A prognostic nomogram to predict the cancer-specific survival of patients with initially diagnosed metastatic gastric cancer: a validation study in a Chinese cohort.

BACKGROUND: Few studies have been designed to predict the survival of Chinese patients initially diagnosed with metastatic gastric cancer (mGC). Therefore, the objective of this study was to construct and validate a new nomogram model to predict cancer-specific survival (CSS) in Chinese patients. METHODS: We collected 328 patients with mGC from Northern Jiangsu People's Hospital as the training cohort and 60 patients from Xinyuan County People's Hospital as the external validation cohort. Multivariate Cox regression was used to identify risk factors, and a nomogram was created to predict CSS. The predictive performance of the nomogram was evaluated using the consistency index (C-index), the calibration curve, and the decision curve analysis (DCA) in the training cohort and the validation cohort. RESULTS: Multivariate Cox regression identified differentiation grade (P < 0.001), T-stage (P < 0.05), N-stage (P < 0.001), surgery (P < 0.05), and chemotherapy (P < 0.001) as independent predictors of CSS. Nomogram of chemotherapy regimens and cycles was also designed by us for the prediction of mGC. Thus, these factors are integrated into the nomogram model: the C-index value was 0.72 (95% CI 0.70-0.85) for the nomogram model and 0.82 (95% CI 0.79-0.89) and 0.73 (95% CI 0.70-0.86) for the internal and external validation cohorts, respectively. Calibration curves and DCA also demonstrated adequate fit and ideal net benefit in prediction and clinical applications. CONCLUSIONS: We established a practical nomogram to predict CSS in Chinese patients initially diagnosed with mGC. Nomograms can be used to individualize survival predictions and guide clinicians in making therapeutic decisions.

Green-gray imbalance: Rapid urbanization reduces the probability of green space exposure in early 21st century China.

Green space exposure provides greater beneficial effects on residents compared to unnatural spaces, commonly referred to as "gray spaces". However, during rapid urbanization, gray spaces expand more quickly than green spaces, often encroaching upon and overtaking these natural environments. This unchecked growth leads to detrimental impacts on the human habitat and overall environmental quality. Consequently, it is essential to meticulously assess the spatial and temporal patterns of residents' exposure levels, as well as to thoroughly investigate the underlying driving mechanisms behind these changes. This study used population-weighted exposure level measurements to assess gray and green space exposure in Chinese cities in the early 21st Century (2000-2019). Additionally, the Gray-Green space Exposure Ratio (GER) was calculated, and the spatiotemporal driving mechanism of GER by each factor was analyzed by geostatistical modeling. The results show that gray space exposure is generally increasing in China, especially in eastern parts of China. The probability of exposure to gray spaces exceeds that of green spaces in some high urbanization rate cities. This trend will continue, albeit at a slower rate. Urban sprawl, built-up area density, and increased electricity consumption were the main drivers of rising GER, whereas greenspace integrity contributed to lower GER; the driving mechanisms for GER changes were spatiotemporal heterogeneous. This study provides a reliable reference for restoring the green space exposure to promote the living environment constructing and residents' access to nature.

Climatic and Economic Background Determine the Disparities in Urbanites' Expressed Happiness during the Summer Heat.

Climate-change-induced extreme weather events increase heat-related mortality and health risks for urbanites, which may also affect urbanites' expressed happiness (EH) and well-being. However, the links among EH, climate, and socioeconomic factors remain unclear. Here we collected ∼6 million geotagged tweets from 44 Chinese prefecture-level cities based on Sina Weibo and performed a quadratic regression model to explore the relationships between summer heat and EH. A three-stage analysis was developed to examine spatiotemporal heterogeneity and identify factors contributing to disparities in urbanites' EH. Results show that all cities exhibited a similar hump-shaped relationship, with an overall optimal temperature (OT) of 22.8 °C. The estimated OT varied geographically, with 25.3, 23.8, and 20.0 °C from north to south. Moreover, a 1 standard deviation increase in heatwave intensity was associated with a 0.813 (95% CI: 0.177, 1.449) standard deviation decrease in EH. Notably, within the geographic scope of this study, it was observed that urbanites in northern China and economically underdeveloped cities faced significantly lower heat risks during the summer heat. This research provides insight for future studies and practical applications concerning extreme weather events, urbanites' mental health, and sustainable urban development goal.

Natural-anthropogenic environment interactively causes the surface urban heat island intensity variations in global climate zones.

The inconstant climate change and rapid urbanization substantially disturb the global thermal balance and induce severe urban heat island (UHI) effect, adversely impacting human development and health. Existing literature has revealed the UHI characteristics and driving factors at an urban scale, but interactions between the main factors of a global grid scale assessment on the context of climate zones remain unclear. Therefore, based on the multidimensional climatic and socio-economic statistical datasets, the multi-time scale of surface urban heat island intensity (SUHI) characteristics was investigated in this study to analyze how natural-anthropogenic drivers affect the variance of SUHI and vary in their importance for the changes of other interaction factors. The results show that the mean value of SUHI in summer is higher than in winter, and in daytime is higher than in nighttime on a seasonal and daily scale. SUHIs in different global climate zones have significant differences. When analyzing drivers' contributions and interactions with LightGBM model and SHAP algorithm, we know that monthly precipitation (PREC), the estimated population (POP) and surface pressure (PRES) are the three major drivers of daytime SUHI. The nighttime SUHI is mainly PREC, POP and anthropogenic heat emission (AHE), the influence rules of the natural driversare mostly opposite to that of daytime. This study highlights the fundamental role of background climate for designing strategies. Irrigation or artificial rainfall will be effective to mitigate SUHI in low rainfall areas, while it is more effective to reduce AHE in high rainfall areas. In where greening can be difficult in the most developed cities, reducing AHE, increasing per capita GDP and controlling the population scale may also contribute to alleviating the SUHI. This study provides ideas for developing responsive urban heat island mitigation policies in a more realistic setting.

A synthetic water-heat-vegetation biodiversity nexus approach to assess coastal vulnerability in eastern China.

Climate change pressure and biodiversity degradation in coastal regions have caused an increase in urban vulnerability. Current coastal vulnerability studies fail to consider the interactions among the perturbations. Increases in such interactions contribute to the indeterminate changes in the ecosystem productivity and impact on human well-being. Therefore, by integrating water, heat, and vegetation biodiversity (WHB) indicators using catastrophe theory in the study, the interaction among subsystems was explored to expound on the multi-effect of the urban. The results showed that (1) the overall vulnerability of China's coastal cities has increased, and high-value areas were mainly distributed in the three southern provinces; (2) the spatial-temporal pattern of vulnerability was highly heterogeneous. As low-low clusters, Shanghai and its surrounding cities exhibited spatial aggregation characteristics; (3) social, physical and financial capitals were the first three main adaptive capacity factors. The distance-based linear model (DistLM) evidenced that per capita GDP, and road density explained about 30 % and 10 % of the difference in vulnerability variation. The proposed framework could help decision-makers detect how vulnerable coastal areas exposed to WHB impacts are, with crucial implications for future sustainable management.

The influence of local background climate on the dominant factors and threshold-size of the cooling effect of urban parks.

Urban parks can mitigate the urban heat island (UHI) by creating microclimates that lower in temperature than their surroundings, which are known as park cooling effect (PCE). The local background climate has a significant impact on the PCE, however the dominant factors and threshold value of efficiency (TVoE) of the PCE under different local background climates are still uncertain. Here, we selected 207 urban parks in 27 cities in East China with four different local background climates, warm temperate sub-humid monsoon (WTC), northern subtropical sub-humid monsoon (NSC), northern subtropical humid monsoon (NHC), and middle subtropical humid monsoon climate (MSC), for comparative studies. The relative contributions of multi-influencing factors to the PCE and TVoE of urban parks were quantified through a multivariate stepwise regression model and curve fitting. The results show that: (1) PCE increases from WTC, NSC, NHC to MSC, and urban parks at low latitudes have a greater cooling effect in general than those at high latitudes; (2) the area of the park is the dominant factor of PCE under four different local background climates (the explanation rate exceeds 50%) and water bodies within urban parks play a more significant role in the cooling effect in high latitudes, dry areas; (3) the TVoE of park on WTC, NSC, NHC, and MSC are 0.81, 0.71, 0.70, and 0.66 ha, respectively, revealing that the background climate significantly affects the TVoE. These findings are essential to decision-makers and can provide actionable knowledge for climate adaptation planning on a regional (climate) scale.

Trends of the contributions of biophysical (climate) and socioeconomic elements to regional heat islands.

The development of urban accumulations in recent decades has led to the transformation of urban heat islands (UHI) into regional heat islands (RHI). The contributions of the biophysical, climate, and socioeconomic factors to RHI in urban agglomeration remain poorly understood. Here Yangtze River Delta urban agglomeration (YRDUA) in eastern China has been selected as a case area to explore the influences trends, of the influencing factors to RHI by using MODIS data from 2003 to 2017. Results showed that, in summer, the area fraction of daytime RHI in YRDUA has increased from 21.74 to 31.03% in 2003 and 2017, respectively. As compared to 2003, the annual nighttime RHI area in 2017 has increased from 7510 to 20,097 km2. The dominant factors of surface RHI intensity (SRHII) showed seasonal variation. Enhanced vegetation index (EVI) (interpretation of 33.27%) was the dominant factor of daytime SRHII in spring. The most important factor was normalized difference build-up density (NDBI) (37.28% and 26.83%, respectively) in summer and autumn. In winter, precipitation (26.16%) was the most influential. At night, Modified Normalized Difference Water Index (MNDWI) had a dominant effect on SRHII in spring (54.12%), autumn (52.62%), and winter (24.19%). The dominant factor of nighttime SRHII in summer was EVI (42%). Moreover, water bodies harm RHI during the day while having a positive effect at night. These findings can provide a theoretical basis for regional environment improvement and regional sustainable development.

Spatiotemporal patterns and characteristics of remotely sensed region heat islands during the rapid urbanization (1995-2015) of Southern China.

Urban agglomeration has become the most salient feature of global urbanization in recent decades, while spatiotemporal patterns and evolution remain poorly understood in urban agglomerations, which limit the decision-makers to make more informed decisions to improve the regional environment. Here we selected one of the most rapidly urbanized regions in the world - Pearl River Delta Metropolitan Region (PRDR), located in southern China, as the case. Landsat images spanning from 1995 to 2015 were used to retrieve land surface temperature (LST). Four types of regional heat island (RHI) degree were defined for further analysis. Then multi-scale spatiotemporal patterns and characteristics of RHI were identified with the help of cloud-based computing, spatial and landscape analysis. We found that (1) traditional urban heat island (UHI) appears as an RHI on an urban agglomeration scale. In PRDR, we found RHI expended with increasing connectivity, especially in the estuary areas where isolated UHI gradually merged during the rapid urbanization. (2) The contribution of main cities in PRDR to RHI and the evolutionary trends and pattern, which is changed from a west-east to a southwest-northeast gradient, have been revealed. (3) Considering the scale effect and different RHI categories, we revealed that during the urbanization, the aggregation of the RHI is significant on a larger-scale, and the area of 4 °C ≤ Relative LST ≤ 8 °C is the stable and high-risk area, which provide scientific bases for the governance of the thermal environment on the regional scale. (4) The study also indicates the cooling effect of forests and water is better than that of grassland, while the cooling effect of grassland is uncertain. The methods and results of this study not only have implications on environmental planning and management in the PRDR but also provide useful insights into the thermal environment research and practice in other urban agglomerations.

Strong contributions of local background climate to the cooling effect of urban green vegetation.

Utilization of urban green vegetation (UGV) has been recognized as a promising option to mitigate urban heat island (UHI) effect. While we still lack understanding of the contributions of local background climate to the cooling effect of UGV. Here we proposed and employed a cooling effect framework and selected eight typical cities located in Temperate Monsoon Climate (TMC) and Mediterranean Climate (MC) demonstrate that local climate condition largely affects the cooling effect of UGV. Specifically, we found increasing (artificial) rainfall and irrigation contribute to improving the cooling intensity of grassland in both climates, particularly in the hot-dry environment. The cities with high relative humidity would restrict the cooling effect of UGV. Increasing wind speed would significantly enhance the tree-covered while weakening the grass-covered UGVs' cooling effect in MC cities. We also identified that, in order to achieve the most effective cooling with the smallest sized tree-covered UGV, the area of trees in both climate zones' cities should generally be planned around 0.5 ha. The method and results enhance understanding of the cooling effect of UGVs on larger (climate) scales and provide important insights for UGV planning and management.

[Virtual screening and antibacterial activity of lead compounds targeting to penicillin-binding protein 3 (PBP3) of Pseudomonas aeruginosa].

OBJECTIVE: This study was carried out to obtain lead compounds targeting penicillin-binding protein 3 (PBP3) of Pseudomonas aeruginosa by virtual screening. METHODS: UCSF dock 6.5 was used for the virtual screening from a database containing 1.04 million small molecules. Hit compounds with simple structures were synthesized and then evaluated for their antibacterial activities. RESULTS: Grid score was used for the first round of screening, and 60000 small molecules whose scores lower than -30 kcal/mol were screened out from the database. These molecules were subjected to the second round of screening using amber score. Approximately 200 hit compounds with scores lower than -20 kcal/mol were analyzed and 4 of them were selected as lead compounds and then synthesized. The minimal inhibition concentrations (MICs) of the lead compounds were between 175-275 µg/mL, which were lower than that of Sulfadiazine (500 µg/mL) significantly. Meanwhile, these compounds were effective for both Gram-negative and Gram-positive bacteria. CONCLUSION: The lead compounds had potential to become new antibacterial agents for conquering the drug resistance of P. aeruginosa.

Characterizing Urban Household Waste Generation and Metabolism Considering Community Stratification in a Rapid Urbanizing Area of China.

The relationship between social stratification and municipal solid waste generation remains uncertain under current rapid urbanization. Based on a multi-object spatial sampling technique, we selected 191 households in a rapidly urbanizing area of Xiamen, China. The selected communities were classified into three types: work-unit, transitional, and commercial communities in the context of housing policy reform in China. Field survey data were used to characterize household waste generation patterns considering community stratification. Our results revealed a disparity in waste generation profiles among different households. The three community types differed with respect to family income, living area, religious affiliation, and homeowner occupation. Income, family structure, and lifestyle caused significant differences in waste generation among work-unit, transitional, and commercial communities, respectively. Urban waste generation patterns are expected to evolve due to accelerating urbanization and associated community transition. A multi-scale integrated analysis of societal and ecosystem metabolism approach was applied to waste metabolism linking it to particular socioeconomic conditions that influence material flows and their evolution. Waste metabolism, both pace and density, was highest for family structure driven patterns, followed by lifestyle and income driven. The results will guide community-specific management policies in rapidly urbanizing areas.

[Impacts of urban cooling effect based on landscape scale: a review].

The urban cooling island (UCI) effect is put forward in comparison with the urban heat island effect, and emphasizes on landscape planning for optimization of function and way of urban thermal environment. In this paper, we summarized current research of the UCI effects of waters, green space, and urban park from the perspective of patch area, landscape index, threshold value, landscape pattern and correlation analyses. Great controversy was found on which of the two factors patch area and shape index has a more significant impact, the quantification of UCI threshold is particularly lacking, and attention was paid too much on the UCI effect of landscape composition but little on that of landscape configuration. More attention should be paid on shape, width and location for water landscape, and on the type of green space, green area, configuration and management for green space landscape. The altitude of urban park and human activities could also influence UCI effect. In the future, the threshold determination should dominate the research of UCI effect, the reasons of controversy should be further explored, the study of time sequence should be strengthened, the UCI effects from landscape pattern and landscape configuration should be identified, and more attention should be paid to spatial scale and resolution for the precision and accuracy of the UCI results. Also, synthesizing the multidisciplinary research should be taken into consideration.