Magnetic Resonance in Chemistry最新文献

Hydroxypropyl methylcellulose acetyl succinate (HPMCAS) is widely used as a pharmaceutical excipient, making a detailed understanding of its tunable structure important for formulation design. Several recently reported peak assignments in the solid-state ¹³C NMR spectrum of HPMCAS have been corrected here using peak integrals in quantitative spectra, spectral editing, empirical chemical-shift predictions based on solution NMR, and full spectrum simulation analogous to deconvolution. Unlike in cellulose, the strong peak at 84 ppm must be assigned to C2 and C3 methyl ethers, instead of regular C4 of cellulose. The proposed assignment of signals at <65 ppm to OCH sites, including C5 of cellulose, could not be confirmed. CH₂ spectral editing showed two resolved OCH₂ bands, a more intense one from O-CH₂ ethers of C6 at >69 ppm and a smaller one from its esters and possibly residual CH₂-OH groups, near 63 ppm. The strong intensities of resolved signals of acetyl, succinoyl, and oxypropyl substituents indicated the substitution of >85% of the OH groups in HPMCAS. The side-group concentrations in three different grades of HPMCAS were quantified.

Sulfur-33(³³S) stable-isotope labeled taurine, 2-aminoethanesulfonic acid, has been synthesized, and a series of solution and solid-state ³³S nuclear magnetic resonance (NMR) experiments at 14.1 and 18.8 T, respectively, have been carried out at room temperature. The single peak of a solution ³³S NMR spectrum in 0.1-mM [³³S]-taurine in D₂O can be observed with the signal-to-noise (S/N) ratio of 9 in 40,000 scans, which paves the way toward in vivo analysis of pharmacokinetics and metabolism of ³³S-labeled taurine. Undistorted magic-angle-spinning (MAS) and static ³³S NMR spectra of polycrystalline [³³S]-taurine are observed with sufficient S/N ratios for analysis, and the magnitudes of ³³S EFG and CS tensors can be obtained.

The quick identification of known organic low molecular weight compounds, also known as structural dereplication, is a highly important task in the chemical profiling of natural resource extracts. To that end, a method that relies on carbon-13 nuclear magnetic resonance (NMR) spectroscopy, elaborated in earlier works of the author's research group, requires the availability of a dedicated database that establishes relationships between chemical structures, biological and chemical taxonomy, and spectroscopy. The construction of such a database, called acd_lotus, was reported earlier, and its usefulness was illustrated by only three examples. This article presents the results of structure searches carried out starting from 58 carbon-13 NMR data sets recorded on compounds selected in the metabolomics section of the biological magnetic resonance bank (BMRB). Two compound retrieval methods were employed. The first one involves searching in the acd_lotus database using commercial software. The second one operates through the freely accessible web interface of the nmrshiftdb2 database, which includes the compounds present in acd_lotus and many others. The two structural dereplication methods have proved to be efficient and can be used together in a complementary way.

¹³C nuclear magnetic resonance (NMR) is traditionally considered an insensitive technique, requiring long acquisition times to measure dilute functionalities on large polymers. With the introduction of cryoprobes and better electronics, sensitivity has improved in a way that allows measurements to take less than 1/20th the time that they previously did. Unfortunately, a high Q-factor with cryoprobes creates baseline curvature related to acoustic ringing that affects quantitative NMR analyses. Manual baseline correction is commonly used to compensate for the baseline roll, but it is a time-intensive process. The outcome of manual baseline correction can vary depending on processing parameters, especially for complicated spectra. Additionally, it can be challenging to distinguish between broad peaks and baseline rolls. A new anti-ring pulse sequence (zgig_pisp) was previously reported to improve on the incumbent single pulse experiment (zgig). The original report presented limited comparison data with ¹³C NMR, but a thorough validation is needed before broader implementation can be considered. In this work, we report the round-robin testing and comparison of zgig_pisp and zgig pulse sequences. During the testing phase, we found that zgig_pisp is practically equivalent to zgig to ±2% for the majority of integrals examined. Additionally, a short broadband inversion pulse (BIP) was demonstrated as an alternative to the originally reported adiabatic CHIRP shaped pulse. The zgig_pisp pulse sequence code for Bruker spectrometers is also simplified.

High-temperature superconducting (HTS) materials have recently been incorporated into the construction of HTS cryogen-free magnets for nuclear magnetic resonance (NMR) spectroscopy. These HTS NMR spectrometers do not require liquid cryogens, thereby providing significant cost savings and facilitating easy integration into chemistry laboratories. However, the optimal performance of these HTS magnets against standard cryogen NMR magnets must be evaluated, especially with demanding modern NMR applications such as NMR in anisotropic media. The stability of the HTS magnets over time and their performance with complex pulse sequence experiments are the main unknown factors of this new technology. In this study, we evaluate the utility of our prototype 400 MHz cryogen-free power-driven HTS NMR spectrometer, installed in the fumehood of a chemistry laboratory, for stereochemical analysis of three commercial natural products (artemisinin, artemether, and dihydroartemisinin) via measurement of anisotropic NMR data, in particular, residual dipolar couplings. The accuracy of measurement of the anisotropic NMR data with the HTS magnet spectrometer is evaluated through the CASE-3D fitting protocol, as implemented in the Mestrenova-StereoFitter software program.

Nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for qualitative and quantitative analysis. However, for complex mixtures, determining the speciation from NMR spectra can be tedious and sometimes even unfeasible. On the other hand, identifying and quantifying structural groups in a mixture from NMR spectra is much easier than doing the same for components. We call this group-based approach “NMR fingerprinting.” In this work, we show that NMR fingerprinting can even be performed in an automated way, without expert knowledge, based only on standard NMR spectra, namely, ¹³C, ¹H, and ¹³C DEPT NMR spectra. Our approach is based on the machine-learning method of support vector classification (SVC), which was trained here on thousands of labeled pure-component NMR spectra from open-source data banks. We demonstrate the applicability of the automated NMR fingerprinting using test mixtures, of which spectra were taken using a simple benchtop NMR spectrometer. The results from the NMR fingerprinting agree remarkably well with the ground truth, which was known from the gravimetric preparation of the samples. To facilitate the application of the method, we provide an interactive website (https://nmr-fingerprinting.de), where spectral information can be uploaded and which returns the NMR fingerprint. The NMR fingerprinting can be used in many ways, for example, for process monitoring or thermodynamic modeling using group-contribution methods—or simply as a first step in species analysis.

Cullen, L. E., Marchiori, A., Rovnyak, D., Magn Reson Chem 2023, 61(9-10), 337. https://doi.org/10.1002/mrc.5340

Figure S1 The convolutional filter developed in this work is illustrated schematically and then applied to a conservative 50% NUS schedule (512/1024, quantile qsin x = 2, e = 2). In (a), the general algorithm is summarized where a given schedule is expanded and gaps are zero-filled, while integer values in the sampling schedule are set to 1; a short filter sequence constituting a repeating pattern is convolved across the NUS sampling schedule. Metrics developed to characterize the repeat sequences are the (b) convolutional score histogram (CSH), displaying convolutional scores for given repeat sequences, and (c) the repeat length curve (RLC) which demonstrates the lengths and frequencies of a single repeat type in a schedule. The example in this figure means that there are 14 isolated occurrences of the test sequence, and only one tract that has four consecutive instances of the filter sequence. Note: A prior version of the Supporting Information contained a typo in panel (a), which is corrected here.

We apologize for this error.

In a clinical setting, ex vivo perfusions are routinely used to maintain and assess organ viability prior to transplants. Organ perfusions are also a model system to examine metabolic flux while retaining the local physiological structure, with significant success using hyperpolarized (HP) ¹³C NMR in this context. We use a novel exocrine pancreas perfusion technique via the common bile duct to assess acinar cell metabolism with HP [1-¹³C]pyruvate. The exocrine component of the pancreas produces digestive enzymes through the ductal system and is often neglected in research on the pancreas. Real-time production of [1-¹³C]lactate, [1-¹³C]alanine, [1-¹³C]malate, [4-¹³C]malate, [1-¹³C]aspartate, and H¹³CO₃⁻ was detected. The appearance of these resonances indicates flux through both pyruvate dehydrogenase and pyruvate carboxylase. We studied excised pancreata from C57BL/6J mice and NOD.Rag1^−/−.AI4^α/β mice, a commonly used model of Type 1 Diabetes (T1D). Pancreata from the T1D mice displayed increased lactate to alanine ratio without changes in oxygen consumption, signifying increased cytosolic NADH levels. The mass isotopologue analysis of the extracted pancreas tissue using gas chromatography–mass spectrometry revealed confirmatory ¹³C enrichment in multiple TCA cycle metabolites that are products of pyruvate carboxylation. The methodology presented here has the potential to provide insight into mechanisms underlying several pancreatic diseases, such as diabetes, pancreatitis, and pancreatic cancer.

The present review is focused on the most recent achievements in the application of liquid phase ¹⁷O nuclear magnetic resonance (NMR) to inorganic, organic, and biochemical molecules focusing on their structure, conformations, and (bio)chemical behavior. The review is composed of four basic parts, namely, (1) simple molecules; (2) water and hydrogen bonding; (3) metal oxides, clusters, and complexes; and (4) biological molecules. Experimental ¹⁷O NMR chemical shifts are thoroughly tabulated. They span a range of as much as almost 650 ppm (from −35.6 to +610.0 ppm) for inorganic and organic molecules, whereas this range is much wider for biological species being of about 1350 ppm (from −12 to +1332 ppm), and in the case of hemoproteins and heme-model compounds, isotropic chemical shifts of up to 2500 ppm were observed. The general prospects and caveats in the modern development of the liquid phase ¹⁷O NMR in chemistry and biochemistry are critically discussed and briefly outlined in view of their future applications.