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Public health is an essential urban issue attracting the increasing attention of scholars and decision-makers while urban planning is an important mechanism to promote health since mounting evidence has shown the planning elements, such as urban green spaces (UGS), could have a positive influence. In previous literature, the studies concerning the impacts of UGSs can be divided into two aspects: the first is to reveal the relationships between UGSs and health using statistical models based on self-reported data, while the second is to take their relationships as presumption and visualize the spatial distributions of UGSs in a geographical information system (GIS) to indicate the existence of health inequalities. I attempt to combine the two pathways, using GIS-based analyses to quantify and visualize UGSs, and subsequently employing the quantified indicators of UGSs to calculate their associations with public health by multiple linear regression (MLR) analysis in SPSS. The study describes a detailed methodology that could be taken as a generic approach to analyze other urban elements and services. A case study is conducted in Linköping central urban area with base areas selected as the spatial unit of analysis. As a consequence, although the elaborate relationships between different indicators of UGSs and public health are not directly provided by the regression models, the correlations between them are indicated to be weak and subtle and require larger samples to reveal. Potential improvements, including the application of panel data and other kinds of regression models, are also summarized for further research.

Xiaoyan Sun, Lingzi Liu, Hui Zou, Caixia Yao, Zhengyu Yan, Baofen Ye Key Laboratory of Biomedical Functional Materials, School of Science, China Pharmaceutical University, Nanjing, Jiangsu 210009, People’s Republic of ChinaCorrespondence: Baofen YeKey Laboratory of Biomedical Functional Materials, School of Science, China Pharmaceutical University, Nanjing, Jiangsu 210009, People’s Republic of ChinaTel +86 13951725591Email baofen_ye@163.comBackground: Particle-based drug delivery systems (DDSs) have a demonstrated value for drug discovery and development. However, some problems remain to be solved, such as limited stimuli, visual-monitoring.Aim: To develop an intelligent multicolor DDSs with both near-infrared (NIR) controlled release and macroscopic color changes.Materials and Methods: Microparticles comprising GO/pNIPAM/PEGDA composite hydrogel inverse opal scaffolds, with dextran and calcium alginate hydrogel were synthesized using SCCBs as the template. The morphology of microparticle was observed under scanning electron microscopy, and FITC-dextran-derived green fluorescence images were determined using a confocal laser scanning microscope. During the drug release, FITC-dextran-derived green fluorescence images were captured using fluorescent inverted microscope. The relationship between the power of NIR and the drug release rate was obtained using the change in optical density (OD) values. Finally, the amount of drug released could be estimated quantitatively used the structural color or the reflection peak position.Results: A fixed concentration 8% (v/v) of PEGDA and 4mg/mL of GO was chosen as the optimal concentration based on the balance between appropriate volume shrinkage and structure color. The FITC-dextran was uniformly encapsulated in the particles by using 0.2 wt% sodium alginate. The microcarriers shrank because of the photothermal response and the intrinsic fluorescence intensity of FITC-dextran in the microparticles gradually decreased at the same time, indicating drug release. With an increasing duration of NIR irradiation, the microparticles gradually shrank, the reflection peak shifted toward blue and the structural color changed from red to orange, yellow, green, cyan, and blue successively. The drug release quantity can be predicted by the structural color of microparticles.Conclusion: The multicolor microparticles have great potential in drug delivery systems because of its vivid reporting color, excellent photothermal effect, and the good stimuli responsivity.Keywords: drug delivery, microparticles, color change, graphene oxide, photothermal effect