Building typological classification in Switzerland using deep learning methods for seismic assessment

Natural disasters, such as earthquakes, have always represented a danger to human life. Seismic risk assessment consists of the evaluation of existing buildings and their expected response in case of an earthquake; the exposure model of buildings plays a key role in risk calculations. With this respect, in recent years, advanced techniques have been developed to speed up and automatize the processes of data acquisition to data interpretation, although it is worth mentioning that the visual survey is essential to train and validate Machine Learning (ML) methods. In the present study, the identification of building types is conducted by exploiting the traditional visual survey to implement a Deep Learning (DL) classification model. As a first step, city mapping schemes are obtained by classifying buildings according to the main features (i.e., construction period and height classes). Then, Random Forest (RF), a supervised learning algorithm, is applied to classify different building types by exploiting all their attributes. The RF model is trained and tested on the cities of Neuchatel and Yverdon-Les-Bains. The decent accuracy of the results encourages the application of the method to different cities, with proper adjustments in datasets, features and algorithms

Inference of single-cell phylogenies from lineage tracing data using Cassiopeia.

The pairing of CRISPR/Cas9-based gene editing with massively parallel single-cell readouts now enables large-scale lineage tracing. However, the rapid growth in complexity of data from these assays has outpaced our ability to accurately infer phylogenetic relationships. First, we introduce Cassiopeia-a suite of scalable maximum parsimony approaches for tree reconstruction. Second, we provide a simulation framework for evaluating algorithms and exploring lineage tracer design principles. Finally, we generate the most complex experimental lineage tracing dataset to date, 34,557 human cells continuously traced over 15 generations, and use it for benchmarking phylogenetic inference approaches. We show that Cassiopeia outperforms traditional methods by several metrics and under a wide variety of parameter regimes, and provide insight into the principles for the design of improved Cas9-enabled recorders. Together, these should broadly enable large-scale mammalian lineage tracing efforts. Cassiopeia and its benchmarking resources are publicly available at www.github.com/YosefLab/Cassiopeia

Deferiprone: Pan-selective Histone Lysine Demethylase Inhibition Activity and Structure Activity Relationship Study

Deferiprone (DFP) is a hydroxypyridinone-derived iron chelator currently in clinical use for iron chelation therapy. DFP has also been known to elicit antiproliferative activities, yet the mechanism of this effect has remained elusive. We herein report that DFP chelates the Fe 2+ ion at the active sites of selected iron-dependent histone lysine demethylases (KDMs), resulting in pan inhibition of a subfamily of KDMs. Specifically, DFP inhibits the demethylase activities of six KDMs - 2A, 2B, 5C, 6A, 7A and 7B - with low micromolar IC 50 s while considerably less active or inactive against eleven KDMs - 1A, 3A, 3B, 4A-E, 5A, 5B and 6B. The KDM that is most sensitive to DFP, KDM6A, has an IC 50 that is between 7- and 70-fold lower than the iron binding equivalence concentrations at which DFP inhibits ribonucleotide reductase (RNR) activities and/or reduces the labile intracellular zinc ion pool. In breast cancer cell lines, DFP potently inhibits the demethylation of H3K4me3 and H3K27me3, two chromatin posttranslational marks that are subject to removal by several KDM subfamilies which are inhibited by DFP in cell-free assay. These data strongly suggest that DFP derives its anti-proliferative activity largely from the inhibition of a sub-set of KDMs. The docked poses adopted by DFP at the KDM active sites enabled identification of new DFP-based KDM inhibitors which are more cytotoxic to cancer cell lines. We also found that a cohort of these agents inhibited HP1-mediated gene silencing and one lead compound potently inhibited breast tumor growth in murine xenograft models. Overall, this study identified a new chemical scaffold capable of inhibiting KDM enzymes, globally changing histone modification profiles, and with specific anti-tumor activities

Activity, stability and structure of laccase in betaine based natural deep eutectic solvents

Natural deep eutectic solvents (NADES) play a role as alternative media to water in living organisms. They are formed by mixing two or more natural compounds in certain ratios producing a liquid having a lower melting point than those of the individual NADES components. Although, the eutectics medium bring several advantages as enhanced solubility of non-polar substrates and/or products, however, these advantages would often be limited by a lower stability of biocatalysts in these systems. To examine this matter, biochemical characterization, thermal stability and tertiary structure of laccase from Bacillus HR03 was investigated as a model in betaine and choline based NADES. In eutectics containing choline, a sudden drop in enzyme activity and stability was observed. Betaine based eutectics exhibited a better media for the laccase stability in comparison with the aqueous buffer and choline chloride eutectics. The enzyme highest activity was observed in 20 (v/v) glycerol:betaine (2:1). Among betaine based eutectics, the enzyme exhibited its highest stability in sorbitol:betaine:water (1:1:1) and glycerol:betaine (2:1) compared to the aqueous buffer at 80 and 90 °C. Associated conformational changes caused by solvents were monitored using fluorescence technique. Finally, the effects of NADES on the enzyme activity and stability were discussed. © 2017 Elsevier B.V

Activity, stability and structure of laccase in betaine based natural deep eutectic solvents

Natural deep eutectic solvents (NADES) play a role as alternative media to water in living organisms. They are formed by mixing two or more natural compounds in certain ratios producing a liquid having a lower melting point than those of the individual NADES components. Although, the eutectics medium bring several advantages as enhanced solubility of non-polar substrates and/or products, however, these advantages would often be limited by a lower stability of biocatalysts in these systems. To examine this matter, biochemical characterization, thermal stability and tertiary structure of laccase from Bacillus HR03 was investigated as a model in betaine and choline based NADES. In eutectics containing choline, a sudden drop in enzyme activity and stability was observed. Betaine based eutectics exhibited a better media for the laccase stability in comparison with the aqueous buffer and choline chloride eutectics. The enzyme highest activity was observed in 20 (v/v) glycerol:betaine (2:1). Among betaine based eutectics, the enzyme exhibited its highest stability in sorbitol:betaine:water (1:1:1) and glycerol:betaine (2:1) compared to the aqueous buffer at 80 and 90 °C. Associated conformational changes caused by solvents were monitored using fluorescence technique. Finally, the effects of NADES on the enzyme activity and stability were discussed. © 2017 Elsevier B.V

Parameters Affecting the Biosynthesis of Gold Nanoparticles Using the Aquatic Extract of Scrophularia striata and their Antibacterial Properties

Green synthesis is a simple, low-cost, non-toxic, environmentally friendly and efficient approach to use. Leaf extract of plants rich in polyphenols, such as flavonoids, is a powerful agent in reducing the synthesis of gold nanoparticles. The purpose of this study is to investigate the parameters affecting the biosynthesis of gold nanoparticles using the aqueous extract of Scrophularia striata plant and their antimicrobial activity. Biosynthesis of gold nanoparticles was accomplished by the interaction of golden salt (HAuCl4, 3H(2)O) with aqueous extract of Scrophularia striata. In order to obtain uniform and spherical nanoparticles, the following parameters affecting the biosynthesis of nanoparticles were investigated and optimized by ultraviolet-spectrophotometric technique; golden salt concentration, extract volume, pH and reaction time. Transmission electron microscopy and X-ray diffraction technique were also used to further characterize nanoparticles. Finally, the anti-bacterial properties of gold nanoparticles were investigated by disc diffusion method. The resulting absorption spectra exhibited strong peaks at 570 nm, which is a specific wavelength for gold nanoparticles. Transmission electron microscopy studies showed that the gold nanoparticles had a spherical shape with a mean diameter of 5-10nm, and the highest diameter of the growth inhibition zone was observed on the diameter of the hafnium bacteria (14mm). In this study, it was observed that, with the aid of Scrophularia striata aqueous extracts, a golden nanoparticle showed an antibacterial activity against gram-negative bacteria

Molecular recording of mammalian embryogenesis

Ontogeny describes the emergence of complex multicellular organisms from single totipotent cells. This field is particularly challenging in mammals, owing to the indeterminate relationship between self-renewal and differentiation, variation in progenitor field sizes, and internal gestation in these animals. Here we present a flexible, high-information, multi-channel molecular recorder with a single-cell readout and apply it as an evolving lineage tracer to assemble mouse cell-fate maps from fertilization through gastrulation. By combining lineage information with single-cell RNA sequencing profiles, we recapitulate canonical developmental relationships between different tissue types and reveal the nearly complete transcriptional convergence of endodermal cells of extra-embryonic and embryonic origins. Finally, we apply our cell-fate maps to estimate the number of embryonic progenitor cells and their degree of asymmetric partitioning during specification. Our approach enables massively parallel, high-resolution recording of lineage and other information in mammalian systems, which will facilitate the construction of a quantitative framework for understanding developmental processes