Magnetic Resonance in Chemistry最新文献

Curcuminoids, including curcumin, demethoxycurcumin, and bisdemethoxycurcumin, are vital for quality control in food, nutraceuticals, and pharmaceuticals. Conventional 1D ¹H NMR can face challenges in spectral interpretation when dealing with overlapping signals and complex coupling patterns, especially in structurally similar compounds like curcuminoids. This study explores the use of selective homodecoupled 1D ¹H NMR spectroscopy as a complementary technique to enhance spectral resolution and facilitate peak assignment in curcuminoid analysis. By collapsing multiplet structures such as doublets observed in the 6.6- to 6.8-ppm region for vinylic protons into singlets, this method offers improved spectral clarity. Although absolute quantification still requires deconvolution, the approach aids in more straightforward relative integration and identification of components within curcuminoid mixtures from turmeric samples. The results demonstrate improved interpretability compared with conventional ¹H NMR under similar conditions. Comparative analysis with HPLC showed excellent agreement, with standard deviations under 2% for most samples. The selective homodecoupled 1D ¹H NMR method proved robust and reliable, offering an effective tool for profiling curcuminoids and potential application to other natural product mixtures.

Carbones bear the same resonance contributor X⁺–C²⁻–Y⁺ (X⁺, Y⁺ = PR₃⁺, CR₂⁺, SR₂⁺, SeR₂⁺, S⁺R₂ = NR) and exhibit unique bonding and donating properties at the central carbon atom. Both the analogues of carbones C⁺–Z²⁻–C⁺ (Z = Si, Ge, Sn, Pb) and the large number of charged main group homologues C=Z=C (Z = B⁻, Al⁻, Ga⁻, N⁺, P⁺, As⁺, Sb⁺, Bi⁺, O²⁺, S²⁺, Se²⁺ and Te²⁺) are known for comparable bonding and donating properties. The electronic structure of the carbone homologues and analogues has been studied on basis of both their geometry and their spatial magnetic properties (through-space-NMR-shieldings [TSNMRSs]) with regard to the present dominating electronic structure (beside carbone-like [⁺C–Z²⁻–C⁺] also allene-like [C=Z=C] or carbene-like [⁺C–Z⁻=C]). TSNMRS values have been calculated using the GIAO perturbation method employing the nucleus independent chemical shift (NICS) concept and the results visualized as iso-chemical-shielding surfaces (ICSS) of various size and direction. The synergy of geometry (bond lengths, bond angles of linear, bent, orthogonal or twisted structures) and the spatial magnetic properties (anisotropy effect of C=C in allene-like or partial C=C double bonds in carbene-like structures, and the ball-like anisotropy effect of central hetero atom Z of carbone-like structures) provide a comprehensive picture of the respective structure and the dominating resonance contributor.

Verbascoside and isoverbascoside are phenylethanoid glycosides with reported biological activities such as neuroprotection, hepatoprotection, anti-inflammatory, antimicrobial, anticancer, and antioxidant properties. These compounds are constitutively present in roots, stems, leaves, and flowers of various plant species, including Tecoma stans. In Mexico, this plant is traditionally used as a safe and effective herbal treatment for chronic diseases and its complications including diabetes and renal and hepatic disorders. The potential pharmacological applications of verbascoside and isoverbascoside have conducted efforts to produce these compounds in cell and plant tissue cultures. In this study, T. stans root and plantlet in vitro cultures were established as potential sources of verbascoside and isoverbascoside, and NMR was used as primary analytical tool. As a first step, proton and bidimensional NMR analysis confirmed the presence of verbascoside and isoverbascoside in T. stans in vitro culture extracts. Subsequently, their contents were quantified by means of quantitative NMR (qNMR) based on the external standard PULCON method. Furthermore, ¹H-NMR spectral data were used to develop a descriptive PLS-DA model, which confirms the qNMR results. This model indicated that differences in the amounts and proportions of verbascoside and isoverbascoside produced by roots and plantlets are the primary factors in distinguishing these samples. These results demonstrate the capability of T. stans in vitro systems as biotechnological tools for obtaining phenylethanoids with high pharmacological potential and confirm the broad applicability of NMR as an analytical platform. However, additional experiments are necessary to improve the phenylethanoids glucoside yields and support the validation of the qNMR method.

The selective refocusing (SERF) and its modified experiments have permitted the unambiguous assignment of peaks and the straightforward determination of ⁿJ_HH. However, they suffer from the presence of intense axial peaks and the evolution of undesirable couplings in the spectra. In partially addressing these challenges, the Clean-G-SERF sequence, a modified version of the gradient-enhanced SERF–based experiment (G-SERF), has been designed to suppress all the axial peaks and eradicate the unwanted evolution, while retaining only the couplings pertaining to the selectively excited proton. Furthermore, the incorporation of a perfect echo block provided the leverage for increasing slice thickness leading to the increased sensitivity. To additionally enhance the resolution in the direct dimension, the improved sequences have been designed by the incorporation of pure shift, where the homonuclear J couplings are refocused in real time. All these methods permitted the unambiguous assignment of peaks to the coupled partners of the selectively excited proton, thereby enabling the accurate measurement of couplings. The broader utility of the designed sequences, cited in the literature as Clean-G-SERF, Clean-PE-SERF, PS-Clean-G-SERF and PS-Clean-PE-SERF have been demonstrated on several chosen examples including the molecular mixtures for the accurate measurement of J_HH.

Pharmaceutical analysis is essential to drug development and quality assurance, ensuring that products meet stringent safety and efficacy standards. Quantitative solid-state NMR (qSSNMR) has become a key technique, enabling precise quantification and characterization of solid drug formulations. This mini-review highlights the evolution of qSSNMR, focusing on improvements in detection limits, resolution, and high-throughput capabilities. This review explores technical advancements and applications for analyzing complex pharmaceutical mixtures. While challenges remain for widespread adoption, efforts in automation, user-friendly software, and collaboration aim to address these.

Quantitative nuclear magnetic resonance (qNMR) can determine the concentration of compounds in solution with remarkable trueness and precision, if the experimental conditions are chosen correctly. However, some users still have difficulty with the correct implementation of these requirements. Knowing which requirements are mandatory and which can be neglected for a given accuracy is one of the major problems. Failure to follow basic requirements s will lead to unreliable results. On the other hand, avoiding unnecessary constraints—for the desired level of trueness and/or precision—can save precious time. The aim of this tutorial is therefore to review in the second section the basic principles of quantitative NMR and explain the impact of different acquisition and processing conditions on trueness and precision. These general guidelines provide both precision and trueness of 1%. To reach 1‰, one has to optimize further their experimental conditions and consider the instrumental imperfections.

Over the past 20 years, the use of quantitative nuclear magnetic resonance (qNMR) technology has grown significantly in pharmaceutical industry. However, its broader adoption is often limited by specialized expertise required to implement best practices. Recent discussions within the qNMR community in China (qNMR-C) have highlighted the benefits of establishing an applicable qNMR platform method—one that serves as a universal approach, adaptable across multiple products. This approach aims to standardize a single set of qNMR parameters to address the majority of quantitative applications and making qNMR more accessible, particularly for researchers new to the field. The present study outlines the rationale behind the proposed qNMR platform method and demonstrates its strategic framework through a series of designed tests. Key parameters influencing qNMR accuracy and precision, including signal-to-noise ratio, data processing, integration approaches, relaxation delays, T₁ relaxation times, and sample weight, were systematically evaluated. A collaborative effort involving 12 NMR instruments across eight laboratories assessed the method's applicability and demonstrated its proper design space. Another objective of this study is to streamline the qNMR workflow, enabling novices to produce reliable, high-quality data early in their learning while ensuring reproducible and meaningful results. Furthermore, this work calls upon the global qNMR community to engage in the continued validation of the proposed platform method, fostering collective knowledge and verifying its robustness across diverse applications.