1. Predicting the pathogenicity of bacterial genomes using widely spread protein families
Shaked Naor-Hoffmann, Dina Svetlitsky, Neta Sal-Man, Yaron Orenstein, Michal Ziv-Ukelson BMC Bioinformatics. 2022 Jun 24;23(1):253.doi: 10.1186/s12859-022-04777-w.
Background:The human body is inhabited by a diverse community of commensal non-pathogenic bacteria, many of which are essential for our health. By contrast, pathogenic bacteria have the ability to invade their hosts and cause a disease. Characterizing the differences between pathogenic and commensal non-pathogenic bacteria is important for the detection of emerging pathogens and for the development of new treatments. Previous methods for classification of bacteria as pathogenic or non-pathogenic used either raw genomic reads or protein families as features. Using protein families instead of reads provided a better interpretability of the resulting model. However, the accuracy of protein-families-based classifiers can still be improved. Results:We developed a wide scope pathogenicity classifier (WSPC), a new protein-content-based machine-learning classification model. We trained WSPC on a newly curated dataset of 641 bacterial genomes, where each genome belongs to a different species. A comparative analysis we conducted shows that WSPC outperforms existing models on two benchmark test sets. We observed that the most discriminative protein-family features in WSPC are widely spread among bacterial species. These features correspond to proteins that are involved in the ability of bacteria to survive and replicate during an infection, rather than proteins that are directly involved in damaging or invading the host.
2. Study on the Ingredient Proportions and After-Treatment of Laser Sintering Walnut Shell Composites
Yueqiang Yu, Yanling Guo, Ting Jiang, Jian Li, Kaiyi Jiang, Hui Zhang Materials (Basel). 2017 Dec 2;10(12):1381.doi: 10.3390/ma10121381.
To alleviate resource shortage, reduce the cost of materials consumption and the pollution of agricultural and forestry waste, walnut shell composites (WSPC) consisting of walnut shell as additive and copolyester hot melt adhesive (Co-PES) as binder was developed as the feedstock of selective laser sintering (SLS). WSPC parts with different ingredient proportions were fabricated by SLS and processed through after-treatment technology. The density, mechanical properties and surface quality of WSPC parts before and after post processing were analyzed via formula method, mechanical test and scanning electron microscopy (SEM), respectively. Results show that, when the volume fraction of the walnut shell powder in the WSPC reaches the maximum (40%), sintered WSPC parts have the smallest warping deformation and the highest dimension precision, although the surface quality, density, and mechanical properties are low. However, performing permeating resin as the after-treatment technology could considerably increase the tensile, bending and impact strength by 496%, 464%, and 516%, respectively.
3. Urban sprawl in Canada: Values in all 33 Census Metropolitan Areas and corresponding 469 Census Subdivisions between 1991 and 2011
Mehrdokht Pourali, Craig Townsend, Angela Kross, Alex Guindon, Jochen A G Jaeger Data Brief. 2022 Feb 10;41:107941.doi: 10.1016/j.dib.2022.107941.eCollection 2022 Apr.
The dataset presented here provides the degree of urban sprawl across 33 Census Metropolitan Areas (CMAs) in Canada of 2011 together with the 469 Census Subdivisions (CSDs) located within the 2011 boundaries of the CMAs, for the years 1991, 2001, and 2011. The dataset contains the values of weighted urban proliferation (WUP) and weighted sprawl per capita (WSPC) and their components. The landscape-oriented value of WUP indicates how strongly the landscape within the boundaries of a reporting unit is sprawled per square meter, while WSPC is inhabitant-oriented and reveals how much on average an inhabitant or workplace is contributing to urban sprawl in the reporting unit. The values of the components of the WUP and WSPC metrics are provided as well: percentage of built-up area (PBA), urban dispersion (DIS), land uptake per person (LUP), and urban permeation (UP). The values of full-time equivalents for the numbers of jobs, which were considered in the calculation of LUP values (pertaining to the number of inhabitants and jobs) are also included in order to facilitate future research.
