Protein kinases C: potential targets for intervention in diabetic nephropathy

Protein kinases C are a family of serine threonine protein kinases that play key roles in extracellular signal transduction. Inappropriate activation of protein kinase C has been implicated in the pathophysiology of many diseases, including diabetes mellitus. Indeed, protein kinase C activation may contribute not only to the pathogenesis of diabetic complications such as nephropathy and retinopathy, but also to insulin resistance. Growing awareness that protein kinase C isoforms subserve specific subcellular functions has led to the development of isoform-specific inhibitors, which may be useful investigational tools and therapeutic agents for attenuating the effects of inappropriate protein kinase C activity. Here we review the role played by protein kinases C in diabetic nephropathy and the recent progress that has been made to modulate its activity using specific inhibitors. Curr Opin Nephrol Hypertens 7:563-570. (C) 1998 Lippincott Wiiliams & Wilkins.

A novel dual-fluorescence strategy for functionally validating microRNA targets in 3-prime untranslated regions: regulation of the inward rectifier potassium channel Kir2.1 by miR-212.

Gene targeting by microRNAs is important in health and disease. We developed a functional assay for identifying microRNA targets and applied it to the K+ channel Kir2.1 (KCNJ2) which is dysregulated in cardiac and vascular disorders. The 3'UTR was inserted downstream of the mCherry red fluorescent protein coding sequence in a mammalian expression plasmid. MicroRNA sequences were inserted into the pSM30 expression vector which provides enhanced green fluorescent protein as an indicator of microRNA expression. HEK293 cells were co-transfected with the mCherry-3'UTR plasmid and a pSM30-based plasmid with a microRNA insert. The principle of the assay is that functional targeting of the 3'UTR by the microRNA results in a decrease in the red/green fluorescence intensity ratio as determined by automated image analysis. The method was validated with miR-1, a known downregulator of Kir2.1 expression, and was used to investigate targeting of the Kir2.1 3'UTR by miR-212. Red/green ratio was lower in miR-212-expressing cells compared to non-targeting controls, an effect that was attenuated by mutating the predicted target site. MiR-212 also reduced inward rectifier current and Kir2.1 protein in HeLa cells. This novel assay has several advantages over traditional luciferase-based assays including larger sample size, amenability to time course studies and adaptability to high-throughput screening.

Gaussian Approximation for Tracking Occluding and Interacting Targets

In this paper, we show how interacting and occluding targets can be tackled successfully within a Gaussian approximation. For that purpose, we develop a general expansion of the mean and covariance of the posterior and we consider a first order approximation of it. The proposed method differs from EKF in that neither a non-linear dynamical model nor a non-linear measurement vector to state relation have to be defined, so it works with any kind of interaction potential and likelihood. The approach has been tested on three sequences (10400, 2500, and 400 frames each one). The results show that our approach helps to reduce the number of failures without increasing too much the computation time with respect to methods that do not take into account target interactions.

Genome-wide profiling of methylation identifies novel targets with aberrant hyper-methylation and reduced expression in low-risk myelodysplastic syndromes

Gene expression profiling signatures may be used to classify the subtypes of Myelodysplastic syndrome (MDS) patients. However, there are few reports on the global methylation status in MDS. The integration of genome-wide epigenetic regulatory marks with gene expression levels would provide additional information regarding the biological differences between MDS and healthy controls. Gene expression and methylation status were measured using high-density microarrays. A total of 552 differentially methylated CpG loci were identified as being present in low-risk MDS; hypermethylated genes were more frequent than hypomethylated genes. In addition, mRNA expression profiling identified 1005 genes that significantly differed between low-risk MDS and the control group. Integrative analysis of the epigenetic and expression profiles revealed that 66.7% of the hypermethylated genes were underexpressed in low-risk MDS cases. Gene network analysis revealed molecular mechanisms associated with the low-risk MDS group, including altered apoptosis pathways. The two key apoptotic genes BCL2 and ETS1 were identified as silenced genes. In addition, the immune response and micro RNA biogenesis were affected by the hypermethylation and underexpression of IL27RA and DICER1. Our integrative analysis revealed that aberrant epigenetic regulation is a hallmark of low-risk MDS patients and could have a central role in these diseases.

Relativistic High Harmonic Generation In Gas Jet Targets

We experimentally demonstrate a new regime of high-order harmonic generation by relativistic-irradiance lasers in gas jet targets. Bright harmonics with both odd and even orders, generated by linearly as well as circularly polarized pulses, are emitted in the forward direction, while the base harmonic frequency is downshifted. A 9 TW laser generates harmonics up to 360 eV, within the 'water window' spectral region. With a 120 TW laser producing 40 uJ/sr per harmonic at 120 eV, we demonstrate the photon number scalability. The observed harmonics cannot be explained by previously suggested scenarios. A novel high-order harmonics generation mechanism [T. Zh. Esirkepov et al., AIP Proceedings, this volume], which explains our experimental findings, is based on the phenomena inherent in the relativistic laser - underdense plasma interactions (self-focusing, cavity evacuation, and bow wave generation), mathematical catastrophe theory which explains formation of electron density singularities (cusps), and collective radiation due to nonlinear oscillations of a compact charge.

Aminopeptidases of malaria parasites:new targets for chemotherapy

Novel targets for new drug development are urgently required to combat malaria, a disease that puts half of the world's population at risk. One group of enzymes identified within the genome of the most lethal of the causative agents of malaria, Plasmodium falciparum, that may have the potential to become new targets for antimalarial drug development are the aminopeptidases. These enzymes catalyse the cleavage of the N-terminal amino acids from proteins and peptides. P. falciparum appears to encode for at least nine aminopeptidases, two neutral aminopeptidases, one aspartyl aminopeptidase, one aminopeptidase P, one prolyl aminopeptidase and four methionine aminopeptidases. Recent advances in our understanding of these genes and their protein products are outlined in this review, including their potential for antimalarial drug development.

Ion Acceleration in Multispecies Targets Driven by Intense Laser Radiation Pressure

The acceleration of ions from ultrathin foils has been investigated by using 250 TW, subpicosecond laser pulses, focused to intensities of up to 3 X 10(20) W cm(-2). The ion spectra show the appearance of narrow-band features for protons and carbon ions peaked at higher energies (in the 5-10 MeV/nucleon range) and with significantly higher flux than previously reported. The spectral features and their scaling with laser and target parameters provide evidence of a multispecies scenario of radiation pressure acceleration in the light sail mode, as confirmed by analytical estimates and 2D particle-in-cell simulations. The scaling indicates that monoenergetic peaks with more than 100 MeV/nucleon are obtainable with moderate improvements of the target and laser characteristics, which are within reach of ongoing technical developments.

Demersal fish biodiversity: species-level indicators and trends-based targets for the Marine Strategy Framework Directive

The maintenance of biodiversity is a fundamental theme of the Marine Strategy Framework Directive. Appropriate indicators to monitor change in biodiversity, along with associated targets representing "good environmental status" (GES), are required to be in place by July 2012. A method for selecting species-specific metrics to fulfil various specified indicator roles is proposed for demersal fish communities. Available data frequently do not extend far enough back in time to allow GES to be defined empirically. In such situations, trends-based targets offer a pragmatic solution. A method is proposed for setting indicator-level targets for the number of species-specific metrics required to meet their trends-based metric-level targets. This is based on demonstrating significant departures from the binomial distribution. The procedure is trialled using North Sea demersal fish survey data. Although fisheries management in the North Sea has improved in recent decades, management goals to stop further decline in biodiversity, and to initiate recovery, are yet to be met.

Can we meet targets for biofuels and renewable energy in transport given the constraints imposed by policy in agriculture and energy?

The deployment of biofuels is significantly affected by policy in energy and agriculture. In the energy arena, concerns regarding the sustainability of biofuel systems and their impact on food prices led to a set of sustainability criteria in EU Directive 2009/28/EC on Renewable Energy. In addition, the 10% biofuels target by 2020 was replaced with a 10% renewable energy in transport target. This allows the share of renewable electricity used by electric vehicles to contribute to the mix in achieving the 2020 target. Furthermore, only biofuel systems that effect a 60% reduction in greenhouse gas emissions by 2020 compared with the fuel they replace are allowed to contribute to meeting the target. In the agricultural arena, cross-compliance (which is part of EU Common Agricultural Policy) dictates the allowable ratio of grassland to total agricultural land, and has a significant impact on which biofuels may be supported. This paper outlines the impact of these policy areas and their implications for the production and use of biofuels in terms of the 2020 target for 10% renewable transport energy, focusing on Ireland. The policies effectively impose constraints on many conventional energy crop biofuels and reinforce the merits of using biomethane, a gaseous biofuel. The analysis shows that Ireland can potentially satisfy 15% of renewable energy in transport by 2020 (allowing for double credit for biofuels from residues and ligno-cellulosic materials, as per Directive 2009/28/EC) through the use of indigenous biofuels: grass biomethane, waste and residue derived biofuels, electric vehicles and rapeseed biodiesel. © 2010 Elsevier Ltd. All rights reserved.

Investigation of the Human Brain Metabolome to Identify Potential Markers for Early Diagnosis and Therapeutic Targets of Alzheimer’s Disease

A study combining high resolution mass spectrometry (liquid chromatography-quadrupole time-of-flight-mass spectrometry, UPLC-QTof-MS) and chemometrics for the analysis of post-mortem brain tissue from subjects with Alzheimer’s disease (AD) (n = 15) and healthy age-matched controls (n = 15) was undertaken. The huge potential of this metabolomics approach for distinguishing AD cases is underlined by the correct prediction of disease status in 94–97% of cases. Predictive power was confirmed in a blind test set of 60 samples, reaching 100% diagnostic accuracy. The approach also indicated compounds significantly altered in concentration following the onset of human AD. Using orthogonal partial least-squares discriminant analysis (OPLS-DA), a multivariate model was created for both modes of acquisition explaining the maximum amount of variation between sample groups (Positive Mode-R2 = 97%; Q2 = 93%; root mean squared error of validation (RMSEV) = 13%; Negative Mode-R2 = 99%; Q2 = 92%; RMSEV = 15%). In brain extracts, 1264 and 1457 ions of interest were detected for the different modes of acquisition (positive and negative, respectively). Incorporation of gender into the model increased predictive accuracy and decreased RMSEV values. High resolution UPLC-QTof-MS has not previously been employed to biochemically profile post-mortem brain tissue, and the novel methods described and validated herein prove its potential for making new discoveries related to the etiology, pathophysiology, and treatment of degenerative brain disorders.