Hepatitis B virus and hepatitis C virus affect mitochondrial function through different metabolic pathways, explaining virus-specific clinical features of chronic hepatitis.

BACKGROUND: Hepatitis C virus (HCV) and hepatitis B virus (HBV) cause chronic hepatitis with important clinical differences. HCV causes hepatic steatosis and insulin resistance, while HBV confers increased risk of liver cancer. We hypothesised these differences may be due to virus-specific effects on mitochondrial function. METHODS: Seahorse technology was utilised to investigate effects of virus infection on mitochondrial function. Cell based assays were used to measure mitochondrial membrane potential and quantify pyruvate and lactate. Mass spectrometry was performed on mitochondria isolated from HBV expressing, HCV infected and control cells cultured with isotope-labelled amino acids, to identify proteins with different abundance. Altered expression of key mitochondrial proteins was confirmed by real time PCR and western blot. RESULTS: Reduced mitochondrial function and ATP production were observed with HCV infection and HBV expression. HCV impairs glycolysis and reduces expression of genes regulating fatty acid oxidation, promoting lipid accumulation. HBV causes lactate accumulation by increasing expression of lactate dehydrogenase A, which converts pyruvate to lactate. In HBV expressing cells there was marked enrichment of pyruvate dehydrogenase kinase, inhibiting conversion of pyruvate to acetyl-CoA and thereby reducing its availability for mitochondrial oxidative phosphorylation. CONCLUSIONS: HCV and HBV impair mitochondrial function and reduce ATP production. HCV reduces acetyl-CoA availability for energy production by impairing fatty acid oxidation, causing lipid accumulation and hepatic steatosis. HBV has no effect on fatty oxidation but reduces acetyl-CoA availability by disrupting pyruvate metabolism. This promotes lactic acidosis and oxidative stress, increasing the risk of disease progression and liver cancer.

Metabolism-based category formation for the prioritisation of genotoxicity hazard assessment for plant protection product residues (Part 4): α-Chloroacetamides.

In dietary risk assessment of plant protection products, residues of active ingredients and their metabolites need to be evaluated for their genotoxic potential. The European Food Safety Authority recommend a tiered approach focussing assessment and testing on classes of similar chemicals. To characterise similarity, in terms of metabolism, a metabolic similarity profiling scheme has been developed from an analysis of 69 α-chloroacetamide herbicides for which either Ames, chromosomal aberration or micronucleus test results are publicly available. A set of structural space alerts were defined, each linked to a key metabolic transformation present in the α-chloroacetamide metabolic space. The structural space alerts were combined with covalent chemistry profiling to develop categories suitable for chemical prioritisation via read-across. The method is a robust and reproducible approach to such read-across predictions, with the potential to reduce unnecessary testing. The key challenge in the approach was identified as being the need for metabolism data individual groups of plant protection products as the basis for the development of the structural space alerts.

Metabolism-based category formation for the prioritisation of genotoxicity hazard assessment for plant protection product residues (part 3): Strobilurins.

In dietary risk assessment of plant protection products, residues of active ingredients and their metabolites need to be evaluated for their genotoxic potential. The European Food Safety Authority recommend a tiered approach focussing assessment and testing on classes of similar chemicals. To characterise similarity, in terms of metabolism, a metabolic similarity profiling scheme has been developed from an analysis of 46 chemicals of strobilurin fungicides and their metabolites for which either Ames, chromosomal aberration or micronucleus test results are publicly available. This profiling scheme consists of a set of ten sub-structures, each linked to a key metabolic transformation present in the strobilurin metabolic space. This metabolic similarity profiling scheme was combined with covalent chemistry profiling and physico-chemistry properties to develop chemical categories suitable for chemical prioritisation via read-across. The method is a robust and reproducible approach to such read-across predictions, with the potential to reduce unnecessary testing. The key challenge in the approach was identified as being the need for metabolism data and individual groups of plant protection products as the basis for the development of such profiling schemes.

PEMT Mediates Hepatitis C Virus-Induced Steatosis, Explains Genotype-Specific Phenotypes and Supports Virus Replication.

The hepatitis C virus (HCV) relies on cellular lipid pathways for virus replication and also induces liver steatosis, but the mechanisms involved are not clear. We performed a quantitative lipidomics analysis of virus-infected cells by combining high-performance thin-layer chromatography (HPTLC) and mass spectrometry, using an established HCV cell culture model and subcellular fractionation. Neutral lipid and phospholipids were increased in the HCV-infected cells; in the endoplasmic reticulum there was an ~four-fold increase in free cholesterol and an ~three-fold increase in phosphatidyl choline (p < 0.05). The increase in phosphatidyl choline was due to the induction of a non-canonical synthesis pathway involving phosphatidyl ethanolamine transferase (PEMT). An HCV infection induced expression of PEMT while knocking down PEMT with siRNA inhibited virus replication. As well as supporting virus replication, PEMT mediates steatosis. Consistently, HCV induced the expression of the pro-lipogenic genes SREBP 1c and DGAT1 while inhibiting the expression of MTP, promoting lipid accumulation. Knocking down PEMT reversed these changes and reduced the lipid content in virus-infected cells. Interestingly, PEMT expression was over 50% higher in liver biopsies from people infected with the HCV genotype 3 than 1, and three times higher than in people with chronic hepatitis B, suggesting that this may account for genotype-dependent differences in the prevalence of hepatic steatosis. PEMT is a key enzyme for promoting the accumulation of lipids in HCV-infected cells and supports virus replication. The induction of PEMT may account for virus genotype specific differences in hepatic steatosis.

Sub-structure-based category formation for the prioritisation of genotoxicity hazard assessment for pesticide residues (part 2): Triazoles.

In dietary risk assessment, residues of pesticidal ingredients or their metabolites need to be evaluated for their genotoxic potential. The European Food Safety Authority recommend a tiered approach focussing assessment and testing on classes of similar chemicals. To characterise similarity and to identify structural alerts associated with genotoxic concern, a set of chemical sub-structures was derived for an example dataset of 66 triazole agrochemicals for which either Ames, chromosomal aberration or micronucleus test results are publicly available. This analysis resulted in a set of ten structural alerts that define the chemical space, in terms of the common parent and metabolic scaffolds, associated with the triazole chemical class. An analysis of the available profiling schemes for DNA and protein reactivity shows the importance of investigating the predictivity of such schemes within a well-defined area of structural space. Structural space alerts, covalent chemistry profiling and physico-chemistry properties were combined to develop chemical categories suitable for chemical prioritisation. The method is a robust and reproducible approach to such read-across predictions, with the potential to reduce unnecessary testing. The key challenge in the approach was identified as being the need for pesticide-class specific metabolism data as the basis for structural space alert development.

Sub-structure-based category formation for the prioritisation of genotoxicity hazard assessment for pesticide residues: Sulphonyl ureas.

In dietary risk assessment, residues of pesticidal ingredients or their metabolites need to be evaluated for their genotoxic potential. The European Food Safety Authority recommend a tiered approach focussing assessment and testing on classes of similar chemicals. To characterise similarity and to identify structural alerts associated with genotoxic concern, a set of chemical sub-structures was derived for an example dataset of 74 sulphonyl urea agrochemicals for which either Ames, chromosomal aberration or micronucleus test results are publicly available. This analysis resulted in a set of seven structural alerts that define the chemical space, in terms of the common parent and metabolic scaffolds, associated with the sulphonyl urea chemical class. An analysis of the available profiling schemes for DNA and protein reactivity shows the importance of investigating the predictivity of such schemes within a well-defined area of structural space. Structural space alerts, covalent chemistry profiling and physico-chemistry properties were combined to develop chemical categories suitable for chemical prioritisation. The method is a robust and reproducible approach to such read-across predictions, with the potential to reduce unnecessary testing. The key challenge in the approach was identified as being the need for pesticide-class specific metabolism data as the basis for structural space alert development.

Molecular fingerprint-derived similarity measures for toxicological read-across: Recommendations for optimal use.

Computational approaches are increasingly used to predict toxicity due, in part, to pressures to find alternatives to animal testing. Read-across is the "new paradigm" which aims to predict toxicity by identifying similar, data rich, source compounds. This assumes that similar molecules tend to exhibit similar activities i.e. molecular similarity is integral to read-across. Various of molecular fingerprints and similarity measures may be used to calculate molecular similarity. This study investigated the value and concordance of the Tanimoto similarity values calculated using six widely used fingerprints within six toxicological datasets. There was considerable variability in the similarity values calculated from the various molecular fingerprints for diverse compounds, although they were reasonably concordant for homologous series acting via a common mechanism. The results suggest generic fingerprint-derived similarities are likely to be optimally predictive for local datasets, i.e. following sub-categorisation. Thus, for read-across, generic fingerprint-derived similarities are likely to be most predictive after chemicals are placed into categories (or groups), then similarity is calculated within those categories, rather than for a whole chemically diverse dataset.

Brain-specific HIV Nef identified in multiple patients with neurological disease.

HIV-1 Nef is a flexible, multifunctional protein with several cellular targets that is required for pathogenicity of the virus. This protein maintains a high degree of genetic variation among intra- and inter-host isolates. HIV Nef is relevant to HIV-associated neurological diseases (HAND) in patients treated with combined antiretroviral therapy because of the protein's role in promoting survival and migration of infected brain macrophages. In this study, we analyzed 2020 HIV Nef sequences derived from 22 different tissues and 31 subjects using a novel computational approach. This approach combines statistical regression and evolved neural networks (ENNs) to classify brain sequences based on the physical and chemical characteristics of functional Nef domains. Based on training, testing, and validation data, the method successfully classified brain Nef sequences at 84.5% and provided informative features for further examination. These included physicochemical features associated with the Src-homology-3 binding domain, the Nef loop (including the AP-2 Binding region), and a cytokine-binding domain. Non-brain sequences from patients with HIV-associated neurological disease were frequently classified as brain, suggesting that the approach could indicate neurological risk using blood-derived virus or for the development of biomarkers for use in assay systems aimed at drug efficacy studies for the treatment of HIV-associated neurological diseases.

Calsyntenin-1 mediates hepatitis C virus replication.

The hepatitis C virus (HCV) RNA genome of 9.6 kb encodes only 10 proteins, and so is highly dependent on host hepatocyte factors to facilitate replication. We aimed to identify host factors involved in the egress of viral particles. By screening the supernatant of HCV-infected Huh7 cells using SILAC-based proteomics, we identified the transmembrane protein calsyntenin-1 as a factor specifically secreted by infected cells. Calsyntenin-1 has previously been shown to mediate transport of endosomes along microtubules in neurons, through interactions with kinesin light chain-1. Here we demonstrate for the first time, we believe, a similar role for calsyntenin-1 in Huh7 cells, mediating intracellular transport of endosomes. In HCV-infected cells we show that calsyntenin-1 contributes to the early stages of the viral replication cycle and the formation of the replication complex. Importantly, we demonstrate in our model that silencing calsyntenin-1 disrupts the viral replication cycle, confirming the reliance of HCV on this protein as a host factor. Characterizing the function of calsyntenin-1 will increase our understanding of the HCV replication cycle and pathogenesis, with potential application to other viruses sharing common pathways.

Time-driven superoscillations with negative refraction.

The flat-lens concept based on negative refraction proposed by Veselago in 1968 has been mostly investigated in the monochromatic regime. It was recently recognized that time development of the superlensing effect discovered in 2000 by Pendry is yet to be assessed and may spring surprises: Time-dependent illumination could improve the spatial resolution of the focusing. We investigate dynamics of flexural wave focusing by a 45°-tilted square lattice of circular holes drilled in a duralumin plate. Time-resolved experiments reveal that the focused image shrinks with time below the diffraction limit, with a lateral resolution increasing from 0.8λ to 0.35λ, whereas focusing under harmonic excitation remains diffraction limited. Modal analysis reveals the role in pulse reconstruction of radiating lens resonances, which repeatedly self-synchronize at the focal spot to shape a superoscillating field.

Mechanism-Based QSAR Modeling of Skin Sensitization.

Many chemicals can induce skin sensitization, and there is a pressing need for non-animal methods to give a quantitative indication of potency. Using two large published data sets of skin sensitizers, we have allocated each sensitizing chemical to one of 10 mechanistic categories and then developed good QSAR models for the seven categories that have a sufficient number of chemicals to allow modeling. Both internal and external validation checks showed that each model had good predictivity.

Proposal of an in silico profiler for categorisation of repeat dose toxicity data of hair dyes.

This study outlines the analysis of 94 chemicals with repeat dose toxicity data taken from Scientific Committee on Consumer Safety opinions for commonly used hair dyes in the European Union. Structural similarity was applied to group these chemicals into categories. Subsequent mechanistic analysis suggested that toxicity to mitochondria is potentially a key driver of repeat dose toxicity for chemicals within each of the categories. The mechanistic hypothesis allowed for an in silico profiler consisting of four mechanism-based structural alerts to be proposed. These structural alerts related to a number of important chemical classes such as quinones, anthraquinones, substituted nitrobenzenes and aromatic azos. This in silico profiler is intended for grouping chemicals into mechanism-based categories within the adverse outcome pathway paradigm.

Chemical determinants of occupational hypersensitivity pneumonitis.

BACKGROUND: Workplace inhalational exposures to low molecular weight (LMW) chemicals cause hypersensitivity pneumonitis (HP) as well as the more common manifestation of respiratory hypersensitivity, occupational asthma (OA). AIMS: To explore whether chemical causation of HP is associated with different structural and physico-chemical determinants from OA. METHODS: Chemical causes of human cases of HP and OA were identified from searches of peer-reviewed literature up to the end of 2011. Each chemical was categorized according to whether or not it had been the attributed cause of at least one case of HP. The predicted asthma hazard was determined for each chemical using a previously developed quantitative structure-activity relationship (QSAR) model. The chemicals in both sets were independently and 'blindly' analysed by an expert in mech anistic chemistry for a qualitative prediction of protein cross-linking potential and determination of lipophilicity (log K ow). RESULTS: Ten HP-causing chemicals were identified and had a higher median QSAR predicted asthma hazard than the control group of 101 OA-causing chemicals (P < 0.01). Nine of 10 HP-causing chemicals were predicted to be protein cross-linkers compared with 24/92 controls (P < 0.001). The distributions of log K ow indicated higher values for the HP list (median 3.47) compared with controls (median 0.81) (P < 0.05). CONCLUSIONS: These findings suggest that chemicals capable of causing HP tend to have higher predicted asthma hazard, are more lipophilic and are more likely to be protein cross-linkers than those causing OA.

Endocannabinoid CB1 antagonists inhibit hepatitis C virus production, providing a novel class of antiviral host-targeting agents.

Direct-acting antivirals have significantly improved treatment outcomes in chronic hepatitis C (CHC), but side effects, drug resistance and cost mean that better treatments are still needed. Lipid metabolism is closely linked with hepatitis C virus (HCV) replication, and endocannabinoids are major regulators of lipid homeostasis. The cannabinoid 1 (CB1) receptor mediates these effects in the liver. We have previously shown upregulation of CB1 receptors in the livers of patients with CHC, and in a HCV cell-culture model. Here, we investigated whether CB1 blockade inhibited HCV replication. The antiviral effect of a CB1 antagonist, N-(piperidin-1-yl)-5-(4-iodophenyl)-1-(2,4-dichlorophenyl)-4-methyl-1H-pyrazole-3-carboxamide (AM251), was examined in HCV strain JFH1 cell-culture and subgenomic replicon models. The effects on the expression of genes involved in lipid metabolism were also measured. CB1 short hairpin RNA (shRNA) was used to confirm that the effects were specific for the cannabinoid receptor. Treatment with AM251 strongly inhibited HCV RNA (~70 %), viral protein (~80 %), the production of new virus particles (~70 %) and virus infectivity (~90 %). As expected, AM251 reduced the expression of pro-lipogenic genes (SREBP-1c, FASN, SCD1 and ACC1) and stimulated genes promoting lipid oxidation (CPT1 and PPARα). This effect was mediated by AMP-activated protein kinase (AMPK). Stable CB1 knockdown of cells infected with HCV showed reduced levels of HCV RNA compared with controls. Thus, reduced CB1 signalling inhibits HCV replication using either pharmacological inhibitors or CB1 shRNA. This may be due, at least in part, to reduced lipogenesis, mediated by AMPK activation. We suggest that CB1 antagonists may represent an entirely new class of drug with activity against HCV.

Scattering by complex inhomogeneous objects: a first-order reciprocity method.

The scattering by slightly inhomogeneous objects has been studied by a first-order method and reciprocity theorem. The scattering calculation reported in this manuscript is based on a simple computation of the field in a defectless structure at different incidence angles. The numerical results have been compared to those given by an exact calculation. It is shown that the method enables to handle complex structures with an affordable computational burden. A major advantage of the method is its ability to treat different defects without recomputing the field, i.e, the main part of the computation time. In addition, for defects in periodic structures, the field computation can be limited to a single period thus leading to an important decrease of the computational time and required memory. This method is believed to provide significant advantages for the engineering of optical devices.

Experiments on seismic metamaterials: molding surface waves.

Materials engineered at the micro- and nanometer scales have had a tremendous and lasting impact in photonics and phononics. At much larger scales, natural soils civil engineered at decimeter to meter scales may interact with seismic waves when the global properties of the medium are modified, or alternatively thanks to a seismic metamaterial constituted of a mesh of vertical empty inclusions bored in the initial soil. Here, we show the experimental results of a seismic test carried out using seismic waves generated by a monochromatic vibrocompaction probe. Measurements of the particles' velocities show a modification of the seismic energy distribution in the presence of the metamaterial in agreement with numerical simulations using an approximate plate model. For complex natural materials such as soils, this large-scale experiment was needed to show the practical feasibility of seismic metamaterials and to stress their importance for applications in civil engineering. We anticipate this experiment to be a starting point for smart devices for anthropic and natural vibrations.

An update on irreversible electroporation of liver tumours.

OBJECTIVE. To investigate the clinical efficacy and safety of irreversible electroporation for ablation of liver tumour in humans. DATA SOURCES. The PubMed and MEDLINE databases were systematically searched. STUDY SELECTION. Clinical research published in English in the last 10 years until October 2013 that address clinical issues related to irreversible electroporation of human liver tumours were selected. "Liver tumor", "local ablative therapy", and "irreversible electroporation" were used as the search terms. DATA EXTRACTION AND SYNTHESIS. The data extracted for this review was analysed by the authors, with a focus on the clinical efficacy and the safety of irreversible electroporation. The complete response rates look promising, ranging from 72% to 100%, except in one study in a subgroup of liver tumours in which the complete response rate was only 50% that was likely due to the inclusion of larger-size tumours. In one study, the local recurrence rate at 12 months was approximately 40%. As for the safety of irreversible electroporation, there were only a few reported complications (cardiac arrhythmia, pneumothorax, and electrolyte disturbance) that were mostly transient and not serious. There was no reported mortality related to the use of irreversible electroporation. CONCLUSION. Irreversible electroporation is a potentially effective liver tumour ablative therapy that gives rise to only mild and transient side-effects. Further studies with better patient selection criteria and longer follow-up are needed to clarify its role as a first-line liver tumour treatment modality.

Sun protection and hydration of stratum corneum: a study by 2-D differential method.

OBJECTIVE: The stratum corneum is the outermost layer of the skin. Its components and its morphology (such as the size of its cells) play a role in sun protection, and it has been noted that the stratum corneum hydration can change these properties. Sunscreens, applied on the skin, can be more or less effective depending on the stratum corneum characteristics. We therefore propose to simulate the quality of the sun protection and the effect of the stratum corneum hydration on the sun protection. METHODS: We first determined the sunscreen distribution on a plastic substrate using an optical coherence tomography device. We were then able to calculate, by 2-D differential method, the extinction of several sunscreens. We modelled the hydration of the stratum corneum, by changing the substrate with corneocytes of different thicknesses. RESULTS: Our results showed that hydrated stratum corneum protects more against the UV. The benefit from changing the substrate varies depending on the sunscreen applied. CONCLUSION: We modelled sunscreens on different substrates using electromagnetic simulations. To compare these results with measurements, we have to carefully hydrate or dehydrate the SC: the simulations did not take into account modifications of the surface (water on the surface for example) or any change in the characteristics of the stratum corneum other than the modification of the corneocytes thickness.

Causal reasoning on biological networks: interpreting transcriptional changes.

MOTIVATION: The interpretation of high-throughput datasets has remained one of the central challenges of computational biology over the past decade. Furthermore, as the amount of biological knowledge increases, it becomes more and more difficult to integrate this large body of knowledge in a meaningful manner. In this article, we propose a particular solution to both of these challenges. METHODS: We integrate available biological knowledge by constructing a network of molecular interactions of a specific kind: causal interactions. The resulting causal graph can be queried to suggest molecular hypotheses that explain the variations observed in a high-throughput gene expression experiment. We show that a simple scoring function can discriminate between a large number of competing molecular hypotheses about the upstream cause of the changes observed in a gene expression profile. We then develop an analytical method for computing the statistical significance of each score. This analytical method also helps assess the effects of random or adversarial noise on the predictive power of our model. RESULTS: Our results show that the causal graph we constructed from known biological literature is extremely robust to random noise and to missing or spurious information. We demonstrate the power of our causal reasoning model on two specific examples, one from a cancer dataset and the other from a cardiac hypertrophy experiment. We conclude that causal reasoning models provide a valuable addition to the biologist's toolkit for the interpretation of gene expression data. AVAILABILITY AND IMPLEMENTATION: R source code for the method is available upon request.