EXPERIENCING HERITAGE DYNAMIC THROUGH VISUALIZATION

Abstract. The present article aims to consider the added value attached to the usage of new technologies in a project aimed to study heritage. Indeed, multimedia devices could be used to create representations useful to develop and disseminate information integrating the architectural and territorial framework and to reach a general understanding.The processed data come from a research project, based on an interdisciplinary approach, address to the study of medieval buildings in Armenia, Vayots Dzor region, with the aim of studying and understanding the cultural heritage.Three different technologies are used to visualize and disseminate the results of the analyses carried out: the video, the hologram, and the virtual reality. These digital visualization methods enable experts to make the topics investigated accessible and comprehensible to a wider general public with a didactic and informative aim.The solid 3D-model of the site allows to virtually reproduce the reality and to provide a spatial perception of the site. Indeed, it is a neutral base, represents the morphological conformation and settlements, a landscape whose reference points are easily identified with the historical architectures, helping the public and spectators to get oriented inside the territory. These methods of representation allow to move from general view to particular, or to a different frame appropriate to the addressed topic. Thus, it binds the scientific research with the visual part, and enable communication, even in a context where it is difficult to use a common spoken or written language.</p

gam genomic assemblies merger

Motivations. In the last 3 years more than 20 assemblers have been proposed to tackle the hard task of assembling. Recent evaluation efforts (Assemblathon 1 and GAGE) demonstrated that none of these tools clearly outperforms the others. However, results clearly show that some assemblers performs better than others on specific regions and statistics while poorly performing on other regions and evaluation measures. With this picture in mind we developed GAM (Genomic Assemblies Merger) whose primary goal is to merge two or more assemblies in order to obtain a more contiguous one. Moreover, as a by-product of the merging step, GAM is able to correct mis-assemblies. GAM does not need global alignment between contigs, making it unique among others Assembly Reconciliation tools. In this way a computationally expensive alignment is avoided, and paralog sequences (likely to create false connection among contigs) do not represent a problem. GAM procedure is based only on the information coming from reads used in the assembling phases, and it can be used even on assemblies obtained with different datasets. Methods. Let us concentrate on the the merging of two assemblies, dubbed M and S. As a preprocessing step, that is an almost mandatory analysis, reads (or a subset of them) used in the assembling phase are aligned against M and S using a SAM-compatible aligner (e.g., BWA, rNA). GAM takes as input M, S and the two SAM files produced in the preprocessing step. The main idea is to identify fragments belonging to M and S having high similarity. For this purpose, GAM identifies regions, named blocks, belonging to M and S that share an high enough amount of reads (i.e. regions sharing the same aligned reads). After all blocks are identified the Assembly Graph (AG) is built: each node corresponds to a block and a directed edge connects block A to block B if the first precedes the second in either M or S (see Fig.1). Once AG is available, the merging phase can start. As a first step GAM identifies genomic regions in which assemblies contradict each other (loops, bifurcations, etc.). These areas represent potential inconsistencies between the two sequences. We chose to be as much conservative as possible electing (for example) M to be the Master assembly: all its contigs are supposed to be correct and cannot be contradicted. S becomes the Slave and everywhere an inconsistency is found, M is preferred to S. After the identification and the resolution of problematic regions, GAM visits the simplified graph, merges contigs accordingly to blocks and edges in AG (each merging phase is performed using a Smith-Waterman algorithm variant) and finally outputs the new improved assembly. GAM is not only limited to contigs, it can also work with scaffolds, filling the N's inserted by an assembler and not by the other. Results. GAM has been tested on several real datasets, in particular on Olea's chloroplast (241X Illumina paired reads and 21X 454 paired reads), Populus trichocarpa (82X Illumina paired reads), boa constrictor (40X Illumina paired reads). Illumina reads have average length of 100 bp and insert size of 500 bp. All tests have been performed on a computer equipped with 8 cores and 32GB RAM. ABySS and CLC were selected as assemblers. Results are summarized in Fig. 1. Olea's chloroplast has been used as a proof of concept experiment. The presence of a reference sequence allowed GAM's output validation (using dnadiff). Two assemblies were obtained with CLC using Illumina and 454 data. GAM was used to merge them. Figure 1 shows how GAM assembly is not only more contiguous but also more correct: while Master (CLC-Illumina) and Slave (CLC-454) have 58 and 39 suspicious regions respectively, GAM has only 14 of those. On Populus trichocarpa and Boa constrictor, CLC assemblies were used as master due to their better contiguity. In both cases assemblies returned by GAM were more contiguous (see Fig. 1)

Diversity and dynamics of seaweed associated microbial communities inhabiting the lagoon of venice

Seaweeds are a group of essential photosynthetic organisms that harbor a rich diversity of associated microbial communities with substantial functions related to host health and defense. Environmental and anthropogenic stressors may disrupt the microbial communities and their metabolic activity, leading to host physiological alterations that negatively affect seaweeds’ performance and survival. Here, the bacterial communities associated with one of the most common seaweed, Ulva laetevirens Areshough, were sampled over a year at three sites of the lagoon of Venice affected by different environmental and anthropogenic stressors. Bacterial communities were characterized through Illumina sequencing of the V4 hypervariable region of 16S rRNA genes. The study demonstrated that the seaweed associated bacterial communities at sites impacted by environmental stressors were host-specific and differed significantly from the less affected site. Furthermore, these communities were significantly distinct from those of the surrounding seawater. The bacterial communities’ composition was significantly correlated with environmental parameters (nutrient concentrations, dissolved oxygen saturation, and pH) across sites. This study showed that several more abundant bacteria on U. laetevirens at stressed sites belonged to taxa related to the host response to the stressors. Overall, environmental parameters and anthropogenic stressors were shown to substantially affect seaweed associated bacterial communities, which reflect the host response to environmental variations

On the occasion of the thirtieth anniversary of the journal Acta Stomatologica Croatica

Introduction: Opioid receptors are currently classified as Mu (\u3bc), Delta (\u3b4), Kappa (\u3ba) plus the opioid related nociceptin/orphanin FQ (N/OFQ) peptide receptor (NOP). Despite compelling evidence for interactions and benefits of targeting more than one receptor type in producing analgesia, clinical ligands are Mu agonists. In this study we have designed a Mu-NOP agonist named DeNo. The Mu agonist component is provided by dermorphin, a peptide isolated from the skin of Phyllomedusa frogs and the NOP component by the endogenous agonist N/OFQ. Methods: We have assessed receptor binding profile of DeNo and compared with dermorphin and N/OFQ. In a series of functional screens we have assessed the ability to (i) increase Ca2+ in cells coexpressing recombinant receptors and a the chimeric protein G\u3b1qi5, (ii) stimulate the binding of GTP\u3b3[35S], (iii) inhibit cAMP formation, (iv) activate MAPKinase, (v) stimulate receptor-G protein and arrestin interaction using BRET, (vi) electrically stimulated guinea pig ileum (gpI) assay and (vii) ability to produce analgesia via the intrathecal route in rats. Results: DeNo bound to Mu (pKi; 9.55) and NOP (pKi; 10.22) and with reasonable selectivity. This translated to increased Ca2+ in G\u3b1qi5 expressing cells (pEC50 Mu 7.17; NOP 9.69), increased binding of GTP\u3b3[35S] (pEC50 Mu 7.70; NOP 9.50) and receptor-G protein interaction in BRET (pEC50 Mu 8.01; NOP 9.02). cAMP formation was inhibited and arrestin was activated (pEC50 Mu 6.36; NOP 8.19). For MAPK DeNo activated p38 and ERK1/2 at Mu but only ERK1/2 at NOP. In the gpI DeNO inhibited electrically-evoked contractions (pEC50 8.63) that was sensitive to both Mu and NOP antagonists. DeNo was antinociceptive in rats. Conclusion: Collectively these data validate the strategy used to create a novel bivalent Mu-NOP peptide agonist by combining dermorphin (Mu) and N/OFQ (NOP). This molecule behaves essentially as the parent compounds in vitro. In the antonocicoeptive assays employed in this study DeNo displays only weak antinociceptive properties

Feature-by-Feature – Evaluating De Novo Sequence Assembly

The whole-genome sequence assembly (WGSA) problem is among one of the most studied problems in computational biology. Despite the availability of a plethora of tools (i.e., assemblers), all claiming to have solved the WGSA problem, little has been done to systematically compare their accuracy and power. Traditional methods rely on standard metrics and read simulation: while on the one hand, metrics like N50 and number of contigs focus only on size without proportionately emphasizing the information about the correctness of the assembly, comparisons performed on simulated dataset, on the other hand, can be highly biased by the non-realistic assumptions in the underlying read generator. Recently the Feature Response Curve (FRC) method was proposed to assess the overall assembly quality and correctness: FRC transparently captures the trade-offs between contigs' quality against their sizes. Nevertheless, the relationship among the different features and their relative importance remains unknown. In particular, FRC cannot account for the correlation among the different features. We analyzed the correlation among different features in order to better describe their relationships and their importance in gauging assembly quality and correctness. In particular, using multivariate techniques like principal and independent component analysis we were able to estimate the “excess-dimensionality” of the feature space. Moreover, principal component analysis allowed us to show how poorly the acclaimed N50 metric describes the assembly quality. Applying independent component analysis we identified a subset of features that better describe the assemblers performances. We demonstrated that by focusing on a reduced set of highly informative features we can use the FRC curve to better describe and compare the performances of different assemblers. Moreover, as a by-product of our analysis, we discovered how often evaluation based on simulated data, obtained with state of the art simulators, lead to not-so-realistic results

Photobacterium profundum under Pressure:A MS-Based Label-Free Quantitative Proteomics Study

Photobacterium profundum SS9 is a Gram-negative bacterium, originally collected from the Sulu Sea. Its genome consists of two chromosomes and a 80 kb plasmid. Although it can grow under a wide range of pressures, P. profundum grows optimally at 28 MPa and 15°C. Its ability to grow at atmospheric pressure allows for both easy genetic manipulation and culture, making it a model organism to study piezophily. Here, we report a shotgun proteomic analysis of P. profundum grown at atmospheric compared to high pressure using label-free quantitation and mass spectrometry analysis. We have identified differentially expressed proteins involved in high pressure adaptation, which have been previously reported using other methods. Proteins involved in key metabolic pathways were also identified as being differentially expressed. Proteins involved in the glycolysis/gluconeogenesis pathway were up-regulated at high pressure. Conversely, several proteins involved in the oxidative phosphorylation pathway were up-regulated at atmospheric pressure. Some of the proteins that were differentially identified are regulated directly in response to the physical impact of pressure. The expression of some proteins involved in nutrient transport or assimilation, are likely to be directly regulated by pressure. In a natural environment, different hydrostatic pressures represent distinct ecosystems with their own particular nutrient limitations and abundances. However, the only variable considered in this study was atmospheric pressure