Metabolites最新文献

Necrotizing enterocolitis (NEC) is the most prevalent and potentially fatal intestinal injury mainly affecting premature infants, with significant long-term consequences for those who survive. This review explores the scale of the problem, highlighting advancements in epidemiology, the understanding of pathophysiology, and improvements in the prediction and diagnosis of this complex, multifactorial, and multifaced disease. Additionally, we focus on the potential role of metabolomics in distinguishing NEC from other conditions, which could allow for an earlier and more accurate classification of intestinal injuries in infants. By integrating metabolomic data with other diagnostic approaches, it is hoped to enhance our ability to predict outcomes and tailor treatments, ultimately improving care for affected infants.

Background/objective: This study aimed to investigate the causal relationship between urate level and female infertility using Mendelian randomization (MR) analysis.

Methods: To identify instrumental variables, we selected independent genetic loci associated with serum urate levels in individuals of European ancestry, utilizing data from large-scale genome-wide association studies (GWAS). The GWAS dataset included information on serum urate levels from 288,649 CKDGen participants. Female infertility data, including different etiologic classifications, consisted of 13,142 female infertility patients and 107,564 controls. We employed four MR methods, namely inverse variance weighted (IVW), MR-Egger, weighted median, and weighted model, to investigate the causal relationship between urate levels and female infertility. The Cochran Q-test was used to assess heterogeneity among single nucleotide polymorphisms (SNPs), and the MR-Egger intercept test was employed to evaluate the presence of horizontal pleiotropy. Additionally, a "leave-one-out" sensitivity analysis was conducted to examine the influence of individual SNPs on the MR study.

Results: The IVW analysis demonstrated that elevated serum urate levels increased the risk of female infertility (odds ratio [OR] = 1.18, 95% confidence interval [CI]: 1.07-1.33). Furthermore, serum urate levels were found to be associated with infertility due to cervical, vaginal, or other unknown causes (OR = 1.16, 95% CI: 1.06-1.26), also confirmed by other methods. Heterogeneity among instrumental variables was assessed using Cochran's Q-test (p < 0.05), so a random-effects IVW approach was employed in the effects model. The MR-Egger intercept test indicated no presence of horizontal pleiotropy. A "leave-one-out" sensitivity analysis was conducted, demonstrating that no individual SNP had a substantial impact on the overall findings.

Conclusions: In the European population, the urate level is significantly and causally associated with an increased risk of female infertility.

Background: Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease. The fruits of Illicium verum, which is a medicinal and edible resource, have been shown to have anti-inflammatory properties.

Methods: In this study, we investigated the effects of I. verum extracts (IVEs) on human RA fibroblasts-like synoviocytes (RA-FLS) by using a sensitive and selective ultra-high-performance liquid chromatography with high-definition mass spectrometry (UPLC-HDMS) method. We subsequently analyzed the metabolites produced after the incubation of cultured RA-FLS with IVEs.

Results: IVEs inhibited the proliferation and suppressed the migration of RA-FLS, and reduced the levels of inflammatory factors including TNF-α and IL-6. Twenty differential metabolites responsible for the effects of IVEs were screened and annotated based on the UPLC-HDMS data by using a cell metabolomics approach.

Discussion: Our findings suggest that treating RA-FLS with IVEs can regulate lipid and amino acid metabolism, indicating that this extract has the potential to modify the metabolic pathways that cause inflammation in RA.

Conclusions: This might lead to novel therapeutic strategies for managing patients with RA.

Background: Niemann-Pick disease type C (NPC) is an inherited disorder characterized by a functional deficiency of cholesterol transport proteins. However, the molecular mechanisms and pathophysiology of the disease remain unknown.

Methods: In this study, we identified several metabolite characteristics of NPC that may fluctuate in a cellular model of the disease, using both global and targeted metabolomic analyses by liquid chromatography/tandem mass spectrometry (LC-MS/MS). Three cell lines, HepG2 cells (wild-type[WT]) and two NPC model HepG2 cell lines in which NPC1 was genetically ablated (knockout [KO]1 and KO2), were used for metabolomic analysis. Data were subjected to enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways.

Results: The enrichment analysis of global metabolomics revealed that 8 pathways in KO1 and 16 pathways in KO2 cells were notably altered. In targeted metabolomics for 15 metabolites, 4 metabolites in KO1 and 10 metabolites in KO2 exhibited statistically significant quantitative changes in KO1 or KO2 relative to WT. Most of the altered metabolites were related to creatinine synthesis and cysteine metabolism pathways.

Conclusions: In the future, our objective will be to elucidate the relationship between these metabolic alterations and pathophysiology.

Background/Objectives: Cardiorespiratory fitness (CRF) levels significantly modulate the risk of cardiometabolic diseases, aging, and mortality. Nevertheless, there is a substantial interindividual variability in CRF responsiveness to a given standardized exercise dose despite the type of training. Predicting the responsiveness to regular exercise has the potential to contribute to personalized exercise medicine applications. This study aimed to identify predictive biomarkers for the classification of CRF responsiveness based on serum and intramuscular metabolic levels before continuous endurance training (ET) or high-intensity interval training (HIIT) programs using a randomized controlled trial. Methods: Forty-three serum and seventy intramuscular (vastus lateralis) metabolites were characterized and quantified via proton nuclear magnetic resonance (¹H NMR), and CRF levels (expressed in METs) were measured in 70 sedentary young men (age: 23.7 ± 3.0 years; BMI: 24.8 ± 2.5 kg·m^-2), at baseline and post 8 weeks of the ET, HIIT, and control (CO) periods. A multivariate binary logistic regression model was used to classify individuals at baseline as Responders or Non-responders to CRF gains after the training programs. Results: CRF responses ranged from 0.9 to 3.9 METs for ET, 1.1 to 4.7 METs for HIIT, and -0.9 to 0.2 METs for CO. The frequency of Responder/Non-responder individuals between ET (76.7%/23.3%) and HIIT (90.0%/10.0%) programs was similar (p = 0.166). The model based on serum O-acetylcarnitine levels [OR (odds ratio) = 4.72, p = 0.012] classified Responder/Non-responders individuals to changes in CRF regardless of the training program with 78.0% accuracy (p = 0.006), while the intramuscular model based on creatinine levels (OR = 4.53, p = 0.0137) presented 72.3% accuracy (p = 0.028). Conclusions: These results highlight the potential value of serum and intramuscular metabolites as biomarkers for the classification of CRF responsiveness previous to different aerobic training programs.

Imaging tests, tumor marker (TM) screening, and biochemical tests provide a definitive diagnosis of hepatocellular carcinoma (HCC). However, some patients with HCC may present TM-negative results, warranting a need for developing more sensitive and accurate screening biomarkers. Various diseases exhibit increased blood levels of bile acids, biosynthesized from cholesterol in the liver, and they have been associated with HCC. Herein, we analyzed plasma bile acids using liquid chromatography/tandem mass spectrometry and integrated them with conventional biomarkers to develop a diagnostic screening model for HCC. Plasma samples were obtained from patients diagnosed with chronic hepatitis, hepatic cirrhosis (HC), and HCC. A QTRAP 6500 mass spectrometer and a Nexera liquid chromatograph with a YMC-Triart C18 analytical column were used. The mobile phase A was a 20 mmol/L ammonium formate solution, and mobile phase B was a methanol/acetonitrile mixture (1:1, v/v) with 20 mmol/L ammonium formate. After determining the concentrations of 32 bile acids, statistical analysis and diagnostic screening model development were performed. Plasma concentrations of bile acids differed between sample groups, with significant differences observed between patients with HC and HCC. By integrating bile acid results with conventional biochemical tests, a potential diagnostic screening model for HCC was successfully developed. Future studies should increase the sample size and analyze the data in detail to verify the diagnostic efficacy of the model.

Introduction: Although aging is a natural phenomenon, in recent years it has accelerated. One key factor implicated in the aging process is oxidative stress. Oxidative stress also plays a role in frailty (frail) and metabolic syndrome (MetS).

Methods: A total of 66 elderly persons (65 years old and older) with no acute or severe chronic disorders were assessed for waist circumference (WC), arterial blood pressure, glycemia, glycated hemoglobin (HbA1c), plasma lipids, and activity of erythrocyte superoxide dismutase (SOD-1). Patients were classified as NonMetS-Nonfrail (n = 19), NonMetS-frail (n = 20), MetS-Nonfrail (n = 17), or MetS-frail (n = 10).

Results: There were no significant differences in superoxide dismutase activity among investigated elderly groups. However, the data suggest that MetS individuals, both frail and nonfrail, have higher risk factors for cardiovascular disease compared to NonMetS individuals. The correlations analyses of SOD-1 and other metabolic indices suggest that SOD-1 levels may be influenced by age, total cholesterol, HDL cholesterol, and fasting glucose levels in certain groups of seniors.

Conclusions: Aging is associated with decreased antioxidant enzyme SOD-1 activity with glucose alteration in frailty syndrome as well as with lipids disturbances in metabolic syndrome. These factors provide a nuanced view of how frailty and metabolic syndrome interact with various health parameters, informing both clinical practice and future research directions.

Background: Neolamarckia cadamba (Rubiaceae) is a well-recognized medicinal plant with recorded therapeutical attributes. However, a thorough assessment of active compounds in its fruits is lacking, limiting their use and valorization in pharmacological industries.

Methods: Thus, this study investigated variations in the fruits' secondary metabolite (SM) profiles, as well as antioxidant activities in aqueous (WA) and ethanol (ET) extracts.

Results: Liquid chromatography-electrospray ionization tandem mass spectrometry identified 541 SMs, of which 14 and 1 (di-O-glucosylquinic acid) were specifically detected in ET and WA, respectively. Phenolic acids (36.97%), flavonoids (28.10%), terpenoids (12.20%), and alkaloids (9.98%) were the dominant SMs. The SM profiles of the fruits in WA and ET were quite different. We revealed 198 differentially extracted (DE) metabolites between WA and ET, including 62 flavonoids, 57 phenolic acids, 45 terpenoids, 14 alkaloids, etc. Most DE flavones (36 out of 40), terpenoids (45 out of 45), and alkaloids (12 out of 14) had higher content in ET. Catechin and its derivatives, procyanidins, and tannins had higher content in WA. ABTS and DPPH assays showed that the antioxidant activity of ET was significantly higher than that of WA.

Conclusions: Our findings will facilitate the efficient extraction and evaluation of specific active compounds in N. cadamba.

Metabolism is a network of chemical reactions that sustain cellular life. Parts of this metabolic network are defined as metabolic pathways containing specific biochemical reactions. Products and reactants of these reactions are called metabolites, which are associated with certain human-defined metabolic pathways. Metabolic knowledgebases, such as the Kyoto Encyclopedia of Gene and Genomes (KEGG) contain metabolites, reactions, and pathway annotations; however, such resources are incomplete due to current limits of metabolic knowledge. To fill in missing metabolite pathway annotations, past machine learning models showed some success at predicting the KEGG Level 2 pathway category involvement of metabolites based on their chemical structure. Here, we present the first machine learning model to predict metabolite association to more granular KEGG Level 3 metabolic pathways. We used a feature and dataset engineering approach to generate over one million metabolite-pathway entries in the dataset used to train a single binary classifier. This approach produced a mean Matthews correlation coefficient (MCC) of 0.806 ± 0.017 SD across 100 cross-validation iterations. The 172 Level 3 pathways were predicted with an overall MCC of 0.726. Moreover, metabolite association with the 12 Level 2 pathway categories was predicted with an overall MCC of 0.891, representing significant transfer learning from the Level 3 pathway entries. These are the best metabolite pathway prediction results published so far in the field.

[Background] Intercropping is considered an effective approach to defending rice disease. [Objectives/Methods] This study aimed to explore the resistance mechanism of rice intraspecific intercropping by investigating soil metabolites and their regulation on the rhizosphere soil microbial community using metabolomic and microbiome analyses. [Results] The results showed that the panicle blast disease occurrence of the resistant variety Shanyou63 (SY63) and the susceptible variety Huangkenuo (HKN) were both decreased in the intercropping compared to monoculture. Notably, HKN in the intercropping system exhibited significantly decreased disease incidence and increased disease resistance-related enzyme protease activity. KEGG annotation from soil metabolomics analysis revealed that phenylalanine metabolic pathway, phenylalanine, tyrosine, and tryptophan biosynthesis pathway, and fructose and mannose metabolic pathway were the key pathways related to rice disease resistance. Soil microbiome analysis indicated that the bacterial genera Nocardioides, Marmoricola, Luedemannella, and Desulfomonile were significantly enriched in HKN after intercropping, while SY63 experienced a substantial accumulation of Ruminiclostridium and Cellulomonas. Omics-based correlation analysis highlighted that the community assembly of Cellulomonas and Desulfomonile significantly affected the content of the metabolites D-sorbitol, D-mannitol, quinic acid, which further proved that quinic acid had a significantly inhibitory effect on the mycelium growth of Magnaporthe oryzae, and these three metabolites had a significant blast control effect. The optimal rice blast-control efficiency on HKN was 51.72%, and Lijiangxintuanheigu (LTH) was 64.57%. [Conclusions] These findings provide a theoretical basis for rice varieties intercropping and sustainable rice production, emphasizing the novelty of the study in elucidating the underlying mechanisms of intercropping-mediated disease resistance.