Evaluating system architectures for driving range estimation and charge planning for electric vehicles

Due to sparse charging infrastructure and short driving ranges, drivers of battery electric vehicles (BEVs) can experience range anxiety, which is the fear of stranding with an empty battery. To help eliminate range anxiety and make BEVs more attractive for customers, accurate range estimation methods need to be developed. In recent years, many publications have suggested machine learning algorithms as a fitting method to achieve accurate range estimations. However, these algorithms use a large amount of data and have high computational requirements. A traditional placement of the software within a vehicle\u27s electronic control unit could lead to high latencies and thus detrimental to user experience. But since modern vehicles are connected to a backend, where software modules can be implemented, high latencies can be prevented with intelligent distribution of the algorithm parts. On the other hand, communication between vehicle and backend can be slow or expensive. In this article, an intelligent deployment of a range estimation software based on ML is analyzed. We model hardware and software to enable performance evaluation in early stages of the development process. Based on simulations, different system architectures and module placements are then analyzed in terms of latency, network usage, energy usage, and cost. We show that a distributed system with cloud‐based module placement reduces the end‐to‐end latency significantly, when compared with a traditional vehicle‐based placement. Furthermore, we show that network usage is significantly reduced. This intelligent system enables the application of complex, but accurate range estimation with low latencies, resulting in an improved user experience, which enhances the practicality and acceptance of BEVs

A rare missense mutation in CHRNA4 associates with smoking behavior and its consequences

Using Icelandic whole-genome sequence data and an imputation approach we searched for rare sequence variants in CHRNA4 and tested them for association with nicotine dependence. We show that carriers of a rare missense variant (allele frequency = 0.24%) within CHRNA4, encoding an R336C substitution, have greater risk of nicotine addiction than non-carriers as assessed by the Fagerstrom Test for Nicotine Dependence (P= 1.2 × 10−4). The variant also confers risk of several serious smoking-related diseases previously shown to be associated with the D398N substitution in CHRNA5. We observed odds ratios (ORs) of 1.7–2.3 for lung cancer(LC;P= 4.0 × 10−4), chronic obstructive pulmonary disease (COPD;P= 9.3 × 10−4), peripheral artery disease (PAD;P= 0.090) and abdominal aortic aneurysms (AAAs; P= 0.12), and the variant associates strongly with the early-onset forms of LC (OR = 4.49,P= 2.2 × 10−4), COPD (OR = 3.22,P= 2.9 × 10−4), PAD (OR = 3.47,P= 9.2 × 10−3) and AAA (OR = 6.44, P= 6.3 × 10−3). Joint analysis of the four smoking-related diseases reveals significant association (P= 6.8 × 10−5), particularly for early-onset cases (P=2.1 × 10−7). Our results are in agreement with functional studies showing that the human α4β2 isoform of the channel containing R336C has less sensitivity for its agonists than the wild-type form following nicotine incubation

Chromosome 15q25 (CHRNA3-CHRNA5) Variation Impacts Indirectly on Lung Cancer Risk

Genetic variants at the 15q25 CHRNA5-CHRNA3 locus have been shown to influence lung cancer risk however there is controversy as to whether variants have a direct carcinogenic effect on lung cancer risk or impact indirectly through smoking behavior. We have performed a detailed analysis of the 15q25 risk variants rs12914385 and rs8042374 with smoking behavior and lung cancer risk in 4,343 lung cancer cases and 1,479 controls from the Genetic Lung Cancer Predisposition Study (GELCAPS). A strong association between rs12914385 and rs8042374, and lung cancer risk was shown, odds ratios (OR) were 1.44, (95% confidence interval (CI): 1.29–1.62, P = 3.69×10−10) and 1.35 (95% CI: 1.18–1.55, P = 9.99×10−6) respectively. Each copy of risk alleles at rs12914385 and rs8042374 was associated with increased cigarette consumption of 1.0 and 0.9 cigarettes per day (CPD) (P = 5.18×10−5 and P = 5.65×10−3). These genetically determined modest differences in smoking behavior can be shown to be sufficient to account for the 15q25 association with lung cancer risk. To further verify the indirect effect of 15q25 on the risk, we restricted our analysis of lung cancer risk to never-smokers and conducted a meta-analysis of previously published studies of lung cancer risk in never-smokers. Never-smoker studies published in English were ascertained from PubMed stipulating - lung cancer, risk, genome-wide association, candidate genes. Our study and five previously published studies provided data on 2,405 never-smoker lung cancer cases and 7,622 controls. In the pooled analysis no association has been found between the 15q25 variation and lung cancer risk (OR = 1.09, 95% CI: 0.94–1.28). This study affirms the 15q25 association with smoking and is consistent with an indirect link between genotype and lung cancer risk

Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders

Personality is influenced by genetic and environmental factors1 and associated with mental health. However, the underlying genetic determinants are largely unknown. We identified six genetic loci, including five novel loci2,3, significantly associated with personality traits in a meta-analysis of genome-wide association studies (N = 123,132–260,861). Of these genomewide significant loci, extraversion was associated with variants in WSCD2 and near PCDH15, and neuroticism with variants on chromosome 8p23.1 and in L3MBTL2. We performed a principal component analysis to extract major dimensions underlying genetic variations among five personality traits and six psychiatric disorders (N = 5,422–18,759). The first genetic dimension separated personality traits and psychiatric disorders, except that neuroticism and openness to experience were clustered with the disorders. High genetic correlations were found between extraversion and attention-deficit– hyperactivity disorder (ADHD) and between openness and schizophrenia and bipolar disorder. The second genetic dimension was closely aligned with extraversion–introversion and grouped neuroticism with internalizing psychopathology (e.g., depression or anxiety)

Zoonotic hepatitis E: animal reservoirs and emerging risks

Hepatitis E virus (HEV) is responsible for enterically-transmitted acute hepatitis in humans with two distinct epidemiological patterns. In endemic regions, large waterborne epidemics with thousands of people affected have been observed, and, in contrast, in non-endemic regions, sporadic cases have been described. Although contaminated water has been well documented as the source of infection in endemic regions, the modes of transmission in non-endemic regions are much less known. HEV is a single-strand, positive-sense RNA virus which is classified in the Hepeviridae family with at least four known main genotypes (1–4) of mammalian HEV and one avian HEV. HEV is unique among the known hepatitis viruses, in which it has an animal reservoir. In contrast to humans, swine and other mammalian animal species infected by HEV generally remain asymptomatic, whereas chickens infected by avian HEV may develop a disease known as Hepatitis-Splenomegaly syndrome. HEV genotypes 1 and 2 are found exclusively in humans while genotypes 3 and 4 are found both in humans and other mammals. Several lines of evidence indicate that, in some cases involving HEV genotypes 3 and 4, animal to human transmissions occur. Furthermore, individuals with direct contact with animals are at higher risk of HEV infection. Cross-species infections with HEV genotypes 3 and 4 have been demonstrated experimentally. However, not all sources of human infections have been identified thus far and in many cases, the origin of HEV infection in humans remains unknown

Overexpression of Cathepsin Z Contributes to Tumor Metastasis by Inducing Epithelial-Mesenchymal Transition in Hepatocellular Carcinoma

The aim of this study was to characterize the oncogenic function and mechanism of Cathepsin Z (CTSZ) at 20q13.3, a frequently amplified region in hepatocellular carcinoma (HCC). Real-time PCR were used to compare CTSZ expression between paired HCC tumor and non-tumor specimens. CTSZ gene was stably transfected into HCC line QGY-7703 cells and its role in tumorigenicity and cell motility was characterized by soft agar, wound-healing, transwell invasion and cell adhesion assay, and tumor xenograft mouse model. Western blot analysis was used to study expression of proteins associated with epithelial-mesenchymal transition (EMT)

Genome-wide association study across European and African American ancestries identifies a SNP in DNMT3B contributing to nicotine dependence

Cigarette smoking is a leading cause of preventable mortality worldwide. Nicotine dependence, which reduces the likelihood of quitting smoking, is a heritable trait with firmly established associations with sequence variants in nicotine acetylcholine receptor genes and at other loci. To search for additional loci, we conducted a genome-wide association study (GWAS) meta-analysis of nicotine dependence, totaling 38,602 smokers (28,677 Europeans/European Americans and 9925 African Americans) across 15 studies. In this largest-ever GWAS meta-analysis for nicotine dependence and the largest-ever cross-ancestry GWAS meta-analysis for any smoking phenotype, we reconfirmed the well-known CHRNA5-CHRNA3-CHRNB4 genes and further yielded a novel association in the DNA methyltransferase gene DNMT3B. The intronic DNMT3B rs910083-C allele (frequency = 44-77%) was associated with increased risk of nicotine dependence at P = 3.7 x 10(-8) (odds ratio (OR) = 1.06 and 95% confidence interval (CI) = 1.04-1.07 for severe vs mild dependence). The association was independently confirmed in the UK Biobank (N = 48,931) using heavy vs never smoking as a proxy phenotype (P = 3.6 x 10(-4), OR = 1.05, and 95% CI = 1.02-1.08). Rs910083-C is also associated with increased risk of squamous cell lung carcinoma in the International Lung Cancer Consortium (N = 60,586, meta-analysis P = 0.0095, OR = 1.05, and 95% CI = 1.01-1.09). Moreover, rs910083-C was implicated as a cis-methylation quantitative trait locus (QTL) variant associated with higher DNMT3B methylation in fetal brain (N = 166, P = 2.3 x 10(-26)) and a cis-expression QTL variant associated with higher DNMT3B expression in adult cerebellum from the Genotype-Tissue Expression project (N = 103, P = 3.0 x 10(-6)) and the independent Brain eQTL Almanac (N = 134, P = 0.028). This novel DNMT3B cis-acting QTL variant highlights the importance of genetically influenced regulation in brain on the risks of nicotine dependence, heavy smoking and consequent lung cancer.Peer reviewe

Naturally Occurring Variants of Human Α9 Nicotinic Receptor Differentially Affect Bronchial Cell Proliferation and Transformation

Isolation of polyadenilated mRNA from human immortalized bronchial epithelial cell line BEP2D revealed the presence of multiple isoforms of RNA coded by the CHRNA9 gene for α9 nicotinic acetylcholine receptor (nAChR). BEP2D cells were homozygous for the rs10009228 polymorphism encoding for N442S amino acid substitution, and also contained mRNA coding for several truncated isoforms of α9 protein. To elucidate the biologic significance of the naturally occurring variants of α9 nAChR, we compared the biologic effects of overexpression of full-length α9 N442 and S442 proteins, and the truncated α9 variant occurring due to a loss of the exon 4 sequence that causes frame shift and early termination of the translation. These as well as control vector were overexpressed in the BEP2D cells that were used in the assays of proliferation rate, spontaneous vs. tobacco nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK)-induced cellular transformation, and tumorigenicity in cell culture and mice. Overexpression of the S442 variant significantly increased cellular proliferation, and spontaneous and NNK-induced transformation. The N442 variant significantly decreased cellular transformation, without affecting proliferation rate. Overexpression of the truncated α9 significantly decreased proliferation and suppressed cellular transformation. These results suggested that α9 nAChR plays important roles in regulation of bronchial cell growth by endogenous acetylcholine and exogenous nicotine, and susceptibility to NNK-induced carcinogenic transformation. The biologic activities of α9 nAChR may be regulated at the splicing level, and genetic polymorphisms in CHRNA9 affecting protein levels, amino acid sequence and RNA splicing may influence the risk for lung cancer

Snail1 induces epithelial-to-mesenchymal transition and tumor initiating stem cell characteristics

<p>Abstract</p> <p>Background</p> <p>Tumor initiating stem-like cells (TISCs) are a subset of neoplastic cells that possess distinct survival mechanisms and self-renewal characteristics crucial for tumor maintenance and propagation. The induction of epithelial-mesenchymal-transition (EMT) by TGFβ has been recently linked to the acquisition of TISC characteristics in breast cancer. In HCC, a TISC and EMT phenotype correlates with a worse prognosis. In this work, our aim is to elucidate the underlying mechanism by which cells acquire tumor initiating characteristics after EMT.</p> <p>Methods</p> <p>Gene and protein expression assays and Nanog-promoter luciferase reporter were utilized in epithelial and mesenchymal phenotype liver cancer cell lines. EMT was analyzed with migration/invasion assays. TISC characteristics were analyzed with tumor-sphere self-renewal and chemotherapy resistance assays. <it>In vivo </it>tumor assay was performed to investigate the role of Snail1 in tumor initiation.</p> <p>Conclusion</p> <p>TGFβ induced EMT in epithelial cells through the up-regulation of Snail1 in Smad-dependent signaling. Mesenchymal liver cancer post-EMT demonstrates TISC characteristics such as tumor-sphere formation but are not resistant to cytotoxic therapy. The inhibition of <it>Snail1 </it>in mesenchymal cells results in decreased <it>Nanog </it>promoter luciferase activity and loss of self-renewal characteristics <it>in vitro</it>. These changes confirm the direct role of Snail1 in some TISC traits. <it>In vivo</it>, the down-regulation of <it>Snail1 </it>reduced tumor growth but was not sufficient to eliminate tumor initiation. In summary, TGFβ induces EMT and TISC characteristics through Snail1 and Nanog up-regulation. In mesenchymal cells post-EMT, Snail1 directly regulates <it>Nanog </it>expression, and loss of Snail1 regulates tumor growth without affecting tumor initiation.</p

Identification of S100A8-correlated genes for prediction of disease progression in non-muscle invasive bladder cancer

<p>Abstract</p> <p>Background</p> <p><it>S100 calcium binding protein A8 </it>(<it>S100A8</it>) has been implicated as a prognostic indicator in several types of cancer. However, previous studies are limited in their ability to predict the clinical behavior of the cancer. Here, we sought to identify a molecular signature based on <it>S100A8 </it>expression and to assess its usefulness as a prognostic indicator of disease progression in non-muscle invasive bladder cancer (NMIBC).</p> <p>Methods</p> <p>We used 103 primary NMIBC specimens for microarray gene expression profiling. The median follow-up period for all patients was 57.6 months (range: 3.2 to 137.0 months). Various statistical methods, including the leave-one-out cross validation method, were applied to identify a gene expression signature able to predict the likelihood of progression. The prognostic value of the gene expression signature was validated in an independent cohort (n = 302).</p> <p>Results</p> <p>Kaplan-Meier estimates revealed significant differences in disease progression associated with the expression signature of <it>S100A8</it>-correlated genes (log-rank test, <it>P </it>< 0.001). Multivariate Cox regression analysis revealed that the expression signature of <it>S100A8</it>-correlated genes was a strong predictor of disease progression (hazard ratio = 15.225, 95% confidence interval = 1.746 to 133.52, <it>P </it>= 0.014). We validated our results in an independent cohort and confirmed that this signature produced consistent prediction patterns. Finally, gene network analyses of the signature revealed that <it>S100A8</it>, <it>IL1B</it>, and <it>S100A9 </it>could be important mediators of the progression of NMIBC.</p> <p>Conclusions</p> <p>The prognostic molecular signature defined by <it>S100A8</it>-correlated genes represents a promising diagnostic tool for the identification of NMIBC patients that have a high risk of progression to muscle invasive bladder cancer.</p