Nuclear Magnetic Resonance Research Articles (Page 1)

Phytochemicals from Stellera chamaejasme alleviate psoriasis by modulating the immune microenvironment via the JAK2/PI3K/AKT pathway.

A candidate reference measurement procedure (RMP) based on isotope dilution (ID) liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed and validated to accurately measure serum and plasma concentrations of mycophenolic acid glucuronide (MPAG). Quantitative nuclear magnetic resonance (qNMR) spectroscopy was utilized for determining the absolute content (mass fraction; g/g) of the reference material, thereby, establishing the traceability to SI units. Separation of MPAG from potential interferences, whether known or unknown, was accomplished by using a Phenomenex Luna C18(2) column. For sample preparation, a protocol based on protein precipitation followed by a high-dilution step was established. A multi-day validation experiment evaluated precision and accuracy. Reproducibility was determined by comparing the results of the procedure between two independent laboratories. Measurement uncertainty (MU) was assessed in accordance with current guidelines. The RMP demonstrated high selectivity and specificity enabling the quantification of MPAG in the range between 0.750 and 600 μg/mL. The intermediate precision and repeatability (n=60, measurements) were found to be in the range from 0.9 to 3.7 % for serum samples and from 1.2 to 4.6 % for plasma samples. The repeatability was less than 3.5 % for serum samples and less than 4.0 % for plasma samples. The relative mean bias ranged from-0.9 to 3.2 % for serum samples and from-0.3 to 2.9 % for plasma samples. The expanded measurement uncertainties (k=2) for single measurements ranged between 2.4 and 7.7 % and were further reduced performing a target value assignment (n=6) resulting in expanded measurement uncertainties between 1.8 and 3.3 % (k=2), respectively. We herein present a new LC-MS/MS-based candidate RMP for MPAG in human serum and plasma which offers a traceable and reliable platform for the standardization of routine assays and evaluation of clinically relevant samples.

Low-field nuclear magnetic resonance (NMR) is a powerful technique for characterizing fluid behavior in shale oil reservoirs. However, the abundant nanopores in shale and the limitations of experimental echo time hinder its further application in characterizing oil occurrence. This study integrates the ratio of longitudinal to transverse relaxation times (T1/T2) with molecular dynamics simulations to determine the distributions of dissolved, adsorbed, and free n-decane in kerogen nanoslits and further develops quantitative models to characterize the occurrence characteristics of n-decane in these confined systems. The results indicate that alkane molecules in the same state exhibit identical T1/T2 values, with the T1/T2 values of dissolved, adsorbed, and free molecules being 25.27, 18.61, and 14.86, respectively. For each occurrence state, both the self-diffusion coefficient of n-decane and its interaction energy with the kerogen nanoslit walls exhibit distinct linear correlations with T1/T2. Furthermore, three mathematical models are developed to quantify the relationships between T1/T2 and the slit width, the adsorption layer thickness (H), and the free-to-adsorbed mass ratio (mf/ma). When T1/T2 ranges from 75.21 to 53.25, mf/ma = 0, indicating the absence of a free state. This state corresponds to slit widths of 1-3 nm, within which H varies linearly with T1/T2. As T1/T2 decreases further from 53.25 to 1.00, mf/ma increases exponentially while H stabilizes at ∼2.86 nm, suggesting three-state coexistence within 3-50 nm slits. Free-state dominance occurs when T1/T2 approaches 1, corresponding to a slit width of approximately 50 nm. Additionally, with increasing kerogen maturity, the kerogen matrix exhibits reduced solubility but enhanced adsorption capacity for n-decane. For kerogen types I-A, II-D, and III-A, T1/T2 shows exponential correlations with both slit width and mf/ma, indicating free-state dominance at slit widths of 45, 50, and 58 nm, respectively. This work is expected to provide novel insights into shale reservoir evaluation and enhanced oil recovery.

Among stable isotope measurement strategies at natural abundance, position-specific isotope analysis (PSIA) is a valuable approach for food authentication and metabolism understanding. In this context, carbon-13 nuclear magnetic resonance (irm-13C NMR) spectroscopy has emerged as an efficient tool. It enables the determination of the absolute 13C intramolecular composition (δ13Ci) when all NMR signals are well-resolved and the global 13C content (δ13Cg) is known. However, in the case of fatty acids with eight carbons or more, 13C-NMR can only resolve six carbon signals. δ13Ci values are thus not attainable without specialized methods. To overcome this limitation, we developed a novel methodology that leverages the concept of isotopic intramolecular referencing by using the methoxy group in the fatty acid methyl esters (FAMEs) as a reference. We thus determined δ13Ci values with improved trueness and repeatability without requiring δ13Cg measurement. Combining this enhancement with the acquisition of 13C NMR spectra using an adiabatic INEPT pulse sequence offered a more time-efficient, sample-efficient, and sustainable approach, rendering the entire process greener. We successfully applied this approach to FAMEs from butter and coconut oil. Subsequent studies will evaluate the effectiveness of the novel isotopomic biomarkers derived from our method in authenticating foodstuffs and elucidating metabolic differences among fatty acids. Additionally, the same intramolecular isotope referencing approach will be of interest for studying other molecules and isotopes.

Amino-silane-based surface passivation schemes are gaining attention in halide perovskite optoelectronics, with varying levels of success. We compare surface treatments using (3-aminopropyl)trimethoxysilane (APTMS) and [3-(2-aminoethylamino)propyl]trimethoxysilane (AEAPTMS), applied via room-temperature vacuum deposition, to the perovskite FA0.78Cs0.22Pb(I0.85Br0.15)3 (FA = formamidinium). Both molecules improve thin-film photoluminescence properties and photovoltaic device performance, although their effectiveness depends strongly on deposition time. We show AEAPTMS has a wider, more robust processing window and yields higher performance under optimized conditions. In contrast, overexposure, particularly with APTMS, reduces performance, with notable reductions in photoluminescence lifetime and absorbance. To probe the underlying chemistry, we employ nuclear magnetic resonance (NMR) spectroscopy and depth-resolved time-of-flight secondary ion mass spectrometry (ToF-SIMS), demonstrating that both amino-silanes react with formamidinium (FA+) cations in solution and in the solid state. This work underscores the importance of optimizing deposition conditions to balance effective passivation with potential performance loss and elucidates previously unrecognized reactive chemistry between amino-silane passivating agents and halide perovskites.

Dynamic nuclear polarization (DNP) is a powerful route for overcoming the inherent sensitivity limitation of solid-state nuclear magnetic resonance (ssNMR) spectroscopy by transferring high electron spin polarization to surrounding nuclear spins. Cross-effect (CE) DNP is the most efficient mechanism in solids. CE requires several conditions to be met, primarily the presence of two coupled electron spins with resonance frequencies separated by the nuclear Larmor frequency. This condition is typically achieved through the presence of large anisotropic spin interactions, which shift the transition frequencies of the two coupled electron spins with respect to each other. Here we present an alternative approach, where the CE condition is met via isotropic interactions. This is advantageous as it makes CE independent of the sample orientation, thus making the enhancements independent of the MAS frequency and enabling the use of fast relaxing polarizing agents. We demonstrate the feasibility of the approach in experiments and simulations for Mn(II) dopants as polarizing agents, making use of the isotropic hyperfine interactions with its 55Mn nuclear spin to achieve the required frequency difference.

The dramatic advances made recently by protein-structure prediction tools like AlphaFold offer an opportunity for the development of new experimental methods designed to test sequence-based predictions rather than build full atomistic structures from scratch. While atomistic methods such as X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, and cryogenic electron microscopy (CryoEM) will always play a critical role in structure determination, their cost and stringent sample preparation requirements can be prohibitive for routine characterization. Spectroscopic methods such as circular dichroism (CD) and Fourier-transform infrared (FTIR) spectroscopy are often cheaper and faster but offer insight only into bulk secondary-structure content such as the total fraction of α-helix or β-sheet present in a protein. In the present contribution, we suggest that isotope-labeled FTIR spectroscopy has the potential to fill this gap, and we demonstrate a new experimental approach to producing isotope-enriched spectra at a low sample cost. We illustrate these concepts experimentally using the protein Top7 V48 V (whose crystal structure is known) as an example. By selectively 12C-labeling individual amino acid residues in only 5 mL of 13C-enriched protein-expression culture, we collect FTIR spectra of each reverse-labeled protein construct at a cost of only a few dollars of isotope-enriched material per sample. Analysis of the resulting isotope reverse-labeled FTIR spectra provides a path to secondary-structure assignments for each amino acid individually rather than only the total secondary structure estimates that are available from traditional FTIR or CD measurements. Combining these residue-specific secondary-structure assignments with knowledge of the protein's primary sequence, we obtain assignments for the secondary structure of each stretch of amino acids in the protein that agree well with the published crystal structure of the protein. Based on these results, we suggest that this approach offers a fast and efficient means of extracting sequence-specific structural information that can be applied to proteins in a wide variety of contexts, from live cells to solubilized membranes.

Among the various mysteries in cuprate high temperature superconductors, the pseudogap (PG) phase stands out for the difficulty in pinning down its origin and its close connection to unconventional superconductivity. It appears above the superconducting transition temperature ​, where part of the low energy spectral weight becomes depleted and several competing or intertwined orders such as charge and pair density waves, nematicity, and spin fluctuations begin to develop. A persistent challenge lies in the systematic discrepancies revealed by different experimental probes, as transport measurements locate the critical doping near , spectroscopic studies around , and symmetry sensitive techniques close to . These variations reflect the distinct sensitivities of each probe to correlation length scales and electronic coherence rather than experimental inconsistency. This review brings together evidence from angle resolved photoemission spectroscopy (ARPES), scanning tunneling microscopy or spectroscopy (STM or STS), nuclear magnetic resonance (NMR), resonant X ray scattering (RXS), and optical conductivity, showing that the pseudogap is a spatially heterogeneous, symmetry breaking electronic state whose onset temperature decreases roughly linearly with doping and terminates sharply at . Three complementary theoretical frameworks, namely quantum criticality, Mott physics, and intertwined orders, collectively describe these observations. Experiments showing the abrupt disappearance of nematic order and a logarithmic rise in the electronic specific heat coefficient suggest that the pseudogap terminates at a quantum critical point. This transition appears to separate a correlation dominated pseudogapped metal from a coherent Fermi liquid phase rather than occurring through a gradual crossover. The doping level identified from transport data aligns with optimal superconductivity, implying that the recovery of long range phase coherence rather than the complete removal of pseudogap features is what ultimately enhances . Unresolved questions include reconciling probe dependent boundaries through systematic cross technique studies on identical crystals and developing correlation length resolved probes to distinguish spatial scales of electronic reconstruction. A major theoretical challenge remains to unify competing frameworks and to elucidate how the pseudogap terminates and coherence emerges at , which represents a key step toward a microscopic theory of high temperature superconductivity in cuprates.

Abstract Spinel‐type high entropy oxides (HEOs) have emerged as promising next‐generation lithium‐ion battery anodes owing to exceptional electrochemical performance. However, suppressing irreversible phase transformations caused by high‐entropy to low‐entropy state transitions during discharge–charge has remained challenging. The core issue stems from an insufficient understanding of phase evolution pathways and the key thermodynamic/kinetic driving forces, which is due to current methodological limitations in analyzing highly disordered structures. Further complicating this challenge is the elusive impact of nanosized effects on both thermodynamic and kinetic processes. This study addresses these challenges through three synergistic approaches: 1) investigating phase evolution mechanisms across different particle sizes to delineate nanosized effects; 2) resolving complex local structures by pair distribution function analyses and 7 Li magic‐angle spinning nuclear magnetic resonance spectroscopy; 3) elucidating influences of high entropy on phase evolution via DFT calculations. Comprehensive results reveal a complex phase evolution process governed by the thermodynamic‐kinetic interplay. The incomplete phase transformations of the rock‐salt‐like intermediate phase during discharge, which are attributable to high entropy‐mediated kinetic sluggish diffusion, account for the transition from high‐entropy to low‐entropy states. By shortening the solid‐state diffusion lengths, the kinetic limitations can be overcome, as demonstrated by nanosized spinel‐type HEOs achieving reversible phase transformations during discharge‐charge.

Depolymerization is the cornerstone of lignin valorization. Although this field of research has advanced significantly in the past decade, there are still obstacles preventing large-scale application. The high cost of precious metal catalysts and the use of pressurized hydrogen gas account for some of the limitations. In this work, it is designed to synergize the reductive acidolytic power of hydrogen iodide and the advantageous physicochemical properties of ionic liquids (ILs) as green solvents for the deep depolymerization of real lignin. The results showed that nearly 100% of model compounds were converted in the reaction medium comprising 1-butyl-3 methylimidazolium iodide ([Bmim]I) plus organic acids and a yield up to 81wt% of depolymerized products of low molecular weights was achieved for real lignins. In addition, a detailed structural assignment of the products was made straightforward by nuclear magnetic resonance chromatography. The advantages of the [Bmim]I/organic acids demonstrated in this study are featured by mild reaction conditions, easy scalability, and cost-effectiveness, paving the way toward the democratization of lignin-derived products.

Mechanisms of assembly and function of the Hsp70-Hsp40 chaperone machinery.

Spinel-type high entropy oxides (HEOs) have emerged as promising next-generation lithium-ion battery anodes owing to exceptional electrochemical performance. However, suppressing irreversible phase transformations caused by high-entropy to low-entropy state transitions during discharge-charge has remained challenging. The core issue stems from an insufficient understanding of phase evolution pathways and the key thermodynamic/kinetic driving forces, which is due to current methodological limitations in analyzing highly disordered structures. Further complicating this challenge is the elusive impact of nanosized effects on both thermodynamic and kinetic processes. This study addresses these challenges through three synergistic approaches: 1) investigating phase evolution mechanisms across different particle sizes to delineate nanosized effects; 2) resolving complex local structures by pair distribution function analyses and 7Li magic-angle spinning nuclear magnetic resonance spectroscopy; 3) elucidating influences of high entropy on phase evolution via DFT calculations. Comprehensive results reveal a complex phase evolution process governed by the thermodynamic-kinetic interplay. The incomplete phase transformations of the rock-salt-like intermediate phase during discharge, which are attributable to high entropy-mediated kinetic sluggish diffusion, account for the transition from high-entropy to low-entropy states. By shortening the solid-state diffusion lengths, the kinetic limitations can be overcome, as demonstrated by nanosized spinel-type HEOs achieving reversible phase transformations during discharge-charge.

Abstract Depolymerization is the cornerstone of lignin valorization. Although this field of research has advanced significantly in the past decade, there are still obstacles preventing large‐scale application. The high cost of precious metal catalysts and the use of pressurized hydrogen gas account for some of the limitations. In this work, it is designed to synergize the reductive acidolytic power of hydrogen iodide and the advantageous physicochemical properties of ionic liquids (ILs) as green solvents for the deep depolymerization of real lignin. The results showed that nearly 100% of model compounds were converted in the reaction medium comprising 1‐butyl‐3 methylimidazolium iodide ([Bmim]I) plus organic acids and a yield up to 81 wt% of depolymerized products of low molecular weights was achieved for real lignins. In addition, a detailed structural assignment of the products was made straightforward by nuclear magnetic resonance chromatography. The advantages of the [Bmim]I/organic acids demonstrated in this study are featured by mild reaction conditions, easy scalability, and cost‐effectiveness, paving the way toward the democratization of lignin‐derived products.

Low-permeability glutenite reservoirs in the Qaidam Basin, NW China, exhibit intricate pore networks and strong heterogeneity that hinder effective hydrocarbon development. Here, we integrate thin-section petrography, scanning electron microscopy (SEM), mercury injection capillary pressure (MICP), and nuclear magnetic resonance (NMR) to characterize pore types and establish quantitative links between fractal dimension and petrophysical properties. The reservoirs are mainly pebbly sandstones and sandy conglomerates with 15–23% quartz, 27–37% feldspar, and 2–20% carbonate/muddy matrix. Helium porosity ranges from 5.12% to 18.11% (mean 9.39%) and air permeability from 60 to 3270 mD (mean 880 mD). Fine pores (1–10 μm) dominate, throats are short and poorly connected, and illite (up to 16.76%) lines pore walls, further reducing permeability. Fractal analysis yields weighted-average dimensions of 2.55, 2.50, and 2.15 for macro-, meso-, and micropores, respectively, giving an overall dimension of 2.52. Higher dimensions correlate negatively with porosity and permeability. Empirical models (quadratic for porosity and exponential for permeability) predict core data within 0.86% and 5.4% error, validated by six blind wells. Reservoirs are classified as Class I (>12%, >1.0 mD), Class II (8–12%, 0.5–1.0 mD), and Class III (<8%, <0.5 mD), providing a robust tool for stimulation design and numerical simulation.

Two novel polyacetylenic compounds were successfully separated from the dichloromethane extract of the aerial parts of Bidens parviflora Willd., known for its ethnomedicinal use in traditional Dai medicine. These compounds were structurally elucidated and identified as (2R)-trideca-3E,5Z,11E-triene-7,9-diyne-1,2,13-triol (1), and (2R)-trideca-11E-ene-5,7,9-triyne-1,2,13-triol (2). Their chemical structures were confirmed through a comprehensive analysis involving ultraviolet (UV) spectroscopy, infrared (IR) spectroscopy, high-resolution electrospray ionization mass spectrometry (HR-ESI-MS), as well as detailed one-dimensional (1D) and two-dimensional (2D) nuclear magnetic resonance (NMR) spectroscopic data, and measurements of specific optical rotation.

Peritonitis is a well-known complication of bowel perforation and abdominal surgery, leading to sepsis and high mortality. Despite its prevalence and severity, the pathogenesis of peritonitis remains incompletely understood, limiting our ability to develop targeted medical therapies. Specifically, little is known about the determinants of the peritoneal nutrient environment for pathogens. The gut microbiome is a well-established source of infectious bacteria in peritonitis, but whether it also modulates levels of nutrients that enable and sustain these infections remains unknown. Using multiple murine models of peritonitis (lipopolysaccharide, cecal slurry), multiple methods of microbiome modulation (germ-free mice and antibiotic-treated mice), novel ex vivo modeling of peritonitis, and nuclear magnetic resonance (NMR) metabolomics of the peritoneal microenvironment, we performed a series of experiments to determine how the gut microbiome influences peritoneal metabolite concentration during peritonitis. We found that both lipopolysaccharide and cecal slurry peritonitis caused consistent changes in high-abundance peritoneal metabolites, and that many of these changes were blunted or completely abrogated in antibiotic-treated and germ-free mice. Moreover, we found that peritoneal washings from septic, microbiome-depleted animals supported less bacterial growth of common intra abdominal pathogens compared to washings from septic conventional animals. We identified the peritoneal nutrients consumed by two common pathogens from the Enterobacteriaceae family, and found that supplementation of gut microbiome-mediated nutrients was sufficient to alter bacterial growth in an ex vivo model. Taken together, we identify the gut microbiome as a key driver of the peritoneal nutrient environment, mediating pathogen growth. These findings suggest microbiome-targeted therapies could mitigate peritonitis risk.

Ten chaetoglobosin alkaloids were isolated from the fermentation culture of a soil-derived fungus, Chaetomium sp., and their structures with absolute configurations were characterized by spectroscopic methods including high-resolution mass spectrometry (HRMS), nuclear magnetic resonance (NMR), X-ray diffraction analysis, and electronic circular dichroism, as well as comparison with literature data. Among them, three compounds (1-3) have not been described previously, and compound 8 is reported for the first time as a new natural product. A preliminary cytostatic screening revealed good inhibitory activity for 1, 6, and 8 against the A549 cell line (lung), and for 1, 2, 4, 6, and 8 against the MDA-MB231 cell line (breast). Further exploration demonstrated that compound 8 exerted in vitro antitumor activity by inducing significant apoptosis and S-phase cycle arrest, as well as blocking the migration and invasion of MDA-MB231 cells.

Parahydrogen-induced hyperpolarization (PHIP), introduced nearly four decades ago, provides an elegant solution to one of the fundamental limitations of nuclear magnetic resonance (NMR)—its notoriously low sensitivity. By converting the spin order of parahydrogen into nuclear spin polarization, NMR signals can be boosted by several orders of magnitude. Here we present a portable, compact, and cost-effective setup that brings PHIP and Signal Amplification by Reversible Exchange (SABRE) experiments within easy reach, operating seamlessly across ultra-low-field (0–10 μT) and high-field (>1 T) conditions at 50% parahydrogen enrichment. The system provides precise control over bubbling pressure, temperature, and gas flow, enabling systematic studies of how these parameters shape hyperpolarization performance. Using the benchmark Chloro(1,5-cyclooctadiene)[1,3-bis(2,4,6-trimethylphenyl)imidazole-2-ylidene]iridium(I) (Ir–IMes) catalyst, we explore the catalyst activation time and response to parahydrogen flow and pressure. Polarization transfer experiments from hydrides to [1-13C]pyruvate leading to the estimation of heteronuclear J-couplings are also presented. We further demonstrate the use of Chloro(1,5-cyclooctadiene)[1,3-bis(2,6-diisopropylphenyl)imidazolidin-2-ylidene]iridium(I) (Ir–SIPr), a recently introduced catalyst that can also be used for pyruvate hyperpolarization. The proposed design is robust, reproducible, and easy to implement in any laboratory, widening the route to explore and expand the capabilities of parahydrogen-based hyperpolarization.

Employing Copper(I)-catalyzed alkyne-azide cycloaddition (CuAAC), an efficient and stereoselective technique, has led to the creation of 1,2,3-triazole derivatives notable for their capability to trace specific metal ions. In this report, a chemical sensor probe BHT based on butylated hydroxy anisole (BHA) was synthesised via CuAAC approach and characterized through spectroscopic techniques comprising Infrared Spectroscopy, Nuclear Magnetic Resonance Spectroscopy, and Mass Spectrometry. On conduction of the chemosensing analysis through UV-Visible and fluorescence spectroscopy in 80% solution of acetonitrile in water, the chemosensor probe selectively recognized Cu(II) and Fe(III) metal ions among a variety of metals tested. In addition to this, the synthesised 1,2,3-triazole based chemosensor also exhibited 'masked-sensing' of Ce(III) ions which remained obscured during the preliminary studies. The sensor probe demonstrated substantially low limits of detection for every metal ion; with the values being 4.48 µM, 3.02 µM, and 1.91 µM for Cu(II), Fe(III), and Ce(III) metal ions respectively.

Accurate characterization of liquid manure properties, such as dry matter (DM), total nitrogen (TN), ammonium nitrogen (NH4-N), and total phosphorus (TP), is essential for effective nutrient management in agriculture. This study investigates the use of near-infrared spectroscopy (NIRS) within the 941–1671 nm range, combined with advanced pre-processing and machine learning techniques to accurately predict the liquid manure properties. The predictive accuracy of NIRS was assessed by comparison with nuclear magnetic resonance (NMR) spectroscopy as a benchmark method. A number of 51 liquid manure samples were analyzed in the laboratory for the reference manure properties and scanned with NIRS and NMR. The NIR data underwent spectral pre-processing, which included two- and three-band index transformations and feature selection. Partial least squares regression (PLSR) and LASSO regression were employed to develop calibration models. According to the results, using cohort-tuned models, NIRS showed fair predictive accuracy for DM (R2 = 0.78, RPD = 2.15) compared to factory-calibrated NMR (R2 = 0.68, RPD = 0.81). Factory-calibrated NMR outperformed for chemical properties, with R2 (RPD) of 0.89 (1.74) for TN, 0.97 (5.70) for NH4-N, and 0.95 (2.64) for TP, versus NIRS’s 0.66 (1.68), 0.84 (2.45), and 0.84 (2.51), respectively. In this study with 51 samples, two- and three-band indices significantly enhanced NIRS performance compared to raw data, with R2 increases of 34%, 57%, 25%, and 33% for DM, TN, NH4-N, and TP, respectively. Feature selection efficiently reduced NIR spectral dimensionality without compromising the prediction accuracy. This study highlights NIRS’s potential as a portable tool for on-site manure characterization, with NMR providing superior laboratory validation, offering complementary approaches for nutrient management.