Inhibition of Mitogen-Activated Protein Kinase Erk1/2 Promotes Protein Degradation of ATP Binding Cassette Transporters A1 and G1 in CHO and in HuH7 cells.

Signal transduction modulates expression and activity of cholesterol transporters. We recently demonstrated that the Ras/mitogen-activated protein kinase (MAPK) signaling cascade regulates protein stability of Scavenger Receptor BI (SR-BI) through Proliferator Activator Receptor (PPARα) -dependent degradation pathways. In addition, MAPK (Mek/Erk 1/2) inhibition has been shown to influence liver X receptor (LXR) -inducible ATP Binding Cassette (ABC) transporter ABCA1 expression in macrophages. Here we investigated if Ras/MAPK signaling could alter expression and activity of ABCA1 and ABCG1 in steroidogenic and hepatic cell lines. We demonstrate that in Chinese Hamster Ovary (CHO) cells and human hepatic HuH7 cells, extracellular signal-regulated kinase 1/2 (Erk1/2) inhibition reduces PPARα-inducible ABCA1 protein levels, while ectopic expression of constitutively active H-Ras, K-Ras and MAPK/Erk kinase 1 (Mek1) increases ABCA1 protein expression, respectively. Furthermore, Mek1/2 inhibitors reduce ABCG1 protein levels in ABCG1 overexpressing CHO cells (CHO-ABCG1) and human embryonic kidney 293 (HEK293) cells treated with LXR agonist. This correlates with Mek1/2 inhibition reducing ABCG1 cell surface expression and decreasing cholesterol efflux onto High Density Lipoproteins (HDL). Real Time reverse transcriptase polymerase chain reaction (RT-PCR) and protein turnover studies reveal that Mek1/2 inhibitors do not target transcriptional regulation of ABCA1 and ABCG1, but promote ABCA1 and ABCG1 protein degradation in HuH7 and CHO cells, respectively. In line with published data from mouse macrophages, blocking Mek1/2 activity upregulates ABCA1 and ABCG1 protein levels in human THP1 macrophages, indicating opposite roles for the Ras/MAPK pathway in the regulation of ABC transporter activity in macrophages compared to steroidogenic and hepatic cell types. In summary, this study suggests that Ras/MAPK signaling modulates PPARα- and LXR-dependent protein degradation pathways in a cell-specific manner to regulate the expression levels of ABCA1 and ABCG1 transporters.

Characterization of Arabidopsis FPS isozymes and FPS gene expression analysis provide insight into the biosynthesis of isoprenoid precursors in seeds

Arabidopsis thaliana contains two genes encoding farnesyl diphosphate (FPP) synthase (FPS), the prenyl diphoshate synthase that catalyzes the synthesis of FPP from isopentenyl diphosphate (IPP) and dimethylallyl diphosphate (DMAPP). In this study, we provide evidence that the two Arabidopsis short FPS isozymes FPS1S and FPS2 localize to the cytosol. Both enzymes were expressed in E. coli, purified and biochemically characterized. Despite FPS1S and FPS2 share more than 90% amino acid sequence identity, FPS2 was found to be more efficient as a catalyst, more sensitive to the inhibitory effect of NaCl, and more resistant to thermal inactivation than FPS1S. Homology modelling for FPS1S and FPS2 and analysis of the amino acid differences between the two enzymes revealed an increase in surface polarity and a greater capacity to form surface salt bridges of FPS2 compared to FPS1S. These factors most likely account for the enhanced thermostability of FPS2. Expression analysis of FPS::GUS genes in seeds showed that FPS1 and FPS2 display complementary patterns of expression particularly at late stages of seed development, which suggests that Arabidopsis seeds have two spatially segregated sources of FPP. Functional complementation studies of the Arabidopsis fps2 knockout mutant seed phenotypes demonstrated that under normal conditions FPS1S and FPS2 are functionally interchangeable. A putative role for FPS2 in maintaining seed germination capacity under adverse environmental conditions is discussed.

Report on a review of selected general and application controls over the Iowa State University of Science and Technology Accounts Receivable System for the period of March 29, 2010 through May 6, 2010

Report on a review of selected general and application controls over the Iowa State University of Science and Technology Accounts Receivable System for the period of March 29, 2010 through May 6, 2010

Audit report of Iowa State University of Science and Technology, Ames, Iowa (Iowa State University) as of and for the years ended June 30, 2010 and 2009

Audit report of Iowa State University of Science and Technology, Ames, Iowa (Iowa State University) as of and for the years ended June 30, 2010 and 2009

The recent breakthroughs in the understanding of host genomics in hepatitis C.

BACKGROUND: Hepatitis C Virus (HCV) infection is spontaneously resolved in about 30% of acutely infected individuals. In those who progress to chronic hepatitis C, HCV therapy permanently eradicates infection in about 40% of cases. It has long been suspected that host genetic factors are key determinants for the control of HCV infection. DESIGN: We will review in this study four genome-wide association studies (GWAS) and two large candidate gene studies that assessed the role of host genetic variation for the natural and treatment-induced control of HCV infection. RESULTS: The studies consistently identified genetic variation in interleukin 28B (IL28B) as the strongest predictor for the control of HCV infection. Importantly, single nucleotide polymorphisms (SNPs) in IL28B strongly predicted both spontaneous and treatment-induced HCV recovery. IL28B is located on chromosome 19 and encodes interferon-λ, a type III interferon with antiviral activity, which is mediated through the JAK-STAT pathway by inducing interferon-stimulated genes. The SNPs identified in the GWAS are in high linkage disequilibrium with coding or functional non-coding SNPs that might modulate function and/or expression of IL28B. The role of the different IL28B alleles on gene expression and cytokine function has not yet been established. CONCLUSIONS: These findings provide strong genetic evidence for the influence of interferon-λ for both the natural and treatment-induced control of HCV infection, and support the further investigation of interferon-λ for the treatment of chronic hepatitis C. Furthermore, genetic testing before HCV therapy could provide important information towards an individualized HCV treatment.

Report of Recommendations to Iowa State University of Science and Technology, Ames, Iowa, for the year ended June 30, 2010

Report on Iowa State University of Science and Technology, Ames, Iowa, for the year ended June 30, 2010

Audit report on the Student Health Facility Revenue Bond Funds of Iowa State University of Science and Technology for the year ended June 30, 2011

Audit report on the Student Health Facility Revenue Bond Funds of Iowa State University of Science and Technology for the year ended June 30, 2011

Agreed-upon procedures report on the Iowa State Center Business Office of Iowa State University of Science and Technology for the year ended June 30, 2011

Agreed-upon procedures report on the Iowa State Center Business Office of Iowa State University of Science and Technology for the year ended June 30, 2011

Audit report of the accompanying Schedule of Debt Service and Coverage for Iowa State University of Science and Technology as of February 10, 2012 for the Athletic Facilities Revenue Bond Funds

Audit report of the accompanying Schedule of Debt Service and Coverage for Iowa State University of Science and Technology as of February 10, 2012 for the Athletic Facilities Revenue Bond Funds

Model-Free Reconstruction of Excitatory Neuronal Connectivity from Calcium Imaging Signals

A systematic assessment of global neural network connectivity through direct electrophysiological assays has remained technically infeasible, even in simpler systems like dissociated neuronal cultures. We introduce an improved algorithmic approach based on Transfer Entropy to reconstruct structural connectivity from network activity monitored through calcium imaging. We focus in this study on the inference of excitatory synaptic links. Based on information theory, our method requires no prior assumptions on the statistics of neuronal firing and neuronal connections. The performance of our algorithm is benchmarked on surrogate time series of calcium fluorescence generated by the simulated dynamics of a network with known ground-truth topology. We find that the functional network topology revealed by Transfer Entropy depends qualitatively on the time-dependent dynamic state of the network (bursting or non-bursting). Thus by conditioning with respect to the global mean activity, we improve the performance of our method. This allows us to focus the analysis to specific dynamical regimes of the network in which the inferred functional connectivity is shaped by monosynaptic excitatory connections, rather than by collective synchrony. Our method can discriminate between actual causal influences between neurons and spurious non-causal correlations due to light scattering artifacts, which inherently affect the quality of fluorescence imaging. Compared to other reconstruction strategies such as cross-correlation or Granger Causality methods, our method based on improved Transfer Entropy is remarkably more accurate. In particular, it provides a good estimation of the excitatory network clustering coefficient, allowing for discrimination between weakly and strongly clustered topologies. Finally, we demonstrate the applicability of our method to analyses of real recordings of in vitro disinhibited cortical cultures where we suggest that excitatory connections are characterized by an elevated level of clustering compared to a random graph (although not extreme) and can be markedly non-local.

Le diabète de type 2 est-il uniquement une affaire d'hyperglycémie? Entre science, humanisme et economie [Type 2 diabetes, is it just a case of hyperglycemia? Confusion between the interests of science, humanity and the economy]

The recommendations for the treatment of type 2 diabetic patients are often centered on the glycemia. These clinical trials based on this approach show only a beneficial effects on the prevention of microangiopathy. The coronary artery disease which is the main cause of mortality among these patients, is not reduced. These data should be interpreted with a systemic prospect. The diabetes vascular complications have multifactorial causes and these clinical trials are motivated for the promotion of hypoglycemic agents. Fortunately, the STENO study offers another glance on the treatment of the diabetes, associating multirisk approach and patients' accompaniment. It obliges to have a critical glance on the research often moved by economic issues and gives to the center a humanistic approach based on the therapeutic relation.

Report on a review of selected application controls over the Iowa State University of Science and Technology Facilities Planning and Management - Facilities Administrative Management Information System for the period of April 18, 2011 through May 16, 2011

Report on a review of selected application controls over the Iowa State University of Science and Technology Facilities Planning and Management - Facilities Administrative Management Information System for the period of April 18, 2011 through May 16, 2011

Report of Recommendations to Iowa State University of Science and Technology, Ames, Iowa, for the year ended June 30, 2011

Report on Iowa State University of Science and Technology, Ames, Iowa, for the year ended June 30, 2011

Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models

Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions.

Modelling the evolution and spread of HIV immune escape mutants.

During infection with human immunodeficiency virus (HIV), immune pressure from cytotoxic T-lymphocytes (CTLs) selects for viral mutants that confer escape from CTL recognition. These escape variants can be transmitted between individuals where, depending upon their cost to viral fitness and the CTL responses made by the recipient, they may revert. The rates of within-host evolution and their concordant impact upon the rate of spread of escape mutants at the population level are uncertain. Here we present a mathematical model of within-host evolution of escape mutants, transmission of these variants between hosts and subsequent reversion in new hosts. The model is an extension of the well-known SI model of disease transmission and includes three further parameters that describe host immunogenetic heterogeneity and rates of within host viral evolution. We use the model to explain why some escape mutants appear to have stable prevalence whilst others are spreading through the population. Further, we use it to compare diverse datasets on CTL escape, highlighting where different sources agree or disagree on within-host evolutionary rates. The several dozen CTL epitopes we survey from HIV-1 gag, RT and nef reveal a relatively sedate rate of evolution with average rates of escape measured in years and reversion in decades. For many epitopes in HIV, occasional rapid within-host evolution is not reflected in fast evolution at the population level.