New approaches for identification of systematic measurement errors in linear steady state and dynamic processes

In this work three new methods are presented for improved identification of measurement biases in linear and nonlinear pseudo steady state processes. In addition to these methods, a new method is outlined for identification of biases in dynamic processes;The first method makes use of information contained in the relationship between individual measurements and the corresponding nodal balance. The performance of this method is demonstrated on a problem from the literature that has proved difficult for earlier methods. Additionally, this work discusses how the new technique can be used as a visual monitoring tool for identifying biased measured variables;The second and third methods examine each process variable individually and do not require the use of process physical constraints. Thus, neither of these methods is affected by the linearity or nonlinearity of process constraints. The second method involves obtaining the maximum likelihood estimate for the expected value of each measured variable. The decision rule is based on testing for a change in the expected value of each variable leading to an inference regarding the presence of a measurement bias. The third is a Bayesian approach that uses a priori information on the unknown parameters involved in the statistical measurement model for each process variable. The decision rule for identifying a bias is based on the mode of the conditional distribution of a change point parameter, given the data (and the prior information);Results of simulation studies are presented for all methods in terms of performance measures commonly used in literature. The studies involve varying the bias magnitude, time of occurrence, and probability of false identification. Using a process example previously employed by other researchers, the performance of the new methods is shown to be superior to current methods;While these methods are shown to be capable of accurately detecting mean shifts, a limitation that applies to all three methods is that it is not possible to ascertain whether the process variable has moved from a biased state to an unbiased state or from an unbiased state to a biased state. In other words, the methods are really concerned with detection of changes in bias, not directly with the detection of nonzero bias

Identifying Factors Influencing Antiretroviral Pharmacology and HIV Persistence in the Spleen

Little is known about ARV pharmacology—and the factors that may influence it—in the spleen, which is a lymphoid organ and contains approximately 0.3% of HIV RNA during suppressive antiretroviral therapy (ART). We sought to characterize how ARVs distribute within the spleen, and determine the degree to which they concentrate and localize with HIV expression. For Aim 1, we measured concentrations of 6 ARVs and 2 phosphorylated metabolites in three species. Generally, mice had the lowest splenic concentration of the three species, and nonhuman primates (NHPs) were most similar to humans. Spleen protein binding was lower than in plasma. Using quantitative proteomics, we quantified protein expression of 9 drug transporters in NHP and human spleens. NHPs had quantifiable Bcrp, Mrp4, and Ent1 concentrations; humans had quantifiable ENT1 concentrations. No relevant predictive relationships between transporters and ARV penetration were identified, nor did sex and viral infection. For Aim 2, through quantitative mass spectrometry imaging (MSI) of NHP spleens, we determined that over 58% of tissue area and 50% of viral RNA was not exposed to detectable ARV. When drug was detected, almost all drug concentrations exceeded 50% inhibitory concentrations. Correcting the images for heme (assumed to be blood contamination) decreased the ARV concentrations by 40%. Fibrosis markers covered 62% of tissue but ARV penetration did not appear to be affected by amount of fibrosis. For Aim 3, we developed NHP and human PBPK models to describe the concentrations of tenofovir and emtricitabine and their metabolites. The final NHP and human models fit the observed data well and revealed species differences for emtricitabine: tissue:plasma AUC penetration ratios were significantly lower in NHPs than in humans. Adjusting partition coefficients did not change the Tmax values for either species for both ARVs, providing evidence that blood flow is the limiting parameter. This multifactorial, translational approach vastly improves our understanding of ARV pharmacology within lymphoid tissues, and informs development of future therapies for HIV eradication strategies in tissue reservoirs (i.e. “kick and kill”). These data highlight ART is not proximate to infected cells, and tissue concentrations of novel therapies must be quantified.Doctor of Philosoph

Modeling and Optimization of Product Profiles in Biomass Pyrolysis

Biomass feed comes in many varieties, but have common chief constituents of hemicellulose, cellulose, and lignin. As the relative proportions of these constituents may vary, customization of the pyrolysis process conditions is required to produce a desired product profile. By recognizing the sources of variation, the reactor settings may be intelligently controlled, to achieve optimal operation. These considerations include biomass classification, feed rate, moisture content, particle size, and inter-particle thermal gradients (which arise during pyrolysis based on heating rate and temperature distribution). This chapter addresses the optimization of product profiles during biomass pyrolysis from a modeling perspective. Fundamental models for packed bed and fluidized bed pyrolyzers are developed, using kinetics from existing literature. The proposed optimization approach (inclusive of the kinetic and process models) can guide practical achievement of desired product profiles of the biomass pyrolysis process

Sexual dimorphism in myocardial acylcarnitine and triglyceride metabolism

Figure S1. Concentrations of non-esterified fatty acid moieties in NOD and Wistar rats by sex. (PPTX 163 kb

Genomic and metabolic disposition of non-obese Type 2 Diabetic rats to increased myocardial fatty acid metabolism

Lipotoxicity of the heart has been implicated as a leading cause of morbidity in Type 2 Diabetes Mellitus (T2DM). While numerous reports have demonstrated increased myocardial fatty acid (FA) utilization in obese T2DM animal models, this diabetic phenotype has yet to be demonstrated in non-obese animal models of T2DM. Therefore, the present study investigates functional, metabolic, and genomic differences in myocardial FA metabolism in non-obese type 2 diabetic rats. The study utilized Goto-Kakizaki (GK) rats at the age of 24 weeks. Each rat was imaged with small animal positron emission tomography (PET) to estimate myocardial blood flow (MBF) and myocardial FA metabolism. Echocardiograms (ECHOs) were performed to assess cardiac function. Levels of triglycerides (TG) and non-esterified fatty acids (NEFA) were measured in both plasma and cardiac tissues. Finally, expression profiles for 168 genes that have been implicated in diabetes and FA metabolism were measured using quantitative PCR (qPCR) arrays. GK rats exhibited increased NEFA and TG in both plasma and cardiac tissue. Quantitative PET imaging suggests that GK rats have increased FA metabolism. ECHO data indicates that GK rats have a significant increase in left ventricle mass index (LVMI) and decrease in peak early diastolic mitral annular velocity (E’) compared to Wistar rats, suggesting structural remodeling and impaired diastolic function. Of the 84 genes in each the diabetes and FA metabolism arrays, 17 genes in the diabetes array and 41 genes in the FA metabolism array were significantly up-regulated in GK rats. Our data suggest that GK rats’ exhibit increased genomic disposition to FA and TG metabolism independent of obesity

Initial biological evaluations of 18F-KS1, a novel ascorbate derivative to image oxidative stress in cancer

Background Reactive oxygen species (ROS)-induced oxidative stress damages many cellular components such as fatty acids, DNA, and proteins. This damage is implicated in many disease pathologies including cancer and neurodegenerative and cardiovascular diseases. Antioxidants like ascorbate (vitamin C, ascorbic acid) have been shown to protect against the deleterious effects of oxidative stress in patients with cancer. In contrast, other data indicate potential tumor-promoting activity of antioxidants, demonstrating a potential temporal benefit of ROS. However, quantifying real-time tumor ROS is currently not feasible, since there is no way to directly probe global tumor ROS. In order to study this ROS-induced damage and design novel therapeutics to prevent its sequelae, the quantitative nature of positron emission tomography (PET) can be harnessed to measure in vivo concentrations of ROS. Therefore, our goal is to develop a novel translational ascorbate-based probe to image ROS in cancer in vivo using noninvasive PET imaging of tumor tissue. The real-time evaluations of ROS state can prove critical in developing new therapies and stratifying patients to therapies that are affected by tumor ROS. Methods We designed, synthesized, and characterized a novel ascorbate derivative (E)-5-(2-chloroethylidene)-3-((4-(2-fluoroethoxy)benzyl)oxy)-4-hydroxyfuran-2(5H)-one (KS1). We used KS1 in an in vitro ROS MitoSOX-based assay in two different head and neck squamous cancer cells (HNSCC) that express different ROS levels, with ascorbate as reference standard. We radiolabeled 18F-KS1 following 18F-based nucleophilic substitution reactions and determined in vitro reactivity and specificity of 18F-KS1 in HNSCC and prostate cancer (PCa) cells. MicroPET imaging and standard biodistribution studies of 18F-KS1 were performed in mice bearing PCa cells. To further demonstrate specificity, we performed microPET blocking experiments using nonradioactive KS1 as a blocker. Results KS1 was synthesized and characterized using 1H NMR spectra. MitoSOX assay demonstrated good correlations between increasing concentrations of KS1 and ascorbate and increased reactivity in SCC-61 cells (with high ROS levels) versus rSCC-61cells (with low ROS levels). 18F-KS1 was radiolabeled with high radiochemical purity (> 94%) and specific activity (~ 100 GBq/μmol) at end of synthesis (EOS). Cell uptake of 18F-KS1 was high in both types of cancer cells, and the uptake was significantly blocked by nonradioactive KS1, and the ROS blocker, superoxide dismutase (SOD) demonstrating specificity. Furthermore, 18F-KS1 uptake was increased in PCa cells under hypoxic conditions, which have been shown to generate high ROS. Initial in vivo tumor uptake studies in PCa tumor-bearing mice demonstrated that 18F-KS1 specifically bound to tumor, which was significantly blocked (threefold) by pre-injecting unlabeled KS1. Furthermore, biodistribution studies in the same tumor-bearing mice showed high tumor to muscle (target to nontarget) ratios. Conclusion This work demonstrates the strong preliminary support of 18F-KS1, both in vitro and in vivo for imaging ROS in cancer. If successful, this work will provide a new paradigm to directly probe real-time oxidative stress levels in vivo. Our work could enhance precision medicine approaches to treat cancer, as well as neurodegenerative and cardiovascular diseases affected by ROS

New approaches for identification of systematic measurement errors in linear steady state and dynamic processes

In this work three new methods are presented for improved identification of measurement biases in linear and nonlinear pseudo steady state processes. In addition to these methods, a new method is outlined for identification of biases in dynamic processes;The first method makes use of information contained in the relationship between individual measurements and the corresponding nodal balance. The performance of this method is demonstrated on a problem from the literature that has proved difficult for earlier methods. Additionally, this work discusses how the new technique can be used as a visual monitoring tool for identifying biased measured variables;The second and third methods examine each process variable individually and do not require the use of process physical constraints. Thus, neither of these methods is affected by the linearity or nonlinearity of process constraints. The second method involves obtaining the maximum likelihood estimate for the expected value of each measured variable. The decision rule is based on testing for a change in the expected value of each variable leading to an inference regarding the presence of a measurement bias. The third is a Bayesian approach that uses a priori information on the unknown parameters involved in the statistical measurement model for each process variable. The decision rule for identifying a bias is based on the mode of the conditional distribution of a change point parameter, given the data (and the prior information);Results of simulation studies are presented for all methods in terms of performance measures commonly used in literature. The studies involve varying the bias magnitude, time of occurrence, and probability of false identification. Using a process example previously employed by other researchers, the performance of the new methods is shown to be superior to current methods;While these methods are shown to be capable of accurately detecting mean shifts, a limitation that applies to all three methods is that it is not possible to ascertain whether the process variable has moved from a biased state to an unbiased state or from an unbiased state to a biased state. In other words, the methods are really concerned with detection of changes in bias, not directly with the detection of nonzero bias.</p

Likelihood and Bayesian Methods for Accurate Identification of Measurement Biases in Pseudo Steady-State Processes

Two new approaches are presented for improved identification of measurement biases in linear pseudo steady-state processes. Both are designed to detect a change in the mean of a measured variable leading to an inference regarding the presence of a biased measurement. The first method is based on a likelihood ratio test for the presence of a mean shift. The second is based on a Bayesian decision rule (relying on prior distributions for unknown parameters) for the detection of a mean shift. The performance of these two methods is compared with that of a method given by Devanathan et al. (2000). For the process studied, both techniques were found to have higher identification power than the method of Devanathan et al. and appears to have excellent but sightly lower type I error performance than the Devanathan et al. method.This is an accepted manuscript of an article published as Likelihood and Bayesian methods for accurate identification of measurement biases in pseudo steady-state processes. Chemical Engineering Research and Design: Part A, 2005, Vol. 83(A12), pp. 1391-1398. With Sriram Devanathan and Derrick Rollins. © 2005. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/</p

Arabidopsis thaliana glyoxalase 2-1 is required during abiotic stress but is not essential under normal plant growth.

The glyoxalase pathway, which consists of the two enzymes, GLYOXALASE 1 (GLX 1) (E.C.: 4.4.1.5) and 2 (E.C.3.1.2.6), has a vital role in chemical detoxification. In Arabidopsis thaliana there are at least four different isoforms of glyoxalase 2, two of which, GLX2-1 and GLX2-4 have not been characterized in detail. Here, the functional role of Arabidopsis thaliana GLX2-1 is investigated. Glx2-1 loss-of-function mutants and plants that constitutively over-express GLX2-1 resemble wild-type plants under normal growth conditions. Insilico analysis of publicly available microarray datasets with ATTEDII, Mapman and Genevestigator indicate potential role(s) in stress response and acclimation. Results presented here demonstrate that GLX2-1 gene expression is up-regulated in wild type Arabidopsis thaliana by salt and anoxia stress, and by excess L-Threonine. Additionally, a mutation in GLX2-1 inhibits growth and survival during abiotic stresses. Metabolic profiling studies show alterations in the levels of sugars and amino acids during threonine stress in the plants. Elevated levels of polyamines, which are known stress markers, are also observed. Overall our results suggest that Arabidopsis thaliana GLX2-1 is not essential during normal plant life, but is required during specific stress conditions

Independent component analyses of polar metabolite fingerprints from <i>A.thaliana glx2-1,</i> GLX2-1-OE, and wild type plants.

<p>Comparison between <i>glx2-1+/−</i> Threonine (a), GLX2-1-OE +/− Threonine (b), Wild type +/− Threonine (c) and GLX2-1OE and Wild type +/− threonine (d) are shown. Independent component analyses scores (IC 01 on X-axis and IC 03 on Y-axis) demonstrates common differences in seedlings in response to <i>GLX2-1</i> levels and/or exogenous Threonine stress.</p