Identifying hybrid heating systems in the residential sector from smart meter data

In this paper, we identify hybrid heating systems on a single residential customer’s premises using smart meter data. A comprehensive methodology is developed at a generic level for residential sector buildings to identify the type of primary and support heating systems. The methodology includes the use of unsupervised and supervised learning algorithms both separately and combined. It is applied to two datasets that vary in size, quality of data, and availability and reliability of background information. The datasets contain hourly electricity consumption profiles of residential customers together with the outdoor temperature. The validation metrics for the developed algorithms are elaborated to provide a probabilistic evaluation of the model. The results show that it is possible to identify the types of both primary and support heating systems in the form of probability of having electric- or non-electric type of heating. The results obtained help estimate the flexibility domain of the residential building sector and thereby generate a high value for the energy system as a whole

Genes related to the white face colour pattern in eight Russian cattle breeds

One of the major effects of domestication is change of animal coat colour to up to complete white colour of the whole body. It is possible that white colour of livestock animals had aesthetic significance for humans as well. The first step towards detection of genes and mutations controlling white colouring in animals is the genome-wide association studies. These studies, however, have not been done for the cattle breeds native to the Russian Federation. The aim of this study was therefore to identify genomic intervals and candidate genes that could be responsible for white face colouring in eight Russian cattle breeds. The data on genome-wide genotyping of 131,709 high-quality single nucleotide polymorphisms (SNPs) on 148 animas have been used in the program ­EMMAX. Association analysis has been performed using two related phenotypes: a) the white face with the rest of the body of any colour and b) white face with the rest of the body of different (non-white) colour. In the first case, the only statistically significant marker found was the SNP BovineHD0500019319 located on cattle chromosome (BTA) 5. The same SNP was the most significant within the cluster of three SNPs on BTA5: 68,803,879–69,365,854 associated also with the second phenotype. Five genes were found within this interval in the cattle genome, out of which the most likely functional candidate was SLC41A2, with the SNP BovineHD0500019319 found within its intronic sequence. SLC41A2 encodes a magnesium transporter protein. However, the function of this gene is not well established. Other members of this gene family are the key genes controlling differences in human skin and animal coat colour. Additional significant association signals with the second phenotype have been detected in BTA 1–4, 6–15, 18, 19, 24, 27, and 29. Overall, 37 genomic intervals have been detected associated with white face colouring in eight Russian native cattle breeds

Biochar as a potential carrier for agricultural beneficial microbes

© SGEM2018. In the recent years, growing interest to biochar as a means of improving soil quality is observed. Biochar is a product of pyrolysis of biomass such as plant residues or organic wastes. Biochars made of manures are special because they can solve two environmental problems simultaneously – waste reduction and soil fertilization, but they are less studied. In our research, we suggest to improve the properties of biochars derived from manures by means of immobilizing beneficial microbes on them. In this study, the choice of the method of such immobilization was made. Biochar from chicken manure produced at 5000C peak temperature for 3 h was used as a model biochar, and Pseudomonas putida able to suppress soil borne phytopathogens was used as a model microbe. Two types of immobilization in laboratory conditions were used. The first one included spreading of night culture concentrated ~3 fold (final cells amount – about 107 gene copies ml-1) on the surface of biochar in a ratio of 1:1, then drying in sterile conditions for 24 h and packing. The second one included wetting biochar in the culture medium with ~1.5 fold concentrated night culture, shaking for 1 h, then drying in sterile conditions for 24 h and packing. To track the survival rate of immobilized bacteria, scanning electron microscopy as well as quantitative PCR were used. It was shown that bacteria survived similarly after both types of immobilization during the first 10 days, however, later wet immobilization seemed to be more effective, which was proved by higher bacterial gene numbers on that biochar as compared with the dry treated one. We suggest that this is due to deeper penetration of microbes into the pores of biochars while using the wet method

<i>In silico</i> mapping of coronary artery disease genes

To date, more than 100 loci associated with coronary artery disease (CAD) have been detected in large-scale genome-wide studies. For some of the several hundreds of genes located in these loci, roles in the pathogenesis of the disease have been shown. However, the genetic mechanisms and specific genes controlling this disease are still not fully understood. This study is aimed at in silico search for new CAD genes. We performed a gene-based association analysis, where all polymorphic variants within a gene are analyzed simultaneously. The analysis was based on the results of the genome-wide association studies (GWAS) available from the open databases MICAD (120,575 people, 85,112 markers) and UK Biobank (337,199 people, 10,894,597 markers). We used the sumFREGAT package implementing a wide range of new methods for gene-based association analysis using summary statistics. We found 88 genes demonstrating significant gene-based associations. Forty-four of the identified genes were already known as CAD genes. Furthermore, we identified 28 additional genes in the known CAD loci. They can be considered as new candidate genes. Finally, we identified sixteen new genes (AGPAT4, ARHGEF12, BDP1, DHX58, EHBP1, FBF1, HSPB9, NPBWR2, PDLIM5, PLCB3, PLEKHM2, POU2F3, PRKD2, TMEM136, TTC29 and UTP20) outside the known loci. Information about the functional role of these genes allows us to consider many of them as candidates for CAD. The 41 identified genes did not have significant GWAS signals and they were identified only due to simultaneous consideration of all variants within the gene in the framework of gene-based analysis. These results demonstrate that gene-based association analysis is a powerful tool for gene mapping. The method can utilize huge amounts of GWAS results accumulated in the world to map different traits and diseases. This type of studies is widely available, as it does not require additional material costs

Case of combined nephropathy in a young child

The article presents a clinical case of combined nephropathy in a young child complicated by metabolic disorders with the development of urolithiasis.В статье представлен клинический случай сочетанной нефропатии у ребёнка раннего возраста, осложнённый метаболическими нарушениями с развитием мочекаменной болезни

Multivariate discovery and replication of five novel loci associated with Immunoglobulin G <i>N</i>-glycosylation

Multivariate analysis methods can uncover the relationship between phenotypic measures characterised by modern omic techniques. Here the authors conduct a multivariate GWAS on IgG N-glycosylation phenotypes and identify 5 novel loci enriched in immune system genes

Genome-wide association study and scan for signatures of selection point to candidate genes for body temperature maintenance under the cold stress in Siberian cattle populations

Design of new highly productive livestock breeds, well-adapted to local climatic conditions is one of the aims of modern agriculture and breeding. The genetics underlying economically important traits in cattle are widely studied, whereas our knowledge of the genetic mechanisms of adaptation to local environments is still scarce. To address this issue for cold climates we used an integrated approach for detecting genomic intervals related to body temperature maintenance under acute cold stress. Our approach combined genome-wide association studies (GWAS) and scans for signatures of selection applied to a cattle population (Hereford and Kazakh Whiteheaded beef breeds) bred in Siberia. We utilized the GGP HD150K DNA chip containing 139,376 single nucleotide polymorphism markers

Weighted functional linear regression models for gene-based association analysis

<div><p>Functional linear regression models are effectively used in gene-based association analysis of complex traits. These models combine information about individual genetic variants, taking into account their positions and reducing the influence of noise and/or observation errors. To increase the power of methods, where several differently informative components are combined, weights are introduced to give the advantage to more informative components. Allele-specific weights have been introduced to collapsing and kernel-based approaches to gene-based association analysis. Here we have for the first time introduced weights to functional linear regression models adapted for both independent and family samples. Using data simulated on the basis of GAW17 genotypes and weights defined by allele frequencies via the beta distribution, we demonstrated that type I errors correspond to declared values and that increasing the weights of causal variants allows the power of functional linear models to be increased. We applied the new method to real data on blood pressure from the ORCADES sample. Five of the six known genes with <i>P</i> < 0.1 in at least one analysis had lower <i>P</i> values with weighted models. Moreover, we found an association between diastolic blood pressure and the <i>VMP1</i> gene (<i>P</i> = 8.18×10⁻⁶), when we used a weighted functional model. For this gene, the unweighted functional and weighted kernel-based models had <i>P</i> = 0.004 and 0.006, respectively. The new method has been implemented in the program package FREGAT, which is freely available at <a href="https://cran.r-project.org/web/packages/FREGAT/index.html" target="_blank">https://cran.r-project.org/web/packages/FREGAT/index.html</a>.</p></div