Development of CMX001 for the Treatment of Poxvirus Infections

CMX001 (phosphonic acid, [[(S)-2-(4-amino-2-oxo-1(2H)-pyrimidinyl)-1-(hydroxymethyl)ethoxy]methyl]mono[3-(hexadecyloxy)propyl] ester) is a lipid conjugate of the acyclic nucleotide phosphonate, cidofovir (CDV). CMX001 is currently in Phase II clinical trials for the prophylaxis of human cytomegalovirus infection and under development using the Animal Rule for smallpox infection. It has proven effective in reduction of morbidity and mortality in animal models of human smallpox, even after the onset of lesions and other clinical signs of disease. CMX001 and CDV are active against all five families of double-stranded DNA (dsDNA) viruses that cause human morbidity and mortality, including orthopoxviruses such as variola virus, the cause of human smallpox. However, the clinical utility of CDV is limited by the requirement for intravenous dosing and a high incidence of acute kidney toxicity. The risk of nephrotoxicity necessitates pre-hydration and probenecid administration in a health care facility, further complicating high volume CDV use in an emergency situation. Compared with CDV, CMX001 has a number of advantages for treatment of smallpox in an emergency including greater potency in vitro against all dsDNA viruses that cause human disease, a high genetic barrier to resistance, convenient oral administration as a tablet or liquid, and no evidence to date of nephrotoxicity in either animals or humans. The apparent lack of nephrotoxicity observed with CMX001 in vivo is because it is not a substrate for the human organic anion transporters that actively secrete CDV into kidney cells. The ability to test the safety and efficacy of CMX001 in patients with life-threatening dsDNA virus infections which share many basic traits with variola is a major advantage in the development of this antiviral for a smallpox indication

The mitochondrial permeability transition in cell death: a common mechanism in necrosis, apoptosis and autophagy

AbstractUsing confocal microscopy, onset of the mitochondrial permeability transition (MPT) in individual mitochondria within living cells can be visualized by the redistribution of the cytosolic fluorophore, calcein, into mitochondria. Simultaneously, mitochondria release membrane potential-indicating fluorophores like tetramethylrhodamine methylester. The MPT occurs in several forms of necrotic cell death, including oxidative stress, pH-dependent ischemia/reperfusion injury and Ca2+ ionophore toxicity. Cyclosporin A (CsA) and trifluoperazine block the MPT in these models and prevent cell killing, showing that the MPT is a causative factor in necrotic cell death. During oxidative injury induced by t-butylhydroperoxide, onset of the MPT is preceded by pyridine nucleotide oxidation, mitochondrial generation of reactive oxygen species, and an increase of mitochondrial free Ca2+, all changes that promote the MPT. During tissue ischemia, acidosis develops. Because of acidotic pH, anoxic cell death is substantially delayed. However, when pH is restored to normal after reperfusion (reoxygenation at pH 7.4), cell death occurs rapidly (pH paradox). This killing is caused by pH-dependent onset of the MPT, which is blocked by reperfusion at acidotic pH or with CsA. In isolated mitochondria, toxicants causing Reye’s syndrome, such as salicylate and valproate, induce the MPT. Similarly, salicylate induces a CsA-sensitive MPT and killing of cultured hepatocytes. These in vitro findings suggest that the MPT is the pathophysiological mechanism underlying Reye’s syndrome in vivo. Kroemer and coworkers proposed that the MPT is a critical event in the progression of apoptotic cell death. Using confocal microscopy, the MPT can be directly documented during tumor necrosis factor-α induced apoptosis in hepatocytes. CsA blocks this MPT and prevents apoptosis. The MPT does not occur uniformly during apoptosis. Initially, a small proportion of mitochondria undergo the MPT, which increases to nearly 100% over 1–3 h. A technique based on fluorescence resonance energy transfer can selectively reveal mitochondrial depolarization. After nutrient deprivation, a small fraction of mitochondria spontaneously depolarize and enter an acidic lysosomal compartment, suggesting that the MPT precedes the normal process of mitochondrial autophagy. A model is proposed in which onset of the MPT to increasing numbers of mitochondria within a cell leads progressively to autophagy, apoptosis and necrotic cell death

Rapid, metal-free and aqueous synthesis of imidazo[1,2-a]pyridine under ambient conditions

A novel, rapid and efficient route to imidazo[1,2-a]pyridines under ambient, aqueous and metal-free conditions is reported. The NaOH-promoted cycloisomerisations of N-propargylpyridiniums give quantitative yield in a few minutes (10 g scale). A comparison of common green metrics to current routes showed clear improvements, with at least a one order of magnitude increase in space-time-yield

PIPS: Pathogenicity Island Prediction Software

The adaptability of pathogenic bacteria to hosts is influenced by the genomic plasticity of the bacteria, which can be increased by such mechanisms as horizontal gene transfer. Pathogenicity islands play a major role in this type of gene transfer because they are large, horizontally acquired regions that harbor clusters of virulence genes that mediate the adhesion, colonization, invasion, immune system evasion, and toxigenic properties of the acceptor organism. Currently, pathogenicity islands are mainly identified in silico based on various characteristic features: (1) deviations in codon usage, G+C content or dinucleotide frequency and (2) insertion sequences and/or tRNA genetic flanking regions together with transposase coding genes. Several computational techniques for identifying pathogenicity islands exist. However, most of these techniques are only directed at the detection of horizontally transferred genes and/or the absence of certain genomic regions of the pathogenic bacterium in closely related non-pathogenic species. Here, we present a novel software suite designed for the prediction of pathogenicity islands (pathogenicity island prediction software, or PIPS). In contrast to other existing tools, our approach is capable of utilizing multiple features for pathogenicity island detection in an integrative manner. We show that PIPS provides better accuracy than other available software packages. As an example, we used PIPS to study the veterinary pathogen Corynebacterium pseudotuberculosis, in which we identified seven putative pathogenicity islands

Veterans walk to beat back pain: study rationale, design and protocol of a randomized trial of a pedometer-based Internet mediated intervention for patients with chronic low back pain

<p>Abstract</p> <p>Background</p> <p>Chronic back pain is a significant problem worldwide and may be especially prevalent among patients receiving care in the U.S. Department of Veterans Affairs healthcare system. Back pain affects adults at all ages and is associated with disability, lost workplace productivity, functional limitations and social isolation. Exercise is one of the most effective strategies for managing chronic back pain. Yet, there are few clinical programs that use low cost approaches to help patients with chronic back pain initiate and maintain an exercise program.</p> <p>Methods/Design</p> <p>We describe the design and rationale of a randomized controlled trial to assess the efficacy of a pedometer-based Internet mediated intervention for patients with chronic back pain. The intervention uses an enhanced pedometer, website and e-community to assist these patients with initiating and maintaining a regular walking program with the primary aim of reducing pain-related disability and functional interference. The study specific aims are: 1) To determine whether a pedometer-based Internet-mediated intervention reduces pain-related functional interference among patients with chronic back pain in the short term and over a 12-month timeframe. 2) To assess the effect of the intervention on walking (measured by step counts), quality of life, pain intensity, pain related fear and self-efficacy for exercise. 3) To identify factors associated with a sustained increase in walking over a 12-month timeframe among patients randomized to the intervention.</p> <p>Discussion</p> <p>Exercise is an integral part of managing chronic back pain but to be effective requires that patients actively participate in the management process. This intervention is designed to increase activity levels, improve functional status and make exercise programs more accessible for a broad range of patients with chronic back pain.</p> <p>Trial Registration Number</p> <p>NCT00694018</p

Subcortical volumetric abnormalities in bipolar disorder.

Considerable uncertainty exists about the defining brain changes associated with bipolar disorder (BD). Understanding and quantifying the sources of uncertainty can help generate novel clinical hypotheses about etiology and assist in the development of biomarkers for indexing disease progression and prognosis. Here we were interested in quantifying case-control differences in intracranial volume (ICV) and each of eight subcortical brain measures: nucleus accumbens, amygdala, caudate, hippocampus, globus pallidus, putamen, thalamus, lateral ventricles. In a large study of 1710 BD patients and 2594 healthy controls, we found consistent volumetric reductions in BD patients for mean hippocampus (Cohen's d=-0.232; P=3.50 × 10(-7)) and thalamus (d=-0.148; P=4.27 × 10(-3)) and enlarged lateral ventricles (d=-0.260; P=3.93 × 10(-5)) in patients. No significant effect of age at illness onset was detected. Stratifying patients based on clinical subtype (BD type I or type II) revealed that BDI patients had significantly larger lateral ventricles and smaller hippocampus and amygdala than controls. However, when comparing BDI and BDII patients directly, we did not detect any significant differences in brain volume. This likely represents similar etiology between BD subtype classifications. Exploratory analyses revealed significantly larger thalamic volumes in patients taking lithium compared with patients not taking lithium. We detected no significant differences between BDII patients and controls in the largest such comparison to date. Findings in this study should be interpreted with caution and with careful consideration of the limitations inherent to meta-analyzed neuroimaging comparisons.Molecular Psychiatry advance online publication, 9 February 2016; doi:10.1038/mp.2015.227

Brain multiplexes reveal morphological connectional biomarkers fingerprinting late brain dementia states

Accurate diagnosis of mild cognitive impairment (MCI) before conversion to Alzheimer’s disease (AD) is invaluable for patient treatment. Many works showed that MCI and AD affect functional and structural connections between brain regions as well as the shape of cortical regions. However, ‘shape connections’ between brain regions are rarely investigated -e.g., how morphological attributes such as cortical thickness and sulcal depth of a specific brain region change in relation to morphological attributes in other regions. To fill this gap, we unprecedentedly design morphological brain multiplexes for late MCI/AD classification. Specifically, we use structural T1-w MRI to define morphological brain networks, each quantifying similarity in morphology between different cortical regions for a specific cortical attribute. Then, we define a brain multiplex where each intra-layer represents the morphological connectivity network of a specific cortical attribute, and each inter-layer encodes the similarity between two consecutive intra-layers. A significant performance gain is achieved when using the multiplex architecture in comparison to other conventional network analysis architectures. We also leverage this architecture to discover morphological connectional biomarkers fingerprinting the difference between late MCI and AD stages, which included the right entorhinal cortex and right caudal middle frontal gyrus

Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer’s Disease using structural MR and FDG-PET images

Alzheimer’s Disease (AD) is a progressive neurodegenerative disease where biomarkers for disease based on pathophysiology may be able to provide objective measures for disease diagnosis and staging. Neuroimaging scans acquired from MRI and metabolism images obtained by FDG-PET provide in-vivo measurements of structure and function (glucose metabolism) in a living brain. It is hypothesized that combining multiple different image modalities providing complementary information could help improve early diagnosis of AD. In this paper, we propose a novel deep-learning-based framework to discriminate individuals with AD utilizing a multimodal and multiscale deep neural network. Our method delivers 82.4% accuracy in identifying the individuals with mild cognitive impairment (MCI) who will convert to AD at 3 years prior to conversion (86.4% combined accuracy for conversion within 1–3 years), a 94.23% sensitivity in classifying individuals with clinical diagnosis of probable AD, and a 86.3% specificity in classifying non-demented controls improving upon results in published literature

The impact of PICALM genetic variations on reserve capacity of posterior cingulate in AD continuum

Phosphatidylinositolbinding clathrin assembly protein (PICALM) gene is one novel genetic player associated with late-onset Alzheimer’s disease (LOAD), based on recent genome wide association studies (GWAS). However, how it affects AD occurrence is still unknown. Brain reserve hypothesis highlights the tolerant capacities of brain as a passive means to fight against neurodegenerations. Here, we took the baseline volume and/or thickness of LOAD-associated brain regions as proxies of brain reserve capacities and investigated whether PICALM genetic variations can influence the baseline reserve capacities and the longitudinal atrophy rate of these specific regions using data from Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. In mixed population, we found that brain region significantly affected by PICALM genetic variations was majorly restricted to posterior cingulate. In sub-population analysis, we found that one PICALM variation (C allele of rs642949) was associated with larger baseline thickness of posterior cingulate in health. We found seven variations in health and two variations (rs543293 and rs592297) in individuals with mild cognitive impairment were associated with slower atrophy rate of posterior cingulate. Our study provided preliminary evidences supporting that PICALM variations render protections by facilitating reserve capacities of posterior cingulate in non-demented elderly

Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease