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Small-scale spatial abilities that involve the mental representation and transformation of two- and three-dimensional images and manipulation of objects at table-top have been studied extensively and are considered predictive of both interest and success in STEM disciplines. However, research investigating the relation of large-scale spatial abilities to STEM disciplines is sparse. The paper describes the design and implementation of a study for assessing individual differences (if any) in spatial abilities in both figural and environmental spaces between STEM experts (with over 10 years of experience) and non-experts (individuals without any studies in STEM fields). Participants' performance in 16 small-, 10 large-scale tasks, and one self-assessment questionnaire at environmental scale was evaluated to assess their corresponding abilities. Results indicate differences between experts and non-experts, which are mostly highlighted for small-scale abilities where experts outperform non-experts. At large scale, some significant differences are identified, which also favor experts. Correlations among the variables tested provide evidence that different abilities are prominent between experts and non-experts.

Research interest in Augmented Reality (AR) has been steadily increasing in the past decades. However, while we see a wide range of publications implementing AR nowadays, it is often the case that the software is not included in the publication, leading to future research having to re-introduce similar custom AR solutions. We identify one such case, that of geolocated AR, which poses a deceptively complex issue, namely that of correctly aligning a virtual view with geo-referenced material around the user. We present here UnityGeoAR, a package for the widely used game engine Unity3D, that handles geolocation, reprojection, and AR view alignment through a minimal Application Programming Interface (API), in an effort to standardize geo-AR development and reduce development and implementation time for such a widely used aspect of AR.

Abstract The essential role of gut microbiota in health and disease is well recognized, but the biochemical details that underlie the beneficial impact remain largely undefined. To maintain its stability, microbiota participates in an interactive host-microbiota metabolic signaling, impacting metabolic phenotypes of the host. Dysbiosis of microbiota results in alteration of certain microbial and host metabolites. Identifying these markers could enhance early detection of certain diseases. We report LC–MS based non-targeted metabolic profiling that demonstrates a large effect of gut microbiota on mammalian tissue metabolites. It was hypothesized that gut microbiota influences the overall biochemistry of host metabolome and this effect is tissue-specific. Thirteen different tissues from germ-free (GF) and conventionally-raised (MPF) C57BL/6NTac mice were selected and their metabolic differences were analyzed. Our study demonstrated a large effect of microbiota on mammalian biochemistry at different tissues and resulted in statistically-significant modulation of metabolites from multiple metabolic pathways (p ≤ 0.05). Hundreds of molecular features were detected exclusively in one mouse group, with the majority of these being unique to specific tissue. A vast metabolic response of host to metabolites generated by the microbiota was observed, suggesting gut microbiota has a direct impact on host metabolism.

Saccharomyces cerevisiae is a sustainable yeast with many applications in the food industry. Here, we study the use of a Saccharomyces cerevisiae model composed of three different industrial strains (a wine, a beer and a baker’s strain) to assess the antifungal activity of three organic plant-based extracts (Hypericum perforatum 10% w/w, Pistacia lentiscus var. Chia 20% w/w and Rosmarinus officinalis 6% w/w). Three different methods were employed (agar disc diffusion, spot assay, and growth curve analysis). Only the Rosmarinus officinalis extract (6% w/w) exhibited inhibitory activity against all the tested yeast strains in the agar disc diffusion method. In the spot assay, all extracts and their carrier oils (sunflower oil and caprylic triglyceride) exerted similar mild antifungal activity. In the growth curve analysis, all extracts significantly lowered the growth rate of the yeasts, but this was not observed for the carrier oils. The results highlighted that it is important to consider more than one method for testing the antimicrobial activity of different compounds. The three yeast strains exhibited differences in their susceptibility to pharmaceutical antifungals, and the beer and baker’s yeasts were resistant to itraconazole. Moreover, polyphenols were detected in all natural extracts which may be linked to their antifungal activity. Our results suggest that we might consider multiple use of these natural extracts in the food industry as food additives or even preservatives to delay food spoilage.

The main topic of this work focuses on the semantic, historical and spatial documentation of Minor Historical Centres (MHC) with a focus on (semi-abandoned alpine) hamlets. The key point is the possibility to standardise spatial information in the domain of MHC and their related cultural, architectural, built and landscape heritage. This work analyses the notions of historical centre and ancient area, which took different meanings and evolved over the centuries. MHC are historical part of cities, villages and hamlets (urban, rural, minor or abandoned) with cultural, social and economic values. Thus, MHC need to be preserved, documented and safeguarded. The spatial and semantic documentation is a fundamental tool for increasing their knowledge. In these places, many actors and stakeholders are involved in different activities, and for this reason, they need to share common knowledge and use a unique language. In this regard, spatial ontology is of relevant interest and usability. Ontologies are conceptual structures that formalise specific knowledge and create a unique and standard thesaurus that ensures semantic interoperability. This paper is part of a PhD research targeted at developing an ontology containing helpful information to manage, share and collect data on MHC due to the lack of an interoperable structure to formalise such knowledge. The main aim is to populate and enrich the already developed ontological structure with data of a mountain semi-abandoned hamlet: Pomieri. The methodological workflow is validated, enriching and populating the ontology, adding classes and instances with information and unstructured data of a real data case study.

As the amount of semi-structured and unstructured information sources expands at an exponential rate, there is a growing demand for semantic information elicitation of the immanent knowledge included in these sources. Semantic information elicitation processes such as semantic information extraction, linking, and annotation aim to make the knowledge explicit and unveil aspects latent in these sources to support knowledge discovery, semantic analysis, and visualization. The paper describes the implementation of Latent Dirichlet Allocation (LDA) topic modeling and association rule mining with FP-Growth for knowledge discovery. RapidMiner, an open-source data mining software is used for the objectives of this work.

Parasitic plants obtain nutrients from their hosts. Here the authors show that nitrogen sufficiency suppresses parasitism in the root parasite Phtheirospermum japonicum by increasing levels of the phytohormone ABA suggesting that the degree of parasitism is regulated by nutrient availability.

Small-scale spatial abilities that involve the mental representation and transformation of two- and three-dimensional images and manipulation of objects at table-top have been studied extensively and are considered predictive of both interest and success in STEM disciplines. However, research investigating the relation of large-scale spatial abilities to STEM disciplines is sparse. The paper describes the design and implementation of a study for assessing individual differences (if any) in spatial abilities in both figural and environmental spaces between STEM experts (with over 10 years of experience) and non-experts (individuals without any studies in STEM fields). Participants' performance in 16 small-, 10 large-scale tasks, and one self-assessment questionnaire at environmental scale was evaluated to assess their corresponding abilities. Results indicate differences between experts and non-experts, which are mostly highlighted for small-scale abilities where experts outperform non-experts. At large scale, some significant differences are identified, which also favor experts. Correlations among the variables tested provide evidence that different abilities are prominent between experts and non-experts. [ABSTRACT FROM AUTHOR]

Because of the need for new sustainable future alternatives, the re-inhabitation of rural areas, hinterlands, small historical urban centres and villages has become a unique real opportunity. Therefore, it is necessary to define and adopt new sustainable urban planning and building permits to follow this path. These processes involve both various actors and disciplines and a variety of spatial and semantic data. For this reason, the present research aims at providing a methodology to build the necessary spatial documentation of historical centres and villages by adopting an ontology-based workflow. Existing ontologies and conceptualisations have been considered together with classes and rules from city historical core regulations. A case study has been selected considering its available spatial datasets and national data models. The bottom-up approach here adopted aims at validating and enriching a reference ontology previously developed in the domain of historical centre by adding new concepts and relations from selected regulation plans and other existing ontologies and data models. Finally, the obtained ontology is also populated with instances of concepts and relations.

Research on knowledge discovery in the geospatial domain currently focuses on semi-structured, even on unstructured rather than fully structured content. The attention has been put on the plethora of resources on the Web, such as html pages, news articles, blogs, social media etc. Semantic information extraction in geospatial-oriented approaches is further used for semantic analysis, search, and retrieval. The aim of this paper is to extract, analyse and visualize geospatial semantic information and emotions from texts on climate change. A collection of articles on climate change is used to demonstrate the developed approach. These articles describe environmental and socio-economic dimensions of climate change across the Earth, and include a wealth of information related to environmental concepts and geographic locations affected by it. The results are analysed in order to understand which specific human emotions are associated with environmental concepts and/or locations, as well as which environmental terms are linked to locations. For the better understanding of the above-mentioned information, semantic networks are used as a powerful visualization tool of the links among concepts – locations – emotions.

Standardised data formats and data models are essential for data integration and interoperability, which in turn adds value to data by allowing its reuse in multiple contexts. For this reason, in recent years extensive efforts have been focused on standards development. When representing the built environment, 3D city models and Building Information Models are particularly relevant, and their integration is now required to underpin use cases that cover the full life-cycle of a built asset, including design and planning as well as operations and management, and to support legal applications such as cadastral systems. For those kinds of data, CityGML by the Open Geospatial Consortium and Industry Foundation Classes by buildingSMART are the most popular reference standards. However, many users report, often through informal channels, the difficulties of working with these formats. This paper summarizes the outcomes of the GeoBIM Benchmark 2019, a scientific initiative funded by ISPRS and EuroSDR to collect insights into the most relevant issues encountered in the management of CityGML and IFC within existing software. Alongside data management (import, visualisation, analysis, export) problems, issues of particular consequence in terms of integration relate to georeferencing IFC files and the conversions among the two kinds of formats and models. Thus, the benchmark was designed to explore these tasks in available software. Following analysis of the benchmark results, a key outcome is the impossibility to find clear patterns in the behaviour of tools, which consequently means there is no consistency in the implementation of standards. Although the results could seem disappointing, the criticality in managing these standards as they are was described and this awareness can be the starting point for further research or further standards development. Finally, this project was useful to gather a wide community around this topic, and the discussion about the GeoBIM-related issues was definitely pushed.

Architectural, built heritage and historical buildings embody cultural heritage value and - as known - they need to be studied, documented, persevered and represented. Although there are many fields involved in these activities, none of these considered individually can fully represent the heritage with a complete level of detail and information. The present work aims to investigate the different levels of detail and granularity among different communities involved in historical buildings tasks to semantically define different concepts. In this context, ontologies are considered as an effective solution for the formal conceptualization of the domains involved, providing a common language for knowledge sharing and reuse. The study starts from existing knowledge (standards, vocabularies, thesauri, classifications) and conceptualisations for regional, urban and architectural heritage and geographic information for various tasks (restoration, documentation and heritage studies, risk prevention, heritage asset and facility management, education and tourism, urban planning and energy refurbishment/performance). A specific use case involving historical buildings in fortified centres across different levels of detail is described to show how existing knowledge and standards conceptualisation need to be integrated and extended.

Saccharomyces cerevisiae is a sustainable yeast with many applications in the food industry. Here, we study the use of a Saccharomyces cerevisiae model composed of three different industrial strains (a wine, a beer and a baker's strain) to assess the antifungal activity of three organic plant-based extracts (Hypericum perforatum 10% w/w, Pistacia lentiscus var. Chia 20% w/w and Rosmarinus officinalis 6% w/w). Three different methods were employed (agar disc diffusion, spot assay, and growth curve analysis). Only the Rosmarinus officinalis extract (6% w/w) exhibited inhibitory activity against all the tested yeast strains in the agar disc diffusion method. In the spot assay, all extracts and their carrier oils (sunflower oil and caprylic triglyceride) exerted similar mild antifungal activity. In the growth curve analysis, all extracts significantly lowered the growth rate of the yeasts, but this was not observed for the carrier oils. The results highlighted that it is important to consider more than one method for testing the antimicrobial activity of different compounds. The three yeast strains exhibited differences in their susceptibility to pharmaceutical antifungals, and the beer and baker's yeasts were resistant to itraconazole. Moreover, polyphenols were detected in all natural extracts which may be linked to their antifungal activity. Our results suggest that we might consider multiple use of these natural extracts in the food industry as food additives or even preservatives to delay food spoilage. [ABSTRACT FROM AUTHOR]

Background: Human mesenchymal stem/stromal cells (MSCs) and their secreted molecules exert beneficial effects in injured tissues by promoting tissue regeneration and angiogenesis and by inhibiting inflammation and fibrosis. We have previously demonstrated that the therapeutic activity of fetal MSCs derived from amniotic fluid (AF-MSCs) and their hepatic progenitor-like cells (HPL) is mediated by paracrine effects in a mouse model of acute hepatic failure (AHF). Methods: Herein, we have combined proteomic profiling of the AF-MSCs and HPL cell secretome with ex vivo and in vivo functional studies to identify specific soluble factors, which underpin tissue regeneration in AHF. Findings: The anti-inflammatory molecule Annexin-A1 (ANXA1) was detected at high levels in both AF-MSC and HPL cell secretome. Further functional analyses revealed that the shRNA-mediated knock-down of ANXA1 in MSCs (shANXA1-MSCs) decreased their proliferative, clonogenic and migratory potential, as well as their ability to differentiate into HPL cells. Liver progenitors (oval cells) from AHF mice displayed reduced proliferation when cultured ex vivo in the presence of conditioned media from shANXA1-MSCs compared to control MSCs secretome. Intra-hepatic delivery of conditioned media from control MSCs but not shANXA1-MSCs reduced liver damage and circulating levels of pro-inflammatory cytokines in AHF. Interpretation: Collectively, our study uncovers secreted Annexin-A1 as a novel effector of MSCs in liver regeneration and further underscores the potential of cell-free therapeutic strategies for liver diseases. Fund: Fondation Santé, GILEAD Asklipeios Grant, Fellowships of Excellence – Siemens, IKY, Reinforcement of Postdoctoral Researchers, IKY. Keywords: MSCs, Secretome, Annexin-A1, Hepatic progenitors, Acute hepatic failure

Historical small urban centres are of increasing interest to different interacting fields such as architectural heritage protection and conservation, urban planning, disaster response, sustainable development and tourism. They are defined at different levels (international, national, regional), by various organizations and standards, incorporate numerous aspects (natural and built environment, infrastructures and open spaces, social, economic, and cultural processes, tangible and intangible heritage) and face various challenges (urbanization, globalization, mass tourism, climate change, etc.). However, their current specification within large-scale geospatial databases is similar to those of urban areas in a broad sense resulting in the loss of many aspects forming this multifaceted concept. The present study considers the available ontologies and data models, coming from various domains and having different granularities and levels of detail, to represent historical small urban centres information. The aim is to define the needs for extension and integration of them in order to develop a multidisciplinary, integrated semantic representation. Relevant conventions and other legislation documents, ontologies and standards for cultural heritage (CIDOC-CRM, CRMgeo, Getty Vocabularies), 3D city models (CityGML), building information models (IFC) and regional landscape plans are analysed to identify concepts, relations, and semantic features that could form a holistic semantic model of historical small urban centres.

Abstract Background Spironucleus salmonicida is an anaerobic parasite that can cause systemic infections in Atlantic salmon. Unlike other diplomonad parasites, such as the human pathogen Giardia intestinalis, Spironucleus species can infiltrate the blood stream of their hosts eventually colonizing organs, skin and gills. How this presumed anaerobe can persist and invade oxygenated tissues, despite having a strictly anaerobic metabolism, remains elusive. Results To investigate how S. salmonicida response to oxygen stress, we performed RNAseq transcriptomic analyses of cells grown in the presence of oxygen or antioxidant-free medium. We found that over 20% of the transcriptome is differentially regulated in oxygen (1705 genes) and antioxidant-depleted (2280 genes) conditions. These differentially regulated transcripts encode proteins related to anaerobic metabolism, cysteine and Fe-S cluster biosynthesis, as well as a large number of proteins of unknown function. S. salmonicida does not encode genes involved in the classical elements of oxygen metabolism (e.g., catalases, superoxide dismutase, glutathione biosynthesis, oxidative phosphorylation). Instead, we found that genes encoding bacterial-like oxidoreductases were upregulated in response to oxygen stress. Phylogenetic analysis revealed some of these oxygen-responsive genes (e.g., nadh oxidase, rubrerythrin, superoxide reductase) are rare in eukaryotes and likely derived from lateral gene transfer (LGT) events into diplomonads from prokaryotes. Unexpectedly, we observed that many host evasion- and invasion-related genes were also upregulated under oxidative stress suggesting that oxygen might be an important signal for pathogenesis. Conclusion While oxygen is toxic for related organisms, such as G. intestinalis, we find that oxygen is likely a gene induction signal for host invasion- and evasion-related pathways in S. salmonicida. These data provide the first molecular evidence for how S. salmonicida could tolerate oxic host environments and demonstrate how LGT can have a profound impact on the biology of anaerobic parasites.

Eukaryotic 5’−3’ mRNA decay plays important roles during development and in response to stress, regulating gene expression post-transcriptionally. In Caenorhabditis elegans, deficiency of DCAP-1/DCP1, the essential co-factor of the major cytoplasmic mRNA decapping enzyme, impacts normal development, stress survival and ageing. Here, we show that overexpression of dcap-1 in neurons of worms is sufficient to increase lifespan through the function of the insulin/IGF-like signaling and its effector DAF-16/FOXO transcription factor. Neuronal DCAP-1 affects basal levels of INS-7, an ageing-related insulin-like peptide, which acts in the intestine to determine lifespan. Short-lived dcap-1 mutants exhibit a neurosecretion-dependent upregulation of intestinal ins-7 transcription, and diminished nuclear localization of DAF-16/FOXO. Moreover, neuronal overexpression of DCP1 in Drosophila melanogaster confers longevity in adults, while neuronal DCP1 deficiency shortens lifespan and affects wing morphogenesis, cell non-autonomously. Our genetic analysis in two model-organisms suggests a critical and conserved function of DCAP-1/DCP1 in developmental events and lifespan modulation.

The massive amount of user-generated content available today presents a new challenge for the geospatial domain and a great opportunity to delve into linguistic, semantic, and cognitive aspects of geographic information. Ontology-based information extraction is a new, prominent field in which a domain ontology guides the extraction process and the identification of pre-defined concepts, properties, and instances from natural language texts. The paper describes an approach for enriching and populating a geospatial ontology using both a top-down and a bottom-up approach in order to enable semantic information extraction. The top-down approach is applied in order to incorporate knowledge from existing ontologies. The bottom-up approach is applied in order to enrich and populate the geospatial ontology with semantic information (concepts, relations, and instances) extracted from domain-specific web content.

The parasitic plant Phtheirospermum japonicum modifies the pectin methylesterification status in its haustoria in a dynamic and tissue-specific manner to allow efficient infection of the host plant. Parasitic plants are globally prevalent pathogens with important ecological functions but also potentially devastating agricultural consequences. Common to all parasites is the formation of the haustorium which requires parasite organ development and tissue invasion into the host. Both processes involve cell wall modifications. Here, we investigated a role for pectins during haustorium development in the facultative parasitic plant Phtheirospermum japonicum. Using transcriptomics data from infected Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa), we identified genes for multiple P. japonicum pectin methylesterases (PMEs) and their inhibitors (PMEIs) whose expression was upregulated by haustoria formation. Changes in PME and PMEI expression were associated with tissue-specific modifications in pectin methylesterification. While de-methylesterified pectins were present in outer haustorial cells, highly methylesterified pectins were present in inner vascular tissues, including the xylem bridge that connects parasite to host. Specifically blocking xylem bridge formation in the haustoria inhibited several PME and PMEI genes from activating. Similarly, inhibiting PME activity using chemicals or by overexpressing PMEI genes delayed haustoria development. Our results suggest a dynamic and tissue-specific regulation of pectin contributes to haustoria initiation and to the establishment of xylem connections between parasite and host. [ABSTRACT FROM AUTHOR]

Abstract Multicolour Flow Cytometry (MFC) produces multidimensional analytical data on the quantitative expression of multiple markers on single cells. This data contains invaluable biomedical information on (1) the marker expressions per cell, (2) the variation in such expression across cells, (3) the variability of cell marker expression across samples that (4) may vary systematically between cells collected from donors and patients. Current conventional and even advanced data analysis methods for MFC data explore only a subset of these levels. The Discriminant Analysis of MultiAspect CYtometry (DAMACY) we present here provides a comprehensive view on health and disease responses by integrating all four levels. We validate DAMACY by using three distinct datasets: in vivo response of neutrophils evoked by systemic endotoxin challenge, the clonal response of leukocytes in bone marrow of acute myeloid leukaemia (AML) patients, and the complex immune response in blood of asthmatics. DAMACY provided good accuracy 91–100% in the discrimination between health and disease, on par with literature values. Additionally, the method provides figures that give insight into the marker expression and cell variability for more in-depth interpretation, that can benefit both physicians and biomedical researchers to better diagnose and monitor diseases that are reflected by changes in blood leukocytes.

Abstract Background Diagnosis of pulmonary thromboembolism (PTE) in dogs relies on computed tomography pulmonary angiography (CTPA), but detailed interpretation of CTPA images is demanding for the radiologist and only large vessels may be evaluated. New approaches for better detection of smaller thrombi include dual energy computed tomography (DECT) as well as computer assisted diagnosis (CAD) techniques. The purpose of this study was to investigate the performance of quantitative texture analysis for detecting dogs with PTE using grey-level co-occurrence matrices (GLCM) and multivariate statistical classification analyses. CT images from healthy (n = 6) and diseased (n = 29) dogs with and without PTE confirmed on CTPA were segmented so that only tissue with CT numbers between −1024 and −250 Houndsfield Units (HU) was preserved. GLCM analysis and subsequent multivariate classification analyses were performed on texture parameters extracted from these images. Results Leave-one-dog-out cross validation and receiver operator characteristic (ROC) showed that the models generated from the texture analysis were able to predict healthy dogs with optimal levels of performance. Partial Least Square Discriminant Analysis (PLS-DA) obtained a sensitivity of 94% and a specificity of 96%, while Support Vector Machines (SVM) yielded a sensitivity of 99% and a specificity of 100%. The models, however, performed worse in classifying the type of disease in the diseased dog group: In diseased dogs with PTE sensitivities were 30% (PLS-DA) and 38% (SVM), and specificities were 80% (PLS-DA) and 89% (SVM). In diseased dogs without PTE the sensitivities of the models were 59% (PLS-DA) and 79% (SVM) and specificities were 79% (PLS-DA) and 82% (SVM). Conclusion The results indicate that texture analysis of CTPA images using GLCM is an effective tool for distinguishing healthy from abnormal lung. Furthermore the texture of pulmonary parenchyma in dogs with PTE is altered, when compared to the texture of pulmonary parenchyma of healthy dogs. The models’ poorer performance in classifying dogs within the diseased group, may be related to the low number of dogs compared to texture variables, a lack of balanced number of dogs within each group or a real lack of difference in the texture features among the diseased dogs.

Nowadays, cultural and historical built heritage can be more effectively preserved, valorised and documented using advanced geospatial technologies. In such a context, there is a major issue concerning the automation of the process and the extraction of useful information from a huge amount of spatial information acquired by means of advanced survey techniques (i.e., highly detailed LiDAR point clouds). In particular, in the case of historical built heritage (HBH) there are very few effective efforts. Therefore, in this paper, the focus is on establishing the connections between semantic and geometrical information in order to generate a parametric, structured model from point clouds using ontology as an effective approach for the formal conceptualisation of application domains. Hence, in this paper, an ontological schema is proposed to structure HBH representations, starting with international standards, vocabularies, and ontologies (CityGML-Geography Markup Language, International Committee for Documentation conceptual reference model (CIDOC-CRM), Industry Foundation Classes (IFC), Getty Art and Architecture Thesaurus (AAT), as well as reasoning about morphology of historical centres by analysis of real case studies) to represent the built and architecture domain. The validation of such schema is carried out by means of its use to guide the segmentation of a LiDAR point cloud from a castle, which is later used to generate parametric geometries to be used in a historical building information model (HBIM).

The pilot survey presented herein explores the possibilities given by three-dimensional (3D)-printed maps to students with visual impairment (VI) for learning the spatial distribution of geographic phenomena. The main research questions are: (a) whether students with VI can perceive two phenomena depicted on the same 3D-printed map and (b) whether they perform better when interacting with individual tactile maps for each spatial phenomenon than when interacting with a single 3D-printed map displaying the two spatial phenomena simultaneously. Our analysis indicates that 3D-printed maps can be a valuable alternative for the education of students with VI even when they represent two spatial phenomena simultaneously. [ABSTRACT FROM AUTHOR]