Ribbon Crystals

A repetitive crystal-like pattern is spontaneously formed upon the twisting of straight ribbons. The pattern is akin to a tessellation with isosceles triangles, and it can easily be demonstrated with ribbons cut from an overhead transparency. We give a general description of developable ribbons using a ruled procedure where ribbons are uniquely described by two generating functions. This construction defines a differentiable frame, the ribbon frame, which does not have singular points, whereby we avoid the shortcomings of the Frenet-Serret frame. The observed spontaneous pattern is modeled using planar triangles and cylindrical arcs, and the ribbon structure is shown to arise from a maximization of the end-to-end length of the ribbon, i.e. from an optimal use of ribbon length. The phenomenon is discussed in the perspectives of incompatible intrinsic geometries and of the emergence of long-range order

A Conserved Developmental Patterning Network Produces Quantitatively Different Output in Multiple Species of Drosophila

Differences in the level, timing, or location of gene expression can contribute to alternative phenotypes at the molecular and organismal level. Understanding the origins of expression differences is complicated by the fact that organismal morphology and gene regulatory networks could potentially vary even between closely related species. To assess the scope of such changes, we used high-resolution imaging methods to measure mRNA expression in blastoderm embryos of Drosophila yakuba and Drosophila pseudoobscura and assembled these data into cellular resolution atlases, where expression levels for 13 genes in the segmentation network are averaged into species-specific, cellular resolution morphological frameworks. We demonstrate that the blastoderm embryos of these species differ in their morphology in terms of size, shape, and number of nuclei. We present an approach to compare cellular gene expression patterns between species, while accounting for varying embryo morphology, and apply it to our data and an equivalent dataset for Drosophila melanogaster. Our analysis reveals that all individual genes differ quantitatively in their spatio-temporal expression patterns between these species, primarily in terms of their relative position and dynamics. Despite many small quantitative differences, cellular gene expression profiles for the whole set of genes examined are largely similar. This suggests that cell types at this stage of development are conserved, though they can differ in their relative position by up to 3–4 cell widths and in their relative proportion between species by as much as 5-fold. Quantitative differences in the dynamics and relative level of a subset of genes between corresponding cell types may reflect altered regulatory functions between species. Our results emphasize that transcriptional networks can diverge over short evolutionary timescales and that even small changes can lead to distinct output in terms of the placement and number of equivalent cells

Ionizing radiation modulates human macrophages towards a pro-inflammatory phenotype preserving their pro-invasive and pro-angiogenic capacities

In order to improve the efficacy of conventional radiotherapy, attention has been paid to immune cells, which not only modulate cancer cell response to therapy but are also highly recruited to tumours after irradiation. Particularly, the effect of ionizing radiation on macrophages, using therapeutically relevant doses, is not well understood. To evaluate how radiotherapy affects macrophage behaviour and macrophage-mediated cancer cell activity, human monocyte derived-macrophages were subjected, for a week, to cumulative ionizing radiation doses, as used during cancer treatment (2Gy/fraction/day). Irradiated macrophages remained viable and metabolically active, despite DNA damage. NF-kappaB transcription activation and increased Bcl-xL expression evidenced the promotion of pro-survival activity. A significant increase of pro-inflammatory macrophage markers CD80, CD86 and HLA-DR, but not CCR7, TNF and IL1B was observed after 10Gy cumulative doses, while anti-inflammatory markers CD163, MRC1, VCAN and IL-10 expression decreased, suggesting the modulation towards a more proinflammatory phenotype. Moreover, ionizing radiation induced macrophage morphological alterations and increased their phagocytic rate, without affecting matrix metalloproteases (MMP)2 and MMP9 activity. Importantly, irradiated macrophages promoted cancer cell-invasion and cancer cell-induced angiogenesis. Our work highlights macrophage ability to sustain cancer cell activities as a major concern that needs to be addressed to improve radiotherapy efficacy

Binding Free Energy Landscape of Domain-Peptide Interactions

Peptide recognition domains (PRDs) are ubiquitous protein domains which mediate large numbers of protein interactions in the cell. How these PRDs are able to recognize peptide sequences in a rapid and specific manner is incompletely understood. We explore the peptide binding process of PDZ domains, a large PRD family, from an equilibrium perspective using an all-atom Monte Carlo (MC) approach. Our focus is two different PDZ domains representing two major PDZ classes, I and II. For both domains, a binding free energy surface with a strong bias toward the native bound state is found. Moreover, both domains exhibit a binding process in which the peptides are mostly either bound at the PDZ binding pocket or else interact little with the domain surface. Consistent with this, various binding observables show a temperature dependence well described by a simple two-state model. We also find important differences in the details between the two domains. While both domains exhibit well-defined binding free energy barriers, the class I barrier is significantly weaker than the one for class II. To probe this issue further, we apply our method to a PDZ domain with dual specificity for class I and II peptides, and find an analogous difference in their binding free energy barriers. Lastly, we perform a large number of fixed-temperature MC kinetics trajectories under binding conditions. These trajectories reveal significantly slower binding dynamics for the class II domain relative to class I. Our combined results are consistent with a binding mechanism in which the peptide C terminal residue binds in an initial, rate-limiting step

Integrated Genome-Scale Prediction of Detrimental Mutations in Transcription Networks

A central challenge in genetics is to understand when and why mutations alter the phenotype of an organism. The consequences of gene inhibition have been systematically studied and can be predicted reasonably well across a genome. However, many sequence variants important for disease and evolution may alter gene regulation rather than gene function. The consequences of altering a regulatory interaction (or “edge”) rather than a gene (or “node”) in a network have not been as extensively studied. Here we use an integrative analysis and evolutionary conservation to identify features that predict when the loss of a regulatory interaction is detrimental in the extensively mapped transcription network of budding yeast. Properties such as the strength of an interaction, location and context in a promoter, regulator and target gene importance, and the potential for compensation (redundancy) associate to some extent with interaction importance. Combined, however, these features predict quite well whether the loss of a regulatory interaction is detrimental across many promoters and for many different transcription factors. Thus, despite the potential for regulatory diversity, common principles can be used to understand and predict when changes in regulation are most harmful to an organism

S100B as a potential biomarker and therapeutic target in multiple sclerosis

Multiple sclerosis (MS) pathology is characterized by neuroinflammation and demyelination. Recently, the inflammatory molecule S100B was identified in cerebrospinal fluid (CSF) and serum of MS patients. Although seen as an astrogliosis marker, lower/physiological levels of S100B are involved in oligodendrocyte differentiation/maturation. Nevertheless, increased S100B levels released upon injury may induce glial reactivity and oligodendrocyte demise, exacerbating tissue damage during an MS episode or delaying the following remyelination. Here, we aimed to unravel the functional role of S100B in the pathogenesis of MS. Elevated S100B levels were detected in the CSF of relapsing-remitting MS patients at diagnosis. Active demyelinating MS lesions showed increased expression of S100B and its receptor, the receptor for advanced glycation end products (RAGE), in the lesion area, while chronic active lesions displayed increased S100B in demyelinated areas with lower expression of RAGE in the rim. Interestingly, reactive astrocytes were identified as the predominant cellular source of S100B, whereas RAGE was expressed by activated microglia/macrophages. Using an ex vivo demyelinating model, cerebral organotypic slice cultures treated with lysophosphatidylcholine (LPC), we observed a marked elevation of S100B upon demyelination, which co-localized mostly with astrocytes. Inhibition of S100B action using a directed antibody reduced LPC-induced demyelination, prevented astrocyte reactivity and abrogated the expression of inflammatory and inflammasome-related molecules. Overall, high S100B expression in MS patient samples suggests its usefulness as a diagnostic biomarker for MS, while the beneficial outcome of its inhibition in our demyelinating model indicates S100B as an emerging therapeutic target in MS.This work was supported by Medal of Honor L’Oréal for Women in Science (FCT, UNESCO, L’Óreal) and innovation grant (Ordem dos Farmacêuticos) to AF, a post-doctoral grant from Fundação para a Ciência e Tecnologia (FCT-SFRH/BPD/96794/2013) and a DuPré Grant from the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS) to AB, and by FCT-Pest- OE/SAU/UI4013 to iMed.ULisboa.info:eu-repo/semantics/publishedVersio

It's not what you say but the way that you say it: an fMRI study of differential lexical and non-lexical prosodic pitch processing

<p>Abstract</p> <p>Background</p> <p>This study aims to identify the neural substrate involved in prosodic pitch processing. Functional magnetic resonance imaging was used to test the premise that prosody pitch processing is primarily subserved by the right cortical hemisphere.</p> <p>Two experimental paradigms were used, firstly pairs of spoken sentences, where the only variation was a single internal phrase pitch change, and secondly, a matched condition utilizing pitch changes within analogous tone-sequence phrases. This removed the potential confounder of lexical evaluation. fMRI images were obtained using these paradigms.</p> <p>Results</p> <p>Activation was significantly greater within the right frontal and temporal cortices during the tone-sequence stimuli relative to the sentence stimuli.</p> <p>Conclusion</p> <p>This study showed that pitch changes, stripped of lexical information, are mainly processed by the right cerebral hemisphere, whilst the processing of analogous, matched, lexical pitch change is preferentially left sided. These findings, showing hemispherical differentiation of processing based on stimulus complexity, are in accord with a 'task dependent' hypothesis of pitch processing.</p

Protein disulphide isomerase-assisted functionalization of proteinaceous substrates

Protein disulphide isomerase (PDI) is an enzyme that catalyzes thiol-disulphide exchange reactions among a broad spectrum of substrates, including proteins and low-molecular thiols and disulphides. As the first protein-folding catalyst reported, the study of PDI has mainly involved the correct folding of several cysteine-containing proteins. Its application on the functionalization of protein-based materials has not been extensively reported. Herein, we review the applications of PDI on the modification of proteinaceous substrates and discuss its future potential. The mechanism involved in PDI functionalization of fibrous protein substrates is discussed in detail. These approaches allow innovative applications in textile dyeing and finishing, medical textiles, controlled drug delivery systems and hair or skin care products.We thank to FCT 'Fundacao para a Ciencia e Tecnologia' (scholarship SFRH/BD/38363/2007) for providing Margarida Fernandes the grant for PhD studies

Quantitative Models of the Mechanisms That Control Genome-Wide Patterns of Transcription Factor Binding during Early Drosophila Development

Transcription factors that drive complex patterns of gene expression during animal development bind to thousands of genomic regions, with quantitative differences in binding across bound regions mediating their activity. While we now have tools to characterize the DNA affinities of these proteins and to precisely measure their genome-wide distribution in vivo, our understanding of the forces that determine where, when, and to what extent they bind remains primitive. Here we use a thermodynamic model of transcription factor binding to evaluate the contribution of different biophysical forces to the binding of five regulators of early embryonic anterior-posterior patterning in Drosophila melanogaster. Predictions based on DNA sequence and in vitro protein-DNA affinities alone achieve a correlation of ∼0.4 with experimental measurements of in vivo binding. Incorporating cooperativity and competition among the five factors, and accounting for spatial patterning by modeling binding in every nucleus independently, had little effect on prediction accuracy. A major source of error was the prediction of binding events that do not occur in vivo, which we hypothesized reflected reduced accessibility of chromatin. To test this, we incorporated experimental measurements of genome-wide DNA accessibility into our model, effectively restricting predicted binding to regions of open chromatin. This dramatically improved our predictions to a correlation of 0.6–0.9 for various factors across known target genes. Finally, we used our model to quantify the roles of DNA sequence, accessibility, and binding competition and cooperativity. Our results show that, in regions of open chromatin, binding can be predicted almost exclusively by the sequence specificity of individual factors, with a minimal role for protein interactions. We suggest that a combination of experimentally determined chromatin accessibility data and simple computational models of transcription factor binding may be used to predict the binding landscape of any animal transcription factor with significant precision