Free intramuscular Mg2+ concentration calculated using both 31 P and 1 H NMRS-based pH in the skeletal muscle of Duchenne muscular dystrophy patients.

Early studies have demonstrated that (total) magnesium was decreased in skeletal muscle of Duchenne muscular dystrophy (DMD) patients. Free intramuscular Mg2+ can be derived from 31 P NMRS measurements. The value of free intramuscular magnesium concentration ([Mg2+ ]) is highly dependent on precise knowledge of intracellular pH, which is abnormally alkaline in dystrophic muscle, possibly due to an expanded interstitial space, potentially causing an underestimation of [Mg2+ ]. We have recently shown that intracellular pH can be derived using 1 H NMRS of carnosine. Our aim was to determine whether 31 P NMRS-based [Mg2+ ] is, in fact, abnormally low in DMD patients, taking advantage of the 1 H NMRS-based pH. A comparative analysis was, therefore, made between [Mg2+ ] values calculated with both 1 H and 31 P NMRS-based approaches to determine pH in 25 DMD patients, on a 3-T clinical NMR scanner. [Mg2+ ] was also assessed with 31 P NMRS only in (forearm or leg) skeletal muscle of 60 DMD patients and 63 age-matched controls. Additionally, phosphodiester levels as well as quantitative NMRI indices including water T2 , fat fraction, contractile cross-sectional area and one-year changes were evaluated. The main finding was that the significant difference in [Mg2+ ] between DMD patients and controls was preserved even when the intracellular pH determined with 1 H NMRS was similar in both groups. Consequently, we observed that [Mg2+ ] is significantly lower in DMD patients compared with controls in the larger database where only 31 P NMRS data were obtained. Significant yet weak correlations existed between [Mg2+ ] and PDE, water T2 and fat fraction. We concluded that low [Mg2+ ] is an actual finding in DMD, whether intracellular pH is normal or alkaline, and that it is a likely consequence of membrane leakiness. The response of Mg2+ to therapeutic treatment remains to be investigated in neuromuscular disorders. Free [Mg2+ ] determination with 31 P NMRS is highly dependent on a precise knowledge of intracellular pH. The pH of Duchenne muscular dystrophy (DMD) patients, as determined by 31 P NMRS, is abnormally alkaline. We have recently shown that intracellular pH could be determined using 1 H NMRS of carnosine, and that intracellular pH was alkaline in a proportion of, but not all, DMD patients with a 31 P NMRS-based alkaline pH. Taking advantage of this 1 H NMRS-based intracellular pH, we found that free intramuscular [Mg2+ ] is in fact abnormally low in DMD patients.

1 H NMRS of carnosine combined with 31 P NMRS to better characterize skeletal muscle pH dysregulation in Duchenne muscular dystrophy.

In recent years, quantitative nuclear magnetic resonance imaging and spectroscopy (NMRI and NMRS) have been used more systematically as outcome measures in natural history and clinical trial studies for Duchenne muscular dystrophy (DMD). Whereas most of these studies have emphasized the evaluation of the fat fraction as an assessment for disease severity, less focus has been placed on metabolic indices measured by NMRS. 31 P NMRS in DMD reveals an alkaline inorganic phosphate (Pi ) pool, originating from either leaky dystrophic myocytes or an increased interstitial space. 1 H NMRS, exploiting the pH-sensitive proton resonances of carnosine, an intracellular dipeptide, was used to distinguish between these two hypotheses. NMR data were obtained in 23 patients with DMD and 14 healthy subjects on a 3-T clinical NMR system. Both 31 P and 1 H NMRS data were acquired at the level of the gastrocnemius medialis muscle. A multi-slice multi-echo imaging acquisition was performed for the determination of water T2 and fat fraction in the same region of interest. Whereas nearly all patients with DMD showed an elevated pH compared with healthy controls when using 31 P NMRS, 1 H NMRS-determined pH was not systematically increased. As expected, the carnosine-based intracellular pH was never found to be alkaline in the absence of a concurrent Pi -based pH elevation. In addition, abnormal intracellular pH, based on carnosine, was never associated with normal water T2 values. We conclude that, in one group of patients, both 1 H and 31 P NMRS showed an alkaline pH, originating from the intracellular compartment and reflecting ionic dysregulation in dystrophic myocytes. In the other patients with DMD, intracellular pH was normal, but an alkaline Pi pool was still present, suggesting an extracellular origin, probably revealing an expanded interstitial volume fraction, often associated with fibrotic changes. The data demonstrate that 1 H NMRS could serve as a biomarker to assess the normalization of intramyocytic pH and sarcolemmal permeability following therapy inducing dystrophin expression in patients with DMD.

Carbones - A Classification on the Magnetic Criterion.

Carbones (carbodiphosphoranes, bent allenes and chalcogen-stabilized carbones) bear the same resonance contributor X+ -C2- -Y+ (X+ , Y+ =PR3 + , CR2 + , SR2 + , SeR2 + , S+ R2 =NR) and exhibit unique bonding and donating properties at the central carbon atom. A classification is given on basis of both the geometry and the magnetic properties (13 C chemical shift of the central carbon atom and the spatial magnetic properties, through-space NMR shieldings (TS NMRSs), actually the anisotropy effect or the ring current effect of aromatic species). TS NMRS values have been calculated using the GIAO perturbation method employing the nucleus independent chemical shift (NICS) concept and the results visualized as iso-chemical-shielding surfaces (ICSS) of various size and direction. The synergy of geometry (linear or bent, orthogonal or twisted structures) and NMR characteristics (extend of the high field shift of the central carbon atom, anisotropy effect of the allene-like C=C double bonds or the ball-like anisotropy effect of carbone-like central carbon atom) provides a comprehensive picture of the dominating resonance contributor.

Self-learning sliding mode control based on adaptive dynamic programming for nonholonomic mobile robots.

This paper proposes a self-learning sliding mode control (SlSMC) strategy with stability guarantee for the trajectory tracking of nonholonomic mobile robots (NMRs) under matched uncertainties, which improves the control performance of NMRs by optimizing the reaching law and the sliding mode surface of SMC as well as retaining the finite-time convergence and the robustness to uncertainties. In the presence of adverse factors such as skidding, slipping and environmental noise, the kinematic model of NMRs is reconstructed and an integral terminal sliding mode controller is designed for the trajectory tracking of NMRs. Then, based on the sliding mode controller, the proposed control strategy formulates the optimization of the SMC's reaching law and the sliding mode surface under stability constraints as two asynchronous optimal control problems with control constraints. Meanwhile, an online continuous-time receding-horizon optimization mechanism based on an actor-critic algorithm is proposed to solve the optimal problems asynchronously and improve online learning efficiency. The stability and the convergence of the proposed strategy are validated both in theory and simulations. Furthermore, extensive contrastive simulation results illustrate that the proposed receding horizon learning-based control strategy outperforms three recent methods in control performance. Finally, experiments of the proposed self-learning SMC strategy are carried out based on a real intelligent vehicle, and the experimental results also verify that the proposed method can meet the actual control needs of NMRs.

Dysregulated Alanine as a Potential Predictive Marker of Glioma-An Insight from Untargeted HRMAS-NMR and Machine Learning Data.

Metabolic alterations play a crucial role in glioma development and progression and can be detected even before the appearance of the fatal phenotype. We have compared the circulating metabolic fingerprints of glioma patients versus healthy controls, for the first time, in a quest to identify a panel of small, dysregulated metabolites with potential to serve as a predictive and/or diagnostic marker in the clinical settings. High-resolution magic angle spinning nuclear magnetic resonance spectroscopy (HRMAS-NMR) was used for untargeted metabolomics and data acquisition followed by a machine learning (ML) approach for the analyses of large metabolic datasets. Cross-validation of ML predicted NMR spectral features was done by statistical methods (Wilcoxon-test) using JMP-pro16 software. Alanine was identified as the most critical metabolite with potential to detect glioma with precision of 1.0, recall of 0.96, and F1 measure of 0.98. The top 10 metabolites identified for glioma detection included alanine, glutamine, valine, methionine, N-acetylaspartate (NAA), γ-aminobutyric acid (GABA), serine, α-glucose, lactate, and arginine. We achieved 100% accuracy for the detection of glioma using ML algorithms, extra tree classifier, and random forest, and 98% accuracy with logistic regression. Classification of glioma in low and high grades was done with 86% accuracy using logistic regression model, and with 83% and 79% accuracy using extra tree classifier and random forest, respectively. The predictive accuracy of our ML model is superior to any of the previously reported algorithms, used in tissue- or liquid biopsy-based metabolic studies. The identified top metabolites can be targeted to develop early diagnostic methods as well as to plan personalized treatment strategies.

Relationship between markers of disease activity and progression in skeletal muscle of GNE myopathy patients using quantitative nuclear magnetic resonance imaging and 31P nuclear magnetic resonance spectroscopy.

BACKGROUND: Quantitative nuclear magnetic resonance imaging (NMRI) is an objective and precise outcome measure for evaluating disease progression in neuromuscular disorders. We aimed to investigate predictive 'disease activity' NMR indices, including water T2 and 31P NMR spectroscopy (NMRS), and its relation to NMR markers of 'disease progression', such as the changes in fat fraction (ΔFat%) and contractile cross-sectional area (ΔcCSA), in GNE myopathy (GNEM) patients. METHODS: NMR was performed on a 3T clinical scanner, at baseline and at a 1-year interval, in 10 GNEM patients and 29 age-matched controls. Dixon-based fat-water imaging and water T2 mapping were acquired in legs and thighs, and in the dominant forearm. 31P NMRS was performed at the level of quadriceps and hamstring. Water T2 and 31P NMRS indices were determined for all muscle groups and visits. Correlations were performed with 'disease progression' indices ΔFat%, ΔcCSA and the muscle fat transformation rate (Rmuscle_transf). RESULTS: In quadriceps, known to be relatively preserved in GNEM, water T2 at baseline was significantly higher compared to controls, and correlated strongly with the one-year evolution of Fat% and cCSA and Rmuscle_transf. Various 31P NMRS indices showed significant differences in quadriceps and hamstring compared to controls and correlations existed between these indices and ΔFat%, ΔcCSA and Rmuscle_transf. CONCLUSIONS: This study demonstrates that disease activity indices such as water T2 and 31P NMRS may predict disease progression in skeletal muscles of GNEM patients, and suggests that these measures may be considered to be valuable surrogate endpoints in the assessment of GNEM disease progression.

Serum metabolite profiles of habitual diet: evaluation by 1H-nuclear magnetic resonance analysis.

BACKGROUND: Objective and reliable methods to measure dietary exposure and prove associations and causation between diet and health are desirable. OBJECTIVE: The aim of this study was to investigate if 1H-nuclear magnetic resonance (1H-NMR) analysis of serum samples may be used as an objective method to discriminate vegan, vegetarian, and omnivore diets. Specifically, the aim was to identify a metabolite pattern that separated meat-eaters from non-meat-eaters and vegans from nonvegans. METHODS: Healthy volunteers (45 men and 75 women) complying with habitual vegan (n = 43), vegetarian (n = 24 + vegetarians adding fish n = 13), or omnivore (n = 40) diets were enrolled in the study. Data were collected on clinical phenotype, body composition, lifestyle including a food-frequency questionnaire (FFQ), and a 4-d weighed food diary. Serum samples were analyzed by routine clinical test and for metabolites by 1H-NMR spectroscopy. NMR data were nonnormalized, UV-scaled, and analyzed with multivariate data analysis [principal component analysis, orthogonal projections to latent structures (OPLS) and OPLS with discriminant analysis]. In the multivariate analysis volunteers were assigned as meat-eaters (omnivores), non-meat-eaters (vegans and vegetarians), vegans, or nonvegans (lacto-ovo-vegetarians, vegetarians adding fish, and omnivores). Metabolites were identified by line-fitting of 1D 1H-NMR spectra and the use of statistical total correlation spectroscopy. RESULTS: Although many metabolites differ in concentration between men and women as well as by age, body mass index, and body composition, it was possible to correctly classify 97.5% of the meat-eaters compared with non-meat-eaters and 92.5% of the vegans compared with nonvegans. The branched-chain amino acids, creatine, lysine, 2-aminobutyrate, glutamine, glycine, trimethylamine, and 1 unidentified metabolite were among the most important metabolites in the discriminating patterns in relation to intake of both meat and other animal products. CONCLUSIONS: 1H-NMR serum metabolomics appears to be a possible objective tool to identify and predict habitual intake of meat and other animal products in healthy subjects. These results should be confirmed in larger cohort studies or intervention trials. This trial was registered at clinicaltrials.gov as NCT02039609.

The Role of Sodium in Diabetic Cardiomyopathy.

Cardiovascular complications are the major cause of mortality and morbidity in diabetic patients. The changes in myocardial structure and function associated with diabetes are collectively called diabetic cardiomyopathy. Numerous molecular mechanisms have been proposed that could contribute to the development of diabetic cardiomyopathy and have been studied in various animal models of type 1 or type 2 diabetes. The current review focuses on the role of sodium (Na+) in diabetic cardiomyopathy and provides unique data on the linkage between Na+ flux and energy metabolism, studied with non-invasive 23Na, and 31P-NMR spectroscopy, polarography, and mass spectroscopy. 23Na NMR studies allow determination of the intracellular and extracellular Na+ pools by splitting the total Na+ peak into two resonances after the addition of a shift reagent to the perfusate. Using this technology, we found that intracellular Na+ is approximately two times higher in diabetic cardiomyocytes than in control possibly due to combined changes in the activity of Na+-K+ pump, Na+/H+ exchanger 1 (NHE1) and Na+-glucose cotransporter. We hypothesized that the increase in Na+ activates the mitochondrial membrane Na+/Ca2+ exchanger, which leads to a loss of intramitochondrial Ca2+, with a subsequent alteration in mitochondrial bioenergetics and function. Using isolated mitochondria, we showed that the addition of Na+ (1-10 mM) led to a dose-dependent decrease in oxidative phosphorylation and that this effect was reversed by providing extramitochondrial Ca2+ or by inhibiting the mitochondrial Na+/Ca2+ exchanger with diltiazem. Similar experiments with 31P-NMR in isolated superfused mitochondria embedded in agarose beads showed that Na+ (3-30 mM) led to significantly decreased ATP levels and that this effect was stronger in diabetic rats. These data suggest that in diabetic cardiomyocytes, increased Na+ leads to abnormalities in oxidative phosphorylation and a subsequent decrease in ATP levels. In support of these data, using 31P-NMR, we showed that the baseline ß-ATP and phosphocreatine (PCr) were lower in diabetic cardiomyocytes than in control, suggesting that diabetic cardiomyocytes have depressed bioenergetic function. Thus, both altered intracellular Na+ levels and bioenergetics and their interactions may significantly contribute to the pathology of diabetic cardiomyopathy.

Neurochemical Profile Quantification of Regional Adult Mice Brain Using: ex vivo 1H High-Resolution Magic Angle Spinning NMR Spectroscopy / 의학물리

The purpose of this study is to quantitate regional neurochemical profile of regional normal adult mice brain and assess regional metabolic differences by using ex vivo 1H high-resolution magic angle spinning nuclear magnetic resonance spectroscopy (1H HR-MAS NMRS). The animals were matched in sex and age. The collected brain tissue included frontal cortex, temporal cortex, thalamus, and hippocampus. Quantitative 1D spectra were acquired on 40 samples with the CPMG pulse sequence (8 kHz spectral window, TR/TE = 5500/2.2 ms, NEX = 128, scan time: 17 min 20 sec). The mass of brain tissue and D2O+TSP solvent were 8~14 mg and 7~13 mg. A total of 16 metabolites were quantified as follow: Acet, NAA, NAAG, tCr, Cr, tCho, Cho, GPC + PC, mIns, Lac, GABA, Glu, Gln, Tau and Ala. As a results, Acet, Cho, NAA, NAAG and mIns were showed significantly different aspects on frontal cortex, hippocampus, temporal cortex and thalamus respectively. The present study demonstrated that absolute metabolite concentrations were significantly different among four brain regions of adult mice. Our finding might be helpful to investigate brain metabolism of neuro-disease in animal model.

Measurement and Assessment of Absolute Quantification from in Vitro Canine Brain Metabolites Using 500 MHz Proton Nuclear Magnetic Resonance Spectroscopy: Preliminary Results

The purpose of this study was to confirm the exactitude of in vitro nuclear magnetic resonance spectroscopy (NMRS) and to complement the defect of in vivo NMRS. It has been difficult to understand the metabolism of a cerebellum using in vivo NMRS owing to the generated inhomogeneity of magnetic fields (B0 and B1 field) by the complexity of the cerebellum structure. Thus, this study tried to more exactly analyze the metabolism of a canine cerebellum using the cell extraction and high resolution NMRS. In order to conduct the absolute metabolic quantification in a canine cerebellum, the spectrum of our phantom included in various brain metabolites (i.e., NAA, Cr, Cho, Ins, Lac, GABA, Glu, Gln, Tau and Ala) was obtained. The canine cerebellum tissue was extracted using the methanol-chloroform water extraction (M/C extraction) and one group was filtered and the other group was not under extract processing. Finally, NMRS of a phantom solution and two extract solution (90% D2O) was progressed using a 500MHz (11.4 T) NMR machine. Filtering a solution of the tissue extract increased the signal to noise ratio (SNR). The metabolic concentrations of a canine cerebellum were more close to rat's metabolic concentration than human's metabolic concentration. The present study demonstrates the absolute quantification technique in vitro high resolution NMRS with tissue extraction as the method to accurately measure metabolite concentration.