ZNRD1 (zinc ribbon domain-containing 1) is a host cellular factor that influences HIV-1 replication and disease progression.

BACKGROUND: Human immunodeficiency virus (HIV) takes advantage of multiple host proteins to support its own replication. The gene ZNRD1 (zinc ribbon domain-containing 1) has been identified as encoding a potential host factor that influenced disease progression in HIV-positive individuals in a genomewide association study and also significantly affected HIV replication in a large-scale in vitro short interfering RNA (siRNA) screen. Genes and polymorphisms identified by large-scale analysis need to be followed up by means of functional assays and resequencing efforts to more precisely map causal genes. METHODS: Genotyping and ZNRD1 gene resequencing for 208 HIV-positive subjects (119 who experienced long-term nonprogression [LTNP] and 89 who experienced normal disease progression) was done by either TaqMan genotyping assays or direct sequencing. Genetic association analysis was performed with the SNPassoc package and Haploview software. siRNA and short hairpin RNA (shRNA) specifically targeting ZNRD1 were used to transiently or stably down-regulate ZNRD1 expression in both lymphoid and nonlymphoid cells. Cells were infected with X4 and R5 HIV strains, and efficiency of infection was assessed by reporter gene assay or p24 assay. RESULTS: Genetic association analysis found a strong statistically significant correlation with the LTNP phenotype (single-nucleotide polymorphism rs1048412; [Formula: see text]), independently of HLA-A10 influence. siRNA-based functional analysis showed that ZNRD1 down-regulation by siRNA or shRNA impaired HIV-1 replication at the transcription level in both lymphoid and nonlymphoid cells. CONCLUSION: Genetic association analysis unequivocally identified ZNRD1 as an independent marker of LTNP to AIDS. Moreover, in vitro experiments pointed to viral transcription as the inhibited step. Thus, our data strongly suggest that ZNRD1 is a host cellular factor that influences HIV-1 replication and disease progression in HIV-positive individuals.

GLUT8 is dispensable for embryonic development but influences hippocampal neurogenesis and heart function.

GLUT8 is a glucose transporter isoform expressed at high levels in testis; at intermediate levels in the brain, including the hippocampus; and at lower levels in the heart and several other tissues. GLUT8 is located in an intracellular compartment and does not appear to translocate to the cell surface, except in blastocysts, where insulin has been reported to induce its surface expression. Here, we generated mice with inactivation of the glut8 gene. We showed that expression of GLUT8 was not required for normal embryonic development and that glut8-/- mice had normal postnatal development, glucose homeostasis, and response to mild stress. Adult glut8-/- mice showed increased proliferation of hippocampal cells but no defect in memory acquisition and retention. Absence of GLUT8 from the heart did not alter heart size and morphology but led to an increase in P-wave duration, which was not associated with abnormal Nav1.5 Na+ channel or connexin expression. Thus, absence of GLUT8 expression in the mouse caused complex but mild physiological alterations.

Skill-biased technological change and the business cycle

Over the past two decades, technological progress in the United States hasbeen biased towards skilled labor. What does this imply for business cycles?We construct a quarterly skill premium from the CPS and use it to identifyskill-biased technology shocks in a VAR with long-run restrictions. Hours fallin response to skill-biased technology shocks, indicating that at least part of thetechnology-induced fall in total hours is due to a compositional shift in labordemand. Skill-biased technology shocks have no effect on the relative price ofinvestment, suggesting that capital and skill are not complementary in aggregateproduction.

Expertise and finance: Mergers motivated by technological change

This paper argues that a large technological innovation may lead to a merger wave by inducing entrepreneurs to seek funds from technologically knowledgeable firms -experts. When a large technological innovation occurs, the ability of non-experts (banks) to discriminate between good and bad quality projects is reduced. Experts can continue to charge a low rate of interest for financing because their expertise enables them to identify good quality projects and to avoid unprofitable investments. On the other hand, non-experts now charge a higher rate of interest in order to screen bad projects. More entrepreneurs, therefore, disclose their projects to experts to raise funds from them. Such experts are, however, able to copy the projects and disclosure to them invites the possibility of competition. Thus the entrepreneur and the expert may merge so as to achieve product market collusion. As well as rationalizing mergers, the model can also explain various forms of venture financing by experts such as corporate investors and business angels.

Technological change and the wealth of nations

We discuss a unified theory of directed technological change and technologyadoption that can shed light on the causes of persistent productivity differencesacross countries. In our model, new technologies are designed in advanced countries and diffuse endogenously to less developed countries. Our framework is richenough to highlight three broad reasons for productivity differences: inappropriatetechnologies, policy-induced barriers to technology adoption, and within-countrymisallocations across sectors due to policy distortions. We also discuss the effectsof two aspects of globalization, trade in goods and migration, on the wealth ofnations through their impact on the direction of technical progress. By doing so,we illustrate some of the equalizing and unequalizing forces of globalization.

Noise in Brain Activity Engenders Perception and Influences Discrimination Sensitivity.

Behavioral and brain responses to identical stimuli can vary with experimental and task parameters, including the context of stimulus presentation or attention. More surprisingly, computational models suggest that noise-related random fluctuations in brain responses to stimuli would alone be sufficient to engender perceptual differences between physically identical stimuli. In two experiments combining psychophysics and EEG in healthy humans, we investigated brain mechanisms whereby identical stimuli are (erroneously) perceived as different (higher vs lower in pitch or longer vs shorter in duration) in the absence of any change in the experimental context. Even though, as expected, participants' percepts to identical stimuli varied randomly, a classification algorithm based on a mixture of Gaussians model (GMM) showed that there was sufficient information in single-trial EEG to reliably predict participants' judgments of the stimulus dimension. By contrasting electrical neuroimaging analyses of auditory evoked potentials (AEPs) to the identical stimuli as a function of participants' percepts, we identified the precise timing and neural correlates (strength vs topographic modulations) as well as intracranial sources of these erroneous perceptions. In both experiments, AEP differences first occurred ∼100 ms after stimulus onset and were the result of topographic modulations following from changes in the configuration of active brain networks. Source estimations localized the origin of variations in perceived pitch of identical stimuli within right temporal and left frontal areas and of variations in perceived duration within right temporoparietal areas. We discuss our results in terms of providing neurophysiologic evidence for the contribution of random fluctuations in brain activity to conscious perception.

European research funding and regional technological capabilities: Network composition analysis

We use network and correspondence analysis to describe the compositionof the research networks in the European BRITE--EURAM program. Our mainfinding is that 27\% of the participants in this program fall into one oftwo sets of highly ``interconnected'' institutions --one centered aroundlarge firms (with smaller firms and research centers providing specializedservices), and the other around universities--. Moreover, these ``hubs''are composed largely of institutions coming from the technologically mostadvanced regions of Europe. This is suggestive of the difficulties of attainingEuropean ``cohesion'', as technically advanced institutions naturally linkwith partners of similar technological capabilities.