Recent studies have established a concept of tumour necrosis factor‐α (TNF‐α)/Fas signalling crosstalk, highlighting TNF‐α as a critical cytokine in sensitizing hepatocytes to death induced by Fas activation. However, in the exact inflammatory response, besides TNF‐α, many other mediators, that might modulate apoptotic response differentially, are released. To resolve the issue, we studied the effects of lipopolysaccharide (LPS), one of the crucial inductors of inflammation in the liver, on apoptotic outcome. We show that LPS‐induced inflammation diminishes the sensitivity of hepatocytes to Fas stimulus in vivo at caspase‐8 level. Analysis of molecular mechanisms revealed an increased expression of various pro‐inflammatory cytokines in non‐parenchymal liver cells and hepatocyte‐specific increase in Bcl‐xL, associated with signal transducer and activator of transcription 3 (Stat3) phosphorylation. Pre‐treatment with ruxolitinib, a selective Janus kinase (JAK) 1/2 inhibitor, prevented the LPS‐induced Stat3 phosphorylation and restored the sensitivity of hepatocytes to Fas‐mediated apoptosis. Furthermore, ruxolitinib pre‐treatment diminished the LPS‐induced Bcl‐xL up‐regulation without an inhibitory effect on LPS‐induced expression of pro‐inflammatory cytokines. In summary, although the reports are showing that the effects of isolated pro‐inflammatory mediators, such as TNF‐α or neutrophils, are pro‐apoptotic, the overall effect of inflammatory milieu on hepatocytes in vivo is Stat3‐dependent desensitization to Fas‐mediated apoptosis.

The discovery of driver mutations is one of the key motivations for cancer genome sequencing. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumour types, we describe DriverPower, a software package that uses mutational burden and functional impact evidence to identify driver mutations in coding and non-coding sites within cancer whole genomes. Using a total of 1373 genomic features derived from public sources, DriverPower’s background mutation model explains up to 93% of the regional variance in the mutation rate across multiple tumour types. By incorporating functional impact scores, we are able to further increase the accuracy of driver discovery. Testing across a collection of 2583 cancer genomes from the PCAWG project, DriverPower identifies 217 coding and 95 non-coding driver candidates. Comparing to six published methods used by the PCAWG Drivers and Functional Interpretation Working Group, DriverPower has the highest F1 score for both coding and non-coding driver discovery. This demonstrates that DriverPower is an effective framework for computational driver discovery. Analysis of cancer genome sequencing data has enabled the discovery of driver mutations. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium the authors present DriverPower, a software package that identifies coding and non-coding driver mutations within cancer whole genomes via consideration of mutational burden and functional impact evidence.

Multi-omics datasets represent distinct aspects of the central dogma of molecular biology. Such high-dimensional molecular profiles pose challenges to data interpretation and hypothesis generation. ActivePathways is an integrative method that discovers significantly enriched pathways across multiple datasets using statistical data fusion, rationalizes contributing evidence and highlights associated genes. As part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we integrated genes with coding and non-coding mutations and revealed frequently mutated pathways and additional cancer genes with infrequent mutations. We also analyzed prognostic molecular pathways by integrating genomic and transcriptomic features of 1780 breast cancers and highlighted associations with immune response and anti-apoptotic signaling. Integration of ChIP-seq and RNA-seq data for master regulators of the Hippo pathway across normal human tissues identified processes of tissue regeneration and stem cell regulation. ActivePathways is a versatile method that improves systems-level understanding of cellular organization in health and disease through integration of multiple molecular datasets and pathway annotations. Multi-omics datasets pose major challenges to data interpretation and hypothesis generation owing to their high-dimensional molecular profiles. Here, the authors develop ActivePathways method, which uses data fusion techniques for integrative pathway analysis of multi-omics data and candidate gene discovery.

Long non-coding RNAs (lncRNAs) are a growing focus of cancer genomics studies, creating the need for a resource of lncRNAs with validated cancer roles. Furthermore, it remains debated whether mutated lncRNAs can drive tumorigenesis, and whether such functions could be conserved during evolution. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we introduce the Cancer LncRNA Census (CLC), a compilation of 122 GENCODE lncRNAs with causal roles in cancer phenotypes. In contrast to existing databases, CLC requires strong functional or genetic evidence. CLC genes are enriched amongst driver genes predicted from somatic mutations, and display characteristic genomic features. Strikingly, CLC genes are enriched for driver mutations from unbiased, genome-wide transposon-mutagenesis screens in mice. We identified 10 tumour-causing mutations in orthologues of 8 lncRNAs, including LINC-PINT and NEAT1, but not MALAT1. Thus CLC represents a dataset of high-confidence cancer lncRNAs. Mutagenesis maps are a novel means for identifying deeply-conserved roles of lncRNAs in tumorigenesis. Joana Carlevaro-Fita, Andrés Lanzós et al. present the Cancer LncRNA Census (CLC), a manually curated dataset of 122 long noncoding RNAs (lncRNAs) with experimentally-validated functions in cancer based on data from the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. CLC lncRNAs have unique gene features, and a number display evidence for cancer-driving functions that are conserved from humans to mice.

Abstract As smartphone use continues to become more embedded within daily life, identifying the factors driving their use in extreme environments may have numerous meaningful implications. Little is currently known about mountaineers’ intentions to use smartphones in high-alpine environments. Therefore, the purpose of this study was to examine the extent to which attitude, subjective norm, and perceived behavioral control predicted mountaineers’ intentions to use smartphones in high-alpine environments. A sample of 167 mountaineers from 37 countries completed a brief questionnaire about their intentions to use smartphones during their next high-alpine expedition. A series of multiple regression analyses were used to determine the salient beliefs influencing mountaineers’ smartphone use in high-alpine environments. The study findings provide a better understanding of the potential factors driving mountaineers’ use of smartphones. More broadly, these findings add to the growing body of literature regarding smartphone use in extreme environments.

Abstract Methadone eliminates heroin use, reduces death rates and criminality associated with heroin use, and improves patients’ health and social productivity. This study included long-term addicts who completed a methadone therapy program as well as relapsed patients. Liver and renal markers important for methadone metabolism were analyzed. Renal markers included urea and creatinine, while hepatic markers included total bilirubin, AST, ALT, γGT, and LDH as nonspecific but significant parameters of liver metabolism. The study included 34 male and 6 female heroin-dependent patients undergoing a rehabilitation program with methadone maintenance treatment (MMT). During therapy, average values of all parameters remained within the reference interval but individual parameters in some patients were very high. Significant differences for urea (0.00) and very high individual variations in all parameters, especially γGT and LDH, were found in patients who were in relapse. Age of the patients did not show a correlation with the presence of significant differences in serum biochemical parameters during therapy. Prolonged use of methadone therapy stabilizes high variations of liver and renal markers. MMT achieves a stabilization of serum indicators relevant for methadone metabolism that correlates with the duration of consumption and the type of opioid substance. The most important hepato-renal markers as indicators of therapy success are γGT, LDH, and creatinine. The validity of former enzymatic tests (AST, ALP, and ALT) should be seriously reconsidered in terms of MTT treatment success and monitoring the health of heroin addicts.

Hydrops fetalis is a serious condition indicating a bad prognosis of affected fetuses. Incidence of immune hydropsfetalis is significantly decreasing, whereas more and more non-immune hydropsfetalisis are identified. We described a case of the most difficult manifestation of hemolytic disease of a newborn due to rhesus incompatibility. Immune hydrops fetalis occurred due to inadequate immune prophylaxis. While treating the newborn, we applied exchange transfusion, additional transfusion and immunoglobulin therapy. With sensitized pregnant patients, it is necessary to regularly monitor the condition of fetus and titer of mother’s antibodies. Considering a difficulty of affected fetuses’ disease, it is necessary to strengthen preventive measures by application of rhesus immunoglobulin with affected Rh negative mothers.

A noninvasive diagnostic procedure that allows for in vivo microscopic examination of the epidermis, the dermoepidermal junction, and the papillary dermis. This aids in the identification of specific diagnostic patterns related to color and cell structure to aid in differentiating malignant and benign lesions.

A key mutational process in cancer is structural variation, in which rearrangements delete, amplify or reorder genomic segments that range in size from kilobases to whole chromosomes1–7. Here we develop methods to group, classify and describe somatic structural variants, using data from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), which aggregated whole-genome sequencing data from 2,658 cancers across 38 tumour types8. Sixteen signatures of structural variation emerged. Deletions have a multimodal size distribution, assort unevenly across tumour types and patients, are enriched in late-replicating regions and correlate with inversions. Tandem duplications also have a multimodal size distribution, but are enriched in early-replicating regions—as are unbalanced translocations. Replication-based mechanisms of rearrangement generate varied chromosomal structures with low-level copy-number gains and frequent inverted rearrangements. One prominent structure consists of 2–7 templates copied from distinct regions of the genome strung together within one locus. Such cycles of templated insertions correlate with tandem duplications, and—in liver cancer—frequently activate the telomerase gene TERT. A wide variety of rearrangement processes are active in cancer, which generate complex configurations of the genome upon which selection can act. Whole-genome sequencing data from more than 2,500 cancers of 38 tumour types reveal 16 signatures that can be used to classify somatic structural variants, highlighting the diversity of genomic rearrangements in cancer.

Abstract Multi-criteria decision-making (MCDM) methods are very useful tools for daily decision-making in different fields. In addition, determining an acceptable solution with respect to different factors is certainly a very demanding and difficult task. In this paper, a new Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS) method for a sustainable supplier selection in the healthcare industry (in a polyclinic) in Bosnia and Herzegovina is developed. The advantages of the developed method are: the consideration of an anti-ideal and ideal solution at the very beginning of the formation of an initial matrix, closer determination of utility degree in relation to both solutions, the proposal of a new way to determine utility functions and their aggregation, the possibility to consider a large set of criteria and alternatives while maintaining the stability of the method. Supplier selection is very important for organizations in the medical industry. Sustainability in the supplier selection process in the medical industry is a strategically important issue, and poorly implemented in the private medical sector. Therefore, the example explains how to use the MARCOS method to select sustainable suppliers in the private medical sector. A case study of a sustainable supplier selection for the healthcare industry (a polyclinic) includes ranking of eight alternatives with regard to 21 criteria for all aspects of sustainability. The results and verification of the new method are carried out throughout a comprehensive sensitivity analysis. 21 scenarios with changes in the weight values of criteria were established, the measurement scale from 1 to 9 was changed to 1–5, a comparison with six other MCDM methods was performed, and it was verified in dynamic conditions which implied a change of the elements of the initial decision-making matrix. All phases of the sensitivity analysis showed the validity of MARCOS method. The obtained results and all scenarios in sensitivity analysis show that A2 remains the best alternative.

Advances in cloud computing make cloud services as an appealing solution for enabling services flexibility and availability on demand to accommodate users' needs. The terms and the guarantees of service provision are negotiated and then stated in a Service Level Agreement (SLA). To facilitate a wider acceptance of such services, beside the standard properties, security has to be taken into consideration as well. One way to facilitate this is to provide a corresponding security assurance case. For that purpose, in this work we propose to split the security service assessment between an independent third party and a service user, where the former assess a security assurance case and the latter negotiates particular security solutions implemented for a service. For the systematic part of the security process that is independently assessed, in this paper we focus on the formal realizability check of service constraints expressed within an SLA. To enable this, we formalize the check at both service design-, and run-time, needed due to frequent updates required to maintain an agreed security level. The formalization is tailored for the SLAC language specifically, which is extended to cover a proposed set of security objectives. Moreover, we use an example of an SLA expressed in terms of SLAC language, which includes security guarantees to illustrate the approach.

Abstract Passive design and landscape variables (e.g., rooftop albedo and shading vegetation) are frequently proposed as important green building techniques. However, there is a paucity of literature demonstrating their large-scale effects with empirically measured building stocks and observed residential energy consumption. This paper uses a spatial Durbin error model (SDEM) approach to test the effects of passive building performance indicators, such as orientation, albedo, and NDVI, on city-wide summertime household billed energy data in Gainesville, FL. Our findings suggest that vegetation and albedo reduce energy consumption, but our model did not produce similar significant results for building orientation and footprint compactness. These results provide evidence to suggest high albedo roofing and purposeful shading are important energy conservation strategies for energy-efficient residential neighborhoods.

Aim To determine stereological structural parameters of the parenchymal part of the placenta, placental weight and volume of adolescent pregnant women and their correlation with newborns' birth weight. Methods This prospective study was conducted on a total of 60 human placentas of term pregnancy, divided into two groups according to the age of pregnant women. Experimental group consisted of 30 placentas of pregnant women aged 13-19 years. Control group consisted of 30 placentas of pregnant women aged 20-35 years. Stereological analysis was performed. Results Volumetric density of terminal villi of adolescent placentas was significantly higher than the one of control group (p <0.0001). The volumetric density of fibrinoid of adolescent placentas was significantly lower than of the control group (p <0.0001). Total volume of terminal villi of adolescent placentas was significantly higher than of the control group (p<0.0001). The total volume of fibrinoid of adolescent placentas was significantly lower than of the control group (p<0.0001). Newborns of adolescent pregnancies had in average lower birth weight of 439.01 g compared to the newborns of the control group (p <0.00001). Conclusion Adolescent pregnancy affects placental structure, weight and volume. Newborns of adolescent pregnancy have optimal body weight.