Integrating Multiple Analytical Datasets to Compare Metabolite Profiles of Mouse Colonic-Cecal Contents and Feces.

The pattern of metabolites produced by the gut microbiome comprises a phenotype indicative of the means by which that microbiome affects the gut. We characterized that phenotype in mice by conducting metabolomic analyses of the colonic-cecal contents, comparing that to the metabolite patterns of feces in order to determine the suitability of fecal specimens as proxies for assessing the metabolic impact of the gut microbiome. We detected a total of 270 low molecular weight metabolites in colonic-cecal contents and feces by gas chromatograph, time-of-flight mass spectrometry (GC-TOF) and ultra-high performance liquid chromatography, quadrapole time-of-flight mass spectrometry (UPLC-Q-TOF). Of that number, 251 (93%) were present in both types of specimen, representing almost all known biochemical pathways related to the amino acid, carbohydrate, energy, lipid, membrane transport, nucleotide, genetic information processing, and cancer-related metabolism. A total of 115 metabolites differed significantly in relative abundance between both colonic-cecal contents and feces. These data comprise the first characterization of relationships among metabolites present in the colonic-cecal contents and feces in a healthy mouse model, and shows that feces can be a useful proxy for assessing the pattern of metabolites to which the colonic mucosum is exposed

Metabolomics in psoriatic disease: pilot study reveals metabolite differences in psoriasis and psoriatic arthritis.

ImportanceWhile "omics" studies have advanced our understanding of inflammatory skin diseases, metabolomics is mostly an unexplored field in dermatology.ObjectiveWe sought to elucidate the pathogenesis of psoriatic diseases by determining the differences in metabolomic profiles among psoriasis patients with or without psoriatic arthritis and healthy controls.DesignWe employed a global metabolomics approach to compare circulating metabolites from patients with psoriasis, psoriasis and psoriatic arthritis, and healthy controls.SettingStudy participants were recruited from the general community and from the Psoriasis Clinic at the University of California Davis in United States.ParticipantsWe examined metabolomic profiles using blood serum samples from 30 patients age and gender matched into three groups: 10 patients with psoriasis, 10 patients with psoriasis and psoriatic arthritis and 10 control participants. Main outcome(s) and measures(s): Metabolite levels were measured calculating the mean peak intensities from gas chromatography time-of-flight mass spectrometry.ResultsMultivariate analyses of metabolomics profiles revealed altered serum metabolites among the study population. Compared to control patients, psoriasis patients had a higher level of alpha ketoglutaric acid (Pso: 288 ± 88;Control209 ± 69; p=0.03), a lower level of asparagine (Pso: 5460 ± 980;Control7260 ± 2100; p=0.02), and a lower level of glutamine (Pso: 86000 ± 20000;Control111000 ± 27000; p=0.02). Compared to control patients, patients with psoriasis and psoriatic arthritis had increased levels of glucuronic acid (Pso + PsA: 638 ± 250;Control347 ± 61; p=0.001). Compared to patients with psoriasis alone, patients with both psoriasis and psoriatic arthritis had a decreased level of alpha ketoglutaric acid (Pso + PsA: 186 ± 80; Pso: 288 ± 88; p=0.02) and an increased level of lignoceric acid (Pso + PsA: 442 ± 280; Pso: 214 ± 64; p=0.02).Conclusions and relevanceThe metabolite differences help elucidate the pathogenesis of psoriasis and psoriatic arthritis and they may provide insights for therapeutic development

Metabolomic profile of patients with left ventricular assist devices: a pilot study

Background: Metabolomic profiling has important diagnostic and prognostic value in heart failure (HF). We investigated whether left ventricular assist device (LVAD) support has an impact on the metabolomic profile of chronic HF patients and if specific metabolic patterns are associated with the development of adverse events. Methods: We applied untargeted metabolomics to detect and analyze molecules such as amino acids, sugars, fatty acids and other metabolites in plasma samples collected from thirty-three patients implanted with a continuous-flow LVAD. Data were analyzed at baseline, i.e., before implantation of the LVAD, and at long-term follow-up. Results: Our results reveal significant changes in the metabolomic profile after LVAD implant compared to baseline. In detail, we observed a pre-implant reduction in amino acid metabolism (aminoacyl-tRNA biosynthesis) and increased galactose metabolism, which reversed over the course of support [median follow-up 187 days (63–334 days)]. These changes were associated with improved patient functional capacity driven by LVAD therapy, according to NYHA functional classification of HF (NYHA class I-II: pre-implant =0% of the patients; post-implant =97% of the patients; P<0.001). Moreover, patients who developed adverse thromboembolic events (n=4, 13%) showed a pre-operative metabolomic fingerprint mainly associated with alterations of fatty acid biosynthesis and mitochondrial beta-oxidation of short-chain saturated fatty acids. Conclusions: Our data provide preliminary evidence that LVAD therapy is associated with changes in the metabolomic profile of HF and suggest the potential use of metabolomics as a new tool to stratify LVAD patients in regard to the risk of adverse events

Identifying individual differences of fluoxetine response in juvenile rhesus monkeys by metabolite profiling

Fluoxetine is the only psychopharmacological agent approved for depression by the US Food and Drug Administration for children and is commonly used therapeutically in a variety of neurodevelopmental disorders. Therapeutic response shows high individual variability, and severe side effects have been observed. In the current study we set out to identify biomarkers of response to fluoxetine as well as biomarkers that correlate with impulsivity, a measure of reward delay behavior and potential side effect of the drug, in juvenile male rhesus monkeys. The study group was also genotyped for polymorphisms of monoamine oxidase A (MAOA), a gene that has been associated with psychiatric disorders. We used peripheral metabolite profiling of blood and cerebrospinal fluid (CSF) from animals treated daily with fluoxetine or vehicle for one year. Fluoxetine response metabolite profiles and metabolite/reward delay behavior associations were evaluated using multivariate analysis. Our analyses identified a set of plasma and CSF metabolites that distinguish fluoxetine-from vehicle-treated animals and metabolites that correlate with impulsivity. Some metabolites displayed an interaction between fluoxetine and MAOA genotype. The identified metabolite biomarkers belong to pathways that have important functions in central nervous system physiology. Biomarkers of response to fluoxetine in the normally functioning brain of juvenile nonhuman primates may aid in finding predictors of response to treatment in young psychiatric populations and in progress toward the realization of a precision medicine approach in the area of neurodevelopmental disorders

APPLICATIONS OF UV-LIGA AND GRAYSCALE LITHOGRAPHY FOR DISPLAY TECHNOLOGIES

In the article MEMS technologies for display production and application presented. UV-LIGA and greyscale lithography based on SU-8 resist approaches were shown. Methods, technologies and structures of heterogeneous materials with soft magnetic properties, pros and cons are discussed. Unique specific parameters of soft magnetic composite material were achieved: magnetic induction of saturation – 2,1 Т, working frequency range – up to 1 MHz, permeability – up to 3000, total loss – 8 W/kg, Curie temperature – above 800 ºС. Electroplating allows deposition of soft magnetic alloys on the conductive substrate. Metals like Fe, Ni, Co with additives like B, P were used to get the best soft magnetic properties. Special codeposition process was developed to allow insertion of soft magnetic composite powder filaments into soft magnetic matrix formed during. It allows developing magnetic micromotors for display production. Simulation of the hybrid step micromotors was carried out in Ansys Maxwell 19. It was demonstrated that it is possible to get 10 mN m tourqe under 25 μm rotor-stator air gap. Only presented microtechnologies can provide such accuracy of the mciromotors elements. As for greyscale photolithography, special grey mask were developed and it was demonstrated the possibility to produce controllable real 3D relief on the SU-8 photoresist. Thus, microtechnologies should be integrated into display technology to provide cost effective production and advanced properties of final products.In the article MEMS technologies for display production and application presented. UV-LIGA and greyscale lithography based on SU-8 resist approaches were shown. Methods, technologies and structures of heterogeneous materials with soft magnetic properties, pros and cons are discussed. Unique specific parameters of soft magnetic composite material were achieved: magnetic induction of saturation – 2,1 Т, working frequency range – up to 1 MHz, permeability – up to 3000, total loss – 8 W/kg, Curie temperature – above 800 ºС. Electroplating allows deposition of soft magnetic alloys on the conductive substrate. Metals like Fe, Ni, Co with additives like B, P were used to get the best soft magnetic properties. Special codeposition process was developed to allow insertion of soft magnetic composite powder filaments into soft magnetic matrix formed during. It allows developing magnetic micromotors for display production. Simulation of the hybrid step micromotors was carried out in Ansys Maxwell 19. It was demonstrated that it is possible to get 10 mN m tourqe under 25 μm rotor-stator air gap. Only presented microtechnologies can provide such accuracy of the mciromotors elements. As for greyscale photolithography, special grey mask were developed and it was demonstrated the possibility to produce controllable real 3D relief on the SU-8 photoresist. Thus, microtechnologies should be integrated into display technology to provide cost effective production and advanced properties of final products

LC-MS metabolomics of psoriasis patients reveals disease severity-dependent increases in circulating amino acids that are ameliorated by anti-TNFα treatment

Psoriasis is an immune-mediated highly heterogeneous skin disease in which genetic as well as environmental factors play important roles. In spite of the local manifestations of the disease, psoriasis may progress to affect organs deeper than the skin. These effects are documented by epidemiological studies, but they are not yet mechanistically understood. In order to provide insight into the systemic effects of psoriasis, we performed a nontargeted high-resolution LC-MS metabolomics analysis to measure plasma metabolites from individuals with mild or severe psoriasis as well as healthy controls. Additionally, the effects of the anti-TNFα drug Etanercept on metabolic profiles were investigated in patients with severe psoriasis. Our analyses identified significant psoriasis-associated perturbations in three metabolic pathways: (1) arginine and proline, (2) glycine, serine and threonine, and (3) alanine, aspartate, and glutamate. Etanercept treatment reversed the majority of psoriasis-associated trends in circulating metabolites, shifting the metabolic phenotypes of severe psoriasis toward that of healthy controls. Circulating metabolite levels pre- and post-Etanercept treatment correlated with psoriasis area and severity index (PASI) clinical scoring (R(2) = 0.80; p < 0.0001). Although the responsible mechanism(s) are unclear, these results suggest that psoriasis severity-associated metabolic perturbations may stem from increased demand for collagen synthesis and keratinocyte hyperproliferation or potentially the incidence of cachexia. Data suggest that levels of circulating amino acids are useful for monitoring both the severity of disease as well as therapeutic response to anti-TNFα treatment

Association between plasma endocannabinoids and appetite in hemodialysis patients: A pilot study

Uremia-associated anorexia may be related to altered levels of long chain n-6 and n-3 polyunsaturated fatty acid (PUFA) derived circulating endocannabinoids (EC) and EC-like compounds that are known to mediate appetite. Our study's hypothesis was that such molecules are associated with appetite in patients with end-stage renal disease. A cross-sectional observational study was performed in 20 chronic hemodialysis patients (9 females, 11 males) and 10 healthy female controls in whom appetite was assessed using the Simplified Nutritional Appetite Questionnaire (SNAQ) and blood drawn in the fasting (and when applicable) pre-dialysis state. Blood levels of PUFA and EC were also measured. Higher blood levels of the long chain n-6 fatty acid 20:4n6 (arachidonic acid) and lower levels of the long chain n-3 fatty acid 20:5n3 (eicosapentaenoic acid) were observed in female hemodialysis patients compared to controls. No differences were observed between male and female patients. In female study participants strong correlations between specific EC-like compounds and total SNAQ scores were noted, including with the n-6 PUFA derived linoleoyl ethanolamide (L-EA; ρ=-0.60, P<.01) and the n-3 PUFA derived docosahexaenoyl ethanolamide (DH-EA; ρ=0.63, P<.01). The L-EA:DH-EA ratio was most strongly associated with the SNAQ score (ρ=-0.74, P≤.001), and its questions associated with appetite (ρ=-0.69, P≤.01) and satiety (ρ=-0.81, P≤.001). These findings support a link between circulating EC and appetite in hemodialysis patients

Urinary metabolomics (GC-MS) reveals that low and high birth weight infants share elevated inositol concentrations at birth

Objective: Metabolomics is a new ‘‘omics’’ platform aimed at high-throughput identification, quantification and characterization of small molecule metabolites. The metabolomics approach has been successfully applied to the classification different physiological states and identification of perturbed biochemical pathways. The purpose of the current investigation is the application of metabolomics to explore biological mechanisms which may lead to the onset of metabolic syndrome in adulthood. Methods: We evaluated differences in metabolites in the urine collected within 12 hours from 23 infants with IUGR (IntraUterine Growth Restriction), or LGA (Large for Gestational Age), compared to control infants (10 patients defined AGA: Appropriate for Gestational Age). Urinary metabolites were quantified by GC-MS and used to highlight similarities between the two metabolic diseases and identify metabolic markers for their predisposition. Quantified metabolites were analyzed using a multivariate statistics coupled with receiver operator characteristic curve (ROC) analysis of identified biomarkers. Results: Urinary myo-inositol was the most important discriminant between LGA + IUGR and control infants, and displayed an area under the ROC curve¼1. Conclusion: We postulate that the increase in plasma and consequently urinary inositol may constitute a marker of altered glucose metabolism during fetal development in both IUGR and LGA newborns