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The underlying cause of tuberculosis (TB) treatment failure is still largely unknown. A 1 H NMR approach was applied to identify and quantify a subset of TB drugs and drug metabolites: ethambutol (EMB), acetyl isoniazid (AcINH), isonicotinic acid, pyrazinamide (PZA), pyrazinoic acid and 5-hydroxy-pyrazinoic acid, from the urine of TB patients. Samples were collected before, during (weeks one, two and four) and after standardised TB treatment. The median concentrations of the EMB and PZA metabolites were comparable between the samples from patients with eventually cured and failed treatment outcomes. The INH metabolites showed comparatively elevated concentrations in the treatment failure patients during and after treatment. Variation in INH metabolite concentrations couldn't be associated with the varying acetylator genotypes, and it is therefore suggested that treatment failure is influenced more so by other conditions, such as environmental factors, or individual variation in other INH metabolic pathways., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Serum 1 H NMR metabolomics has been used as a diagnostic tool for screening type 2 diabetes (T2D) with chronic kidney disease (CKD) as comorbidity. This work aimed to evaluate 1 H NMR data to detect the initial kidney damage and CKD in T2D subjects, through multivariate statistical analysis. Clinical data and biochemical parameters were obtained for classifying five experimental groups using KDIGO guidelines: Control (healthy subjects), T2D, T2D-CKD-mild, T2D-CKD-moderate, and T2D-CKD-severe. Serum 1 H NMR spectra were recorded to follow two strategies: one based on metabolite-to-creatinine (Met/Cr) ratios as targeted metabolomics, and the second one based on untargeted metabolomics from the 1 H NMR profile. A prospective biomarkers panel of the early stage of T2D-CKD based in metabolite-to-creatinine ratio (ornithine/Cr, serine/Cr, mannose/Cr, acetate/Cr, acetoacetate/Cr, formate/Cr, and glutamate/Cr) was proposed. Later, a statistical model based on non-targeted metabolomics was used to predict initial CKD, and its metabolic pathway analysis allowed identifying the most affected pathways: phenylalanine, tyrosine, and tryptophan biosynthesis; valine, leucine, and isoleucine degradation; glyoxylate and dicarboxylate metabolism; glycine, serine, and threonine metabolism; and histidine metabolism. Nonetheless, further studies with a larger cohort are advised to precise ranges in metabolite-to-creatinine ratios and evaluate the prediction pertinency to detect initial CKD in T2D patients in both statistical models proposed., Competing Interests: Declaration of Competing Interest Alma L. Saucedo reports financial support was provided by National Council for Science and Technology. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Proton magnetic resonance spectroscopy ( 1 H-MRS) allows measuring specific brain metabolic alterations in Huntington's disease (HD), and these metabolite profiles may serve as non-invasive biomarkers associated with disease progression. Despite this potential, previous findings are inconsistent. Accordingly, we performed a meta-analysis on available in vivo 1 H-MRS studies in premanifest (Pre-HD) and symptomatic HD stages (Symp-HD), and quantified neurometabolic changes relative to controls in 9 Pre-HD studies (227 controls and 188 mutation carriers) and 14 Symp-HD studies (326 controls and 306 patients). Our results indicated decreased N-acetylaspartate and creatine in the basal ganglia in both Pre-HD and Symp-HD. The overall level of myo-inositol was decreased in Pre-HD while increased in Symp-HD. Besides, Symp-HD patients showed more severe metabolism disruption than Pre-HD patients. Taken together, 1 H-MRS is important for elucidating progressive metabolite changes from Pre-HD to clinical conversion; N-acetylaspartate and creatine in the basal ganglia are already sensitive at the preclinical stage and are promising biomarkers for tracking disease progression; overall myo-inositol is a possible characteristic metabolite for distinguishing HD stages., Competing Interests: Declaration of competing interest The authors report no conflict of interest., (Copyright © 2023. Published by Elsevier Inc.)

Drugs and drug metabolites containing a carboxylic-acid moiety can undergo in vivo conjugation to form 1-β-O-acyl-glucuronides (1-β-O-AGs). In addition to hydrolysis, these conjugates can undergo spontaneous acyl migration, and anomerisation reactions, resulting in a range of positional isomers. Facile transacylation has been suggested as a mechanism contributing to the toxicity of acyl glucuronides, with the kinetics of these processes thought to be a factor. Previous 1 H NMR spectroscopic and HPLC-MS studies have been conducted to measure the degradation rates of the 1-β-O-AGs of three nonsteroidal anti-inflammatory drugs (ibufenac, R-ibuprofen, S-ibuprofen) and a dimethyl-analogue (termed here as "bibuprofen"). These studies have also determined the relative contributions of hydrolysis and acyl migration in both buffered aqueous solution, and human plasma. Here, a detailed kinetic analysis is reported, providing the individual rate constants for the acyl migration and hydrolysis reactions observed in buffer for each of the 4 AGs, together with the overall degradation rate constants of the parent 1-β-O-AGs. Computational modelling of the reactants and transition states of the transacylation reaction using density functional theory indicated differences in the activation energies that reflected the influence of both substitution and stereochemistry on the rate of transacylation/hydrolysis., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Urine is an equally attractive biofluid for metabolomics analysis, as it is a challenging matrix analytically. Accurate urine metabolite concentration estimates by Nuclear Magnetic Resonance (NMR) are hampered by pH and ionic strength differences between samples, resulting in large peak shift variability. Here we show that calculating the spectra of original samples from mixtures of samples using linear algebra reduces the shift problems and makes various error estimates possible. Since the use of two-dimensional (2D) NMR to confirm metabolite annotations is effectively impossible to employ on every sample of large sample sets, stabilization of metabolite peak positions increases the confidence in identifying metabolites, avoiding the pitfall of oranges-to-apples comparisons.

Objectives: This study aimed to reveal the anti-fibrotic effects of Botrychium ternatum (Thunb.) Sw. (BT) against idiopathic pulmonary fibrosis (IPF) and to preliminarily analyze its potential mechanism on bleomycin-induced IPF rats., Methods: The inhibition of fibrosis progression in vivo was assessed by histopathology combined with biochemical indicators. In addition, the metabolic regulatory mechanism was investigated using 1H-nuclear magnetic resonance-based metabolomics combined with multivariate statistical analysis., Key Findings: Firstly, biochemical analysis revealed that BT notably suppressed the expression of hydroxyproline and transforming growth factor-β1 in the pulmonary tissue. Secondly, Masson's trichrome staining and hematoxylin and eosin showed that BT substantially improved the structure of the damaged lung and significantly inhibited the proliferation of collagen fibers and the deposition of extracellular matrix. Finally, serum metabolomic analysis suggested that BT may exert anti-fibrotic effects by synergistically regulating tyrosine metabolism; phenylalanine, tyrosine and tryptophan biosynthesis; and synthesis and degradation of ketone bodies., Conclusions: Our study not only clarifies the potential anti-fibrotic mechanism of BT against IPF at the metabolic level but also provides a theoretical basis for developing BT as an effective anti-fibrotic agent., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Royal Pharmaceutical Society. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Introduction: Breeding for oil palm resistance against basal stem rot caused by Ganoderma boninense is challenging and time-consuming. Advanced oil palm gene pools are very limited, hence it is assumed that parental palms have experienced genetic drift and lost their resistance genes against Ganoderma. High-throughput selection criteria should be developed. Metabolomic analysis using 1 H nuclear magnetic resonance (NMR) spectroscopy is easy, and the resulting metabolite can be used as a diagnostic tool for detecting disease in various host-pathogen combinations., Objectives: The objective of this study was to identify metabolite variations in Dura (D) and Pisifera (P) parental palms with different resistance levels against Ganoderma and moderately resistant DxP using 1 H NMR analysis., Methods: Leaf tissues of seven different oil palm categories consisting of: resistant, moderate, and susceptible Dura (D); moderate and susceptible Pisifera (P); resistant Tenera/Pisifera (T/P) parental palms; and moderately resistant DxP variety progenies, were sampled and their metabolites were determined using NMR spectroscopy., Results: Twenty-nine types of metabolites were identified, and most of the metabolites fall in the monosaccharides, amino acids, and fatty acids compound classes. The PCA, PLS-DA, and heatmap multivariate analysis indicated two identified groups of resistance based on their metabolites. The first group consisted of resistant T/P, moderate P, resistant D, and moderately resistant DxP. In contrast, the second group consisted of susceptible P, moderate D, and susceptible D. Glycerol and ascorbic acid were detected as biomarker candidates by OPLS-DA to differentiate moderately resistant DxP from susceptible D and P. The pathway analysis suggested that glycine, serine, and threonine metabolism and taurine and hypotaurine metabolism were involved in the oil palm defense mechanism against Ganoderma., Conclusion: A metabolomic study with 1 H NMR was able to describe the metabolite composition that could differentiate the characteristics of oil palm resistance against basal stem rot (BSR) caused by G. boninense. These metabolites revealed in this study have enormous potential to become support tools for breeding new oil palm varieties with higher resistance against BSR., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Total amount of creatine (Cr) and phosphocreatine, or total creatine (tCr), may have a significant impact on the performance of skeletal muscles. In sports such as bodybuilding, it is popular to take Cr supplements to maintain tCr level. However, no study has explored the quantitative relationship between exercise intensity and the induced change in muscle's tCr. In this well-controlled study, straight-leg plantar flexion with specific load and duration was performed by 10 healthy subjects inside an MRI scanner, immediately followed by 1 H MR spectroscopy (MRS) for measuring tCr concentration in gastrocnemius. For repeatability assessment, the experiment was repeated for each subject on two different days. Across all the subjects, baseline tCr was 46.6 ± 2.4 mM, ranging from 40.6 to 50.1 mM; with exercise, tCr significantly decreased by 10.9% ± 1.0% with 6-lb load and 21.0% ± 1.3% with 12-lb load (p < 0.0001). Between two different days, baseline tCr, percentage decrease induced by exercise with a 6-lb and 12-lb load differed by 2.2% ± 2.3%, 11.7% ± 6.0% and 4.9% ± 3.2%, respectively. In conclusion, the proposed protocol of controlled exercise stimulation and MRS acquisition can reproducibly monitor tCr level and its exercise-induced change in skeletal muscles. The measured tCr level is sensitive to exercise intensity, so can be used to quantitatively assess muscle performance or fatigue., (© 2024 The Author(s). Physiological Reports published by Wiley Periodicals LLC on behalf of The Physiological Society and the American Physiological Society.)

This study presents a new strategy to discriminate between opium samples obtained from different geographical regions. Nuclear magnetic resonance (NMR) profiling and chemometrics were applied to geographical classification of opium originating from Myanmar and Afghanistan, which are two major opium producing countries in the world. A total of 50 Myanmar and 46 Afghanistan authentic opium samples were analyzed by 1 H-NMR, and the chemical profiles were characterized. Different sample preparation procedures, data processing methods, and chemometrics were compared to obtain the best classification effect. It was found that drying and the addition of buffer solutions were unnecessary for classification purposes; thus, the gum opium samples were extracted directly with CD 3 OD, which shortened sample preparation time. A full discrimination between the two geographical origins was achieved by 1 H-NMR profiling and orthogonal partial least squares discriminant analysis. All 30 opium samples were classified correctly by the developed orthogonal partial least squares discriminant analysis model. Compared with traditional chromatography and mass spectrometry profiling methods, the 1 H-NMR profiling method was faster (with instrument analysis time of less than 3 min) and reproducible. This study provides new insights into the applying of NMR profiling and chemometrics to rapid drug profiling analysis., (© 2023 John Wiley & Sons, Ltd.)

Introduction: Herbal preparations are extensively utilised for the treatment of diseases in Asian countries. However, the variations in origin, climate, and production processes can lead to inconsistencies in the quality of herbal preparations. Existing quality control methods only target a few components in the finished product but ignore the control in the pharmaceutical process. Therefore, this study intends to develop a comprehensive component analysis method for intermediates in the pharmaceutical process to reveal the change patterns of substances and deepen the process understanding., Objective: This study aims to develop a rapid and comprehensive process characterisation and critical process identification method for herbal preparations., Methods: Six batches of Trichosanthis Pericarpium injection (TPI) intermediates were collected from the production process. Proton nuclear magnetic resonance ( 1 H-NMR) spectra were acquired for qualitative and quantitative analysis of the se intermediates. Subsequently, chemometrics were used to identify critical processes and potential chemical markers., Results: A total of 39 components in intermediates were identified, and the transfer of 25 components during the production process was investigated. Column chromatography was determined as the critical process. Nine components were identified as chemical markers., Conclusion: The application of 1 H-NMR facilitated a comprehensive reflection of the chemical composition information of process intermediates, enabling investigations into the transfer of multi-component substances and accurate identification of critical processes and chemical markers., (© 2024 John Wiley & Sons Ltd.)

Aims: To assess if advanced characterization of serum glycoprotein and lipoprotein profile, measured by proton nuclear magnetic resonance spectroscopy ( 1 H-NMRS) improves a predictive clinical model of cardioautonomic neuropathy (CAN) in subjects with type 1 diabetes (T1D)., Methods: Cross-sectional study (ClinicalTrials.gov Identifier: NCT04950634). CAN was diagnosed using Ewing's score. Advanced characterization of macromolecular complexes including glycoprotein and lipoprotein profiles in serum samples were measured by 1 H-NMRS. We addressed the relationships between these biomarkers and CAN using correlation and regression analyses. Diagnostic performance was assessed by analyzing their areas under the receiver operating characteristic curves (AUC ROC )., Results: Three hundred and twenty-three patients were included (46% female, mean age and duration of diabetes of 41 ± 13 years and 19 ± 11 years, respectively). The overall prevalence of CAN was 28% [95% confidence interval (95%CI): 23; 33]. Glycoproteins such as N-acetylglucosamine/galactosamine and sialic acid showed strong correlations with inflammatory markers such as high-sensitive C-reactive protein, fibrinogen, IL-10, IL-6, and TNF-α. On the contrary, we did not find any association between the former and CAN. A stepwise binary logistic regression model (R 2  = 0.078; P = 0.003) retained intermediate-density lipoprotein-triglycerides (IDL-TG) [β:0.082 (95%CI: 0.005; 0.160); P = 0.039], high-density lipoprotein-triglycerides (HDL-TGL)/HDL-Cholesterol [β:3.633 (95%CI: 0.873; 6.394); P = 0.010], and large-HDL particle number [β: 3.710 (95%CI: 0.677; 6.744); P = 0.001] as statistically significant determinants of CAN. Adding these lipoprotein particles to a clinical prediction model of CAN that included age, duration of diabetes, and A 1c enhanced its diagnostic performance, improving AUC ROC from 0.546 (95%CI: 0.404; 0.688) to 0.728 (95%CI: 0.616; 0.840)., Conclusions: When added to clinical variables, 1 H-NMRS-lipoprotein particle profiles may be helpful to identify those patients with T1D at risk of CAN., (© 2024. The Author(s), under exclusive licence to Italian Society of Endocrinology (SIE).)

Wilson disease (WD) is an autosomal recessive disorder characterized by abnormal copper metabolism. The accumulation of copper in the liver can progress to liver fibrosis and, ultimately, cirrhosis, which is a primary cause of death in WD patients. Metabonomic technology offers an effective approach to investigate the traditional Chinese medicine (TCM) syndrome types of WD-related liver fibrosis by monitoring the alterations in small molecule metabolites within the body. In this study, we employed 1 H-Nuclear Magnetic Resonance ( 1 H NMR) metabonomics to assess the metabolic profiles associated with five TCM syndrome types of WD-related liver fibrosis and analyzed the diagnostic and predictive capabilities of various metabolites. The study found a variety of metabolites, each with varying levels of diagnostic and predictive capabilities. Furthermore, the discerned differential metabolic pathways were primarily associated with various pathways involving carbohydrate metabolism, amino acid metabolism, and lipid metabolism. This study has identified various characteristic metabolic markers and pathways associated with different TCM syndromes of liver fibrosis in WD, providing a substantial foundation for investigating the mechanisms underlying these TCM syndromes., Competing Interests: Declaration of Competing Interest The authors declare that they have no Conflict of Interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The MAPK signaling pathway with BRAF mutations has been shown to drive the pathogenesis of 40-60% of melanomas. Inhibitors of this pathway's BRAF and MEK components are currently used to treat these malignancies. However, responses to these treatments are not always successful. Therefore, identifying noninvasive biomarkers to predict treatment responses is essential for personalized medicine in melanoma. Using noninvasive 1 H magnetic resonance spectroscopy ( 1 H MRS), we previously showed that BRAF inhibition reduces lactate and alanine tumor levels in the early stages of effective therapy and could be considered as metabolic imaging biomarkers for drug response. The present work demonstrates that these metabolic changes observed by 1 H MRS and those assessed by 31 P MRS are also found in preclinical human melanoma models treated with MEK inhibitors. Apart from 1 H and 31 P MRS, additional supporting in vitro biochemical analyses are described. Our results indicate significant early metabolic correlations with response levels to MEK inhibition in the melanoma models and are consistent with our previous study of BRAF inhibition. Given these results, our study supports the potential clinical utility of noninvasive MRS to objectively image metabolic biomarkers for the early prediction of melanoma's response to MEK inhibition.

Background: To perform fast, reproducible, and absolute quantitative measurements in an automated manner has become of paramount importance when monitoring industrial processes, including fermentations. Due to its numerous advantages - including its inherent quantitative nature - Proton Nuclear Magnetic Resonance ( 1 H NMR) spectroscopy provides an ideal tool for the time-resolved monitoring of fermentations. However, analytical conditions, including non-automated sample preparation and long relaxation times (T 1 ) of some metabolites, can significantly lengthen the experimental time and make implementation in an industrial set up unfeasible., Results: We present a high throughput method based on Standard Operating Procedures (SOPs) and 1 H NMR, which lays the foundation for what we call Fermentation Analytical Technology (FAT). Our method was developed for the accurate absolute quantification of metabolites produced during Escherichia coli industrial fermentations. The method includes: (1) a stopped flow system for non-invasive sample collection followed by sample quenching, (2) automatic robot-assisted sample preparation, (3) fast 1 H NMR measurements, (4) metabolites quantification using multivariate curve resolution (MCR), and (5) metabolites absolute quantitation using a novel correction factor (k) to compensate for the short recycle delay (D1) employed in the 1 H NMR measurements. The quantification performance was tested using two sample types: buffer solutions of chemical standards and real fermentation samples. Five metabolites - glucose, acetate, alanine, phenylalanine and betaine - were quantified. Absolute quantitation ranged between 0.64 and 3.40 mM in pure buffer, and 0.71-7.76 mM in real samples., Significance: The proposed method is generic and can be straight forward implemented to other types of fermentations, such as lactic acid, ethanol and acetic acid fermentations. It provides a high throughput automated solution for monitoring fermentation processes and for quality control through absolute quantification of key metabolites in fermentation broth. It can be easily implemented in an at-line industrial setting, facilitating the optimization of the manufacturing process towards higher yields and more efficient and sustainable use of resources., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Counterfeit Baijiu has been emerging because of the price variances of real-aged Chinese Baijiu. Accurate identification of different vintages is of great interest. In this study, the combination of gas chromatography-mass spectrometry (GC-MS) and proton nuclear magnetic resonance ( 1 H NMR) spectroscopy was applied for the comprehensive analysis of chemical constituents for Maotai-flavor Baijiu. Furthermore, a novel data fusion strategy combined with machine learning algorithms has been established. The results showed that the midlevel data fusion combined with the random forest algorithm were the best and successfully applied for classification of different Baijiu vintages. A total of 14 differential compounds (belonging to fatty acid ethyl esters, alcohols, organic acids, and aldehydes) were identified, and used for evaluation of commercial Maotai-flavor Baijiu. Our results indicated that both volatiles and nonvolatiles contributed to the vintage differences. This study demonstrated that GC-MS and 1 H NMR spectra combined with a data fusion strategy are practical for the classification of different vintages of Maotai-flavor Baijiu.

Introduction: Olive oil, derived from the olive tree (Olea europaea L.), is used in cooking, cosmetics, and soap production. Due to its high value, some producers adulterate olive oil with cheaper edible oils or fraudulently mislabel oils as olive to increase profitability. Adulterated products can cause allergic reactions in sensitive individuals and can lack compounds which contribute to the perceived health benefits of olive oil, and its corresponding premium price., Objective: There is a need for robust methods to rapidly authenticate olive oils. By utilising machine learning models trained on the nuclear magnetic resonance (NMR) spectra of known olive oil and edible oils, samples can be classified as olive and authenticated. While high-field NMRs are commonly used for their superior resolution and sensitivity, they are generally prohibitively expensive to purchase and operate for routine screening purposes. Low-field benchtop NMR presents an affordable alternative., Methods: We compared the predictive performance of partial least squares discrimination analysis (PLS-DA) models trained on low-field 60 MHz benchtop proton ( 1 H) NMR and high-field 400 MHz 1 H NMR spectra. The data were acquired from a sample set consisting of 49 extra virgin olive oils (EVOOs) and 45 other edible oils., Results: We demonstrate that PLS-DA models trained on low-field NMR spectra are highly predictive when classifying EVOOs from other oils and perform comparably to those trained on high-field spectra. We demonstrated that variance was primarily driven by regions of the spectra arising from olefinic protons and ester protons from unsaturated fatty acids in models derived from data at both field strengths., (© 2024 The Authors. Phytochemical Analysis published by John Wiley & Sons Ltd.)

This study introduces a new NMR-based methodology for identification (ID) and quantification (purity, strength) assays of widely used amino acids. A detailed analysis of four amino acids and their available salts was performed with both a high-field (600 MHz) and a benchtop (60 MHz) NMR instrument. To assess sensitivity constraints, samples for 1 H NMR analysis were initially prepared using only 10 mg of analyte and 1 mg of maleic acid (MA) as an internal calibrant (IC) and secondary chemical shift reference. The characteristic dispersion of the peak patterns indicating the presence or absence of a counterion (mostly chloride) was conserved at both high and low-field strength instruments, showing that the underlying NMR spectroscopic parameters, i.e., chemical shifts and coupling constants, are independent of the magnetic field strength. However, as the verbal descriptions of 1 H NMR spectra are challenging in the context of reference materials and pharmaceutical monographs, an alternative method for the identification (ID) of amino acids is proposed that uses 13 C NMR patterns from multiplicity-edited HSQC (ed-HSQC), which are both compound-specific and straightforward to document. For ed-HSQC measurements, the sample amount was increased to 30 mg of the analyte and several acquisition parameters were tested, including t 1 increments used in the pulse program, number of scans, and repetition time. Excellent congruence with deviations <0.1 ppm was achieved for the 13 C chemical shifts from 1D 13 C NMR spectra (150 MHz) vs. those extracted from ed-HSQC (15 MHz traces). Finally, all samples of amino acid candidate reference materials were quantified by 1 H qNMR (abs-qHNMR) at both 600 and 60 MHz. At high field, both IC and relative quantitations were performed, however, with the low-field instrument, only the IC method was used. The results showed that the analyzed reference material candidates were generally highly pure compounds. To achieve adequately low levels of uncertainty for such high-purity materials, the sample amounts were increased to 100 mg of analytes and 10 mg of the IC and replicates were analyzed for selected amino acids., Competing Interests: Declaration of Competing Interest SPK and MN are owners and JL an employee of NMR Solutions, Kuopio, Finland. The other authors have nothing to declare., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The present study proposes the development of new wine recognition models based on Artificial Intelligence (AI) applied to the mid-level data fusion of 1 H NMR and Raman data. In this regard, a supervised machine learning method, namely Support Vector Machines (SVMs), was applied for classifying wine samples with respect to the cultivar, vintage, and geographical origin. Because the association between the two data sources generated an input space with a high dimensionality, a feature selection algorithm was employed to identify the most relevant discriminant markers for each wine classification criterion, before SVM modeling. The proposed data processing strategy allowed the classification of the wine sample set with accuracies up to 100% in both cross-validation and on an independent test set and highlighted the efficiency of 1 H NMR and Raman data fusion as opposed to the use of a single-source data for differentiating wine concerning the cultivar and vintage., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

Purpose: Retrospective frequency-and-phase correction (FPC) methods attempt to remove frequency-and-phase variations between transients to improve the quality of the averaged MR spectrum. However, traditional FPC methods like spectral registration struggle at low SNR. Here, we propose a method that directly integrates FPC into a 2D linear-combination model (2D-LCM) of individual transients ("model-based FPC"). We investigated how model-based FPC performs compared to the traditional approach, i.e., spectral registration followed by 1D-LCM in estimating frequency-and-phase drifts and, consequentially, metabolite level estimates., Methods: We created synthetic in-vivo-like 64-transient short-TE sLASER datasets with 100 noise realizations at 5 SNR levels and added randomly sampled frequency and phase variations. We then used this synthetic dataset to compare the performance of 2D-LCM with the traditional approach (spectral registration, averaging, then 1D-LCM). Outcome measures were the frequency/phase/amplitude errors, the SD of those ground-truth errors, and amplitude Cramér Rao lower bounds (CRLBs). We further tested the proposed method on publicly available in-vivo short-TE PRESS data., Results: 2D-LCM estimates (and accounts for) frequency-and-phase variations directly from uncorrected data with equivalent or better fidelity than the conventional approach. Furthermore, 2D-LCM metabolite amplitude estimates were at least as accurate, precise, and certain as the conventionally derived estimates. 2D-LCM estimation of FPC and amplitudes performed substantially better at low-to-very-low SNR., Conclusion: Model-based FPC with 2D linear-combination modeling is feasible and has great potential to improve metabolite level estimation for conventional and dynamic MRS data, especially for low-SNR conditions, for example, long TEs or strong diffusion weighting., (© 2024 International Society for Magnetic Resonance in Medicine.)

Background: One-dimensional proton nuclear magnetic resonance (1D 1 H NMR) spectroscopy is a non-destructive, non-targeted analytical technique providing both qualitative and quantitative insights, particularly beneficial for mixture analysis. However, the qualitative analysis of 1D 1 H NMR spectra for mixture samples is laborious and time-consuming, involving extensive database searches and verification experiments like spiking. This process heavily relies on the analyst's expertise, leading to efficiency discrepancies. There is a pressing need for a reliable method to streamline operations and enhance the efficiency of qualitative analysis in complex mixtures., Results: We introduce a library-aided method for spectral profiling, named LAMAIS. This method achieves compound identification through similarity assessment between samples and template data, allowing rapid, automatic compound identification and full-spectrum peak assignment without the need for fitting. LAMAIS correctly identifies over 90 % of components in synthetic mixtures and more than 75 % in experimental mixtures, surpassing other representative methods with a higher F2 score. Our reference library, which currently includes 71 compounds, is tailored to capture the commonality of primary metabolites across diverse plant species. The analysis of real-world samples yielded encouraging results, underscoring LAMAIS's versatility as an auxiliary tool suitable for a variety of botanical sources. For analyst convenience, interactive graphics are utilized as the output format., Significance: LAMAIS excels, demonstrating competitiveness and reliability. The approach minimizes repetitive tasks and sample wastage, improving the efficiency of 1D 1 H NMR qualitative analysis. Constructing a reference library effectively preserves knowledge, mitigates reliance on human experience, and addresses gaps in the analysis of plant source samples., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Metabolomics has emerged as a powerful tool for identifying biomarkers of disease, and nuclear magnetic resonance (NMR) spectroscopy allows for the simultaneous detection of a wide range of metabolites. However, due to complex interactions within metabolic networks, metabolites often exhibit high correlation and collinearity. To address this challenge, self-organizing maps (SOMs) of Kohonen maps and counter propagation-artificial neural networks (CP-ANN) were employed in this study to model proton nuclear magnetic resonance spectroscopic ( 1 HNMR) data from control samples and breast cancer (BC) patients. Blood serum samples from a control group (n=24) and BC patients (n=18) were used to extract metabolites using methanol and chloroform solvents in optimum extraction conditions. The 1 HNMR data was preprocessed by performing phase, baseline, and shift corrections. Subsequently, the preprocessed data was modeled using Kohonen network as an unsupervised technique and CP-ANN as a supervised technique. In this regard, the model built with CP-ANN successfully distinguished between the two classes with an accuracy of 100 % for both group and sensitivity of 96 % and 100 % for control group and BC patients, respectively. Additionally, CP-ANN algorithm demonstrated predictive capabilities by accurately classifying test samples with 90 % sensitivity, 98 % specificity, and 96 % accuracy for control group and 100 % sensitivity, 90 % specificity, and 96 % accuracy for BC patients. Furthermore, analysis of the resulting topological map revealed 14 significant variables (biomarkers) such as sarcosine, lysine, trehalose, tryptophan, and betaine that effectively differentiated between healthy individuals and BC patients., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Purpose of Review: Proton nuclear magnetic resonance (NMR) can rapidly assess lipoprotein concentrations and sizes in biological samples. It may be especially useful for quantifying high-density lipoprotein (HDL), which exhibits diverse particle sizes and concentrations. We provide a critical review of the strengths and limitations of NMR for quantifying HDL subclasses., Recent Findings: Recent studies using NMR have shed light on HDL's role in various disorders, ranging from residual cardiovascular risk to host susceptibility to infection. However, accurately quantifying HDL particle number, size, and concentration (HDL-P) remains a challenge. Discrepancies exist between NMR and other methods such as gel electrophoresis, ion mobility analysis and size-exclusion chromatography in estimating the abundance of HDL species and the ratio of apolipoprotein A-I (APOA1) to HDL particles., Summary: NMR is a low-cost method for quantifying HDL-P that is readily applicable to clinical and translational studies. However, inconsistencies between the results of NMR quantification of HDL-P and other independent methods hinder the interpretation of NMR results. Because proton NMR apparently fails to accurately quantify the sizes and concentrations of HDL, the relevance of such studies to HDL biology poses challenges. This limits our understanding of pathophysiological implications of HDL-P as determined by NMR, particularly in determining cardiovascular disease (CVD) risk., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

This study aims to investigate the potential of using advanced spectroscopies for cheese quality monitoring. For this purpose, six semi-hard cheeses manufactured using lactic acid bacteria (LAB) and/or propionic acid bacteria (PAB) were explored using near-infrared spectroscopy (NIRS) and Proton Nuclear Magnetic Resonance ( 1 H NMR) spectroscopy. The spectral data were analyzed using principal component analysis for extraction of possible discriminative patterns in quality parameters. The results show that the green analytical, but primarily bulk-sensitive, NIRS method was able to discriminate the cheese varieties primarily due to differences in the first overtone CH stretching region between 1650 and 1720 nm, in particular by the lactate methylene absorption at 1674 nm. A total of 25 metabolites were identified in the 1 H NMR spectra of the cheese extracts, several of which were associated with the LAB and PAB metabolic pathways. PAB-associated metabolites include propionate, acetate, and glutamate, while LAB-associated metabolites include lactate and acetoin among others., Competing Interests: Declaration of competing interest All co-authors have agreed with the contents of the manuscript in its submitted form, and we declare no conflicts of interest. The submission is an original work, and the abovementioned paper has not been published elsewhere, accepted for publication elsewhere and is not under editorial review elsewhere., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Creatine chemical exchange saturation transfer (CrCEST) MRI is an emerging high resolution and noninvasive method for measuring muscle specific oxidative phosphorylation (OXPHOS). However, CrCEST measurements are sensitive to changes in muscle pH, which might confound the measurement and interpretation of creatine recovery time (τ Cr ). Even with the same prescribed exercise stimulus, the extent of acidification and hence its impact on τ Cr is expected to vary between individuals. To address this issue, a method to measure pH pre- and post-exercise and its impact on CrCEST MRI with high temporal resolution is needed. In this work, we integrate carnosine 1 H- magnetic resonance spectroscopy (MRS) and 3D CrCEST to establish "mild" and "moderate/intense" exercise stimuli. We then test the dependence of CrCEST recovery time on pH using different exercise stimuli. This comprehensive metabolic imaging protocol will enable personalized, muscle specific OXPHOS measurements in both healthy aging and myriad other disease states impacting muscle mitochondria., (© 2024. The Author(s).)

Introduction: The purpose of this study was to examine N-acetyl aspartate (NAA)/creatine (Cr) and glutamate, glutamine, and gamma-aminobutyric acid complex (Glx)/Cr levels in patients with obsessive compulsive disorder (OCD) and healthy controls' orbitofrontal cortex (OFC) and caudate nucleus (CN) by proton magnetic resonance spectroscopy (1H-MRS) method and to investigate their relationship with oxidative stress markers glutathione peroxidase (GPx) and superoxide dismutase (SOD)., Methods: This study included patients with OCD (n = 25) and healthy controls (n = 25) ranging in age from 18 to 65. We used the ELISA method to evaluate serum SOD and GPx levels. Levels of NAA/Cr and Glx/Cr in the orbitofrontal cortex and caudate nucleus were measured using the 1H-MRS method., Results: Our study did not detect statistically significant differences in the orbitofrontal cortex Glx/Cr and NAA/Cr levels between the OCD patients and the control group. OCD patients exhibited a decrease in NAA/Cr levels, consistent with impaired neuronal integration, and an increase in Glx/Cr levels, consistent with hyperactivation, in the caudate nucleus compared to the control group. We observed a negative correlation between NAA/Cr levels in the caudate nucleus and the levels of SOD and GPx., Conclusions: Our study is the first to assess CN and OFC together in OCD patients using 3 T MR, investigating the relationship between neurometabolite concentrations and oxidative stress parameters. The negative correlation we observed between NAA/Cr levels and SOD and GPx in the caudate nucleus suggests that increased oxidative stress in this brain region in OCD patients may contribute to impaired neuronal integration and functionality., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Objective: To investigate the performance of diffusion-tensor imaging (DTI) and hydrogen proton magnetic resonance spectroscopy ( 1 H-MRS) parameters in predicting the immunohistochemistry (IHC) biomarkers of glioma., Methods: Patients with glioma confirmed by pathology from March 2015 to September 2019 were analyzed, the preoperative DTI and 1 H-MRS images were collected, apparent diffusion coefficient (ADC) and fractional anisotropy (FA), in the lesion area were measured, the relative values relative ADC (rADC) and relative FA (rFA) were obtained by the ratio of them in the lesion area to the contralateral normal area. The peak of each metabolite in the lesion area of 1 H-MRS image: N-acetylaspartate (NAA), choline (Cho), and creatine (Cr), and metabolite ratio: NAA/Cho, NAA/(Cho + Cr) were selected and calculated. The preoperative IHC data were collected including CD34, Ki-67, p53, S-100, syn, vimentin, NeuN, Nestin, and glial fibrillary acidic protein., Results: One predicting parameter of DTI was screened, the rADC of the Ki-67 positive group was lower than that of the negative group. Two parameters of 1 H-MRS were found to have significant reference values for glioma grades, the NAA and Cr decreased as the grade of glioma increased, moreover, Ki-67 Li was negatively correlated with NAA and Cr., Conclusion: NAA and Cr have potential application value in predicting glioma grades and tumor proliferation activity. Only rADC has predictive value for Ki-67 expression among DTI parameters., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2024.)

Catecholamines and amino acid transmitter systems are known to interact, the exact links and their impact on cognitive control functions have however remained unclear. Using a multi-modal imaging approach combining EEG and proton-magnetic resonance spectroscopy ( 1 H-MRS), we investigated the effect of different degrees of pharmacological catecholaminergic enhancement onto theta band activity (TBA) as a measure of interference control during response inhibition and execution. It was central to our study to evaluate the predictive impact of in-vivo baseline GABA+ concentrations in the striatum, the anterior cingulate cortex (ACC) and the supplemental motor area (SMA) of healthy adults under varying degrees of methylphenidate (MPH) stimulation. We provide evidence for a predictive interrelation of baseline GABA+ concentrations in cognitive control relevant brain areas onto task-induced TBA during response control stimulated with MPH. Baseline GABA+ concentrations in the ACC, the striatum, and the SMA had a differential impact on predicting interference control-related TBA in response execution trials. GABA+ concentrations in the ACC appeared to be specifically important for TBA modulations when the cognitive effort needed for interference control was high - that is when no prior task experience exists, or in the absence of catecholaminergic enhancement with MPH. The study highlights the predictive role of baseline GABA+ concentrations in key brain areas influencing cognitive control and responsiveness to catecholaminergic enhancement, particularly in high-effort scenarios., Competing Interests: Declaration of competing interest None., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Proton magnetic resonance spectroscopy ( 1 H-MRS) is increasingly used for clinical brain tumour diagnosis, but suffers from limited spectral quality. This retrospective and comparative study aims at improving paediatric brain tumour classification by performing noise suppression on clinical 1 H-MRS. Eighty-three/forty-two children with either an ependymoma (ages 4.6 ± 5.3/9.3 ± 5.4), a medulloblastoma (ages 6.9 ± 3.5/6.5 ± 4.4), or a pilocytic astrocytoma (8.0 ± 3.6/6.3 ± 5.0), recruited from four centres across England, were scanned with 1.5T/3T short-echo-time point-resolved spectroscopy. The acquired raw 1 H-MRS was quantified by using Totally Automatic Robust Quantitation in NMR (TARQUIN), assessed by experienced spectroscopists, and processed with adaptive wavelet noise suppression (AWNS). Metabolite concentrations were extracted as features, selected based on multiclass receiver operating characteristics, and finally used for identifying brain tumour types with supervised machine learning. The minority class was oversampled through the synthetic minority oversampling technique for comparison purposes. Post-noise-suppression 1 H-MRS showed significantly elevated signal-to-noise ratios (P < .05, Wilcoxon signed-rank test), stable full width at half-maximum (P > .05, Wilcoxon signed-rank test), and significantly higher classification accuracy (P < .05, Wilcoxon signed-rank test). Specifically, the cross-validated overall and balanced classification accuracies can be improved from 81% to 88% overall and 76% to 86% balanced for the 1.5T cohort, whilst for the 3T cohort they can be improved from 62% to 76% overall and 46% to 56%, by applying Naïve Bayes on the oversampled 1 H-MRS. The study shows that fitting-based signal-to-noise ratios of clinical 1 H-MRS can be significantly improved by using AWNS with insignificantly altered line width, and the post-noise-suppression 1 H-MRS may have better diagnostic performance for paediatric brain tumours., (© 2024 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.)

Introduction: The cacao tree (Theobroma cacao), a perennial crop that serves as a source of cacao beans, can suffer from drastic climate changes such as irregular rainfall and shorter rainy seasons. The search for hybrids which are capable of producing specific metabolites favoring adaptation in new climatic conditions is a challenge in cacao farming., Objectives: We aimed to (1) analyze the metabolic changes in calli of three cacao genotypes during water deficit induced by incubation with polyethylene glycol and (2) assess their response to water deficit stress with regard to somatic embryo differentiation., Methods: Metabolic profiling was carried out using 1 H-NMR spectroscopy and multivariate data analysis was applied to crude extracts of calli grown in non-stress or water deficit stress conditions., Results: Water deficit stress influences the capacity of calli to produce embryos. The SCA12 genotype exhibited the best conversion capacity under severe conditions and was considered as tolerant to drought, followed by the SCA6 genotype (mid-tolerant) and the MA12 genotype (sensitive). Fifty-four metabolites were identified in the three cacao genotypes and discriminant metabolites were identified. Metabolites involved in water stress tolerance such as fructose, trans-aconitic acid, leucine, and hydroxybenzene derivatives were observed in SCA12, the tolerant genotype., Conclusion: These results demonstrate the utility of 1 H-NMR metabolomics as an essential tool for the analysis of the drought tolerance characteristics of T. cacao., (© 2024 John Wiley & Sons Ltd.)

Introduction: The prevalence of type 2 diabetes has surged to epidemic proportions and despite treatment administration/adherence, some individuals experience poorly controlled diabetes. While existing literature explores metabolic changes in type 2 diabetes, understanding metabolic derangement in poorly controlled cases remains limited., Objective: This investigation aimed to characterize the urine metabolome of poorly controlled type 2 diabetes in a South African cohort., Method: Using an untargeted proton nuclear magnetic resonance metabolomics approach, urine samples from 15 poorly controlled type 2 diabetes patients and 25 healthy controls were analyzed and statistically compared to identify differentiating metabolites., Results: The poorly controlled type 2 diabetes patients were characterized by elevated concentrations of various metabolites associated with changes to the macro-fuel pathways (including carbohydrate metabolism, ketogenesis, proteolysis, and the tricarboxylic acid cycle), autophagy and/or apoptosis, an uncontrolled diet, and kidney and liver damage., Conclusion: These results indicate that inhibited cellular glucose uptake in poorly controlled type 2 diabetes significantly affects energy-producing pathways, leading to apoptosis and/or autophagy, ultimately contributing to kidney and mild liver damage. The study also suggests poor dietary compliance as a cause of the patient's uncontrolled glycemic state. Collectively these findings offer a first-time comprehensive overview of urine metabolic changes in poorly controlled type 2 diabetes and its association with secondary diseases, offering potential insights for more targeted treatment strategies to prevent disease progression, treatment efficacy, and diet/treatment compliance., (© 2024. The Author(s).)

Type 2 diabetes (T2D) is a complex chronic metabolic disorder characterized by hyperglycemia because of insulin resistance. Diabetes with chronic hyperglycemia may alter brain metabolism, including brain glucose and neurotransmitter levels; however, detailed, longitudinal studies of metabolic alterations in T2D are lacking. To shed insight, here, we characterized the consequences of poorly controlled hyperglycemia on neurochemical profiles that reflect metabolic alterations of the brain in both humans and animal models of T2D. Using in vivo 1 H magnetic resonance spectroscopy, we quantified 12 metabolites cross-sectionally in T2D patients and 20 metabolites longitudinally in T2D db/db mice versus db+ controls. We found significantly elevated brain glucose (91%, p < 0.001), taurine (22%, p = 0.02), glucose+taurine (56%, p < 0.001), myo-inositol (12%, p = 0.02), and choline-containing compounds (10%, p = 0.01) in T2D patients versus age- and sex-matched controls, findings consistent with measures in T2D db/db versus control db+ littermates. In mice, hippocampal and striatal neurochemical alterations in brain glucose, ascorbate, creatine, phosphocreatine, γ-aminobutyric acid, glutamate, glutamine, glutathione, glycerophosphoryl-choline, lactate, myo-inositol, and taurine persisted in db/db mice with chronic disease progression from 16 to 48 weeks of age, which were distinct from control db+ mice. Overall, our study demonstrates the utility of 1 H magnetic resonance spectroscopy as a non-invasive tool for characterizing and monitoring brain metabolic changes with T2D progression., (© 2023 International Society for Neurochemistry.)

Proton magnetic resonance spectroscopy ( 1 H MRS) presents a powerful tool for revealing molecular-level metabolite information, complementary to the anatomical insight delivered by magnetic resonance imaging (MRI), thus playing a significant role in in vivo/in vitro biological studies. However, its further applications are generally confined by spectral congestion caused by numerous biological metabolites contained within the limited proton frequency range. Herein, we propose a pure-shift-based 1 H localized MRS method as a proof of concept for high-resolution studies of biological samples. Benefitting from the spectral simplification from multiplets to singlet peaks, this method addresses the challenge of spectral congestion encountered in conventional MRS experiments and facilitates metabolite analysis from crowded NMR resonances. The performance of the proposed pure-shift 1 H MRS method is demonstrated on different kinds of samples, including brain metabolite phantom and in vitro biological samples of intact pig brain tissue and grape tissue, using a 7.0 T animal MRI scanner. This proposed MRS method is readily implemented in common commercial NMR/MRI instruments because of its generally adopted pulse-sequence modules. Therefore, this study takes a meaningful step for MRS studies toward potential applications in metabolite analysis and disease diagnosis.

Background: 1 H-MRS is increasingly used in basic and clinical research to explain brain function and alterations respectively. In psychosis research it is now one of the main tools to investigate imbalances in the glutamatergic system. Interestingly, however, the findings are extremely variable even within patients of similar disease states. One reason may be the variability in analysis strategies, despite suggestions for standardization. Therefore, our study aimed to investigate the extent to which the basis set configuration- which metabolites are included in the basis set used for analysis- would affect the spectral fit and estimated glutamate (Glu) concentrations in the anterior cingulate cortex (ACC), and whether any changes in levels of glutamate would be associated with psychotic-like experiences and autistic traits., Methods: To ensure comparability, we utilized five different exemplar basis sets, used in research, and two different analysis tools, r-based spant applying the ABfit method and Osprey using the LCModel., Results: Our findings revealed that the types of metabolites included in the basis set significantly affected the glutamate concentration. We observed that three basis sets led to more consistent results across different concentration types (i.e., absolute Glu in mol/kg, Glx (glutamate + glutamine), Glu/tCr), spectral fit and quality measurements. Interestingly, all three basis sets included phosphocreatine. Importantly, our findings also revealed that glutamate levels were differently associated with both schizotypal and autistic traits depending on basis set configuration and analysis tool, with the same three basis sets showing more consistent results., Conclusions: Our study highlights that scientific results may be significantly altered depending on the choices of metabolites included in the basis set, and with that emphasizes the importance of carefully selecting the configuration of the basis set to ensure accurate and consistent results, when using MR spectroscopy. Overall, our study points out the need for standardized analysis pipelines and reporting., (© 2024. The Author(s).)

Whether patients with myasthenia gravis (MG) exhibit cognitive impairment is controversial. Also the underlying mechanisms are unknown. We aimed to investigate alterations in cognitive function, neurometabolite levels, and brain function in patients with MG and to explore the associations between abnormal regional brain functional activity, neurometabolite concentrations in the MPFC and left thalamus, and cognitive activity in patients with MG. Neuropsychological tests, proton magnetic resonance spectroscopy, and resting-state functional magnetic resonance imaging were performed on 41 patients with MG and 45 race-, sex-, age-, and education-matched healthy controls (HCs). The results suggest that MG is accompanied by cognitive decline, as indicated by global cognitive function, visual-spatial function, language, memory, abnormalities in regional brain functional activity, and neurometabolite alterations (including GABA, NAA, and Cho) in the medial prefrontal cortex (MPFC) and left thalamus. Cognitive impairment in patients with MG may be related to abnormal regional brain functional activity and changes in neurometabolites, and regional brain functional activity may be modulated by specific neurometabolites., (Copyright © 2024 IBRO. Published by Elsevier Inc. All rights reserved.)

Metabolomics has become an important tool in elucidating the complex relationship between a plant genotype and phenotype. For over 20 years, nuclear magnetic resonance (NMR) spectroscopy has been known for its robustness, quantitative capabilities, simplicity, and cost-efficiency. 1 H NMR is the method of choice for analyzing a broad range of relatively abundant metabolites, which can be used for both capturing the plant chemical profile at one point in time and understanding the pathways that underpin plant defense. This systematic Review explores how 1 H NMR-based plant metabolomics has contributed to understanding the role of various compounds in plant responses to biotic stress, focusing on both primary and secondary metabolites. It clarifies the challenges and advantages of using 1 H NMR in plant metabolomics, interprets common trends observed, and suggests guidelines for method development and establishing standard procedures.

Previous studies reported decreased glutamate levels in the anterior cingulate cortex (ACC) in non-treatment-resistant schizophrenia and first-episode psychosis. However, ACC glutamatergic changes in subjects at high-risk for psychosis, and the effects of commonly experienced environmental emotional/social stressors on glutamatergic function in adolescents remain unclear. In this study, adolescents recruited from the general population underwent proton magnetic resonance spectroscopy (MRS) of the pregenual ACC using a 3-Tesla scanner. We explored longitudinal data on the association of combined glutamate-glutamine (Glx) levels, measured by MRS, with subclinical psychotic experiences. Moreover, we investigated associations of bullying victimization, a risk factor for subclinical psychotic experiences, and help-seeking intentions, a coping strategy against stressors including bullying victimization, with Glx levels. Finally, path analyses were conducted to explore multivariate associations. For a contrast analysis, gamma-aminobutyric acid plus macromolecule (GABA+) levels were also analyzed. Negative associations were found between Glx levels and subclinical psychotic experiences at both Times 1 (n = 219, mean age 11.5 y) and 2 (n = 211, mean age 13.6 y), as well as for over-time changes (n = 157, mean interval 2.0 y). Moreover, effects of bullying victimization and bullying victimization × help-seeking intention interaction effects on Glx levels were found (n = 156). Specifically, bullying victimization decreased Glx levels, whereas help-seeking intention increased Glx levels only in bullied adolescents. Finally, associations among bullying victimization, help-seeking intention, Glx levels, and subclinical psychotic experiences were revealed. GABA+ analysis revealed no significant results. This is the first adolescent study to reveal longitudinal trajectories of the association between glutamatergic function and subclinical psychotic experiences and to elucidate the effect of commonly experienced environmental emotional/social stressors on glutamatergic function. Our findings may deepen the understanding of how environmental emotional/social stressors induce impaired glutamatergic neurotransmission that could be the underpinning of liability for psychotic experiences in early adolescence., (© 2024. The Author(s).)

A subgroup of patients with schizophrenia is believed to have aberrant excess of glutamate in the frontal cortex; this subgroup is thought to show poor response to first-line antipsychotic treatments that focus on dopamine blockade. If we can identify this subgroup early in the course of illness, we can reduce the repeated use of first-line antipsychotics and potentially stratify first-episode patients to intervene early with second-line treatments such as clozapine. The use of proton magnetic resonance spectroscopy (1H-MRS) to measure glutamate and Glx (glutamate plus glutamine) may provide a means for such a stratification. We must first establish if there is robust evidence linking elevations in anterior cingulate cortex (ACC) glutamate metabolites to poor response, and determine if the use of antipsychotics worsens the glutamatergic excess in eventual nonresponders. In this study, we estimated glutamate levels at baseline in 42 drug-naive patients with schizophrenia. We then treated them all with risperidone at a standard dose range of 2-6 mg/day and followed them up for 3 months to categorize their response status. We expected to see baseline "hyperglutamatergia" in nonresponders, and expected this to worsen over time at the follow-up. In line with our predictions, nonresponders had higher glutamate than responders, but patients as a group did not differ in glutamate and Glx from the healthy control (HC) group before treatment-onset (F 1,79  = 3.20, p = 0.046, partial η2 = 0.075). Glutamatergic metabolites did not change significantly over time in both nonresponders and responders over the 3 months of antipsychotic exposure (F 1,31  = 1.26, p = 0.270, partial η2 = 0.039). We conclude that the use of antipsychotics without prior knowledge of later response delays symptom relief in a subgroup of first-episode patients, but does not worsen the glutamatergic excess seen at the baseline. Given the current practice of nonstratified use of antipsychotics, longer-time follow-up MRS studies are required to see if improvement in symptoms accompanies a dynamic shift in glutamate profile., (© 2023. The Author(s), under exclusive licence to American College of Neuropsychopharmacology.)

Objective: Malignant pleural effusion (MPE) is a common complication of lung cancer with poor prognosis. Benign pleural effusion (BPE), such as tuberculous and pneumonic pleural effusion, usually has a good prognosis. Differential diagnosis between MPE and BPE remains a clinical challenge., Methods: 52 MPE, 93 BPE, and their corresponding serum samples were analyzed by hydrogen nuclear magnetic resonance ( 1 HNMR) based metabolomics., Results: The 1 HNMR study showed that some amino acids and betaine in MPE are significantly altered in pleural effusion and serum compared to BPE patients. Levels of serum glucose and glutamine have strong positive correlation with those in pleural effusion (r>0.6) for MPE patients. The area under the receiver operating characteristic curve (AUROC) values of metabolites in pleural effusion or serum were less than 0.805 in differentiating MPE from BPE. Improved an AUROC value of 0.901 was observed using pleural effusion-serum ratios of glutamic acid in differentiating MPE from BPE, which was further validated by 15 double-blind samples., Conclusions: Compared with BPE patients, amino acids and betaine in MPE are significantly altered in pleural effusion and serum. Pleural effusion-serum ratio of glutamic acid may contribute to the rapid diagnosis of MPE from BPE by 1 HNMR analysis., (© 2024 by the Association of Clinical Scientists, Inc.)

Purpose: MELAS syndrome is a genetic disorder caused by mitochondrial DNA mutations. We previously described that MELAS patients had increased CSF glutamate and decreased CSF glutamine levels and that oral glutamine supplementation restores these values. Proton magnetic resonance spectroscopy ( 1 H-MRS) allows the in vivo evaluation of brain metabolism. We aimed to compare 1 H-MRS of MELAS patients with controls, the 1 H-MRS after glutamine supplementation in the MELAS group, and investigate the association between 1 H-MRS and CSF lactate, glutamate, and glutamine levels., Methods: We conducted an observational case-control study and an open-label, single-cohort study with single-voxel MRS (TE 144/35 ms). We assessed the brain metabolism changes in the prefrontal (PFC) and parieto-occipital) cortex (POC) after oral glutamine supplementation in MELAS patients. MR spectra were analyzed with jMRUI software., Results: Nine patients with MELAS syndrome (35.8 ± 3.2 years) and nine sex- and age-matched controls were recruited. Lactate/creatine levels were increased in MELAS patients in both PFC and POC (0.40 ± 0.05 vs. 0, p < 0.001; 0.32 ± 0.03 vs. 0, p < 0.001, respectively). No differences were observed between groups in glutamate and glutamine (Glx/creatine), either in PFC (p = 0.930) or POC (p = 0.310). No differences were observed after glutamine supplementation. A positive correlation was found between CSF lactate and lactate/creatine only in POC (0.85, p = 0.003)., Conclusion: No significant metabolite changes were observed in the brains of MELAS patients after glutamine supplementation. While we found a positive correlation between lactate levels in CSF and 1 H-MRS in MELAS patients, we could not monitor treatment response over short periods with this tool., Trial Registration: ClinicalTrials.gov Identifier: NCT04948138; initial release 24/06/2021; first patient enrolled on 1/07/2021. https://clinicaltrials.gov/ct2/show/NCT04948138., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: The histamine-3 receptor (H3R) may have a role in cognitive processes through its action as a presynaptic heteroreceptor inhibiting the release of glutamate in the brain. To explore this, we examined anterior cingulate cortex (ACC) and striatum H3R availability in patients with schizophrenia and characterized their relationships with glutamate levels in corresponding brain regions., Methods: We employed a cross-sectional study, recruiting 12 patients with schizophrenia and 12 healthy volunteers. Participants underwent positron emission tomography using the H3R-specific radio ligand [11C]MK-8278, followed by proton magnetic resonance spectroscopy to measure glutamate levels, recorded as Glu and Glx. Based on existing literature, the ACC and striatum were selected as regions of interest., Results: We found significant inverse relationships between tracer uptake and Glu (r = -0.66, P = .02) and Glx (r = -0.62, P = .04) levels in the ACC of patients, which were absent in healthy volunteers (Glu: r = -0.19, P = .56, Glx: r = 0.10, P = .75). We also found a significant difference in striatal (F1,20 = 6.00, P = .02) and ACC (F1,19 = 4.75, P = .04) Glx levels between groups., Conclusions: These results provide evidence of a regionally specific relationship between H3Rs and glutamate levels, which builds on existing preclinical literature. Our findings add to a growing literature indicating H3Rs may be a promising treatment target in schizophrenia, particularly for cognitive impairment, which has been associated with altered glutamate signaling., (© The Author(s) 2024. Published by Oxford University Press on behalf of CINP.)

Cow milk contains essential nutrients for humans, and its bulk composition is usually analyzed using Fourier transform infrared spectroscopy. The higher sensitivity of nuclear magnetic resonance (NMR) spectroscopy can augment the extractible qualitative and quantitative information from milk to nearly 60 compounds, enabling us to monitor the health of cows and milk quality. Proton ( 1 H) NMR spectroscopy produces complex spectra that require expert knowledge for identifying and quantifying metabolites. Therefore, an efficient and reproducible methodology is required to transform complex milk 1 H NMR spectra into annotated and quantified milk metabolome data. In this study, standard operating procedures for screening the milk metabolome using 1 H NMR spectra are developed. A chemical shift library of 63 milk metabolites was established and implemented in the open-access Signature Mapping (SigMa) software. SigMa is a spectral analysis tool that transforms 1 H NMR spectra into a quantitative metabolite table. The applicability of the proposed methodology to whole milk, skim milk, and ultrafiltered milk is demonstrated, and the method is tested on ultrafiltered colostrum samples from dairy cows ( n = 88) to evaluate whether metabolic changes in colostrum may reflect the metabolic status of cows.

The classical approach restricts the detection of metabolites in serum samples by using nuclear magnetic resonance (NMR) spectroscopy; however, the presence of copious proteins and lipoproteins emphasize and necessitate the development of a contemporary, high-throughput tactic. To eliminate the lipoproteins and proteins from sera to engender filtered sera (FS), the study was executed with 50 μl serum obtained from five healthy individuals with 5 years of age difference from 25 to 45 years old and the application of a unique mechanical filter with molecular weight cut-off value of 2KDa. The 10 μl FS from each individual was pooled to make 50 μl final volume filled in a co-axial tube for acquisition of a battery of 1D/2D investigations at 800 MHz NMR spectrometer and the assigned metabolites was confirmed through mass spectrometry as well as by comparing 1 H NMR spectra of individual metabolites. This innovative tactic is commissioning to reveal more than 100 metabolites. In contrast to the protein precipitation method, 24 new metabolites were recognized in the present study. The present innovative approach characterizes nucleosides, nitrogenous bases, and volatile metabolites that possibly produce a landmark for the delineation of a comprehensive metabolic profile applicable for detection of the molecular cause of pathogenicity, early-stage disease detection and prognosis, inborn error of metabolism, and forensic investigations exerting the least volume of FS and NMR spectroscopy. The assignment of 100 metabolites using 1 H NMR-based FS is described for the first time in the present report., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier B.V.)

γ-Aminobutyric acid (GABA), as the primary inhibitory neurotransmitter, is extremely important for maintaining healthy brain function, and deviations from GABA homeostasis are related to various brain diseases. Short-echo-time (short-TE) proton MR spectroscopy ( 1 H-MRS) has been employed to measure GABA concentration from various human brain regions at high magnetic fields. The aim of this study was to investigate the effect of spectral linewidth on GABA quantification and explore the application of an optimized basis-set preparation approach using a spectral-linewidth-matched (LM) basis set in LCModel to improve the reproducibility of GABA quantification from short-TE 1 H-MRS. In contrast to the fixed-linewidth basis-set approach, the LM basis-set preparation approach, where all metabolite basis spectra were simulated with a linewidth 4 Hz narrower than that of water, showed a smaller standard deviation of estimated GABA concentration from synthetic spectra with varying linewidths and lineshapes. The test-retest reproducibility was assessed by the mean within-subject coefficient of variation, which improved from 19.2% to 12.0% in the thalamus, from 27.9% to 14.9% in the motor cortex, and from 9.7% to 2.8% in the medial prefrontal cortex using LM basis sets at 7 T. We conclude that spectral linewidth has a large effect on GABA quantification from short-TE 1 H-MRS data and that using LM basis sets in LCModel can improve the reproducibility of GABA quantification., (© 2023 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.)

Objective: This study aimed to investigate the impact of puerarin early intervention on growth parameters and Hepatic Fat Signal Fraction (HFF) quantification in Intrauterine Growth Restricted(IUGR)rats through Proton Magnetic resonance spectroscopy (1H-MRS)., Methods: Pregnant rats were divided into three groups: control, IUGR with puerarin treatment, and IUGR without treatment. The treatment and nontreatment groups were received a low-protein diet during pregnancy, while the control group received a normal diet. After birth, pups in the treatment group received a unilateral intraperitoneal injection of 50 mg/kg/d puerarin. Male rats were evaluated at 3,8 and 12 weeks, including measurements of weight, body length and waist circumference and body mass index (BMI). Conventional magnetic resonance imaging and 1HMRS were conducted using a 3.0 T whole-body MR scanner., Results: Newborn pups in the treatment and non-treatment groups showed significantly lower body weight, BMI, and body length at 3 weeks compared to the control group. However, there were no significant differences in HFF and waist circumference between the three groups at 3 weeks. At 8 and 12 weeks post-delivery, significant differences in body weight, BMI, waist circumference were observed in newborn pups of IUGR non-treatment rats compared to the control group. In contrast, there were no significant differences in body weight, BMI, waist circumference between the treatment group and the control group at 8 and 12 weeks. Moreover, the treatment group exhibited notably higher HFF compared to the control group at both time points. At 12 weeks post-birth, a significant difference in HFF was observed between the IUGR non-treatment and treatment groups, although no significant difference was found at 8 weeks., Conclusion: Early intervention with puerarin following birth has a significant impact on liver fat content and may potentially reduce adult obesity among IUGR rats.

The accurate diagnosis of brain tumour is very important in modern neuro-oncology medicine. Magnetic resonance spectroscopy (MRS) is supposed to be a promising tool for detecting cancerous lesions. However, the interpretation of MRS data is complicated by the fact that not all cancerous lesions exhibit elevated choline (Cho) levels. The main goal of our study was to investigate the lack of Cho lesion /Cho ref elevation in the population of grade II-III gliomas. 89 cases of gliomas grade II and III were used for the retrospective analysis - glioma (astrocytoma or oligodendroglioma) grade II (74 out of 89 cases [83%]) and III (15 out of 89 cases [17%]) underwent conventional MRI extended by MRS before treatment. Histopathological diagnosis was obtained either by biopsy or surgical resection. Gliomas were classified to the group of no-choline elevation when the ratio of choline measured within the tumour (Cho lesion ) to choline from NABT (Cho ref ) were equal to or lower than 1. Significant differences were observed between ratios of Cho lesion /Cr lesion calculated for no-choline elevation and glial tumour groups as well as in the NAA lesion /Cr lesion ratio between the no-choline elevation group and glial tumour group. With consistent data concerning choline level elevation and slightly lower NAA value, the Cho lesion /NAA lesion ratio is significantly higher in the WHO II glial tumour group compared to the no-choline elevation cases ( p < 0.000). In the current study the results demonstrated possibility of lack of choline elevation in patients with grade II-III gliomas, so it is important to remember that the lack of elevated choline levels does not exclude neoplastic lesion.

The specific spatial and temporal distribution of lipids in membranes play a crucial role in determining the biochemical and biophysical properties of the system. In nature, the asymmetric distribution of lipids is a dynamic process with ATP-dependent lipid transporters maintaining asymmetry, and passive transbilayer diffusion, that is, flip-flop, counteracting it. In this chapter, two probe-free techniques, 1 H NMR and time-resolved small angle neutron scattering, are described in detail as methods of investigating lipid flip-flop rates in synthetic liposomes that have been generated with an asymmetric bilayer composition., (Copyright © 2024. Published by Elsevier Inc.)

Major depressive disorder (MDD) is underlined by neurochemical changes in the brain. Proton magnetic resonance spectroscopy ( 1 H MRS) is a useful tool for their examination as it provides information about the levels of metabolites. This review summarises the current knowledge of 1 H MRS findings from rodent models of MDD, assesses the results from both a biological and a technical perspective, and identifies the main sources of bias. From a technical point of view, bias-introducing factors are the diversity of the measured volumes and their positioning in the brain, the data processing, and the metabolite concentration expression. The biological variables are strain, sex, and species, as well as the model itself, and in vivo vs. ex vivo exploration. This review identified some consistency in the 1 H MRS findings in the models of MDD: lower levels of glutamine, glutamate + glutamine, and higher levels of myo-inositol and taurine in most of the brain regions of MDD models. This may suggest changes in regional metabolism, neuronal dysregulation, inflammation, and a compensatory effect reaction in the MDD rodent models., Competing Interests: Declaration of Competing Interest Both authors of the paper have contributed substantially to the scientific process leading up to the writing of the manuscript. The authors declare no conflict of interest and certify that the submission is original work and is not under review at any other publication., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: The aim of this study was to determine whether neurometabolite abnormalities indicating neuroinflammation and neuronal injury are detectable in individuals post-coronavirus disease 2019 (COVID-19) with persistent neuropsychiatric symptoms., Methods: All participants were studied with proton magnetic resonance spectroscopy at 3 T to assess neurometabolite concentrations (point-resolved spectroscopy, relaxation time/echo time = 3000/30 ms) in frontal white matter (FWM) and anterior cingulate cortex-gray matter (ACC-GM). Participants also completed the National Institutes of Health Toolbox cognition and motor batteries and selected modules from the Patient-Reported Outcomes Measurement Information System., Results: Fifty-four participants were evaluated: 29 post-COVID-19 (mean ± SD age, 42.4 ± 12.3 years; approximately 8 months from COVID-19 diagnosis; 19 women) and 25 controls (age, 44.1 ± 12.3 years; 14 women). When compared with controls, the post-COVID-19 group had lower total N-acetyl compounds (tNAA; ACC-GM: -5.0%, P = .015; FWM: -4.4%, P = .13), FWM glutamate + glutamine (-9.5%, P = .001), and ACC-GM myo-inositol (-6.2%, P = .024). Additionally, only hospitalized patients post-COVID-19 showed age-related increases in myo-inositol, choline compounds, and total creatine (interaction P = .029 to <.001). Across all participants, lower FWM tNAA and higher ACC-GM myo-inositol predicted poorer performance on several cognitive measures (P = .001-.009), while lower ACC-GM tNAA predicted lower endurance on the 2-minute walk (P = .005)., Conclusions: In participants post-COVID-19 with persistent neuropsychiatric symptoms, the lower-than-normal tNAA and glutamate + glutamine indicate neuronal injury, while the lower-than-normal myo-inositol reflects glial dysfunction, possibly related to mitochondrial dysfunction and oxidative stress in Post-COVID participants with persistent neuropsychiatric symptoms., Competing Interests: Potential conflicts of interest. S. K. is a member of the Scientific Advisory Board at Merck, Regeneron, Silverback Therapeutics, Zhuhai Yufan Biotechnologies, and The Liver Company and has received grants paid to the institution from Gilead Sciences and Arbutus Pharmaceuticals. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2023. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: The main aim of the present study is to determine the role of metabolites observed using proton magnetic resonance spectroscopy (1H-MRS) in obsessive-compulsive disorder (OCD). As the literature describing biochemical changes in OCD yields conflicting results, we focused on accurate metabolite quantification of total N-acetyl aspartate (tNAA), total creatine (tCr), total choline-containing compounds (tCh), and myo-inositol (mI) in the anterior cingulate cortex (ACC) to capture the small metabolic changes between OCD patients and controls and between OCD patients with and without medication., Methods: In total 46 patients with OCD and 46 healthy controls (HC) matched for age and sex were included in the study. The severity of symptoms in the OCD was evaluated on the day of magnetic resonance imaging (MRI) using the Yale-Brown Obsessive-Compulsive Scale (YBOCS). Subjects underwent 1H-MRS from the pregenual ACC (pgACC) region to calculate concentrations of tNAA, tCr, tCho, and mI. Twenty-eight OCD and 28 HC subjects were included in the statistical analysis. We compared differences between groups for all selected metabolites and in OCD patients we analyzed the relationship between metabolite levels and symptom severity, medication status, age, and the duration of illness., Results: Significant decreases in tCr (U = 253.00, p = 0.022) and mI (U = 197.00, p = 0.001) in the pgACC were observed in the OCD group. No statistically significant differences were found in tNAA and tCho levels; however, tCho revealed a trend towards lower concentrations in OCD patients (U = 278.00, p = 0.062). Metabolic concentrations showed no significant correlations with the age and duration of illness. The correlation statistics found a significant negative correlation between tCr levels and YBOCS compulsions subscale (cor = -0.380, p = 0.046). tCho and YBOCS compulsions subscale showed a trend towards a negative correlation (cor = -0.351, p = 0.067). Analysis of subgroups with or without medication showed no differences., Conclusions: Patients with OCD present metabolic disruption in the pgACC. The decrease in tCr shows an important relationship with OCD symptomatology. tCr as a marker of cerebral bioenergetics may also be considered as a biomarker of the severity of compulsions. The study failed to prove that metabolic changes correlate with the medication status or the duration of illness. It seems that a disruption in the balance between these metabolites and their transmission may play a role in the pathophysiology of OCD., (© 2023. BioMed Central Ltd., part of Springer Nature.)