Coupling of CityGML-based Semantic City Models with Energy Simulation Tools: some Experiences

More and more cities are creating and adopting three-dimensional virtual city models as a means for data integration, harmonisation and storage, often based on CityGML, which is an international standard conceived specifically as information and data model for semantic city models at urban and territorial scale. A centralised database can thus foster the development of new integrated applications profiting from such an harmonised data source, in that detailed information is retrieved about building characteristics or any other relevant entities needed for urban planning (infrastructures, hydrography and terrain models, etc.). This paper focuses on the adoption of a CityGML-based semantic 3D virtual city model to perform energy simulations. It deals primarily with the demand side, and concentrated particularly on the spatial and temporal evaluation of the net energy demand for space heating of buildings in a city. Two approaches are presented: the first one deals with the estimation of the heating energy demand of buildings adopting a standard-based approach, which allow obtaining monthly values of heating energy demand. The second approach describes the first results as how a dynamic simulation tool can be connected to a CityGML-based city model in order to benefit from the amount of harmonised data stored therein and further refine the results, e.g. in terms of time resolution. As test area, a part of the city of Trento (Italy) was chosen

The iron-sulfur cluster assembly (ISC) protein Iba57 executes a tetrahydrofolate-independent function in mitochondrial [4Fe-4S] protein maturation

Mitochondria harbor the bacteria-inherited iron-sulfur cluster assembly (ISC) machinery to generate [2Fe-2S] and [4Fe-4S] proteins. In yeast, assembly of [4Fe-4S] proteins specifically involves the ISC proteins Isa1, Isa2, Iba57, Bol3, and Nfu1. Functional defects in their human equivalents cause the multiple mitochondrial dysfunction syndromes (MMDS), severe disorders with a broad clinical spectrum. The bacterial Iba57 ancestor YgfZ was described to require tetrahydrofolate (THF) for its function in the maturation of selected [4Fe-4S] proteins. Both YgfZ and Iba57 are structurally related to an enzyme family catalyzing THF-dependent one-carbon transfer reactions including GcvT of the glycine cleavage system. On this basis, a universally conserved folate requirement in ISC-dependent [4Fe-4S] protein biogenesis was proposed. To test this idea for mitochondrial Iba57, we performed genetic and biochemical studies in S. cerevisiae, and we solved the crystal structure of Iba57 from the thermophilic fungus Chaetomium thermophilum. We provide three lines of evidence for the THF independence of the Iba57-catalyzed [4Fe-4S] protein assembly pathway. First, yeast mutants lacking folate show no defect in mitochondrial [4Fe-4S] protein maturation. Second, the 3D structure of Iba57 lacks many of the side chain contacts to THF as defined in GcvT, and the THF binding pocket is constricted. Third, mutations in conserved Iba57 residues that are essential for THF-dependent catalysis in GcvT do not impair Iba57 function in vivo, in contrast to an exchange of the invariant, surface-exposed cysteine residue. We conclude that mitochondrial Iba57, despite structural similarities to both YgfZ and THF-binding proteins, does not utilize folate for its function

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

CopySwitch—in vivo Optimization of Gene Copy Numbers for Heterologous Gene Expression in Bacillus subtilis

The Gram-positive bacterium Bacillus subtilis has long been used as a host for production and secretion of industrially relevant enzymes like amylases and proteases. It is imperative for optimal efficiency, to balance protein yield and correct folding. While there are numerous ways of doing so on protein or mRNA level, our approach aims for the underlying number of coding sequences. Gene copy numbers are an important tuning valve for the optimization of heterologous gene expression. While some genes are best expressed from many gene copies, for other genes, medium or even single copy numbers are the only way to avoid formation of inclusion bodies, toxic gene dosage effects or achieve desired levels for metabolic engineering. In order to provide a simple and robust method to address above-mentioned issues in the Gram-positive bacterium Bacillus subtilis, we have developed an automatable system for the tuning of heterologous gene expression based on the host’s intrinsic natural competence and homologous recombination capabilities. Strains are transformed with a linearized, low copy number plasmid containing an antibiotic resistance marker and homology regions up- and downstream of the gene of interest. Said gene is copied onto the vector, rendering it circular and replicative and thus selectable. We could show an up to 3.6-fold higher gfp (green fluorescent protein) expression and up to 1.3-fold higher mPLC (mature phospholipase C) expression after successful transformation. Furthermore, the plasmid-borne gfp expression seems to be more stable, since over the whole cultivation period the share of fluorescent cells compared to all measured cells is consistently higher. A major benefit of this method is the ability to work with very large regions of interest, since all relevant steps are carried out in vivo and are thus far less prone to mechanical DNA damage

Analyzing the basic principles of tissue microarray data measuring the cooperative phenomena of marker proteins in invasive breast cancer

Background: The analysis of a protein-expression pattern from tissue microarray (TMA) data will not immediately give an answer on synergistic or antagonistic effects between the observed proteins. But contrary to apparent first impression, it is possible to reveal those cooperative phenomena from TMA data. The data is (1) preserving a lot of the original physiological information content and (2) because of minor variances between the tumor samples, contains several related slightly different biological states. We present here a largely assumption-free combinatorial analysis, related to correlation networks but with much less arbitrary constraints. A strong focus was put on the analysis of the basic data to analyze how the cooperative phenomena might be imprinted in the TMA data structure. Results: The study design was based on two independent panels of 589 and 366 invasive breast cancer cases from different institutions, assembled on tissue microarrays. The combinatorial analysis generates an optimal rank ordering of protein-expression coherence. The outcome of the analysis corresponds to all the single observations scattered over several publications and integrates them in one context. This means all these scattered observations can also be deduced from one TMA experiment. A comprehensive statistical meta-analysis of the TMA data suggests the existence of a superposition of three basic coherence situations, and offers the opportunity to analyze these data properties with additional real-world data and synthetic data in more detail. Conclusion: The presented algorithm gives molecular pathologists a tool to extract dependency information from TMA data. Beyond this practical benefit, some light was shed on how dependency aspects might be imprinted into expression data. This will certainly foster the refinement of algorithms to reconstruct dependency networks. The implementation of the algorithm is at the moment not end-user suitable, but available on request

Development of a Univariate Membrane-Based Mid-Infrared Method for Protein Quantitation and Total Lipid Content Analysis of Biological Samples

Biological samples present a range of complexities from homogeneous purified protein to multicomponent mixtures. Accurate qualification of such samples is paramount to downstream applications. We describe the development of an MIR spectroscopy-based analytical method offering simultaneous protein quantitation (0.25–5 mg/mL) and analysis of total lipid or detergent species, as well as the identification of other biomolecules present in biological samples. The method utilizes a hydrophilic PTFE membrane engineered for presentation of aqueous samples in a dried format compatible with fast infrared analysis. Unlike classical quantification techniques, the reported method is amino acid sequence independent and thus applicable to complex samples of unknown composition. By comparison to existing platforms, this MIR-based method enables direct quantification using minimal sample volume (2 µL); it is well-suited where repeat access and limited sample size are critical parameters. Further, accurate results can be derived without specialized training or knowledge of IR spectroscopy. Overall, the simplified application and analysis system provides a more cost-effective alternative to high-throughput IR systems for research laboratories with minimal throughput demands. In summary, the MIR-based system provides a viable alternative to current protein quantitation methods; it also uniquely offers simultaneous qualification of other components, notably lipids and detergents

Carbon nanotubes and helical carbon nanofibers grown by chemical vapour deposition on C60 fullerene supported Pd nanoparticles

Chemical vapour deposition (CVD) represents a cheap and versatile method to produce carbon nanostructures. Here we present how we by using a standard CVD setup together with Pd nano particles as a catalyst can produce helical fibers with very periodic pitch, helicity, and narrow diameter distribution. The C60 supported Pd catalyst particles are produced by a wet chemistry process and applied to silicon substrates. By raising the growth temperature from 550 °C to 800 °C we can tune the growth products from helical carbon fibers to straight hollow carbon fibers and finally to carbon nanotubes at the highest temperatures. In the intermediate temperature region of 650 °C a mixture of all three components appears. At 550 °C the efficiency of the process is optimized by the amount of water during the growth. Different from most previous studies we can detect most of the catalyst particles embedded in the grown structures. In all fibers the catalyst particles are situated exactly in the middle of the fibers suggesting a two-directional growth. From the shape of the catalyst particles and by adopting a simple model we conclude that the fibers coil due to blocked carbon diffusion pathways on or through the catalyst particles