Multivariate Modeling Identifies Neutrophil- and Th17-Related Factors as Differential Serum Biomarkers of Chronic Murine Colitis

Background: Diagnosis of chronic intestinal inflammation, which characterizes inflammatory bowel disease (IBD), along with prediction of disease state is hindered by the availability of predictive serum biomarker. Serum biomarkers predictive of disease state will improve trials for therapeutic intervention, and disease monitoring, particularly in genetically susceptible individuals. Chronic inflammation during IBD is considered distinct from infectious intestinal inflammation thereby requiring biomarkers to provide differential diagnosis. To address whether differential serum biomarkers could be identified in murine models of colitis, immunological profiles from both chronic spontaneous and acute infectious colitis were compared and predictive serum biomarkers identified via multivariate modeling.Methodology/Principal Findings: Discriminatory multivariate modeling of 23 cytokines plus chlorotyrosine and nitrotyrosine (protein adducts from reactive nitrogen species and hypochlorite) in serum and tissue from two murine models of colitis was performed to identify disease-associated biomarkers. Acute C. rodentium-induced colitis in C57BL/6J mice and chronic spontaneous Helicobacter-dependent colitis in TLR4−/− x IL-10−/− mice were utilized for evaluation. Colon profiles of both colitis models were nearly identical with chemokines, neutrophil- and Th17-related factors highly associated with intestinal disease. In acute colitis, discriminatory disease-associated serum factors were not those identified in the colon. In contrast, the discriminatory predictive serum factors for chronic colitis were neutrophil- and Th17-related factors (KC, IL-12/23p40, IL-17, G-CSF, and chlorotyrosine) that were also elevated in colon tissue. Chronic colitis serum biomarkers were specific to chronic colitis as they were not discriminatory for acute colitis.Conclusions/Significance: Immunological profiling revealed strikingly similar colon profiles, yet distinctly different serum profiles for acute and chronic colitis. Neutrophil- and Th17-related factors were identified as predictive serum biomarkers of chronic colitis, but not acute colitis, despite their presence in colitic tissue of both diseases thereby demonstrating the utility of mathematical modeling for identifying disease-associated serum biomarkers.</p

Multivariate Modeling Identifies Neutrophil- and Th17-Related Factors as Differential Serum Biomarkers of Chronic Murine Colitis

Diagnosis of chronic intestinal inflammation, which characterizes inflammatory bowel disease (IBD), along with prediction of disease state is hindered by the availability of predictive serum biomarker. Serum biomarkers predictive of disease state will improve trials for therapeutic intervention, and disease monitoring, particularly in genetically susceptible individuals. Chronic inflammation during IBD is considered distinct from infectious intestinal inflammation thereby requiring biomarkers to provide differential diagnosis. To address whether differential serum biomarkers could be identified in murine models of colitis, immunological profiles from both chronic spontaneous and acute infectious colitis were compared and predictive serum biomarkers identified via multivariate modeling.Discriminatory multivariate modeling of 23 cytokines plus chlorotyrosine and nitrotyrosine (protein adducts from reactive nitrogen species and hypochlorite) in serum and tissue from two murine models of colitis was performed to identify disease-associated biomarkers. Acute C. rodentium-induced colitis in C57BL/6J mice and chronic spontaneous Helicobacter-dependent colitis in TLR4(-/-) x IL-10(-/-) mice were utilized for evaluation. Colon profiles of both colitis models were nearly identical with chemokines, neutrophil- and Th17-related factors highly associated with intestinal disease. In acute colitis, discriminatory disease-associated serum factors were not those identified in the colon. In contrast, the discriminatory predictive serum factors for chronic colitis were neutrophil- and Th17-related factors (KC, IL-12/23p40, IL-17, G-CSF, and chlorotyrosine) that were also elevated in colon tissue. Chronic colitis serum biomarkers were specific to chronic colitis as they were not discriminatory for acute colitis.Immunological profiling revealed strikingly similar colon profiles, yet distinctly different serum profiles for acute and chronic colitis. Neutrophil- and Th17-related factors were identified as predictive serum biomarkers of chronic colitis, but not acute colitis, despite their presence in colitic tissue of both diseases thereby demonstrating the utility of mathematical modeling for identifying disease-associated serum biomarkers

Diagrammar In Classical Scalar Field Theory

In this paper we analyze perturbatively a g phi^4 classical field theory with and without temperature. In order to do that, we make use of a path-integral approach developed some time ago for classical theories. It turns out that the diagrams appearing at the classical level are many more than at the quantum level due to the presence of extra auxiliary fields in the classical formalism. We shall show that several of those diagrams cancel against each other due to a universal supersymmetry present in the classical path integral mentioned above. The same supersymmetry allows the introduction of super-fields and super-diagrams which considerably simplify the calculations and make the classical perturbative calculations almost "identical" formally to the quantum ones. Using the super-diagrams technique we develop the classical perturbation theory up to third order. We conclude the paper with a perturbative check of the fluctuation-dissipation theorem.Comment: 67 pages. Improvements inserted in the third order calculation

Gut Microbiome Phenotypes Driven by Host Genetics Affect Arsenic Metabolism

Large individual differences in susceptibility to arsenic-induced diseases are well-documented and frequently associated with different patterns of arsenic metabolism. In this context, the role of the gut microbiome in directly metabolizing arsenic and triggering systemic responses in diverse organs raises the possibility that gut microbiome phenotypes affect the spectrum of metabolized arsenic species. However, it remains unclear how host genetics and the gut microbiome interact to affect the biotransformation of arsenic. Using an integrated approach combining 16S rRNA gene sequencing and HPLC-ICP-MS arsenic speciation, we demonstrate that IL-10 gene knockout leads to a significant taxonomic change of the gut microbiome, which in turn substantially affects arsenic metabolism.National Institute of Environmental Health Sciences (P30 ES010126)National Institute of Environmental Health Sciences (NIEHS grant P30 ES002109)University of Georgia. College of Public Health (internal grant)University of Georgia (Faculty Research Grant (FRG)

Gut Microbiome Perturbations Induced by Bacterial Infection Affect Arsenic Biotransformation

Exposure to arsenic affects large human populations worldwide and has been associated with a long list of human diseases, including skin, bladder, lung, and liver cancers, diabetes, and cardiovascular disorders. In addition, there are large individual differences in susceptibility to arsenic-induced diseases, which are frequently associated with different patterns of arsenic metabolism. Several underlying mechanisms, such as genetic polymorphisms and epigenetics, have been proposed, as these factors closely impact the individuals’ capacity to metabolize arsenic. In this context, the role of the gut microbiome in directly metabolizing arsenic and triggering systemic responses in diverse organs raises the possibility that perturbations of the gut microbial communities affect the spectrum of metabolized arsenic species and subsequent toxicological effects. In this study, we used an animal model with an altered gut microbiome induced by bacterial infection, 16S rRNA gene sequencing, and inductively coupled plasma mass spectrometry-based arsenic speciation to examine the effect of gut microbiome perturbations on the biotransformation of arsenic. Metagenomics sequencing revealed that bacterial infection significantly perturbed the gut microbiome composition in C57BL/6 mice, which in turn resulted in altered spectra of arsenic metabolites in urine, with inorganic arsenic species and methylated and thiolated arsenic being perturbed. These data clearly illustrated that gut microbiome phenotypes significantly affected arsenic metabolic reactions, including reduction, methylation, and thiolation. These findings improve our understanding of how infectious diseases and environmental exposure interact and may also provide novel insight regarding the gut microbiome composition as a new risk factor of individual susceptibility to environmental chemicals.National Institute of Environmental Health Sciences (Massachusetts Institute of Technology. Center for Environmental Health Sciences Grant P30 ES002109)National Institute of Environmental Health Sciences (University of North Carolina. Center for Environmental Health and Susceptibility Grant P30 ES010126

An updated view of hypothalamic-vascular-pituitary unit function and plasticity

The discoveries of novel functional adaptations of the hypothalamus and anterior pituitary gland for physiological regulation have transformed our understanding of their interaction. The activity of a small proportion of hypothalamic neurons can control complex hormonal signalling, which is disconnected from a simple stimulus and the subsequent hormone secretion relationship and is dependent on physiological status. The interrelationship of the terminals of hypothalamic neurons and pituitary cells with the vasculature has an important role in determining the pattern of neurohormone exposure. Cells in the pituitary gland form networks with distinct organizational motifs that are related to the duration and pattern of output, and modifications of these networks occur in different physiological states, can persist after cessation of demand and result in enhanced function. Consequently, the hypothalamus and pituitary can no longer be considered as having a simple stratified relationship: with the vasculature they form a tripartite system, which must function in concert for appropriate hypothalamic regulation of physiological processes, such as reproduction. An improved understanding of the mechanisms underlying these regulatory features has implications for current and future therapies that correct defects in hypothalamic–pituitary axes. In addition, recapitulating proper network organization will be an important challenge for regenerative stem cell treatment