Cellular Growth Kinetics Distinguish a Cyclophilin Inhibitor from an HSP90 Inhibitor as a Selective Inhibitor of Hepatitis C Virus

During antiviral drug discovery, it is critical to distinguish molecules that selectively interrupt viral replication from those that reduce virus replication by adversely affecting host cell viability. In this report we investigate the selectivity of inhibitors of the host chaperone proteins cyclophilin A (CypA) and heat-shock protein 90 (HSP90) which have each been reported to inhibit replication of hepatitis C virus (HCV). By comparing the toxicity of the HSP90 inhibitor, 17-(Allylamino)-17-demethoxygeldanamycin (17-AAG) to two known cytostatic compounds, colchicine and gemcitabine, we provide evidence that 17-AAG exerts its antiviral effects indirectly through slowing cell growth. In contrast, a cyclophilin inhibitor, cyclosporin A (CsA), exhibited selective antiviral activity without slowing cell proliferation. Furthermore, we observed that 17-AAG had little antiviral effect in a non-dividing cell-culture model of HCV replication, while CsA reduced HCV titer by more than two orders of magnitude in the same model. The assays we describe here are useful for discriminating selective antivirals from compounds that indirectly affect virus replication by reducing host cell viability or slowing cell growth

Current technical approaches to brain energy metabolism

Neuroscience is a technology‐driven discipline and brain energy metabolism is no exception. Once satisfied with mapping metabolic pathways at organ level, we are now looking to learn what it is exactly that metabolic enzymes and transporters do and when, where do they reside, how are they regulated, and how do they relate to the specific functions of neurons, glial cells, and their subcellular domains and organelles, in different areas of the brain. Moreover, we aim to quantify the fluxes of metabolites within and between cells. Energy metabolism is not just a necessity for proper cell function and viability but plays specific roles in higher brain functions such as memory processing and behavior, whose mechanisms need to be understood at all hierarchical levels, from isolated proteins to whole subjects, in both health and disease. To this aim, the field takes advantage of diverse disciplines including anatomy, histology, physiology, biochemistry, bioenergetics, cellular biology, molecular biology, developmental biology, neurology, and mathematical modeling. This article presents a well‐referenced synopsis of the technical side of brain energy metabolism research. Detail and jargon are avoided whenever possible and emphasis is given to comparative strengths, limitations, and weaknesses, information that is often not available in regular articles.Fondecyt, Grant Number: 1160317; MINECO, Grant Numbers: SAF2016‐78114‐R and RTC‐2015‐3237‐1; CIBERFES, Grant Numer: CB16/10/00282; SP3‐People‐MC‐ITN program, Grant Number: 608381; EU BATCure, Grant Number: 666918; FEDER (European regional development fund); Investissement d'Avenir, Grant Number: ANR‐11‐INBS‐0011; French State in the context of the “Investments for the future” Program IdEx and the LabEx TRAIL, Grant Numbers: ANR‐10‐IDEX and ANR‐10‐LABX‐57; French–Swiss ANR‐FNS, Grant Numer: ANR‐15‐ CE37‐0012. University of Nottingham; BBSRC, Grant Numers: BB/L019396/1 and BB/K009192/1; MRC, Grant Number: MR/L020661/1; Deutsche Forschungsgemeinschaft, Grant Numers: DFG SPP 1757, SFB 894, and FOR 2289; European Commission, Grant Number: H2020‐FETPROACT 732344; Neurofibres, Grant Number: H2020‐MSCA‐ITN‐722053 EU‐GliaPhD; US National Institutes of Health, Grant Number: R01NS087611; Teva Pharmaceuticals; Agilent Technologies. IdEx, Grant Number: ANR‐10‐IDEX‐03‐02; French–Swiss ANR‐FNS, Grant number: 310030E‐164271; National Institutes of Neurologic Disease and Stroke at the National Institutes of Health, Grant Numer: R01 NS077773; University of Zurich and the Swiss National Science Foundation; Comisión Nacional de Investigación Científica y Tecnológica, Grant Numer: PB 01; Fondo Nacional de Desarrollo Científico y Tecnológico, Grant Numer: 1160317; Ministerio de Economía y Competitividad, Grant Numer: RTC‐2015‐3237‐1,SAF2016‐78114‐R; Agence Nationale de la Recherche, Grant Numers: ANR‐10‐IDEX, ANR‐10‐IDEX‐03‐02, ANR‐10‐LABX‐57, ANR‐11‐INBS‐0011, and ANR‐15‐ CE37‐0012; Biotechnology and Biological Sciences Research Council, Grant Numers: BB/L019396/1 and BB/K009192/1; Medical Research Council, Grant Numer: MR/L020661/1.Peer reviewe

Leukodystrophies: a proposed classification system based on pathological changes and pathogenetic mechanisms

Leukodystrophies are genetically determined disorders characterized by the selective involvement of the central nervous system white matter. Onset may be at any age, from prenatal life to senescence. Many leukodystrophies are degenerative in nature, but some only impair white matter function. The clinical course is mostly progressive, but may also be static or even improving with time. Progressive leukodystrophies are often fatal, and no curative treatment is known. The last decade has witnessed a tremendous increase in the number of defined leukodystrophies also owing to a diagnostic approach combining magnetic resonance imaging pattern recognition and next generation sequencing. Knowledge on white matter physiology and pathology has also dramatically built up. This led to the recognition that only few leukodystrophies are due to mutations in myelin- or oligodendrocyte-specific genes, and many are rather caused by defects in other white matter structural components, including astrocytes, microglia, axons and blood vessels. We here propose a novel classification of leukodystrophies that takes into account the primary involvement of any white matter component. Categories in this classification are the myelin disorders due to a primary defect in oligodendrocytes or myelin (hypomyelinating and demyelinating leukodystrophies, leukodystrophies with myelin vacuolization); astrocytopathies; leuko-axonopathies; microgliopathies; and leuko-vasculopathies. Following this classification, we illustrate the neuropathology and disease mechanisms of some leukodystrophies taken as example for each category. Some leukodystrophies fall into more than one category. Given the complex molecular and cellular interplay underlying white matter pathology, recognition of the cellular pathology behind a disease becomes crucial in addressing possible treatment strategies

Temperature dependence of methanol and the tensile strength of insulation paper: kinetics of the changes of mechanical properties during ageing

This paper reports the temperature-dependence of methanol generation and the tensile index under ageing conditions for two paper/oil systems: one consisting of a standard wood Kraft paper and the other of a thermally-upgraded Kraft paper (TUK). A linear correlation between methanol and the tensile index for these paper/oil systems was observed in a previous study at 170 °C. In the current study, the correlation was extended to a large range of temperatures (150–190 °C). The experimental data were fitted with a modified Calvini’s kinetic model, while the Arrhenius equation was used to model the kinetic of changes of the paper’s mechanical properties during ageing. Good agreement with the temperature (lnk vs. 1/T) was observed for the rate constants of the chain-end group production, methanol formation, and the decrease of mechanical properties. The Arrhenius equation applied to this data grouping showed activation energy of 130 ± 29 kJ/mol for the decrease in mechanical strength of the standard Kraft paper, while the value was 118 ± 55 kJ/mol for the TUK paper. These values are of the same order of magnitude as those obtained in this study and in the literature for the depolymerization of cellulose and the generation of methanol that was reported. This confirmed the close relationship between cellulose depolymerization, methanol generation and the reduction of the paper’s mechanical strength during ageing, dominated by the acid hydrolysis mechanism. The results, which can be seen as a benchmark and pave the way to further research, provide an opportunity for applying the proposed correlations to estimate the insulation condition in operating transformers