41 research outputs found
Investigating Potential Mechanisms of Obesity by Metabolomics
Obesity is a serious health problem with an increased risk of several common diseases including diabetes, cardiovascular disease, and cancer. Metabolomics is an emerging analytical technique for systemic determination of metabolite profiles, which is useful for understanding the biochemical changes in obesity or related diseases both in individual organs and at the organism level. Increasingly, this technology has been applied to the study of obesity, complementing transcriptomics and/or proteomics analyses. Indeed, the alterations of metabolites in biofluids/tissues are direct indicators of variations in physiology or pathology. In this paper, we will examine the obesity-related alterations in significant metabolites that have been identified by metabolomics as well as their metabolic pathway associations. Issues concerning the screening of biologically significant metabolites related to obesity will also be discussed
NMR-based metabolomics: global analysis of metabolites to address problems in prostate cancer
Comparison of CT colonography, colonoscopy, sigmoidoscopy and faecal occult blood tests for the detection of advanced adenoma in an average risk population.
Seminal plasma enables selection and monitoring of active surveillance candidates using nuclear magnetic resonance-based metabolomics: A preliminary investigation
Background: Diagnosis and monitoring of localized prostate cancer requires discovery and validation of noninvasive biomarkers. Nuclear magnetic resonance (NMR)-based metabolomics of seminal plasma reportedly improves diagnostic accuracy, but requires validation in a high-risk clinical cohort.
Materials and methods: Seminal plasma samples of 151 men being investigated for prostate cancer were analyzed with 1H-NMR spectroscopy. After adjustment for buffer (add-to-subtract) and endogenous enzyme influence on metabolites, metabolite profiling was performed with multivariate statistical analysis (principal components analysis, partial least squares) and targeted quantitation.
Results: Seminal plasma metabolites best predicted low- and intermediate-risk prostate cancer with differences observed between these groups and benign samples. Lipids/lipoproteins dominated spectra of high grade samples with less metabolite contributions. Overall prostate cancer prediction using previously described metabolites was not validated.
Conclusion: Metabolomics of seminal plasma in vitro may assist urologists with diagnosis and monitoring of either low or intermediate grade prostate cancer. Less clinical benefit may be observed for high-risk patients. Further investigation in active surveillance cohorts, and/or in combination with in vivo magnetic resonance spectroscopic imaging may further optimize localized prostate cancer outcomes
Prostate-based biofluids for the detection of prostate cancer: A comparative study of the diagnostic performance of cell-sourced RNA biomarkers
Background
Prostate cancer (PCa) diagnosis requires improvement with the aid of more accurate biomarkers. Postejaculate urethral washings (PEUW) could be a physiological equivalent to urine obtained following rectal prostatic massage, the current basis for the prostate cancer antigen 3 (PCA3) test. The aim of this study was to investigate if PEUW contained prostate-based material, evidenced by the presence of prostate specific antigen (PSA), and to evaluate the diagnostic performance of PEUW-based biomarkers.
Methods
Male patients referred for elevated serum PSA or abnormal digital rectal examination provided ejaculate and PEUW samples. PSA, PCA3, and β2-microglobulin (β2M) were quantified in ejaculate and PEUW and compared with absolute and clinically significant (according to D\u27Amico criteria) PCa presence, as determined by biopsies. Diagnostic performance was determined and compared with serum PSA using receiver operating characteristic analysis.
Results
From 83 patients who provided PEUW samples, paired analysis with ejaculate samples was possible for 38 patients, while analysis in an unpaired, extended cohort was possible for 62 patients. PSA and PCA3 were detected in PEUW, normalized to β2M, and PCA3:PSA was calculated. In predicting absolute PCa status, PCA3:β2M in ejaculate [area under the curve (AUC) 0.717] and PEUW (AUC 0.569) were insignificantly better than PCA3:PSA (AUC 0.668 and 0.431, respectively) and comparable with serum PSA (AUC 0.617) with similar trends observed for the extended cohort. When considering clinically significant PCa presence, serum PSA in the comparison (AUC 0.640) and extended cohorts (AUC 0.665) was comparable with PCA3: β2M (AUC 0.667) and PCA3:PSA (AUC 0.605) in ejaculate, with lower estimates for PEUW in the comparison (PCA3: β2M AUC 0.496; PCA3:PSA AUC 0.342) and extended (PCA3: β2M AUC 0.497; PCA3:PSA AUC 0.469) cohorts. The statistical analysis was limited by sample size.
Conclusion
PEUW contains prostatic material, but has limited diagnostic accuracy when considering cell-derived DNA analysis. PCA3-based markers in ejaculate are comparable to serum PSA and digital rectal examination–urine markers
Digital single-operator pancreatoscopy for the treatment of symptomatic pancreatic duct stones: a prospective multicenter cohort trial
BACKGROUND
Digital single-operator pancreatoscopy (DSOP)-guided lithotripsy is a novel treatment modality for pancreatic endotherapy, with demonstrated technical success in retrospective series of between 88 % and 100 %. The aim of this prospective multicenter trial was to systematically evaluate DSOP in patients with chronic pancreatitis and symptomatic pancreatic duct stones.
METHODS
Patients with symptomatic chronic pancreatitis and three or fewer stones ≥ 5mm in the main pancreatic duct (MPD) of the pancreatic head or body were included. The primary end point was complete stone clearance (CSC) in three or fewer treatment sessions with DSOP. Current guidelines recommend extracorporeal shock wave lithotripsy (ESWL) for MPD stones > 5 mm. A performance goal was developed to show that the CSC rate of MPD stones using DSOP was above what has been previously reported for ESWL. Secondary end points were pain relief measured with the Izbicki pain score (IPS), number of interventions, and serious adverse events (SAEs).
RESULTS
40 chronic pancreatitis patients were included. CSC was achieved in 90 % of patients (36/40) on intention-to-treat analysis, after a mean (SD) of 1.36 (0.64) interventions (53 procedures in total). The mean (SD) baseline IPS decreased from 55.3 (46.2) to 10.9 (18.3). Overall pain relief was achieved in 82.4 % (28/34) after 6 months of follow-up, with complete pain relief in 61.8 % (21/34) and partial pain relief in 20.6 % (7/34). SAEs occurred in 12.5 % of patients (5/40), with all treated conservatively.
CONCLUSION
DSOP-guided endotherapy is effective and safe for the treatment of symptomatic MPD stones in highly selected patients with chronic pancreatitis. It significantly reduces pain and could be considered as an alternative to standard ERCP techniques for MPD stone treatment in these patients
NMRDyn: A Program for NMR Relaxation Studies of Protein Association
Self-association is an important biological phenomenon that is associated with many cellular processes. NMR relaxation measurements provide data about protein molecular dynamics at the atomic level and are sensitive to changes induced by self-association. Thus, measurements and analysis of NMR relaxation data can provide structurally resolved information on self-association that would not be accessible otherwise. Here, we present a computer program, NMRdyn, which analyses relaxation data to provide parameters defining protein self-association. Unlike existing relaxation analysis software, NMRdyn can explicitly model the monomer-oligomer equilibrium while fitting measured relaxation data. Additionally, the program is packaged with a user-friendly interface, which is important because relaxation data can often be large and complex. NMRdyn is available from http://research1t.imb.uq.edu.au/nmr/NMRdyn
Modeling Meets Metabolomics-The WormJam Consensus Model as Basis for Metabolic Studies in the Model Organism Caenorhabditis elegans.
Metabolism is one of the attributes of life and supplies energy and building blocks to organisms. Therefore, understanding metabolism is crucial for the understanding of complex biological phenomena. Despite having been in the focus of research for centuries, our picture of metabolism is still incomplete. Metabolomics, the systematic analysis of all small molecules in a biological system, aims to close this gap. In order to facilitate such investigations a blueprint of the metabolic network is required. Recently, several metabolic network reconstructions for the model organism Caenorhabditis elegans have been published, each having unique features. We have established the WormJam Community to merge and reconcile these (and other unpublished models) into a single consensus metabolic reconstruction. In a series of workshops and annotation seminars this model was refined with manual correction of incorrect assignments, metabolite structure and identifier curation as well as addition of new pathways. The WormJam consensus metabolic reconstruction represents a rich data source not only for in silico network-based approaches like flux balance analysis, but also for metabolomics, as it includes a database of metabolites present in C. elegans, which can be used for annotation. Here we present the process of model merging, correction and curation and give a detailed overview of the model. In the future it is intended to expand the model toward different tissues and put special emphasizes on lipid metabolism and secondary metabolism including ascaroside metabolism in accordance to their central role in C. elegans physiology
Altered Metabolism of Growth Hormone Receptor Mutant Mice: A Combined NMR Metabonomics and Microarray Study
Growth hormone is an important regulator of post-natal growth and metabolism. We have investigated the metabolic consequences of altered growth hormone signaling in mutant mice that have truncations at position 569 and 391 of the intracellular domain of the growth hormone receptor, and thus exhibit either low (around 30% maximum) or no growth hormone-dependent STATS signaling respectively. These mutants result in altered liver metabolism, obesity and insulin resistance