Magnetic Resonance in Chemistry最新文献

The aim of this study is to investigate the metabolic alterations associated with pheochromocytomas and paragangliomas (PPGLs) and the impact of surgical resection on the serum metabolome using untargeted nuclear magnetic resonance (NMR) metabolomics. For this, the study included 34 patients diagnosed with PPGLs. Pre-operative and postoperative serum samples were analyzed using 1D-proton NMR spectroscopy, and NMR spectral data were processed using Bruker software Topspin. The quantitative metabolic profiles were estimated using CHENOMX NMR-Suite, and multivariate data were analyzed using partial least squares discriminant analysis (PLS-DA) and orthogonal PLS-DA followed by random forest (RF) classification method (a machine learning approach). The multivariate analysis revealed distinct metabolic differences between pre-operative and postoperative samples with respect to normal control (NC) samples, indicating a metabolic shift following tumor resection. RF classification, with an out-of-bag error rate of 0.186, effectively distinguished between NC, presurgery, and postsurgery groups, underscoring the distinct metabolic states in PPGL and the restorative effect of surgical intervention. Pre-operative serum profiles of PPGL patients were characterized by decreased levels of key metabolites, including glucose, citrate, amino acids (glutamine, glycine, leucine, valine, tyrosine, and alanine), histidine, myo-inositol, and creatinine, suggesting altered energy metabolism, and amino acid catabolism induced by catecholamine excess. Postsurgical profiles showed partial metabolic restoration, with significant increases in proline, glutamate, and 3-hydroxybutyrate (3-HB) (p < 0.01), indicating normalization involving lipid oxidation and amino acid metabolism. Although plasma metanephrines normalized postsurgery, full biochemical recovery lagged, as metabolic profiles of postoperative patients remained distinct from healthy controls. In conclusion, the present untargeted NMR metabolomics revealed significant metabolic reprogramming in PPGL patients and captured the partial normalization of metabolic pathways following tumor resection. Metabolites such as proline, glutamate, and 3-HB emerged as potential biomarkers of treatment response. These findings underscore the utility of metabolomics to identify biomarkers for monitoring disease progression, assessing postsurgical recovery, and improving our understanding of PPGL pathophysiology.

The landscape of chronic liver disease has changed significantly, with metabolic dysfunction-associated steatotic liver disease (MASLD) now emerging as the most widespread form worldwide. In Asia, particularly in India, the prevalence of MASLD is increasing, largely driven by poor dietary habits and a sedentary way of life. MASLD spans from fat deposition to inflammation and fibrosis. Fibrosis stands out as the most critical indicator of liver-related complications and overall risk of death in MASLD. Early identification of fibrosis is critical, but current tests are often invasive or unreliable. Whereas studies have explored metabolic changes in MASLD, few have focused on distinguishing early-stage fibrosis from steatosis. In this study, we used NMR-based metabolomics to analyze serum samples from n = 103 MASLD patients, divided into fibrosis (n = 44) and non-fibrosis (n = 59) groups based on standard noninvasive scoring systems. We identified seven metabolites—arginine, glycerol, aspartate, glucose, phenylalanine, histidine, and citrate—that significantly differed between the two groups and showed good diagnostic potential (AUROC > 0.70). Pathway analysis revealed disruptions in arginine and nitrogen metabolism, associated with liver scarring processes, and in energy and lipid metabolism, pointing to mitochondrial dysfunction and lipotoxic stress. Reduced aspartate levels also suggested loss of natural protection against fibrosis. This is the first study of the MASLD cohort to differentiate early-stage fibrosis from steatosis using metabolomics. Our findings highlight the potential of a simple NMR-based blood test to aid early diagnosis, guide treatment decisions, and personalize care—offering a noninvasive alternative to improve MASLD management.

Accurate assignment of metabolites is the backbone of metabolomics studies. Two-dimensional (2D) NMR plays a critical role in the accurate assignment of metabolites. Characterization of 2D spectra such as ¹H–¹³C HSQC and ¹H–¹H TOCSY combined with database queries enables reliable metabolite identification for metabolic profiling and biological interpretation. However, recording a high-quality ¹H–¹³C HSQC spectrum at ¹³C natural abundance in biofluids requires extensive NMR signal averaging, often taking up to 24 h. Reducing the number of t₁ increments or scans is not useful in metabolomics as it compromises the sensitivity needed to detect low-abundance metabolites. “NMR by Ordered Acquisition using ¹H detection,” or NOAH, supersequences are ideally suited for accelerated data collection in biofluids. Instead of shortening individual experiments, NOAH enables the simultaneous acquisition of multiple 2D experiments without compromising sensitivity. The principle of NOAH lies in utilizing the undisturbed magnetization from one experiment (e.g., ¹H–¹³C HSQC) for subsequent experiments (e.g., ¹H–¹H TOCSY) within the same scan. Previous studies have demonstrated the utility of the HSQC + TOCSY NOAH-2 supersequence for metabolomics applications. Nevertheless, due to the complexity of biofluids, even regular 2D TOCSY spectra often suffer from signal overlap, arising from numerous metabolite peaks, multiplet structures, and limited ¹H chemical shift dispersion. The pure shift F₁-PSYCHE TOCSY experiment addresses this challenge by offering a single peak per resonance, thereby greatly reducing signal overlap. In this work, we present HSQC + F₁-PSYCHE TOCSY NOAH-2 supersequence for the analysis of human urine.

The monocyte migration at the inflammatory site is regulated by monocyte chemoattractant protein-1 (MCP/CCL2), a crucial CC chemokine existing in equilibrium between monomers and dimers under physiological conditions. The present study unveils the relative structure-stability and functional features for engineered murine CCL2-P8A monomer (CCL2-M) in comparison to dimer (CCL2-WT) using a combination of nuclear magnetic resonance (NMR), biophysical and cell-based techniques. We delineate here the NMR assignment and structural characteristics of wild-type and monomeric versions of CCL2 protein. The structural features revealed that the overall topology of the CCL2-M is similar to that of the monomeric subunit of the CCL2-WT protein. The conformational dynamics of CCL2-M exhibit extensive fluctuations in the μs–ms timescales, with fewer residues accessing alternative conformations than CCL2 dimer, indicating differential native state ruggedness of the monomer. Native state hydrogen exchange analysis shows that most residues in the CCL2 monomer are readily accessible to solvent and exchangeable, suggesting lower stability of the CCL2 monomer than the dimer. Cell-based transwell migration assay demonstrates that CCL2 monomer induces chemotactic migration of monocyte/macrophages similar to its dimeric counterpart. These investigations align closely with the structural–functional aspects of CCL2 and form the basis for the structure-based drug discovery targeting its cognate G-protein coupled receptor CCR2.

One new resorcylic acid lactone (RAL), curvulomycin E (1), along with 10 known compounds (2–11), was obtained from the Beibu Gulf coral-derived fungus Curvularia lunata GXIMD 02512. Their structures were determined by extensive spectroscopic data interpretation and comparison with literature. The absolute configurations of 1 and 10 were accomplished by ECD calculations. Structurally, curvulomycin E (1) with a methoxy substituent at C-12 is generally uncommon in the 12-membered RAL family. Compounds 2–4 exhibited cytotoxicity against MDA-MB-231 and KTC-1 cells with IC₅₀ values ranging from 10.8 to 26.5 μM. The preliminary structure–activity relationship is discussed. Compound 2 further arrested the cell cycle at the S phase and dose-dependently induced apoptosis in MDA-MB-231 cells.