1H NMR Metabolomics Research Articles

Discrimination of serum samples of prostate cancer and benign prostatic hyperplasia with 1H-NMR metabolomics.

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 1H-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 1H-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 1H-NMR-based serum metabolomics as a promising tool for improved prostate cancer screening, offering an alternative to the limitations of current screening methods.

Metabolomic assessment of African snail (Achatina fulica) meal on growth performance of giant river prawn (Macrobrachium rosenbergii)

This study aimed to investigate the effects of replacing fishmeal (FM) with African giant snail (Achatina fulica) meal (SM) on the growth performance of giant river prawn (Macrobrachium rosenbergii), as well as to analyze the associated metabolomic changes. Six diets were formulated, replacing FM with SM at different inclusion levels ranging from 0 % to 100 %. Growth performance and feed conversion ratio of prawns fed diets with FM replaced by SM up to 80 % were not significantly different from control. In contrast, significantly decreased growth performance and higher feed conversion ratio (FCR) occurred with diets containing 100 % SM. To gain insights into the metabolic regulation of prawns fed different diets, a 1H NMR metabolomics approach was used to assess the metabolic changes in prawns fed diets containing 0 % and 80 % SM. The results revealed up-regulated metabolites significantly involved in several metabolic pathways, including alanine, aspartate, and glutamate metabolism; citrate cycle (TCA cycle); aminoacyl-tRNA biosynthesis; and valine, leucine, and isoleucine biosynthesis. These findings imply that including SM in the diet might modulate the regulation of muscle amino acids and tRNA synthesis, suggesting a potential impact on protein biosynthesis mechanisms. Additionally, alterations in the TCA cycle may reflect changes in carbon utilization, potentially contributing to the growth performance of giant river prawns when fishmeal is replaced with SM without adversely affecting their growth. In conclusion, this study demonstrated that SM could be a promising alternative protein source in aquafeed. The metabolomic approach provides valuable insights into the metabolic changes in prawns fed different diets, aiding in the development of more effective aquafeeds in the future. The study's limitations, such as the simplified diet formulation and the limited scope of the metabolomic analysis, were acknowledged and discussed, highlighting the need for further research to build upon these findings.

Identification of Potential Biomarkers and Metabolic Changes in the Serum of Breast Lump Patients Among Kelantanese Based on 1H NMR Metabolomics

This case-control study, conducted at the Hospital USM BestARi unit, aimed to identify the serum metabolic fingerprint among individuals with breast lumps and healthy controls, and to discover potential biomarkers. Serum samples from healthy controls, benign breast lump patients, and malignant breast lump patients were analyzed using proton nuclear magnetic resonance spectroscopy (1H NMR). A multivariate data analysis approach was employed, with the OPLS-DA and clustered heat map techniques effectively differentiating between the three groups. The study revealed significant metabolite variations across the groups and proposed D-glucose, glycerol, and glycine as potential biomarkers for breast cancer diagnosis. Metabolic pathways such as alanine, aspartate, glutamate metabolism, and glycine, serine, and threonine metabolism were implicated. The metabolomics approach coupled with multivariate analysis successfully identified key metabolites leading to group separation and suggested altered metabolic pathways. However, further research and integration with other ‘omics’ technologies are necessary for clinical translation.

Extended automated quantification algorithm (AQuA) for targeted 1H NMR metabolomics of highly complex samples: application to plant root exudates

IntroductionThe Automated Quantification Algorithm (AQuA) is a rapid and efficient method for targeted NMR-based metabolomics, currently optimised for blood plasma. AQuA quantifies metabolites from 1D-1H NMR spectra based on the height of only one signal per metabolite, which minimises the computational time and workload of the method without compromising the quantification accuracy.ObjectivesTo develop a fast and computationally efficient extension of AQuA for quantification of selected metabolites in highly complex samples, with minimal prior sample preparation. In particular, the method should be capable of handling interferences caused by broad background signals.MethodsAn automatic baseline correction function was combined with AQuA into an automated workflow, the extended AQuA, for quantification of metabolites in plant root exudate NMR spectra that contained broad background signals and baseline distortions. The approach was evaluated using simulations as well as a spike-in experiment in which known metabolite amounts were added to a complex sample matrix.ResultsThe extended AQuA enables accurate quantification of metabolites in 1D-1H NMR spectra with varying complexity. The method is very fast (< 1 s per spectrum) and can be fully automated.ConclusionsThe extended AQuA is an automated quantification method intended for 1D-1H NMR spectra containing broad background signals and baseline distortions. Although the method was developed for plant root exudates, it should be readily applicable to any NMR spectra displaying similar issues as it is purely computational and applied to NMR spectra post-acquisition.

Technical Report: A Comprehensive Comparison between Different Quantification Versions of Nightingale Health's 1H-NMR Metabolomics Platform.

1H-NMR metabolomics data is increasingly used to track health and disease. Nightingale Health, a major supplier of 1H-NMR metabolomics, has recently updated the quantification strategy to further align with clinical standards. Such updates, however, might influence backward replicability, particularly affecting studies with repeated measures. Using data from BBMRI-NL consortium (~28,000 samples from 28 cohorts), we compared Nightingale data, originally released in 2014 and 2016, with a re-quantified version released in 2020, of which both versions were based on the same NMR spectra. Apart from two discontinued and twenty-three new analytes, we generally observe a high concordance between quantification versions with 73 out of 222 (33%) analytes showing a mean ρ > 0.9 across all cohorts. Conversely, five analytes consistently showed lower Spearman's correlations (ρ < 0.7) between versions, namely acetoacetate, LDL-L, saturated fatty acids, S-HDL-C, and sphingomyelins. Furthermore, previously trained multi-analyte scores, such as MetaboAge or MetaboHealth, might be particularly sensitive to platform changes. Whereas MetaboHealth replicated well, the MetaboAge score had to be retrained due to use of discontinued analytes. Notably, both scores in the re-quantified data recapitulated mortality associations observed previously. Concluding, we urge caution in utilizing different platform versions to avoid mixing analytes, having different units, or simply being discontinued.

Application of 1H NMR metabolomics analysis to sparkling wines aged with different types of sugar added to the liqueur de dosage

Over the past decade, 1H NMR metabolomic studies have become increasingly popular in wine research since they can provide a chemical fingerprint with information regarding authenticity, geographical origin, vintage, and wine composition. Comparatively few 1H NMR-based studies have evaluated sparkling wines. In the present study, quantitative 1H NMR metabolomics was applied to assess the composition of finished traditional method (bottle-fermented) sparkling wines aged for 18-months in cellar conditions (14 °C, 70% relative humidity) following liqueur d′expedition (dosage) additions with six sugar types (glucose, fructose, sucrose derived from sugar beets and sugar cane, maltose, and MCR Sucraisin®) and a zero-dosage control. No systematic trends were observed when comparing the metabolite profile across sugar types, nor between the zero-dosage control and treatments with sugar additions. Multivariate statistical approaches using principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) did not effectively discriminate between dosage treatments nor wine age, while orthogonal projections to latent structures discriminant analysis (OPLS-DA) successfully discriminated between wines by age and was validated through permutation tests. This study presents the first application of 1H NMR metabolomics coupled with multivariate analysis to monitor the aging of sparkling wines.

Metabolomic Profiling of Second-Trimester Amniotic Fluid for Predicting Preterm Delivery: Insights from NMR Analysis.

Preterm delivery (PTD) is a notable pregnancy complication, affecting one out of every ten births. This study set out to investigate whether analyzing the metabolic composition of amniotic fluid (AF) collected from pregnant women during the second trimester of pregnancy could offer valuable insights into prematurity. The research employed 1H-NMR metabolomics to examine AF samples obtained from 17 women who gave birth prematurely (between 29+0 and 36+5 weeks of gestation) and 43 women who delivered at full term. The application of multivariate analysis revealed metabolites (dimethylglycine, glucose, myo-inositol, and succinate) that can serve as possible biomarkers for the prognosis and early diagnosis of preterm delivery. Additionally, pathway analysis unveiled the most critical metabolic pathways relevant to our research hypothesis. In summary, these findings suggest that the metabolic composition of AF in the second trimester can be a potential indicator for identifying biomarkers associated with the risk of PTD.

Hyperpolarized 1H and 13C NMR Spectroscopy in a Single Experiment for Metabolomics.

The application of NMR spectroscopy to complex mixture analysis and, in particular, to metabolomics is limited by the low sensitivity of NMR. We recently showed that dissolution dynamic nuclear polarization (d-DNP) could enhance the sensitivity of 13C NMR for complex metabolite mixtures, leading to the detection of highly sensitive 13C NMR fingerprints of complex samples such as plant extracts or urine. While such experiments provide heteronuclear spectra, which are complementary to conventional NMR, hyperpolarized 1H NMR spectra would also be highly useful, with improved limits of detection and compatibility with the existing metabolomics workflow and databases. In this technical note, we introduce an approach capable of recording both 1H and 13C hyperpolarized spectra of metabolite mixtures in a single experiment and on the same hyperpolarized sample. We investigate the analytical performance of this method in terms of sensitivity and repeatability, and then we show that it can be efficiently applied to a plant extract. Significant sensitivity enhancements in 1H NMR are reported with a repeatability suitable for metabolomics studies without compromising on the performance of hyperpolarized 13C NMR. This approach provides a way to perform both 1H and 13C hyperpolarized NMR metabolomics with unprecedented sensitivity and throughput.

Predictive Performance of 1 H-NMR Metabolomics-Derived Biomarkers of Bacterial Vaginosis.

1 H-NMR metabolomics-derived biomarkers maltose, acetate, formate, and lactate have excellent potential as predictive biomarkers for bacterial vaginosis with an area under curve of 0.97 (95% confidence interval, 0.88-1.00), sensitivity of 0.90, and specificity of 0.95.

1H NMR metabolomics techniques demonstrated the effectiveness of methoxy substituted 2-benzylidene-1-indanone, A1 and A2A Adenosine Receptor antagonists, in modulating glucose production in the liver of diabetic rats

The physiological function of the liver in the overall disposal of postprandial glucose is important in the management of diabetes. Our recent research showed that benzylidene indanone derivative 2-(3,4-dihydroxybenzylidene)-4-methoxy-2,3-dihydro-1H-inden-1-one (2-BI) showed antihyperglycemic activity, but its role in glucose homeostasis in the liver is unknown. 1H NMR metabolomics approach was used to unravel the effectiveness of 2-BI, on hepatic glucose production in fructose-streptozotocin (STZ) diabetics. Diabetes was induced in Sprague–Dawley rats using fructose-streptozotocin. Metabolites were extracted from the liver tissue and analyzed by 1H NMR spectroscopy. Pathway analysis was performed on the identified metabolites. The unsupervised principal components analysis score plot showed clear differentiation. The control group (NC) was clearly separated from the diabetic group (DBC) and was clustered near the treated diabetic groups (DBI and DGT). There is a significant (p < 0.01) increased level of 12 metabolites in diabetes rats that are crucial in liver glucose homeostasis. Treatment with 2-BI was able to lower the level of these metabolites. Detailed pathway analysis of the spiked metabolite levels shows an effect on the glycolysis/gluconeogenesis, butanoate, amino acid, nitrogen, and nucleotide (pyrimidine) metabolism. 2-BI reduced hyperglycemia in diabetic rats via the attenuation of hepatic glucose production and advancement of liver insulin sensitivity.

Anemarrhena asphodeloides Bunge total saponins ameliorate diabetic cardiomyopathy by modifying the PI3K/AKT/HIF-1α pathway to restore glycolytic metabolism

Ethnopharmacological relevanceBased on the theory of traditional Chinese medicine (TCM), diabetic cardiomyopathy (DCM) belongs to the category of "Xiaoke disease" according to the symptoms, and "stasis-heat" is the main pathogenesis of DCM. The Chinese medicine Anemarrhena asphodeloides Bunge (AAB), as a representative of heat-clearing and engendering fluid, is often used clinically in the treatment of DCM. Anemarrhena asphodeloides Bunge total saponins (RATS) are the main bioactive components of AAB, the modern pharmacologic effects of RATS are anti-inflammatory, hypoglycemic, and cardioprotective. However, the potential protective mechanisms of RATS against DCM remain largely undiscovered. Aim of the studyThe primary goal of this study was to explore the effect of RATS on DCM and its mechanism of action. Materials and methodsStreptozotocin and a high-fat diet were used to induce DCM in rats. UHPLC/Q-TOF-MS was used to determine the chemical components of RATS. The degenerative alterations and apoptotic cells in the heart were assessed by HE staining and TUNEL. Network pharmacology was used to anticipate the probable targets and important pathways of RATS. The alterations in metabolites and main metabolic pathways in heart tissue were discovered using 1 H-NMR metabolomics. Ultimately, immunohistochemistry was used to find critical pathway protein expression. ResultsFirst of all, UHPLC/Q-TOF-MS analysis showed that RATS contained 11 active ingredients. In animal experiments, we found that RATS lowered blood glucose and lipid levels in DCM rats, and alleviated cardiac pathological damage, and decreased cardiomyocyte apoptosis. Furthermore, the study found that RATS effectively reduced inflammatory factor release and the level of oxidative stress. Mechanistically, RATS downregulated the expression levels of PI3K, AKT, HIF-1α, LDHA, and GLUT4 proteins. Additionally, glycolysis was discovered to be a crucial pathway for RATS in the therapy of DCM. ConclusionsOur findings suggest that the protective effect of RATS on DCM may be attributed to the inhibition of the PI3K/AKT/HIF-1α pathway and the correction of glycolytic metabolism.

Grapevine shoots extract as an alternative to SO2 in rosé wines. A double approach: Classical measurements and 1H NMR metabolomics

The consumption of rosé wines has increased in the recent years, largely due to their attractive color and their simplicity, elegance, and freshness. However, rosé wines can easily oxidise, turning into an orange-brownish color, which leads its rejection by consumers. It is likely that alternatives to sulfur dioxide (SO2) in rosé wines have not yet been studied for this reason. The current work investigates the use of a natural stilbene extract, glutathione and combinations of both as possible alternatives to SO2 in rosé wines. The parameters selected for the evaluation of alternatives were fermentation kinetics, enological parameters related to quality, the main phenolic compounds, glutathione, grape reaction product, and amino acids and biogenic amines. Moreover, a 1H-NMR-based metabolomics study was carried out after 12 months of bottling. The results highlighted that stilbene extract inhibits malolactic fermentation, thereby preserving rosé wine quality. However, color-related parameters, phenolic compounds (malvidin 3-glucoside, caftaric and ferulic acids), glutathione, grape reaction product and amino acids were only slightly affected by the treatments. The 1H NMR targeted metabolomic study indicated that the stilbene treatment significantly affected the contents of threonine, myo-inositol, choline, arabinose and methanol in comparison to SO2 wines. The use of glutathione did not improve the quality of the rosé wines in any case (alone or in combination with the stilbene extract). We can conclude that stilbenes could be an alternative to SO2 to preserve the quality of rosé wines.

Non-invasive biomarkers for mild cognitive impairment and Alzheimer's disease

Alzheimer's disease is the most common type of dementia in the elderly. It is a progressive degenerative disorder that may begin to develop up to 15 years before clinical symptoms appear. The identification of early biomarkers is crucial to enable a prompt diagnosis and to start effective interventions. In this work, we conducted a metabolomic study using proton Nuclear Magnetic Resonance (1H NMR) spectroscopy in serum samples from patients with neuropathologically confirmed Alzheimer's disease (AD, n = 51), mild cognitive impairment (MCI, n = 27), and cognitively healthy controls (HC, n = 50) to search for metabolites that could be used as biomarkers. Patients and controls underwent yearly clinical follow-ups for up to six years. MCI group included samples from three subgroups of subjects with different disease progression rates. The first subgroup included subjects that remained clinically stable at the MCI stage during the period of study (stable MCI, S-MCI, n = 9). The second subgroup accounted for subjects which were diagnosed with MCI at the moment of blood extraction, but progressed to clinical dementia in subsequent years (MCI-to-dementia, MCI-D, n = 14). The last subgroup was composed of subjects that had been diagnosed as dementia for the first time at the moment of sample collection (incipient dementia, Incp-D, n = 4). Partial Least Square Discriminant Analysis (PLS-DA) models were developed. Three models were obtained, one to discriminate between AD and HC samples with high sensitivity (93.75%) and specificity (94.75%), another model to discriminate between AD and MCI samples (100% sensitivity and 82.35% specificity), and a last model to discriminate HC and MCI with lower sensitivity and specificity (67% and 50%). Differences within the MCI group were further studied in an attempt to determine those MCI subjects that could develop AD-type dementia in the future. The relative concentration of metabolites, and metabolic pathways were studied. Alterations in the pathways of alanine, aspartate and glutamate metabolism, pantothenate and CoA biosynthesis, and beta-alanine metabolism, were found when HC and MCI- D patients were compared. In contrast, no pathway was found disturbed in the comparison of S-MCI with HC groups. These results highlight the potential of 1H NMR metabolomics to support the diagnosis of dementia in a less invasive way, and set a starting point for the study of potential biomarkers to identify MCI or HC subjects at risk of developing AD in the future.

Integrated network analysis and metabolomics reveal the molecular mechanism of Yinchen Sini decoction in CCl4-induced acute liver injury.

Objective: Yinchen Sini decoction (YCSND), a traditional Chinese medicine (TCM) formula, plays a crucial role in the treatment of liver disease. However, the bioactive constituents and pharmacological mechanisms of action remain unclear. The present study aimed to reveal the molecular mechanism of YCSND in the treatment of acute liver injury (ALI) using integrated network analysis and metabolomics. Methods: Ultra-high-performance liquid chromatography coupled with Q-Exactive focus mass spectrum (UHPLC-QE-MS) was utilized to identify metabolites in YCSND, and high-performance liquid chromatography (HPLC) was applied to evaluate the quality of four botanical drugs in YCSND. Cell damage and ALI models in mice were established using CCl4. 1H-NMR metabolomics approach, along with histopathological observation using hematoxylin and eosin (H&E), biochemical measurements, and reverse transcription quantitative real-time PCR (RT-qPCR), was applied to evaluate the effect of YCSND on CCl4- induced ALI. Network analysis was conducted to predict the potential targets of YCSND in ALI. Result: Our results showed that 89 metabolites in YCSND were identified using UHPLC-QE-MS. YCSND protected against ALI by reducing the levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), and malondialdehyde (MDA) contents and increasing those of superoxide dismutase (SOD), and glutathione (GSH) both in vivo and in vitro. The 1H-NMRmetabolic pattern revealed that YCSND reversed CCl4-induced metabolic abnormalities in the liver. Additionally, the Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analysis identified five pathways related to liver injury, including the PI3K-AKT, MAPK, HIF-1, apoptosis, and TNF signaling pathways. Moreover, RT-qPCR showed YCSND regulated the inflammatory response (Tlr4, Il6, Tnfα, Nfκb1, Ptgs2, and Mmp9) and apoptosis (Bcl2, Caspase3, Bax, and Mapk3), and inhibited PI3K-AKT signaling pathway (Pi3k and Akt1). Combined network analysis and metabolomics showed a link between the key targets (Tlr4, Ptgs2, and Mmp9) and vital metabolites (choline, xanthine, lactate, and 3-hydroxybutyric acid) of YCSND in ALI. Conclusion: Overall, the results contribute to the understanding of the therapeutic effects of YCSND on ALI, and indicate that the integrated network analysis and metabolomics could be a powerful strategy to reveal the pharmacological effects of TCM.

Influence of Different Types, Utilization Times, and Volumes of Aging Barrels on the Metabolite Profile of Red Wine Revealed by 1H-NMR Metabolomics Approach.

It is well recognized that the aging process is a critical step in winemaking because it induces substantial chemical changes linked to the organoleptic properties and stability of the finished wines. Therefore, this study aimed to investigate the influence of different types, utilization times, and volumes of aging barrels on the metabolite profile of red wines, produced from Thai-grown Shiraz grapes, using a non-targeted proton nuclear magnetic resonance (1H-NMR) metabolomics approach. As a result, 37 non-volatile polar metabolites including alcohols, amino acids, organic acids, carbohydrates and low-molecular-weight phenolics were identified. Chemometric analysis allowed the discrimination of wine metabolite profiles associated with different types of aging containers (oak barrels vs. stainless-steel tanks), as well as the utilization times (2, 6 and >10 years old) and volumes (225, 500 and 2000 L) of the wooden barrels employed. Significant variations in the concentration of formate, fumarate, pyruvate, succinate, citrate, gallate, acetate, tyrosine, phenylalanine, histidine, γ-aminobutyrate, methionine and choline were statistically suggested as indicators accountable for the discrimination of samples aged under different conditions. These feature biomarkers could be applied to manipulate the use of aging containers to achieve the desired wine maturation profiles.

Peripheral Blood Serum NMR Metabolomics Is a Powerful Tool to Discriminate Benign and Malignant Ovarian Tumors.

Ovarian cancer is the major cause of death from gynecological cancer and the third most common gynecological malignancy worldwide. Despite a slight improvement in the overall survival of ovarian carcinoma patients in recent decades, the cure rate has not improved. This is mainly due to late diagnosis and resistance to therapy. It is therefore urgent to develop effective methods for early detection and prognosis. We hypothesized that, besides being able to distinguish serum samples of patients with ovarian cancer from those of patients with benign ovarian tumors, 1H-NMR metabolomics analysis might be able to predict the malignant potential of tumors. For this, serum 1H-NMR metabolomics analyses were performed, including patients with malignant, benign and borderline ovarian tumors. The serum metabolic profiles were analyzed by multivariate statistical analysis, including principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) methods. A metabolic profile associated with ovarian malignant tumors was defined, in which lactate, 3-hydroxybutyrate and acetone were increased and acetate, histidine, valine and methanol were decreased. Our data support the use of 1H-NMR metabolomics analysis as a screening method for ovarian cancer detection and might be useful for predicting the malignant potential of borderline tumors.

Metabolic characterisation of transglutaminase 2 inhibitor effects in breast cancer cell lines.

Transglutaminase 2 (TG2), which mediates post-translational modifications of multiple intracellular enzymes, is involved in the pathogenesis and progression of cancer. We used 1 H-NMR metabolomics to study the effects of AA9, a novel TG2 inhibitor, on two breast cancer cell lines with distinct phenotypes, MCF-7 and MDA-MB-231. AA9 can promote apoptosis in both cell lines, but it is particularly effective in MD-MB-231, inhibiting transamidation reactions and decreasing cell migration and invasiveness. This metabolomics study provides evidence of a major effect of AA9 on MDA-MB-231 cells, impacting glutamate and aspartate metabolism, rather than on MCF-7 cells, characterised by choline and O-phosphocholine decrease. Interestingly, AA9 treatment induces myo-inositol alteration in both cell lines, indicating action on phosphatidylinositol metabolism, likely modulated by the G protein activity of TG2 on phospholipase C. Considering the metabolic deregulations that characterise various breast cancer subtypes, the existence of a metabolic pathway affected by AA9 further points to TG2 as a promising hot spot. The metabolomics approach provides a powerful tool to monitor the effectiveness of inhibitors and better understand the role of TG2 in cancer.

Salbutamol Attenuates Diabetic Skeletal Muscle Atrophy by Reducing Oxidative Stress, Myostatin/GDF-8, and Pro-Inflammatory Cytokines in Rats.

Type 2 diabetes is a metabolic disorder that leads to accelerated skeletal muscle atrophy. In this study, we aimed to evaluate the effect of salbutamol (SLB) on skeletal muscle atrophy in high-fat diet (HFD)/streptozotocin (STZ)-induced diabetic rats. Male Sprague Dawley rats were divided into four groups (n = 6): control, SLB, HFD/STZ, and HFD/STZ + SLB (6 mg/kg orally for four weeks). After the last dose of SLB, rats were assessed for muscle grip strength and muscle coordination (wire-hanging, rotarod, footprint, and actophotometer tests). Body composition was analyzed in live rats. After that, animals were sacrificed, and serum and gastrocnemius (GN) muscles were collected. Endpoints include myofibrillar protein content, muscle oxidative stress and antioxidants, serum pro-inflammatory cytokines (interleukin-1β, interleukin-2, and interleukin-6), serum muscle markers (myostatin, creatine kinase, and testosterone), histopathology, and muscle 1H NMR metabolomics. Findings showed that SLB treatment significantly improved muscle strength and muscle coordination, as well as increased lean muscle mass in diabetic rats. Increased pro-inflammatory cytokines and muscle markers (myostatin, creatine kinase) indicate muscle deterioration in diabetic rats, while SLB intervention restored the same. Also, Feret's diameter and cross-sectional area of GN muscle were increased by SLB treatment, indicating the amelioration in diabetic rat muscle. Results of muscle metabolomics exhibit that SLB treatment resulted in the restoration of perturbed metabolites, including histidine-to-tyrosine, phenylalanine-to-tyrosine, and glutamate-to-glutamine ratios and succinate, sarcosine, and 3-hydroxybutyrate (3HB) in diabetic rats. These metabolites showed a pertinent role in muscle inflammation and oxidative stress in diabetic rats. In conclusion, findings showed that salbutamol could be explored as an intervention in diabetic-associated skeletal muscle atrophy.

Evidence supporting a causal relationship between an ApoB-independent 1H-NMR metabolomics profile and atherosclerotic cardiovascular disease

Evidence supporting a causal relationship between an ApoB-independent 1H-NMR metabolomics profile and atherosclerotic cardiovascular disease

Discrimination of Sayamakaori and Yabukita Which Are Original Plant Source of Japanese Green Tea and Identification of Specific Compounds for the Former by Nuclear Magnetic Resonance Metabolomics Techniques Combined with Isolation by Chromatography Methods

Camellia sinensis leaves are one of the most economically important crops, and various tea cultivars are available in Japan. In the present study, we compared the constituents of Camellia sinensis var. sinensis cv. Yabukita (“Yabukita”), a standard tea cultivar, and those of C. sinensis var. sinensis cv. Sayamakaori (“Sayamakaori”), grown in Saitama Prefecture, using proton nuclear magnetic resonance (1H-NMR) metabolomics technology. Principal component analysis and hierarchical cluster analysis of 1H-NMR spectroscopic data of the MeOH extracts of C. sinensis leaves revealed differences in the metabolic profiles of each tea cultivar. Chromatographic separation based on 1H-NMR spectral data showed that kaempferol 3- O-β-D-glucopyranosyl-(1 → 3)-α-L-rhamnopyranosyl-(1 → 6)-β-D-glucopyranoside was a distinct component of “Sayamakaori”. This compound can be used as maker for the identification of “Sayamakaori” and the maintenance of its quality.