Generative Street Addresses from Satellite Imagery

We describe our automatic generative algorithm to create street addresses from satellite images by learning and labeling roads, regions, and address cells. Currently, 75% of the world’s roads lack adequate street addressing systems. Recent geocoding initiatives tend to convert pure latitude and longitude information into a memorable form for unknown areas. However, settlements are identified by streets, and such addressing schemes are not coherent with the road topology. Instead, we propose a generative address design that maps the globe in accordance with streets. Our algorithm starts with extracting roads from satellite imagery by utilizing deep learning. Then, it uniquely labels the regions, roads, and structures using some graph- and proximity-based algorithms. We also extend our addressing scheme to (i) cover inaccessible areas following similar design principles; (ii) be inclusive and flexible for changes on the ground; and (iii) lead as a pioneer for a unified street-based global geodatabase. We present our results on an example of a developed city and multiple undeveloped cities. We also compare productivity on the basis of current ad hoc and new complete addresses. We conclude by contrasting our generative addresses to current industrial and open solutions. Keywords: road extraction; remote sensing; satellite imagery; machine learning; supervised learning; generative schemes; automatic geocodin

Potential Association of DCBLD2 Polymorphisms with Fall Rates of FEV1 by Aspirin Provocation in Korean Asthmatics

Aspirin exacerbated respiratory disease (AERD) is a clinical syndrome characterized by chronic rhinosinusitis with nasal polyposis and aspirin hypersensitivity. The aspirin-induced bronchospasm is mediated by mast cell and eosinophilic inflammation. Recently, it has been reported that the expression of discoidin, CUB and LCCL domain-containing protein 2 (DCBLD2) is up-regulated in lung cancers and is regulated by transcription factor AP-2 alpha (TFAP2A), a component of activator protein-2 (AP-2) that is known to regulate IL-8 production in human lung fibroblasts and epithelial cells. To investigate the associations between AERD and DCBLD2 polymorphisms, 12 common variants were genotyped in 163 AERD subjects and 429 aspirin tolerant asthma (ATA) controls. Among these variants, seven SNPs (rs1371687, rs7615856, rs828621, rs828618, rs828616, rs1062196, and rs8833) and one haplotype (DCBLD2-ht1) show associations with susceptibility to AERD. In further analysis, this study reveals significant associations between the SNPs or haplotypes and the percentage of forced expiratory volume in one second (FEV1) decline following aspirin challenge using multiple linear regression analysis. Furthermore, a non-synonymous SNP rs16840208 (Asp723Asn) shows a strong association with FEV1 decline in AERD patients. Although further studies for the non-synonymous Asp723Asn variation are needed, our findings suggest that DCBLD2 could be related to FEV1-related phenotypes in asthmatics

The diagnostic accuracy of high b-value diffusion- and T2-weighted imaging for the detection of prostate cancer: a meta-analysis

Purpose: This study aims to investigate the role of diffusion-weighted imaging (DWI) and T2-weighted imaging (T2WI) in combination for the detection of prostate cancer, specifically assessing the role of high b-values (> 1000 s/mm2), with a systematic review and meta-analysis of the existing published data.  Methods: The electronic databases MEDLINE, EMBASE, and OpenSIGLE were searched between inception and September 1, 2017. Eligible studies were those that reported the sensitivity and specificity of DWI and T2WI for the diagnosis of prostate cancer by visual assessment using a histopathologic reference standard. The QUADAS-2 critical appraisal tool was used to assess the quality of included studies. A meta-analysis with pooling of sensitivity, specificity, likelihood, and diagnostic odds ratios was undertaken, and a summary receiver-operating characteristics (sROC) curve was constructed. Predetermined subgroup analysis was also performed.  Results: Thirty-three studies were included in the final analysis, evaluating 2949 patients. The pooled sensitivity and specificity were 0.69 (95% CI 0.68–0.69) and 0.84 (95% CI 0.83–0.85), respectively, and the sROC AUC was 0.84 (95% CI 0.81–0.87). Subgroup analysis showed significantly better sensitivity with high b-values (> 1000 s/mm2). There was high statistical heterogeneity between studies.  Conclusion: The diagnostic accuracy of combined DWI and T2WI is good with high b-values (> 1000 s/mm2) seeming to improve overall sensitivity while maintaining specificity. However, further large-scale studies specifically looking at b-value choice are required before a categorical recommendation can be made

Positive Association between Aspirin-Intolerant Asthma and Genetic Polymorphisms of FSIP1: a Case-Case Study

<p>Abstract</p> <p>Background</p> <p>Aspirin-intolerant asthma (AIA), which is caused by non-steroidal anti-inflammatory drugs (NSAIDs) such as aspirin, causes lung inflammation and reversal bronchi reduction, leading to difficulty in breathing. Aspirin is known to affect various parts inside human body, ranging from lung to spermatogenesis. <it>FSIP1</it>, also known as <it>HDS10</it>, is a recently discovered gene that encodes fibrous sheath interacting protein 1, and is regulated by amyloid beta precursor protein (APP). Recently, it has been reported that a peptide derived from APP is cleaved by α disintegrin and metalloproteinase 33 (<it>ADAM33</it>), which is an asthma susceptibility gene. It has also been known that the <it>FSIP1 </it>gene is expressed in airway epithelium.</p> <p>Objectives</p> <p>Aim of this study is to find out whether <it>FSIP1 </it>polymorphisms affect the onset of AIA in Korean population, since it is known that AIA is genetically affected by various genes.</p> <p>Methods</p> <p>We conducted association study between 66 single nucleotide polymorphisms (SNPs) of the <it>FSIP1 </it>gene and AIA in total of 592 Korean subjects including 163 AIA and 429 aspirin-tolerant asthma (ATA) patients. Associations between polymorphisms of <it>FSIP1 </it>and AIA were analyzed with sex, smoking status, atopy, and body mass index (BMI) as covariates.</p> <p>Results</p> <p>Initially, 18 SNPs and 4 haplotypes showed associations with AIA. However, after correcting the data for multiple testing, only one SNP showed an association with AIA (corrected <it>P</it>-value = 0.03, OR = 1.63, 95% CI = 1.23-2.16), showing increased susceptibility to AIA compared with that of ATA cases. Our findings suggest that <it>FSIP1 </it>gene might be a susceptibility gene for aspirin intolerance in asthmatics.</p> <p>Conclusion</p> <p>Although our findings did not suggest that SNPs of <it>FSIP1 </it>had an effect on the reversibility of lung function abnormalities in AIA patients, they did show significant evidence of association between the variants in <it>FSIP1 </it>and AIA occurrence among asthmatics in a Korean population.</p

Single nucleotide polymorphisms in bone turnover-related genes in Koreans: ethnic differences in linkage disequilibrium and haplotype

<p>Abstract</p> <p>Background</p> <p>Osteoporosis is defined as the loss of bone mineral density that leads to bone fragility with aging. Population-based case-control studies have identified polymorphisms in many candidate genes that have been associated with bone mass maintenance or osteoporotic fracture. To investigate single nucleotide polymorphisms (SNPs) that are associated with osteoporosis, we examined the genetic variation among Koreans by analyzing 81 genes according to their function in bone formation and resorption during bone remodeling.</p> <p>Methods</p> <p>We resequenced all the exons, splice junctions and promoter regions of candidate osteoporosis genes using 24 unrelated Korean individuals. Using the common SNPs from our study and the HapMap database, a statistical analysis of deviation in heterozygosity depicted.</p> <p>Results</p> <p>We identified 942 variants, including 888 SNPs, 43 insertion/deletion polymorphisms, and 11 microsatellite markers. Of the SNPs, 557 (63%) had been previously identified and 331 (37%) were newly discovered in the Korean population. When compared SNPs in the Korean population with those in HapMap database, 1% (or less) of SNPs in the Japanese and Chinese subpopulations and 20% of those in Caucasian and African subpopulations were significantly differentiated from the Hardy-Weinberg expectations. In addition, an analysis of the genetic diversity showed that there were no significant differences among Korean, Han Chinese and Japanese populations, but African and Caucasian populations were significantly differentiated in selected genes. Nevertheless, in the detailed analysis of genetic properties, the LD and Haplotype block patterns among the five sub-populations were substantially different from one another.</p> <p>Conclusion</p> <p>Through the resequencing of 81 osteoporosis candidate genes, 118 unknown SNPs with a minor allele frequency (MAF) > 0.05 were discovered in the Korean population. In addition, using the common SNPs between our study and HapMap, an analysis of genetic diversity and deviation in heterozygosity was performed and the polymorphisms of the above genes among the five populations were substantially differentiated from one another. Further studies of osteoporosis could utilize the polymorphisms identified in our data since they may have important implications for the selection of highly informative SNPs for future association studies.</p

A Holistic Framework for Addressing the World using Machine Learning

© 2018 IEEE. Millions of people are disconnected from basic services due to lack of adequate addressing. We propose an automatic generative algorithm to create street addresses from satellite imagery. Our addressing scheme is coherent with the street topology, linear and hierarchical to follow human perception, and universal to be used as a unified geocoding system. Our algorithm starts with extracting road segments using deep learning and partitions the road network into regions. Then regions, streets, and address cells are named using proximity computations. We also extend our addressing scheme to cover inaccessible areas, to be flexible for changes, and to lead as a pioneer for a unified geodatabase