach to study the metabolome of saliva that is sensitive to metabolic changes in HNSCC and straightforward to collect in a non-invasive manner. Salivary fucose was of particular interest and therefore, controlled longitudinal studies are required to assess its clinical relevance as a diagnostic biomarker in HNSCC.

The potential of nuclear magnetic resonance to track lipids in planta.

Nuclear Magnetic Resonance (NMR) provides a highly flexible platform for non invasive analysis and imaging biological samples, since the manipulation of nuclear spin allows the tailoring of experiments to maximize the informativeness of the data. MRI is capable of visualizing a holistic picture of the lipid storage in living plant/seed. This review has sought to explain how the technology can be used to acquire functional and physiological data from plant samples, and how to exploit it to characterize lipid deposition invivo. At the same time, we have referred to the current limitations of NMR technology as applied to plants, and in particular of the difficulty of transferring methodologies optimized for animal/medical subjects to plant ones. A forward look into likely developments in the field is included, anticipating its key future role in the study of living plant.

Metabolomic analysis of percutaneous fine-needle aspiration specimens of thyroid nodules: Potential application for the preoperative diagnosis of thyroid cancer.

Thyroid nodules are a very common problem. Since malignant thyroid nodules should be treated surgically, preoperative diagnosis of thyroid cancer is very crucial. Cytopathologic analysis of percutaneous fine-needle aspiration (FNA) specimens is the current gold standard for diagnosing thyroid nodules. However, this method has led to high rates of inconclusive results. Metabolomics has emerged as a useful tool in medical fields and shown great potential in diagnosing various cancers. Here, we evaluated the potential of nuclear magnetic resonance (NMR) analysis of percutaneous FNA specimens for preoperative diagnosis of thyroid cancer. We analyzed metabolome of FNA samples of papillary thyroid carcinoma (n = 35) and benign follicular nodule (n = 69) using a proton NMR spectrometer. The metabolomic profiles showed a considerable discrimination between benign and malignant nodules. Receiver operating characteristic (ROC) curve analysis indicated that seven metabolites could serve as discriminators (area under ROC curve value, 0.64–0.85). These findings demonstrated that NMR analysis of percutaneous FNA specimens of thyroid nodules can be potentially useful in the accurate and rapid preoperative diagnosis of thyroid cancer.

Modeling21Ne NMR parameters for carbon nanosystems

The potential of nuclear magnetic resonance (NMR) technique in probing the structure of porous systems including carbon nanostructures filled with inert gases is analysed theoretically using accurate calculations of neon ((21) Ne) nuclear magnetic shieldings. The CBS estimates of (21) Ne NMR parameters were performed for single atom, its dimer and neon interacting with acetylene, ethylene and 1,3-cyclopentadiene. Several levels of theory including restricted Hartree-Fock (RHF), Møller-Plesset perturbation theory to the second order (MP2), density functional theory (DFT) with van Voorhis and Scuseria's t-dependent gradient-corrected correlation functional (VSXC), coupled cluster with single and doubles excitations (CCSD), with single, doubles and triples included in a perturbative way (CCSD(T)) and single, doubles and tripes excitations (CCSDT) combined with polarization-consistent aug-pcS-n series of basis sets were employed. The impact of neon confinement inside selected fullerene cages used as an NMR probe was studied at the RHF/pcS-2 level of theory. A sensitivity of neon probe to the proximity of multiple CC bonds in C2 H2 , C2 H4 , C5 H6 and inside C28 , C30 , C32 , C34 and C60 fullerenes was predicted from (21) Ne NMR parameters' changes. Copyright © 2013 John Wiley & Sons, Ltd.

Assessment of moisture protective properties of wood coatings by a portable NMR sensor

We have evaluated the potential of nuclear magnetic resonance (NMR) spectroscopy based on small portable magnets for in situ assessment of moisture protective properties of wood coatings. Low field 1H NMR with a unilateral permanent magnet was used to monitor and map the local moisture content (MC) of wood specimens uncoated or coated with various types of commercial paint systems. The MC beneath a coating layer was measured with a penetration depth up to 5 mm and with a depth resolution of 0.2 mm. The method is quick, noninvasive, simple to perform, and does not require removing wooden parts from the structure.

A 59Co NMR study to observe the effects of ball milling on small ferromagnetic cobalt particles

To demonstrate the potential of nuclear magnetic resonance (NMR) spectroscopy for investigating detailed structural properties in ferromagnetic materials, three different particle sized cobalt (Co) powders have been ball milled for 24 h are accurately characterised by internal-field 59Co NMR. The 59Co NMR spectra show distinct resonance bands corresponding to the different Co sites, face-centred-cubic (fcc), hexagonal-close-packed (hcp) and stacking faults (sfs), in Co metal powders. The hcp+fcc→hcp phase transition encouraged by ball-milling was observed and quantitative values for each Co environment were obtained.

Identification of an apple juice compound directly in the 1H-spectrum of the mixture with hyphenated techniques and push button NMR: example fruit juice screening

Nuclear Magnetic Resonance (NMR) has been used for structure analysis of pure compounds over decades. Opposite to this, the extraordinary potential of NMR has just started to be recognized and exploited in the analysis of mixtures in the context of biofluids and food beverages. In our contribution, we will show results of studies done in the field of beer and the already developed BRUKER-SGF-Profiling Method, the NMR Fruit-Juice Screener. We will show, that from the very same set of spectra several specific parameters can be derived. 1H NMR in combination with pattern recognition: 1. can distinguish between direct juices and juices from re-diluted concentrates, 2. can identify the geographical origin of the fruits used to produce the juices, 3. can even identify mixing of direct juices and concentrates, 4. can identify artificial addition of different sugars, glucose syrup and RTK. Two approaches for quantification of individual metabolites in juices and beer were successfully applied. The first is based on integration of individual lines in the individual spectra after identification which can be done by combining spectral match technology with pure compound spectra from a reference spectral data base. The second approach is Partial Least Squares Regression (PLS), a supervised prediction approach which uses calibration models obtained from a training data set. The latter approach proved most successful even for the prediction of parameters which are not directly related to individual metabolites like the gravity of beer from proton NMR spectra. LC-NMR cannot be used in a high throughput screening scenario, as it is not sensitive enough in the on-flow-mode, thus comparison between NMR results and LC-MS is important. Therefore combining flow-injection-NMR and LC-MS is a promising approach. The two most important analytical tools can be hyphenated and in its most stringent form also time synchronised. This allows to create NMR and LC-MS data for either individual statistical evaluations or for combined methods such as the NMR/LC-MS covariance. This for example allows combining molecular ion information directly with the corresponding NMR signals of the same compound and as such gives so far unreached structural information. In our contribution we will show the power of the hyphenated techniques, the application of the MetabolicProfiler™. As an example we identify the structure of the most differentiating metabolite in apple juice concentrates from China and Poland directly from the statistical evaluation of the mixture spectra and the SBASE database.

RAPID IDENTIFICATION OF NON-SPORING ANAEROBES USING NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY AND AN IDENTIFICATION STRATEGY

Purpose: The non-sporing anaerobes cause a wide spectrum of infections. They are difficult to culture and their identification is tedious and time-consuming. Rapid identification of anaerobes is highly desirable. Towards this end, the potential of nuclear magnetic resonance (NMR) spectroscopy for providing a fingerprint within the proton spectrum of six genera belonging to anaerobes reflecting their characteristic metabolites has been investigated. Methods: NMR analysis was carried out using Mercury plus Varian 300 MHz (7.05 T) NMR spectrophotometer on six different anaerobes. These included Bacteroides fragilis, Prevotella melaninogenica, Prevotella denticola, Fusobacterium necrophorum, Peptococcus niger and Peptostreptococcus spp. After the NMR analysis (256/512 scans), the different peaks were noted. The eight pus specimens, which yielded pure culture of anaerobe, also were analysed similarly. Results: The major resonances of multiplex of amino acids/lipid at 0.9 ppm along with lactate/lipid at 1.3 ppm, acetate at 1.92 ppm and multiplex of lysine at 3.0 ppm remained constant to label the organism as an anaerobe. There was a difference found in the MR spectra of different genera and species. A simple algorithm was developed for the identification of the six different anaerobes studied. The MR spectra of the pure culture of the organism matched the MR spectra of pus from which the organism was isolated. Conclusions: MR-based identification was of value in the identification of anaerobes. However, a larger database of the peaks produced by anaerobes needs to be created for identification of all genera and species. It could then have the potential of diagnosing an anaerobic infection in vivo and thus expedite management of deep-seated abscesses.

Rapid identification of non-sporing anaerobes using nuclear magnetic resonance spectroscopy and an identification strategy

The non-sporing anaerobes cause a wide spectrum of infections. They are difficult to culture and their identification is tedious and time-consuming. Rapid identification of anaerobes is highly desirable. Towards this end, the potential of nuclear magnetic resonance (NMR) spectroscopy for providing a fingerprint within the proton spectrum of six genera belonging to anaerobes reflecting their characteristic metabolites has been investigated. NMR analysis was carried out using Mercury plus Varian 300 MHz (7.05 T) NMR spectrophotometer on six different anaerobes. These included Bacteroides fragilis, Prevotella melaninogenica, Prevotella denticola, Fusobacterium necrophorum, Peptococcus niger and Peptostreptococcus spp. After the NMR analysis (256/512 scans), the different peaks were noted. The eight pus specimens, which yielded pure culture of anaerobe, also were analysed similarly. The major resonances of multiplex of amino acids/lipid at 0.9 ppm along with lactate/lipid at 1.3 ppm, acetate at 1.92 ppm and multiplex of lysine at 3.0 ppm remained constant to label the organism as an anaerobe. There was a difference found in the MR spectra of different genera and species. A simple algorithm was developed for the identification of the six different anaerobes studied. The MR spectra of the pure culture of the organism matched the MR spectra of pus from which the organism was isolated. MR-based identification was of value in the identification of anaerobes. However, a larger database of the peaks produced by anaerobes needs to be created for identification of all genera and species. It could then have the potential of diagnosing an anaerobic infection in vivo and thus expedite management of deep-seated abscesses.

T 1-T 2 correlation analysis of complex foods

The potential of nuclear magnetic resonance two-dimensionalT 1-T 2 correlation spectroscopy for quality control in food science is explored for three types of food, namely, egg (white and yolk), cellular tissue (fruit and vegetable) and hydrocolloids (creams and baked products). The complications of cross-relaxation and diffusive exchange are highlighted and various tools for peak assignment are discussed.

Measuring in-vivo metabolism using nuclear magnetic resonance.

This review introduces physiologists and clinical investigators to an ever-widening array of nuclear magnetic resonance applications. In particular, it highlights a multiple tracer technique that provides a comprehensive picture of metabolic processes within human liver. Magnetic resonance spectroscopy is an important technique for studying metabolism in the brain, liver, heart and skeletal muscle. One fundamental advantage is that the studies are inherently noninvasive, so time-dependent information can be obtained. For example, 31P nuclear magnetic resonance investigations indicate that greater maximal oxygen uptake and oxidative capacity in trained athletes can be partially attributed to adaptations enhancing the rates at which phosphocreatine and inorganic phosphate recover during stress. In-vivo measurements of lipids and glycogen by 1H and 13C spectroscopy demonstrate that accumulation of intracellular lipids and impaired rates of glycogen synthesis contribute to insulin resistance and type 2 diabetes mellitus. Similar techniques can be used to analyze blood and urine samples obtained during administration of 2H or 13C tracers to yield information that cannot be easily obtained by mass spectrometry. Additional information available from nuclear magnetic resonance yields a comprehensive picture of liver metabolic pathways from a single clinical study. A variety of magnetic resonance spectroscopy protocols have been validated and exploited for clinical studies, but relatively few investigators are comfortable with technical aspects of these protocols and utilize them for clinical research. Increased interaction between spectroscopists and other investigators is needed if the potential of nuclear magnetic resonance for studying in-vivo metabolism is to be fully realized.

Prospects for the rapid detection of mealiness in apples by nondestructive NMR relaxometry

The potential of nuclear magnetic resonance (NMR) relaxometry for quantitative evaluation of apple mealiness has been investigated. The degree of “mealiness” was defined by several mechanical techniques, including penetration, compression and shear rupture as well as by the BRIX (soluble solids) and juiciness levels. These data were correlated with both magnetic resonance imaging (MRI) and NMR water proton transverse relaxation time measurements on a fruit-by-fruit basis. It was found that increasing mealiness caused a systematic increase in the transverse relaxation rate. The potential for rapid, on-line NMR/MRI detection of apple mealiness is discussed.