Galectin-1 as a potential cancer target

Galectins are a family of structurally related carbohydrate-binding proteins, which are defined by their affinity for poly-N-acetyllactosamine-enriched glycoconjugates and sequence similarities in the carbohydrate recognition domain. Galectin-1, a member of this family, contributes to different events associated with cancer biology, including tumour transformation, cell cycle regulation, apoptosis, cell adhesion, migration and inflammation. In addition, recent evidence indicates that galectin-1 contributes to tumour evasion of immune responses. Given the increased interest of tumour biologists and clinical oncologists in this field and the potential use of galectins as novel targets for anticancer drugs, we summarise here recent advances about the role of galectin-1 in different events of tumour growth and metastasis

HIV Services Utilization in Los Angeles County, California

Recipients of HIV/AIDS prevention services in Los Angeles County California were surveyed in 2004 by 220 HIV prevention service provider staff from 51 agencies funded by the Office of AIDS Programs and Policy. This resulted in 2,102 usable surveys for cluster analysis purposes. This Countywide Risk Assessment Survey assessed demographics, sexual history, substance use, perceptions regarding HIV/AIDS, and use of 18 different services at both the agency administering the survey and at other agencies. The 36 types of service use data were subjected to a cluster analysis that found five clusters. These service pattern clusters differed from each other on proportion HIV positive, HIV testing history, history of abuse, education, type of residence, type of funding, intervention type, and ethnicity. The analysis also suggests that domestic violence services availability and utilization should be examined more thoroughly in the future for HIV infected/affected populations

Population based allele frequencies of disease associated polymorphisms in the Personalized Medicine Research Project

<p>Abstract</p> <p>Background</p> <p>There is a lack of knowledge regarding the frequency of disease associated polymorphisms in populations and population attributable risk for many populations remains unknown. Factors that could affect the association of the allele with disease, either positively or negatively, such as race, ethnicity, and gender, may not be possible to determine without population based allele frequencies.</p> <p>Here we used a panel of 51 polymorphisms previously associated with at least one disease and determined the allele frequencies within the entire Personalized Medicine Research Project population based cohort. We compared these allele frequencies to those in dbSNP and other data sources stratified by race. Differences in allele frequencies between self reported race, region of origin, and sex were determined.</p> <p>Results</p> <p>There were 19544 individuals who self reported a single racial category, 19027 or (97.4%) self reported white Caucasian, and 11205 (57.3%) individuals were female. Of the 11,208 (57%) individuals with an identifiable region of origin 8337 or (74.4%) were German.</p> <p>41 polymorphisms were significantly different between self reported race at the 0.05 level. Stratification of our Caucasian population by self reported region of origin revealed 19 polymorphisms that were significantly different (p = 0.05) between individuals of different origins. Further stratification of the population by gender revealed few significant differences in allele frequencies between the genders.</p> <p>Conclusions</p> <p>This represents one of the largest population based allele frequency studies to date. Stratification by self reported race and region of origin revealed wide differences in allele frequencies not only by race but also by region of origin within a single racial group. We report allele frequencies for our Asian/Hmong and American Indian populations; these two minority groups are not typically selected for population allele frequency detection. Population wide allele frequencies are important for the design and implementation of studies and for determining the relevance of a disease associated polymorphism for a given population.</p

Adhesion to carbon nanotube conductive scaffolds forces action-potential appearance in immature rat spinal neurons

In the last decade, carbon nanotube growth substrates have been used to investigate neurons and neuronal networks formation in vitro when guided by artificial nano-scaled cues. Besides, nanotube-based interfaces are being developed, such as prosthesis for monitoring brain activity. We recently described how carbon nanotube substrates alter the electrophysiological and synaptic responses of hippocampal neurons in culture. This observation highlighted the exceptional ability of this material in interfering with nerve tissue growth. Here we test the hypothesis that carbon nanotube scaffolds promote the development of immature neurons isolated from the neonatal rat spinal cord, and maintained in vitro. To address this issue we performed electrophysiological studies associated to gene expression analysis. Our results indicate that spinal neurons plated on electro-conductive carbon nanotubes show a facilitated development. Spinal neurons anticipate the expression of functional markers of maturation, such as the generation of voltage dependent currents or action potentials. These changes are accompanied by a selective modulation of gene expression, involving neuronal and non-neuronal components. Our microarray experiments suggest that carbon nanotube platforms trigger reparative activities involving microglia, in the absence of reactive gliosis. Hence, future tissue scaffolds blended with conductive nanotubes may be exploited to promote cell differentiation and reparative pathways in neural regeneration strategies

Your Resting Brain CAREs about Your Risky Behavior

Research on the neural correlates of risk-related behaviors and personality traits has provided insight into mechanisms underlying both normal and pathological decision-making. Task-based neuroimaging studies implicate a distributed network of brain regions in risky decision-making. What remains to be understood are the interactions between these regions and their relation to individual differences in personality variables associated with real-world risk-taking.We employed resting state functional magnetic resonance imaging (R-fMRI) and resting state functional connectivity (RSFC) methods to investigate differences in the brain's intrinsic functional architecture associated with beliefs about the consequences of risky behavior. We obtained an individual measure of expected benefit from engaging in risky behavior, indicating a risk seeking or risk-averse personality, for each of 21 participants from whom we also collected a series of R-fMRI scans. The expected benefit scores were entered in statistical models assessing the RSFC of brain regions consistently implicated in both the evaluation of risk and reward, and cognitive control (i.e., orbitofrontal cortex, nucleus accumbens, lateral prefrontal cortex, dorsal anterior cingulate). We specifically focused on significant brain-behavior relationships that were stable across R-fMRI scans collected one year apart. Two stable expected benefit-RSFC relationships were observed: decreased expected benefit (increased risk-aversion) was associated with 1) stronger positive functional connectivity between right inferior frontal gyrus (IFG) and right insula, and 2) weaker negative functional connectivity between left nucleus accumbens and right parieto-occipital cortex.Task-based activation in the IFG and insula has been associated with risk-aversion, while activation in the nucleus accumbens and parietal cortex has been associated with both risk seeking and risk-averse tendencies. Our results suggest that individual differences in attitudes toward risk-taking are reflected in the brain's functional architecture and may have implications for engaging in real-world risky behaviors

Targeting of Pseudorabies Virus Structural Proteins to Axons Requires Association of the Viral Us9 Protein with Lipid Rafts

The pseudorabies virus (PRV) Us9 protein plays a central role in targeting viral capsids and glycoproteins to axons of dissociated sympathetic neurons. As a result, Us9 null mutants are defective in anterograde transmission of infection in vivo. However, it is unclear how Us9 promotes axonal sorting of so many viral proteins. It is known that the glycoproteins gB, gC, gD and gE are associated with lipid raft microdomains on the surface of infected swine kidney cells and monocytes, and are directed into the axon in a Us9-dependent manner. In this report, we determined that Us9 is associated with lipid rafts, and that this association is critical to Us9-mediated sorting of viral structural proteins. We used infected non-polarized and polarized PC12 cells, a rat pheochromocytoma cell line that acquires many of the characteristics of sympathetic neurons in the presence of nerve growth factor (NGF). In these cells, Us9 is highly enriched in detergent-resistant membranes (DRMs). Moreover, reducing the affinity of Us9 for lipid rafts inhibited anterograde transmission of infection from sympathetic neurons to epithelial cells in vitro. We conclude that association of Us9 with lipid rafts is key for efficient targeting of structural proteins to axons and, as a consequence, for directional spread of PRV from pre-synaptic to post-synaptic neurons and cells of the mammalian nervous system

Combination of novel and public RNA-seq datasets to generate an mRNA expression atlas for the domestic chicken

Background: The domestic chicken (Gallus gallus) is widely used as a model in developmental biology and is also an important livestock species. We describe a novel approach to data integration to generate an mRNA expression atlas for the chicken spanning major tissue types and developmental stages, using a diverse range of publicly-archived RNA-seq datasets and new data derived from immune cells and tissues. Results: Randomly down-sampling RNA-seq datasets to a common depth and quantifying expression against a reference transcriptome using the mRNA quantitation tool Kallisto ensured that disparate datasets explored comparable transcriptomic space. The network analysis tool Graphia was used to extract clusters of co-expressed genes from the resulting expression atlas, many of which were tissue or cell-type restricted, contained transcription factors that have previously been implicated in their regulation, or were otherwise associated with biological processes, such as the cell cycle. The atlas provides a resource for the functional annotation of genes that currently have only a locus ID. We cross-referenced the RNA-seq atlas to a publicly available embryonic Cap Analysis of Gene Expression (CAGE) dataset to infer the developmental time course of organ systems, and to identify a signature of the expansion of tissue macrophage populations during development. Conclusion: Expression profiles obtained from public RNA-seq datasets - despite being generated by different laboratories using different methodologies - can be made comparable to each other. This meta-analytic approach to RNA-seq can be extended with new datasets from novel tissues, and is applicable to any species

Syndromics: A Bioinformatics Approach for Neurotrauma Research

Substantial scientific progress has been made in the past 50 years in delineating many of the biological mechanisms involved in the primary and secondary injuries following trauma to the spinal cord and brain. These advances have highlighted numerous potential therapeutic approaches that may help restore function after injury. Despite these advances, bench-to-bedside translation has remained elusive. Translational testing of novel therapies requires standardized measures of function for comparison across different laboratories, paradigms, and species. Although numerous functional assessments have been developed in animal models, it remains unclear how to best integrate this information to describe the complete translational “syndrome” produced by neurotrauma. The present paper describes a multivariate statistical framework for integrating diverse neurotrauma data and reviews the few papers to date that have taken an information-intensive approach for basic neurotrauma research. We argue that these papers can be described as the seminal works of a new field that we call “syndromics”, which aim to apply informatics tools to disease models to characterize the full set of mechanistic inter-relationships from multi-scale data. In the future, centralized databases of raw neurotrauma data will enable better syndromic approaches and aid future translational research, leading to more efficient testing regimens and more clinically relevant findings

Xaf1 can cooperate with TNFα in the induction of apoptosis, independently of interaction with XIAP

XIAP-associated factor 1 (Xaf1) binds XIAP and re-localizes it to the nucleus, thus inhibiting XIAP activity and enhancing apoptosis [1]. Xaf1 expression is reduced or absent in tumor samples and cell lines suggesting it may function as a tumor suppressor [2–5]. To further study Xaf1 function we generated Xaf1 inducible cells in the osteosarcoma cell line Saos-2. Despite Xaf1 inducing apoptosis that is dramatically enhanced by TNFα we find no evidence for an interaction between Xaf1 and XIAP. Furthermore, Xaf1 expression sensitized XIAP −/− fibroblasts to TNFα, demonstrating the existence of a novel mechanism of Xaf1 induced apoptosis distinct from antagonizing XIAP. Xaf1 expression promotes cytochrome c release that cannot be blocked by inhibition of caspase activity. This implicates a role for the mitochondrial apoptotic pathway, consistent with the ability of Bcl2 to block Xaf1 induced apoptosis. The data indicate that in Saos2 cells Xaf1 activates the mitochondrial apoptotic pathway to facilitate cytochrome c release, thus amplifying apoptotic signals from death receptors.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45342/1/11010_2005_Article_9094.pd