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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.)

Proton magnetic resonance spectroscopic imaging ( 1 H-MRSI) is a powerful tool that enables the multidimensional non-invasive mapping of the neurochemical profile at high resolution over the entire brain. The constant demand for higher spatial resolution in 1 H-MRSI has led to increased interest in post-processing-based denoising methods aimed at reducing noise variance. The aim of the present study was to implement two noise-reduction techniques, Marchenko-Pastur principal component analysis (MP-PCA) based denoising and low-rank total generalized variation (LR-TGV) reconstruction, and to test their potential with and impact on preclinical 14.1 T fast in vivo 1 H-FID-MRSI datasets. Since there is no known ground truth for in vivo metabolite maps, additional evaluations of the performance of both noise-reduction strategies were conducted using Monte Carlo simulations. Results showed that both denoising techniques increased the apparent signal-to-noise ratio (SNR) while preserving noise properties in each spectrum for both in vivo and Monte Carlo datasets. Relative metabolite concentrations were not significantly altered by either method and brain regional differences were preserved in both synthetic and in vivo datasets. Increased precision of metabolite estimates was observed for the two methods, with inconsistencies noted for lower-concentration metabolites. Our study provided a framework for how to evaluate the performance of MP-PCA and LR-TGV methods for preclinical 1 H-FID MRSI data at 14.1 T. While gains in apparent SNR and precision were observed, concentration estimations ought to be treated with care, especially for low-concentration metabolites., (© 2024 The Author(s). NMR in Biomedicine published by John Wiley & Sons Ltd.)

Mitragyna speciosa is a perennial plant native to Asia, well known for its psychoactive properties. Its major alkaloid mitragynine is known to have sedative and euphoric effects. Hence, the plant has been a subject of abuse, leading to addiction, necessitating efficient analytical methods to detect its psychoactive constituents. However, current chromatography-based methods for detecting the alkaloids are time consuming and costly. Quantitative nuclear magnetic resonance (qNMR) spectroscopy emerges as a promising alternative due to its nondestructive nature, structural insights, and short analysis time. Hence, a rapid and precise qNMR method was developed to quantify selected major psychoactive alkaloids in various parts of M. speciosa. Mitragynine, specioliatine, and speciogynine were quantified in relation to the integral value of the -OCH 3 groups of the alkaloids and the internal standard 1,4-dinitrobenzene. The precision and reproducibility of the method gave a relative standard deviation (RSD) of 2%, demonstrating the reliability of the method. In addition, the method showed excellent specificity, sensitivity, high linearity range (R 2  = 0.999), and limits of detection (LOD) and quantification (LOQ) values. The analysis revealed that the red-veined M. speciosa leaves contained higher levels of mitragynine (32.34 mg/g), specioliatine (16.84 mg/g) and speciogynine (7.69 mg/g) compared to the green-veined leaves, stem bark, or fruits., (© 2024 John Wiley & Sons Ltd.)

Proton MRS is used clinically to collect localized, quantitative metabolic data from living tissues. However, the presence of baselines in the spectra complicates accurate MRS data quantification. The occurrence of baselines is not specific to short-echo-time MRS data. In short-echo-time MRS, the baseline consists typically of a dominating macromolecular (MM) part, and can, depending on B 0 shimming, poor voxel placement, and/or localization sequences, also contain broad water and lipid resonance components, indicated by broad components (BCs). In long-echo-time MRS, the MM part is usually much smaller, but BCs may still be present. The sum of MM and BCs is denoted by the baseline. Many algorithms have been proposed over the years to tackle these artefacts. A first approach is to identify the baseline itself in a preprocessing step, and a second approach is to model the baseline in the quantification of the MRS data themselves. This paper gives an overview of baseline handling algorithms and also proposes a new algorithm for baseline correction. A subset of suitable baseline removal algorithms were tested on in vivo MRSI data (semi-LASER at T E  = 40 ms) and compared with the new algorithm. The baselines in all datasets were removed using the different methods and subsequently fitted using spectrIm-QMRS with a TDFDFit fitting model that contained only a metabolite basis set and lacked a baseline model. The same spectra were also fitted using a spectrIm-QMRS model that explicitly models the metabolites and the baseline of the spectrum. The quantification results of the latter quantification were regarded as ground truth. The fit quality number (FQN) was used to assess baseline removal effectiveness, and correlations between metabolite peak areas and ground truth models were also examined. The results show a competitive performance of our new proposed algorithm, underscoring its automatic approach and efficiency. Nevertheless, none of the tested baseline correction methods achieved FQNs as good as the ground truth model. All separately applied baseline correction methods introduce a bias in the observed metabolite peak areas. We conclude that all baseline correction methods tested, when applied as a separate preprocessing step, yield poorer FQNs and biased quantification results. While they may enhance visual display, they are not advisable for use before spectral fitting., (© 2024 John Wiley & Sons 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.)

Prostate cancer continues to be a prominent health concern for men globally. Current screening techniques, primarily the prostate-specific antigen (PSA) test and digital rectal examination (DRE), possess inherent limitations, with prostate biopsy being the definitive diagnostic procedure. The invasive nature of the biopsy and other drawbacks of current screening tests create the need for non-invasive and more accurate diagnostic methods. This study utilized 1 H-NMR (Proton Nuclear Magnetic Resonance) based serum metabolomics to differentiate between prostate cancer (PCa) and benign prostatic hyperplasia (BPH). Serum samples from 40 PCa and 41 BPH patients were analysed using 1 H-NMR spectroscopy. PepsNMR was utilized for preprocessing the raw NMR data, and the binned spectra were examined for patterns distinguishing PCa and BPH. Principal component analysis (PCA) showed a moderate separation between PCa and BPH, highlighting the distinct metabolic profiles of both conditions. A logistic regression model was then developed, which demonstrated good performance in distinguishing between the two conditions. The results showed significant variance in multiple metabolites between PCa and BPH, such as isovaleric acid, ethylmalonic acid, formate, and glutamic acid. This research underlines the potential of 1 H-NMR-based serum metabolomics as a promising tool for improved prostate cancer screening, offering an alternative to the limitations of current screening methods.

Background: Multiple sclerosis (MS) is an inflammatory demyelinating disease with neurodegenerative features causing risk for neurologic irreversible disability over time. Examination of normal-appearing white matter (NAWM) changes in MS by proton magnetic resonance spectroscopy (1H-MRS), may detect diffuse white matter pathology that is associated with neurodegeneration., Methods: In this observational study of in total twenty-six patients with MS, starting treatment with dimethyl fumarate (DMF), we measured the absolute concentration of metabolites in periventricular NAWM using 1H-MRS at baseline and after one and three years of treatment. Metabolite concentrations were analyzed both cross-sectionally, in relation to 10 controls and longitudinally in relation to disease activity., Results: Patients with MS had higher concentrations of myo-inositol (mIns) in NAWM at baseline compared with controls (mean 5.98 ± 1.37 (SD) and 4.32 ± 1.16 (SD), p<0.01, independent samples t-test). The disease duration was inversely correlated with concentrations of total N-acetylaspartate and N-acetylaspartylglutamate (tNA) (r = -0.62, p<0.01) in NAWM as well as positively to the ratio of mIns and tNA (r = 0.51, p = 0.03). Metabolite concentrations during one-year (n = 19) and three-years (n = 11) follow-up were generally stable. The dropouts were caused by treatment switch after one year, mainly due to new MRI activity. Cross-sectional analyses showed that there was an inverse correlation between concentrations of tNA and mIns at both baseline and at 1 and 3-years follow-up (r = -0.44 to -0.65, p = 0.04 to 0.004). Metabolite concentrations were stable during 1-year follow-up independently of disease activity., Conclusions: Higher concentrations of the astrogliosis marker mIns in MS compared to controls, the inverse relation between MS disease duration and the neuroaxonal integrity marker tNA, as well as the consistent inverse relation between these two metabolites during follow-up, showed that non-lesional white matter pathology is present in this cohort of MS patients in early disease stages. However, metabolite concentrations during follow-up were generally stable and did not reflect differences in disease activity among patients., Competing Interests: AT, KS, YL and PL report no competing interests. JM has received honoraria for Advisory boards for Sanofi Genzyme and Merck, and lecture honorarium from Merck., (Copyright: © 2024 Tisell et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

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.)

Magnetic Resonance Spectroscopic Imaging (MRSI) is a powerful technique that can map the metabolic profile in the brain non-invasively. Extracranial lipid contamination and insufficient B 0 homogeneity however hampers robustness, and as a result has hindered widespread use of MRSI in clinical and research settings. Over the last six years we have developed highly effective extracranial lipid suppression methods with a second order gradient insert (ECLIPSE) utilizing inner volume selection (IVS) and outer volume suppression (OVS) methods. While ECLIPSE provides > 100-fold in lipid suppression with modest radio frequency (RF) power requirements and immunity to B 1 + field variations, axial coverage is reduced for non-elliptical head shapes. In this work we detail the design, construction, and utility of MC-ECLIPSE, a pulsed second order gradient coil with Z2 and X2Y2 fields, combined with a 54-channel multi-coil (MC) array. The MC-ECLIPSE platform allows arbitrary region of interest (ROI) shaped OVS for full-axial slice coverage, in addition to MC-based B 0 field shimming, for robust human brain proton MRSI. In vivo experiments demonstrate that MC-ECLIPSE allows axial brain coverage of 92-95 % is achieved following arbitrary ROI shaped OVS for various head shapes. The standard deviation (SD) of the residual B 0 field following SH2 and MC shimming were 25 ± 9 Hz and 18 ± 8 Hz over a 5 cm slab, and 18 ± 5 Hz and 14 ± 6 Hz over a 1.5 cm slab, respectively. These results demonstrate that B 0 magnetic field shimming with the MC array supersedes second order harmonic capabilities available on standard MRI systems for both restricted and large ROIs. Furthermore, MC based B 0 shimming provides comparable shimming performance to an unrestricted SH5 shim set for both restricted, and 5-cm slab shim challenges. Phantom experiments demonstrate the high level of localization performance achievable with MC-ECLIPSE, with ROI edge chemical shift displacements ranging from 1-3 mm with a median value of 2 mm, and transition width metrics ranging from 1-2.5 mm throughout the ROI edge. Furthermore, MC based B 0 shimming is comparable to performance following a full set of unrestricted spherical harmonic fields up to order 5. Short echo time MRSI and GABA-edited MRSI acquisitions in the human brain following MC-shimming and arbitrary ROI shaping demonstrate full-axial slice coverage and extracranial lipid artifact free spectra. MC-ECLIPSE allows full-axial coverage and robust MRSI acquisitions, while allowing interrogation of cortical tissue proximal to the skull, which has significant value in a wide range of neurological and psychiatric conditions., Competing Interests: Declaration of competing interest The authors have no competing interests (financial or personal) to disclose., (Copyright © 2024. Published by Elsevier Inc.)

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.)

Background: The familial hypercholesterolemia (FH) diagnosis is based on clinical and genetic criteria. A relevant proportion of FH patients fulfilling the criteria for definite FH have negative genetic testing. Increasing the identification of true genetic-based FH is a clinical challenge. Deepening the analysis of lipoprotein alterations could help increase the yield of genetic testing. We evaluated whether the number, size, and composition of lipoproteins assessed by 1H-NMR could increase the identification of FH patients with pathogenic gene variants., Methods: We studied 294 clinically definite FH patients, 222 (75.5%) with positive genetic testing, as the discovery cohort. As an external validation cohort, we studied 88 children with FH, 72 (81%) with positive genetic testing. The advanced lipoprotein test based on 1H-NMR (Liposcale®) was performed at baseline after a lipid-lowering drug washout of at least 6 weeks. The association of variables with genetic variants was evaluated by random forest and logistic regression. Areas under the curve (AUCs) were calculated. A predictive formula was developed and applied to the validation cohort., Results: A formula derived from nuclear magnetic resonance (NMR) lipoprotein analyses improved the identification of genetically positive FH patients beyond low-density lipoprotein (LDL)-cholesterol levels (AUC = 0.87). The parameters contributing the most to the identification formula were LDL particle number, high-density lipoprotein size, and remnant cholesterol. The formula also increases the classification of FH children with a pathogenic genetic variation., Conclusion: NMR lipoprotein profile analysis identifies differences beyond standard lipid parameters that help identify FH with a positive pathogenic gene variant, increasing the yield of genetic testing in FH patients., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

In this work, the HR MAS NMR (high-resolution magic-angle spinning nuclear magnetic resonance) spectroscopy technique was combined with standard histological examinations to investigate the metabolic features of high-grade serous ovarian cancer (HGSOC) with a special focus on the relation between a metabolic profile and a cancer cell fraction. The studied group consisted of 44 patients with HGSOC and 18 patients with benign ovarian tumors. Normal ovarian tissue was also excised from 13 control patients. The metabolic profiles of 138 tissue specimens were acquired on a Bruker Avance III 400 MHz spectrometer. The NMR spectra of the HGSOC samples could be discriminated from those acquired from the non-transformed tissue and were shown to depend on tumor purity. The most important features that differentiate the samples with a high fraction of cancer cells from the samples containing mainly fibrotic stroma are the increased intensities in the spectral regions corresponding to phosphocholine/glycerophosphocholine, phosphoethanolamine/serine, threonine, uridine nucleotides and/or uridine diphosphate (UDP) nucleotide sugars. Higher levels of glutamine, glutamate, acetate, lysine, alanine, leucine and isoleucine were detected in the desmoplastic stroma within the HGSOC lesions compared to the stroma of benign tumors. The HR MAS NMR analysis of the metabolic composition of the epithelial and stromal compartments within HGSOC contributes to a better understanding of the disease's biology.

This study aimed to evaluate the dose-dependent brain temperature effects of transcranial photobiomodulation (t-PBM). Thirty adult subjects with major depressive disorder were randomized to three t-PBM sessions with different doses (low: 50 mW/cm 2 , medium: 300 mW/cm 2 , high: 850 mW/cm 2 ) and a sham treatment. The low and medium doses were administered in continuous wave mode, while the high dose was administered in pulsed wave mode. A 3T MRI scanner was used to perform proton magnetic resonance spectroscopy ( 1 H-MRS). A voxel with a volume of 30 × 30 × 15 mm 3 was placed on the left prefrontal region. Brain temperature (°C) was derived by analyzing 1 H-MRS spectrum chemical shift differences between the water (~ 4.7 ppm) and N-acetyl aspartate (NAA) (~ 2.01 ppm) peaks. After quality control of the data, the following group numbers were available for both pre- and post-temperature estimations: sham (n = 10), low (n = 11), medium (n = 10), and high (n = 8). We did not detect significant temperature differences for any t-PBM-active or sham groups post-irradiation (p-value range = 0.105 and 0.781). We also tested for potential differences in the pre-post variability of brain temperature in each group. As for t-PBM active groups, the lowest fluctuation (variance) was observed for the medium dose (σ 2  = 0.29), followed by the low dose (σ 2  = 0.47), and the highest fluctuation was for the high dose (σ 2  = 0.67). t-PBM sham condition showed the overall lowest fluctuation (σ 2  = 0.11). Our 1 H-MRS thermometry results showed no significant brain temperature elevations during t-PBM administration., (© 2024. The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.)

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.)

Objective: Many patients with long COVID experience neurological and psychological symptoms. Signal abnormalities on MR images in the corpus callosum have been reported. Knowledge about the metabolic profile in the splenium of the corpus callosum (CCS) may contribute to a better understanding of the pathophysiology of long COVID., Materials and Methods: Eighty-one subjects underwent proton MR spectroscopy examination. The metabolic concentrations of total N-acetylaspartate (NAA), choline-containing compounds (Cho), total creatine (Cr), myo-inositol (mI), and NAA/Cho in the CCS were statistically compared in the group of patients containing 58 subjects with positive IgG COVID-19 antibodies or positive SARS-CoV-2 qPCR test at least two months before the MR and the group of healthy controls containing 23 subjects with negative IgG antibodies., Results: An age-dependent effect of SARS-CoV-2 on Cho concentrations in the CCS has been observed. Considering the subjective threshold of age = 40 years, older patients showed significantly increased Cho concentrations in the CCS than older healthy controls (p = 0.02). NAA, Cr, and mI were unchanged. All metabolite concentrations in the CCS of younger post-COVID-19 patients remained unaffected by SARS-CoV-2. Cho did not show any difference between symptomatic and asymptomatic patients (p = 0.91)., Discussion: Our results suggest that SARS-CoV-2 disproportionately increases Cho concentration in the CCS among older post-COVID-19 patients compared to younger ones. The observed changes in Cho may be related to the microstructural reorganization in the CCS also reported in diffusion measurements rather than increased membrane turnover. These changes do not seem to be related to neuropsychological problems of the post-COVID-19 patients. Further metabolic studies are recommended to confirm these observations., (© 2024. The Author(s).)

Achieving high-resolution and high signal-to-noise ratio (SNR) in vivo metabolic imaging via fast magnetic resonance spectroscopic imaging (MRSI) has been a longstanding challenge. This study combines the methods of relaxation enhancement (RE) and subspace imaging for the first time, enabling high-resolution and high-SNR in vivo MRSI of rodent brains at 9.4 T. Specifically, an RE-based chemical shift imaging sequence, which combines a frequency-selective pulse to excite only the metabolite frequencies with minimum perturbation of the water spins and a pair of adiabatic pulses to spatially localize the slice of interest, is designed and evaluated in vivo. This strategy effectively shortens the apparent T 1 of metabolites, thereby increasing the SNR during relatively short repetition time ((T R ) compared with acquisitions with only spatially selective wideband excitations, and does not require water suppression. The SNR was further enhanced via a state-of-the-art subspace reconstruction method. A novel subspace learning strategy tailored for 9.4 T and RE acquisitions is developed. In vivo, high-resolution (e.g., voxel size of 0.6 × 0.6 × 1.5 mm 3 ) MRSI of both healthy mouse brains and a glioma-bearing mouse brain in 12.5 min has been demonstrated., (© 2024 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.)

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.)

In vivo proton ( 1 H) magnetic resonance spectroscopy (MRS) is a powerful non-invasive method that can measure Alzheimer's disease (AD)-related neuropathological alterations at the molecular level. AD biomarkers include amyloid-beta (Aβ) plaques and hyperphosphorylated tau neurofibrillary tangles. These biomarkers can be detected via postmortem analysis but also in living individuals through positron emission tomography (PET) or biofluid biomarkers of Aβ and tau. This review offers an overview of biochemical abnormalities detected by 1 H MRS within the biologically defined AD spectrum. It includes a summary of earlier studies that explored the association of 1 H MRS metabolites with biofluid, PET, and postmortem AD biomarkers and examined how apolipoprotein e 4 allele carrier status influences brain biochemistry. Studying these associations is crucial for understanding how AD pathology affects brain homeostasis throughout the AD continuum and may eventually facilitate the development of potential novel therapeutic approaches.

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.)

The antimicrobial effects of high hydrostatic pressure (HHP) treatments on chill-stored seafood are well-documented, while their impact on the metabolic profile of seafood, especially the metabolome of fish flesh, and remains underexplored. Addressing this gap, this study investigates the effects of HHP on the metabolome of chill-stored rose shrimp by conducting multivariate data analysis based on untargeted proton nuclear magnetic resonance observations. Vacuum-packed rose shrimp samples were subjected to HHP at 0, 400, 500, and 600 MPa for 10 min and then stored at 2-4°C. The microorganism analysis and metabolic analysis were carried out on days 1 and 14. HHP treatment effectively deactivated Lactobacillus spp., Escherichia coli, Pseudomonas spp., total Coliforms, and sulfite-reducing anaerobic bacteria. Consequently, HHP treatment significantly reduced the formation rate of decay-related metabolites, such as hypoxanthine, trimethylamine, and biogenic amines, which exhibited significant accumulation in untreated samples. Multivariate unsupervised analyses provided insights into the overall changes in the metabolite profile induced by HHP. Metabolic pathway analysis revealed several pathways underlying spoilage, including pyruvate metabolism, valine, leucine, and isoleucine biosynthesis, purine metabolism, methane metabolism, glycine, serine, and threonine metabolism, citrate cycle (TCA cycle), glycolysis/gluconeogenesis, alanine, aspartate, and glutamate metabolism, sulfur metabolism, pantothenate and CoA biosynthesis, glutathione metabolism, and glyoxylate and dicarboxylate metabolism. Importantly, these pathways underwent alterations due to the application of HHP, particularly at high-pressure levels. In summary, the results unveil the potential mechanisms of HHP effects on chill-stored rose shrimps., (© 2024 The Author(s). Journal of Food Science published by Wiley Periodicals LLC on behalf of Institute of Food Technologists.)

Purpose: This goal of this study was to optimize spectrally selective 1 H-MRS methods for large-volume acquisition of low-concentration metabolites with downfield resonances at 7 T and 3 T, with particular attention paid to detection of nicotinamide adenine dinucleotide (NAD + ) and tryptophan., Methods: Spectrally selective excitation was used to avoid magnetization-transfer effects with water, and various sinc pulses were compared with a band-selective, uniform response, pure-phase (E-BURP) pulse. Localization using a single-slice selective pulse was compared with voxel-based localization that used three orthogonal refocusing pulses, and low bandwidth refocusing pulses were used to take advantage of the chemical shift displacement of water. A technique for water sideband removal was added, and a method of coil channel combination for large volumes was introduced., Results: Proposed methods were compared qualitatively with previously reported techniques at 7 T. Sinc pulses resulted in reduced water signal excitation and improved spectral quality, with a symmetric, low bandwidth-time product pulse performing best. Single-slice localization allowed shorter TEs with large volumes, enhancing signal, whereas low-bandwidth slice-selective localization greatly reduced the observed water signal. Gradient cycling helped remove water sidebands, and frequency aligning and pruning individual channels narrowed spectral linewidths. High-quality brain spectra of NAD + and tryptophan are shown in 4 subjects at 3 T., Conclusion: Improved spectral quality with higher downfield signal, shorter TE, lower nuisance signal, reduced artifacts, and narrower peaks was realized at 7 T. These methodological improvements allowed for previously unachievable detection of NAD + and tryptophan in human brain at 3 T in under 5 min., (© 2024 The Author(s). Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

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.)

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.)

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).)