Increased entropy of signal transduction in the cancer metastasis phenotype

Studies into the statistical properties of biological networks have led to important biological insights, such as the presence of hubs and hierarchical modularity. There is also a growing interest in studying the statistical properties of networks in the context of cancer genomics. However, relatively little is known as to what network features differ between the cancer and normal cell physiologies, or between different cancer cell phenotypes. Based on the observation that frequent genomic alterations underlie a more aggressive cancer phenotype, we asked if such an effect could be detectable as an increase in the randomness of local gene expression patterns. Using a breast cancer gene expression data set and a model network of protein interactions we derive constrained weighted networks defined by a stochastic information flux matrix reflecting expression correlations between interacting proteins. Based on this stochastic matrix we propose and compute an entropy measure that quantifies the degree of randomness in the local pattern of information flux around single genes. By comparing the local entropies in the non-metastatic versus metastatic breast cancer networks, we here show that breast cancers that metastasize are characterised by a small yet significant increase in the degree of randomness of local expression patterns. We validate this result in three additional breast cancer expression data sets and demonstrate that local entropy better characterises the metastatic phenotype than other non-entropy based measures. We show that increases in entropy can be used to identify genes and signalling pathways implicated in breast cancer metastasis. Further exploration of such integrated cancer expression and protein interaction networks will therefore be a fruitful endeavour.Comment: 5 figures, 2 Supplementary Figures and Table

MicroRNA-Integrated and Network-Embedded Gene Selection with Diffusion Distance

Gene network information has been used to improve gene selection in microarray-based studies by selecting marker genes based both on their expression and the coordinate expression of genes within their gene network under a given condition. Here we propose a new network-embedded gene selection model. In this model, we first address the limitations of microarray data. Microarray data, although widely used for gene selection, measures only mRNA abundance, which does not always reflect the ultimate gene phenotype, since it does not account for post-transcriptional effects. To overcome this important (critical in certain cases) but ignored-in-almost-all-existing-studies limitation, we design a new strategy to integrate together microarray data with the information of microRNA, the major post-transcriptional regulatory factor. We also handle the challenges led by gene collaboration mechanism. To incorporate the biological facts that genes without direct interactions may work closely due to signal transduction and that two genes may be functionally connected through multi paths, we adopt the concept of diffusion distance. This concept permits us to simulate biological signal propagation and therefore to estimate the collaboration probability for all gene pairs, directly or indirectly-connected, according to multi paths connecting them. We demonstrate, using type 2 diabetes (DM2) as an example, that the proposed strategies can enhance the identification of functional gene partners, which is the key issue in a network-embedded gene selection model. More importantly, we show that our gene selection model outperforms related ones. Genes selected by our model 1) have improved classification capability; 2) agree with biological evidence of DM2-association; and 3) are involved in many well-known DM2-associated pathways

Lithium Treatment of APPSwDI/NOS2−/− Mice Leads to Reduced Hyperphosphorylated Tau, Increased Amyloid Deposition and Altered Inflammatory Phenotype

Lithium is an anti-psychotic that has been shown to prevent the hyperphosphorylation of tau protein through the inhibition of glycogen-synthase kinase 3-beta (GSK3β). We recently developed a mouse model that progresses from amyloid pathology to tau pathology and neurodegeneration due to the genetic deletion of NOS2 in an APP transgenic mouse; the APPSwDI/NOS2−/− mouse. Because this mouse develops tau pathology, amyloid pathology and neuronal loss we were interested in the effect anti-tau therapy would have on amyloid pathology, learning and memory. We administered lithium in the diets of APPSwDI/NOS2−/− mice for a period of eight months, followed by water maze testing at 12 months of age, immediately prior to sacrifice. We found that lithium significantly lowered hyperphosphorylated tau levels as measured by Western blot and immunocytochemistry. However, we found no apparent neuroprotection, no effect on spatial memory deficits and an increase in histological amyloid deposition. Aβ levels measured biochemically were unaltered. We also found that lithium significantly altered the neuroinflammatory phenotype of the brain, resulting in enhanced alternative inflammatory response while concurrently lowering the classical inflammatory response. Our data suggest that lithium may be beneficial for the treatment of tauopathies but may not be beneficial for the treatment of Alzheimer's disease

Rasch model analysis of the Depression, Anxiety and Stress Scales (DASS)

<p>Abstract</p> <p>Background</p> <p>There is a growing awareness of the need for easily administered, psychometrically sound screening tools to identify individuals with elevated levels of psychological distress. Although support has been found for the psychometric properties of the Depression, Anxiety and Stress Scales (DASS) using classical test theory approaches it has not been subjected to Rasch analysis. The aim of this study was to use Rasch analysis to assess the psychometric properties of the DASS-21 scales, using two different administration modes.</p> <p>Methods</p> <p>The DASS-21 was administered to 420 participants with half the sample responding to a web-based version and the other half completing a traditional pencil-and-paper version. Conformity of DASS-21 scales to a Rasch partial credit model was assessed using the RUMM2020 software.</p> <p>Results</p> <p>To achieve adequate model fit it was necessary to remove one item from each of the DASS-21 subscales. The reduced scales showed adequate internal consistency reliability, unidimensionality and freedom from differential item functioning for sex, age and mode of administration. Analysis of all DASS-21 items combined did not support its use as a measure of general psychological distress. A scale combining the anxiety and stress items showed satisfactory fit to the Rasch model after removal of three items.</p> <p>Conclusion</p> <p>The results provide support for the measurement properties, internal consistency reliability, and unidimensionality of three slightly modified DASS-21 scales, across two different administration methods. The further use of Rasch analysis on the DASS-21 in larger and broader samples is recommended to confirm the findings of the current study.</p

A Functional Henipavirus Envelope Glycoprotein Pseudotyped Lentivirus Assay System

<p>Abstract</p> <p>Background</p> <p>Hendra virus (HeV) and Nipah virus (NiV) are newly emerged zoonotic paramyxoviruses discovered during outbreaks in Queensland, Australia in 1994 and peninsular Malaysia in 1998/9 respectively and classified within the new <it>Henipavirus </it>genus. Both viruses can infect a broad range of mammalian species causing severe and often-lethal disease in humans and animals, and repeated outbreaks continue to occur. Extensive laboratory studies on the host cell infection stage of HeV and NiV and the roles of their envelope glycoproteins have been hampered by their highly pathogenic nature and restriction to biosafety level-4 (BSL-4) containment. To circumvent this problem, we have developed a henipavirus envelope glycoprotein pseudotyped lentivirus assay system using either a luciferase gene or green fluorescent protein (GFP) gene encoding human immunodeficiency virus type-1 (HIV-1) genome in conjunction with the HeV and NiV fusion (F) and attachment (G) glycoproteins.</p> <p>Results</p> <p>Functional retrovirus particles pseudotyped with henipavirus F and G glycoproteins displayed proper target cell tropism and entry and infection was dependent on the presence of the HeV and NiV receptors ephrinB2 or B3 on target cells. The functional specificity of the assay was confirmed by the lack of reporter-gene signals when particles bearing either only the F or only G glycoprotein were prepared and assayed. Virus entry could be specifically blocked when infection was carried out in the presence of a fusion inhibiting C-terminal heptad (HR-2) peptide, a well-characterized, cross-reactive, neutralizing human mAb specific for the henipavirus G glycoprotein, and soluble ephrinB2 and B3 receptors. In addition, the utility of the assay was also demonstrated by an examination of the influence of the cytoplasmic tail of F in its fusion activity and incorporation into pseudotyped virus particles by generating and testing a panel of truncation mutants of NiV and HeV F.</p> <p>Conclusions</p> <p>Together, these results demonstrate that a specific henipavirus entry assay has been developed using NiV or HeV F and G glycoprotein pseudotyped reporter-gene encoding retrovirus particles. This assay can be conducted safely under BSL-2 conditions and will be a useful tool for measuring henipavirus entry and studying F and G glycoprotein function in the context of virus entry, as well as in assaying and characterizing neutralizing antibodies and virus entry inhibitors.</p

To Each According to His Need? Variability in the Responses to Inequity in Nonhuman Primates

While it is well established that humans respond to inequity, it remains unclear the extent to which this behavior occurs in our nonhuman primate relatives. By comparing a variety of species, spanning from New World and Old World monkeys to great apes, scientists can begin to answer questions about how the response to inequity evolved, what the function of this response is, and why and how different contexts shape it. In particular, research across nonhuman primate species suggests that the response is quite variable across species, contexts and individuals. In this paper, we aim to review these differences in an attempt to identify and better understand the patterns that emerge from the existing data with the goal of developing directions for future research. To begin, we address the importance of considering socio-ecological factors in nonhuman primates in order to better understand and predict expected patterns of cooperation and aversion to inequity in different species, following which we provide a detailed analysis of the patterns uncovered by these comparisons. Ultimately, we use this synthesis to propose new ideas for research to better understand this response and, hence, the evolution of our own responses to inequity

Behavioral, Ecological, and Evolutionary Aspects of Meat-Eating by Sumatran Orangutans (Pongo abelii)

Meat-eating is an important aspect of human evolution, but how meat became a substantial component of the human diet is still poorly understood. Meat-eating in our closest relatives, the great apes, may provide insight into the emergence of this trait, but most existing data are for chimpanzees. We report 3 rare cases of meat-eating of slow lorises, Nycticebus coucang, by 1 Sumatran orangutan mother–infant dyad in Ketambe, Indonesia, to examine how orangutans find slow lorises and share meat. We combine these 3 cases with 2 previous ones to test the hypothesis that slow loris captures by orangutans are seasonal and dependent on fruit availability. We also provide the first (to our knowledge) quantitative data and high-definition video recordings of meat chewing rates by great apes, which we use to estimate the minimum time necessary for a female Australopithecus africanus to reach its daily energy requirements when feeding partially on raw meat. Captures seemed to be opportunistic but orangutans may have used olfactory cues to detect the prey. The mother often rejected meat sharing requests and only the infant initiated meat sharing. Slow loris captures occurred only during low ripe fruit availability, suggesting that meat may represent a filler fallback food for orangutans. Orangutans ate meat more than twice as slowly as chimpanzees (Pan troglodytes), suggesting that group living may function as a meat intake accelerator in hominoids. Using orangutan data as a model, time spent chewing per day would not require an excessive amount of time for our social ancestors (australopithecines and hominids), as long as meat represented no more than a quarter of their diet

Rare coding variants in ten genes confer substantial risk for schizophrenia

Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3–50, P < 2.14 × 10−6) and 32 genes at a false discovery rate of <5%. These genes have the greatest expression in central nervous system neurons and have diverse molecular functions that include the formation, structure and function of the synapse. The associations of the NMDA (N-methyl-d-aspartate) receptor subunit GRIN2A and AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid) receptor subunit GRIA3 provide support for dysfunction of the glutamatergic system as a mechanistic hypothesis in the pathogenesis of schizophrenia. We observe an overlap of rare variant risk among schizophrenia, autism spectrum disorders1, epilepsy and severe neurodevelopmental disorders2, although different mutation types are implicated in some shared genes. Most genes described here, however, are not implicated in neurodevelopment. We demonstrate that genes prioritized from common variant analyses of schizophrenia are enriched in rare variant risk3, suggesting that common and rare genetic risk factors converge at least partially on the same underlying pathogenic biological processes. Even after excluding significantly associated genes, schizophrenia cases still carry a substantial excess of URVs, which indicates that more risk genes await discovery using this approach