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Land use mix (LUM) is a key part of urban form, but the definitions and measures of LUM are debated. This study aims to reveal the spatial characteristics of LUM patterns by using a sample of 216 streets in Shanghai, a megacity of China. Firstly, a systematic quantitative framework for sustainable LUM is proposed. Then, an LUM degree index (LMDI) that integrates diversity, proximity and compatibility is developed to address the possible bias of a single dimension. Results suggest that areas with high diversity are not necessarily mixed, due to inaccessibility or negative externalities of land uses. Subsequently, spatial characteristics of LUM patterns that combine LMDI with dominant mix‐typologies are analyzed. Results show that residential & service‐dominated streets tend to exhibit higher mix, and are mainly distributed in the city center or the administrative core area. However, 44.4% of the streets with residential & industrial‐dominated or equally distributed mix have lower mix degree and are generally located in the outskirts. More optimized policies for urban periphery areas should be considered. LUM patterns present a detailed perspective to measure and depict the spatial features of LUM, and have the potential to assist urban planners in making decisions. [ABSTRACT FROM AUTHOR]

The identification and utilization of broad-spectrum resistance genes is the most effective and economical strategy of controlling rice blast disease. Kangfeng B (KFB), an elite Chinese rice cultivar, has been shown to exhibit broad-spectrum resistance to 53 isolates of Magnaporthe oryzae, the rice blast causative agent, from different regions of China. In this study, we identified a dominant blast-resistance gene at the Pi2/Pi9 locus from cultivar KFB, through genetic analysis and physical mapping. Allele-specific marker-based assessment revealed that Pi2, Pi9, and Piz-t are not the blast-resistance genes in KFB. By combining bulked segregation analysis (BSA) and recessive class analysis (RCA), the blast-resistance gene was fine-mapped to an approximately 249-kb interval between markers InDel-22 and Rm7213 on chromosome 6. Three bacterial artificial chromosome (BAC) clones spanning the region were identified. This region contains 19 predicted genes, including 7 nucleotide binding site–leucine-rich repeat (NBS-LRR) genes at the Pi2/Pi9 locus in japonica cv. Nipponbare genome. Further sequence comparison of the four functional NBS-LRR genes revealed that NBS-LRR2 and NBS-LRR4, as evidenced by their allelic/orthologous to Pi9 or Pi2, had significant differences of 9 to 43 and 14 to 48 amino acids in KFB, respectively, unlike the other known Pi2/Pi9 alleles, suggesting that KFB carries a hitherto undocumented member of the Pi2/Pi9 multigene family. It was tentatively designated as Pi-kf2(t). Our results provide essential information for the isolation of the Pi-kf2(t) gene and will facilitate both map-based cloning and marker-assisted selection of this gene for rice blast-resistance breeding. [ABSTRACT FROM AUTHOR]

Cancer, as well as the phenomena of cancer villagers, has attracted great concern from national and internal publics because of the high morality for population. Reference to long latency periods and multiple causalities for several cancers, cancer villages have usually used as circumstantial evidence for an association with cancers and environmental determinants relevant to economic-agricultural and demographic development even though there was no official definition and unified discrimination rule. On the assumption that all reported cancer villages are real and credible, this study primarily aimed to test the hypothesis that the water quality has caused concentration of cancer villages. The temporal and spatial pattern of Chinese cancer villages reported by media and literatures were firstly explored by means of spatial mapping and regression analysis. Considering the insignificant Moran'I coefficient, stepwise regression model combined with principal component regression model were performed to identify the association between cumulative number of cancer villages and water quality and other social-economic-environmental factors. The findings showed that there are at least 462 cancer villages across 226 counties in 29 out of 31 provincial administrative units were reported in China by the end of 2017, with an average of 7 new cancer villages per year, since the initial cancer village appeared in 1954. The number of cancer villages increased slowly before 2000 and dramatically accelerated during 10th and 11th Five-Year Plan period. The cumulative number of cancer villages increased gradient from West to East with regionally clustered and uneven spatial distribution. Cancer villages tend to cluster along the middle and lower reaches of major rivers and their branches, especially in Yangtze River Delta, the Bohai economic rim, the borders of Hunan, Hubei and Jiangxi provinces, as well as the borders of Yunnan and Guizhou province. Cumulative occurrence of cancer villages might be affected by domestic economic development, urbanization, as well as discharge of heavy metals in waste industrial water. • Since 1954, more than 462 cancer villages (CVs) across 226 counties in China; • CVs especially occurred during 2000–2010; • CVs mainly located in lower river reaches in central and eastern China; • CVs were comprehensive result of economic growth and urbanization. [ABSTRACT FROM AUTHOR]

Aim: Evidence on the association between natural-built environments and depression is largely derived from the general population and prone to residential self-selection bias because of the nature of cross-sectional research design. Despite emerging adulthood, which includes the university years, is a critical stage for forming life-long health habits, studies on this topic focusing on undergraduate students are limited. The current study aims to illustrate the underlying mechanisms for how the campus-based environments affect depression in undergraduate students., Methods: Based on a nationwide representative analytical sample of 22,009 Chinese undergraduates in 2018, we examined participants' reports of depression and campus-centered natural/built environments within multiple buffer sizes including 0.5, 1.0, and 2.5 km. After disentangling residential self-selection, we explored the moderating role of the socioeconomic attributes of undergraduates. The depression outcome was measured by the nine-item Patient Health Questionnaire (PHQ9). Indicators of exposure to green and blue space, transportation infrastructure, and food environments were objectively assessed using different circular buffers around each campus address., Results: Modeling results indicated that campus neighborhoods with more scattered trees (0.5 km), water (0.5, 1.0, and 2.5 km), and street intersections (1.0 and 2.5 km) were protective against depression. In contrast, those living near denser distributions of outlets serving take-away sweets and fast food (0.5, 1.0, and 2.5 km) were susceptible to depression. These associations were modified by undergraduates' socioeconomic attributes (e.g., grade, Hukou status, and ethnicity) and varied according to geographical scales and exposure metrics., Conclusion: To deliver effective environmental interventions to curb the prevalence of depression among undergraduate students, further planning policies should focus on the careful conception of the campus-based environment, especially regarding different spatial scales., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Yang, Cui, Dijst, Tian, Chen and Huang.)