Advanced searches left 3/3

Metabolomics - Crossref

Summarized by Plex Scholar
Last Updated: 08 August 2022

* If you want to update the article please login/register

Integration of transcriptomics, proteomics, and metabolomics data to reveal HER2-associated metabolic heterogeneity in gastric cancer with response to immunotherapy and neoadjuvant chemotherapy

A deeper understanding of human epidermal growth factor receptor 2 -coexpressed metabolic pathways may provide new insights into tumour-intrinsic precision medicine. To perform untargeted metabolomics analysis, 224 matched blood samples of GC patients and healthy individuals were collected and assembled into a standardized metabolomics study. In addition, the GC's metabolic landscape revealed that alanine, aspartate, and glutamate metabolism was highly correlated with GC's prevalence and progression of GC. Consensus clustering was used to group patients with GC into four subtypes with differing metabolic characteristics. The GG and mixed subtypes were discovered to be extremely sensitive to chemotherapy, whereas the infant and AAG subtypes were more likely to benefit from immunotherapy. Conclusions Transcriptomic and proteomic studies revealed the close link between HER-2 level and patient with GC's immune status and metabolic characteristics.

Source link: https://doi.org/10.3389/fimmu.2022.951137


Interpretable machine learning-derived nomogram model for early detection of diabetic retinopathy in type 2 diabetes mellitus: a widely targeted metabolomics study

Abstract Objective The first detection of diabetic retinopathy is the first step to prioritizing therapy and avoiding permanent blindness. This research seeks to develop a machine learning system for DR early detection by using metabolomics and clinical measurements. Methods From 2017 to 2018, 950 students were recruited from two affiliated hospitals of Wenzhou Medical University and Anhui Medical University. Healthy volunteers, type 2 diabetes, and DR patients were among 69 matched blocks discovered from a propensity score matching-based metabolomics analysis. Models of multivariable conditional logistic regression models were developed for the nomogram model and later developed. Males accounted for 56. 7 years, with a median deviation of 9. 2, and females accounted for 66. 4 percent. Based on the DT model, 2-pyrrolidone completely separated healthy controls from diabetic patients, and thiamine triphosphate may be the primary metabolite for DR detection. Conclusions The nomogram gives a more complete and positive estimate for DR detection.

Source link: https://doi.org/10.1038/s41387-022-00216-0


Integrated network pharmacology and hepatic metabolomics to reveal the mechanism of Acanthopanax senticosus against major depressive disorder

Acanthopanax senticosus Harms is a common herbal medicine widely used for its antifatigue and antistress properties, as well as tonifying qi, boosting spleen, and kidney, and calming the mind. The current research sought to investigate the effect of ASH on MDD and potential therapeutic mechanisms. Based on network pharmacology, the chemical compound target network was predicted. Materials and Methods: Based on network pharmacology, the chemical compound target network was forecast. The investigation of differential metabolites and related metabolic pathways was carried out by Simultaneously, a chronic mild stress model mice were orally administered ASH for six weeks, and hepatic metabolomics based on gas chromatography (u2013mass spectrometry was carried out to identify distinct metabolites and related metabolic pathways. Conclusion: Based on these findings, it was speculated that the potential mechanism of ASH on MDD was related to the control of metabolism of several excitatory amino acids and carbohydrates, as well as the spelling of DAO, MAOB, GAA, HK1, and PYGM.

Source link: https://doi.org/10.3389/fcell.2022.900637


Metabolomics Analysis of Lettuce (Lactuca sativa L.) Affected by Low Potassium Supply

Lettuce is a globally popular leafy vegetable. Potassium is a vital macronutrient for lettuce growth and development, and it has a major role in its metabolites. Biomarkers that are representative of changes in the K status of lettuce before the occurrence of biophysical changes can be used to determine the early K status of lettuce. We investigated lettuce's metabolic response in a closed cultivation room under controlled conditions to determine the effect of low K on diverse metabolites. To determine the effect of low K on diverse metabolites, we investigated the metabolic response of lettuce in a controlled environment. Low K caused an increase in 40 metabolites and a decrease in 12 metabolites. Low-K stress samples revealed an increase in low-K stress samples and could be used as potential metabolic biomarkers. uridine, cis-aconitate, and D-gulono-lactone were among FA 18:1+3O, uridine, cis-aconitate, and D-gulono-lactone, as a potential metabolic biomarkers. This report confirms the effect of low K on lettuce metabolism, as well as identify biomarkers that can be used to monitor lettuce K status.

Source link: https://doi.org/10.3390/agriculture12081153


Serum Orotidine: A Novel Biomarker of Increased CVD Risk in Type 2 Diabetes Discovered Through Metabolomics Studies

Before and after adjustment for renal function and other CVD risk factors, a logistic regression was used to determine the correlation between incident CVD events and each of the 671 metabolites detected by the Metabolon platform. In a validation set from the Joslin Heart Study, 599 people with T2D with and without clinical evidence of significant coronary heart disease were followed up by absolute quantification assays. Orotidine's addition to established clinical predictors also improved C statistics and discrimination indices for CVD risk compared to the clinical predictors alone. Orotidine, in addition, may be a biological mediator of elevated CVD risk associated with poor kidney function, and may also help with T2D CVD risk prediction.

Source link: https://doi.org/10.2337/dc21-1789


Early detection of ureteropelvic junction obstruction in neonates with prenatal diagnosis of renal pelvis dilatation using 1H NMR urinary metabolomics

Abstract: In utero on prenatal ultrasonography, pelvis dilatation is found and can resolve spontaneously. To find specific urinary biomarkers for Upjo, specific urinary biomarkers were performed on newborns with prenatally diagnosed unilateral RPD and healthy controls. In UPJO patients, a discriminant metabolite network was identified in lower amounts. In patients with UPJO i. e. , two key metabolic pathways appeared to be impaired. Patients with transient dilatations and controls are clearly distinguished from patients who need surgery for UPJO in this prospective analysis.

Source link: https://doi.org/10.1038/s41598-022-17664-4


Biochemical Signatures in Growth Hormone Deficiency: a Pilot Study Using Metabolomics Approaches by Direct Infusion-mass Spectrometry

Abstract Purpose: The discovery of biomarkers that measure growth hormone deficiencies and monitor growth hormone replacement therapy is still difficult. metabolomics stands out as a versatile tool for large-scale identification and quantification of small molecules present in biological matrixes, among the u201c omics u201d methods used for screening biomarkers. Metabolomic results enable us to determine the phenotypic state, and therefore, metabolomics is a key ally in investigating biomarkers and investigating biological processes. Changes in glycerophospholipid metabolism were shown by data analysis, which revealed shifts in proteinogenic/glycogenic acids, carnitines, n acyl-amines, unsaturated fatty acids, and sulfur amino acids, as shown by pathway analysis. Regardless of GH therapy, GHD patients remain with elevations in lipids and amino acids compared to healthier control. Conclusion: GHRT alters the metabolism of GHD patients in order to compensate for GHD-induced dysregulations.

Source link: https://doi.org/10.21203/rs.3.rs-1021675/v1

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions