Geosimulation model using geographic automata for simulating land-use patterns in urban partitions

金沢大学理工研究域環境デザイン学系Cellular automata (CA) are an effective means of urban-growth simulation. Moreover, the development of a planning support system associated with the theory of artificial intelligence has recently become a new global challenge. In this paper we investigate a geosimulation model using CA based on the geographic information system (GIS) for visualising land-use patterns in urban partitions. Most recent simulation models using CA have been developed in regular grid nets or networks, where adjacent grids or networks in urban space are easily addressed. Our project explores how to utilise an irregular polygon dataset in a GIS database in order to deal with spatial microsimulation. A new concept used in this project takes into account the effects of urban planning, such as land-use zoning and street networks, at the level of parcels and blocks in urban space. Adjacent irregular parcels on both sides of a street are intended targets in the simulation. In this paper, a method of simulating land-use patterns in urban space after the implementation of land-readjustment projects is discussed

Genome-wide association study revealed novel loci which aggravate asymptomatic hyperuricaemia into gout

Objective The first ever genome-wide association study (GWAS) of clinically defined gout cases and asymptomatic hyperuricaemia (AHUA) controls was performed to identify novel gout loci that aggravate AHUA into gout. Methods We carried out a GWAS of 945 clinically defined gout cases and 1003 AHUA controls followed by 2 replication studies. In total, 2860 gout cases and 3149 AHUA controls (all Japanese men) were analysed. We also compared the ORs for each locus in the present GWAS (gout vs AHUA) with those in the previous GWAS (gout vs normouricaemia). Results This new approach enabled us to identify two novel gout loci (rs7927466 of CNTN5 and rs9952962 of MIR302F) and one suggestive locus (rs12980365 of ZNF724) at the genome-wide significance level (p<5.0×10– 8). The present study also identified the loci of ABCG2, ALDH2 and SLC2A9. One of them, rs671 of ALDH2, was identified as a gout locus by GWAS for the first time. Comparing ORs for each locus in the present versus the previous GWAS revealed three ‘gout vs AHUA GWAS’-specific loci (CNTN5, MIR302F and ZNF724) to be clearly associated with mechanisms of gout development which distinctly differ from the known gout risk loci that basically elevate serum uric acid level. Conclusions This meta-analysis is the first to reveal the loci associated with crystal-induced inflammation, the last step in gout development that aggravates AHUA into gout. Our findings should help to elucidate the molecular mechanisms of gout development and assist the prevention of gout attacks in high-risk AHUA individuals