Luminance, colour, viewpoint and border enhanced disparity energy model

The visual cortex is able to extract disparity information through the use of binocular cells. This process is reflected by the Disparity Energy Model, which describes the role and functioning of simple and complex binocular neuron populations, and how they are able to extract disparity. This model uses explicit cell parameters to mathematically determine preferred cell disparities, like spatial frequencies, orientations, binocular phases and receptive field positions. However, the brain cannot access such explicit cell parameters; it must rely on cell responses. In this article, we implemented a trained binocular neuronal population, which encodes disparity information implicitly. This allows the population to learn how to decode disparities, in a similar way to how our visual system could have developed this ability during evolution. At the same time, responses of monocular simple and complex cells can also encode line and edge information, which is useful for refining disparities at object borders. The brain should then be able, starting from a low-level disparity draft, to integrate all information, including colour and viewpoint perspective, in order to propagate better estimates to higher cortical areas.Portuguese Foundation for Science and Technology (FCT); LARSyS FCT [UID/EEA/50009/2013]; EU project NeuroDynamics [FP7-ICT-2009-6, PN: 270247]; FCT project SparseCoding [EXPL/EEI-SII/1982/2013]; FCT PhD grant [SFRH-BD-44941-2008

Task and spatial frequency modulations of object processing: an EEG study.

Visual object processing may follow a coarse-to-fine sequence imposed by fast processing of low spatial frequencies (LSF) and slow processing of high spatial frequencies (HSF). Objects can be categorized at varying levels of specificity: the superordinate (e.g. animal), the basic (e.g. dog), or the subordinate (e.g. Border Collie). We tested whether superordinate and more specific categorization depend on different spatial frequency ranges, and whether any such dependencies might be revealed by or influence signals recorded using EEG. We used event-related potentials (ERPs) and time-frequency (TF) analysis to examine the time course of object processing while participants performed either a grammatical gender-classification task (which generally forces basic-level categorization) or a living/non-living judgement (superordinate categorization) on everyday, real-life objects. Objects were filtered to contain only HSF or LSF. We found a greater positivity and greater negativity for HSF than for LSF pictures in the P1 and N1 respectively, but no effects of task on either component. A later, fronto-central negativity (N350) was more negative in the gender-classification task than the superordinate categorization task, which may indicate that this component relates to semantic or syntactic processing. We found no significant effects of task or spatial frequency on evoked or total gamma band responses. Our results demonstrate early differences in processing of HSF and LSF content that were not modulated by categorization task, with later responses reflecting such higher-level cognitive factors

Synthetic biology to access and expand nature's chemical diversity

Bacterial genomes encode the biosynthetic potential to produce hundreds of thousands of complex molecules with diverse applications, from medicine to agriculture and materials. Accessing these natural products promises to reinvigorate drug discovery pipelines and provide novel routes to synthesize complex chemicals. The pathways leading to the production of these molecules often comprise dozens of genes spanning large areas of the genome and are controlled by complex regulatory networks with some of the most interesting molecules being produced by non-model organisms. In this Review, we discuss how advances in synthetic biology — including novel DNA construction technologies, the use of genetic parts for the precise control of expression and for synthetic regulatory circuits — and multiplexed genome engineering can be used to optimize the design and synthesis of pathways that produce natural products

Behavioral genetics and taste

This review focuses on behavioral genetic studies of sweet, umami, bitter and salt taste responses in mammals. Studies involving mouse inbred strain comparisons and genetic analyses, and their impact on elucidation of taste receptors and transduction mechanisms are discussed. Finally, the effect of genetic variation in taste responsiveness on complex traits such as drug intake is considered. Recent advances in development of genomic resources make behavioral genetics a powerful approach for understanding mechanisms of taste

A consensus S. cerevisiae metabolic model Yeast8 and its ecosystem for comprehensively probing cellular metabolism

Genome-scale metabolic models (GEMs) represent extensive knowledgebases that provide a platform for model simulations and integrative analysis of omics data. This study introduces Yeast8 and an associated ecosystem of models that represent a comprehensive computational resource for performing simulations of the metabolism of Saccharomyces cerevisiae––an important model organism and widely used cell-factory. Yeast8 tracks community development with version control, setting a standard for how GEMs can be continuously updated in a simple and reproducible way. We use Yeast8 to develop the derived models panYeast8 and coreYeast8, which in turn enable the reconstruction of GEMs for 1,011 different yeast strains. Through integration with enzyme constraints (ecYeast8) and protein 3D structures (proYeast8DB), Yeast8 further facilitates the exploration of yeast metabolism at a multi-scale level, enabling prediction of how single nucleotide variations translate to phenotypic traits

Extensive innate immune gene activation accompanies brain aging, increasing vulnerability to cognitive decline and neurodegeneration: a microarray study

BACKGROUND: This study undertakes a systematic and comprehensive analysis of brain gene expression profiles of immune/inflammation-related genes in aging and Alzheimer’s disease (AD). METHODS: In a well-powered microarray study of young (20 to 59 years), aged (60 to 99 years), and AD (74 to 95 years) cases, gene responses were assessed in the hippocampus, entorhinal cortex, superior frontal gyrus, and post-central gyrus. RESULTS: Several novel concepts emerge. First, immune/inflammation-related genes showed major changes in gene expression over the course of cognitively normal aging, with the extent of gene response far greater in aging than in AD. Of the 759 immune-related probesets interrogated on the microarray, approximately 40% were significantly altered in the SFG, PCG and HC with increasing age, with the majority upregulated (64 to 86%). In contrast, far fewer immune/inflammation genes were significantly changed in the transition to AD (approximately 6% of immune-related probesets), with gene responses primarily restricted to the SFG and HC. Second, relatively few significant changes in immune/inflammation genes were detected in the EC either in aging or AD, although many genes in the EC showed similar trends in responses as in the other brain regions. Third, immune/inflammation genes undergo gender-specific patterns of response in aging and AD, with the most pronounced differences emerging in aging. Finally, there was widespread upregulation of genes reflecting activation of microglia and perivascular macrophages in the aging brain, coupled with a downregulation of select factors (TOLLIP, fractalkine) that when present curtail microglial/macrophage activation. Notably, essentially all pathways of the innate immune system were upregulated in aging, including numerous complement components, genes involved in toll-like receptor signaling and inflammasome signaling, as well as genes coding for immunoglobulin (Fc) receptors and human leukocyte antigens I and II. CONCLUSIONS: Unexpectedly, the extent of innate immune gene upregulation in AD was modest relative to the robust response apparent in the aged brain, consistent with the emerging idea of a critical involvement of inflammation in the earliest stages, perhaps even in the preclinical stage, of AD. Ultimately, our data suggest that an important strategy to maintain cognitive health and resilience involves reducing chronic innate immune activation that should be initiated in late midlife

Repeatability and response to therapy of dynamic contrast-enhanced Magnetic Resonance Imaging biomarkers in rheumatoid arthritis in a large multicentre trial setting.

Objectives To determine the repeatability, and response to therapy, of Dynamic Contrast-Enhanced (DCE) MRI biomarkers of synovitis in hand and wrist of Rheumatoid Arthritis (RA) patients, and in particular the performance of the transfer constant Ktrans, in a multicentre trial setting Methods DCE-MRI and RA MRI scoring (RAMRIS) were performed with meticulous standardisation at baseline, 6 and 24 weeks in a sub-study of fostamatinib monotherapy in reducing synovitis compared with placebo or adalimumab. Analysis employed statistical shape modelling to avoid biased regions-of-interest, kinetic modelling and heuristic analyses. Repeatability was also evaluated. Results At early study termination, DCE-MRI data had been acquired from 58 patients in 19 imaging centres. Ktrans intra-subject coefficient of variation (N=14) was 30%. Ktrans change demonstrated inferiority of fostamatinib (N=11) relative to adalimumab (N=10) after 6 weeks (treatment ratio=1.92, p=0.003), and failed to distinguish fostamatinib from placebo (N=10, p=0.79). RAMRIS showed superiority of fostamatinib relative to placebo at 6 weeks (p=0.023), and did not distinguish fostamatinib from adalimumab at either 6 weeks (p=0.175) or 24 weeks (p=0.230). Conclusion This demonstrated repeatability of Ktrans, and its ability to distinguish treatment groups, show that DCE-MRI biomarkers are suitable for use in multicentre RA trials.</p