[Corrigendum] Sulforaphane suppresses the viability and metastasis, and promotes the apoptosis of bladder cancer cells by inhibiting the expression of FAT­1.

Following the publication of the above paper, the authors drew the Editor's attention to the fact that their article contained two textual errors located in the same sentence: In the 'Sample collection' subsection of the Materials and methods section on p. 1086 (the first sentence), the text here should have read as follows (changes highlighted in bold): 'In the present study, 85 bladder cancer tissues and 27 adjacent normal tissues were collected from patients with BC who attended the Bao'an Central Hospital of Shenzhen and Shenzhen Hospital of Southern Medical University between 2014 and 2018 for treatment.' (i.e. the samples were not exclusively collected from the Shenzhen Hospital of Southern Medical University as stated, and the collection dates should have been written as 2014 and 2018, not as 2010 and 2014). The authors are grateful to the Editor of International Journal of Molecular Medicine for allowing them the opportunity to publish this Corrigendum, and they apologize for any inconvenience caused to the readership of the Journal. [International Journal of Molecular Medicine 46: 1085­1095, 2020; DOI: 10.3892/ijmm.2020.4665].

Artificial intelligence for hepatitis evaluation.

Recently, increasing attention has been paid to the application of artificial intelligence (AI) to the diagnosis of diverse hepatic diseases, which comprises traditional machine learning and deep learning. Recent studies have shown the possible value of AI based data mining in predicting the incidence of hepatitis, classifying the different stages of hepatitis, diagnosing or screening for hepatitis, forecasting the progression of hepatitis, and predicting response to antiviral drugs in chronic hepatitis C patients. More importantly, AI based on radiology has been proven to be useful in predicting hepatitis and liver fibrosis as well as grading hepatocellular carcinoma (HCC) and differentiating it from benign liver tumors. It can predict the risk of vascular invasion of HCC, the risk of hepatic encephalopathy secondary to hepatitis B related cirrhosis, and the risk of liver failure after hepatectomy in HCC patients. In this review, we summarize the application of AI in hepatitis, and identify the challenges and future perspectives.

Investigating the impacts of three-dimensional spatial structures on CO2 emissions at the urban scale.

In response to carbon dioxide (CO2) emissions, numerous studies have investigated the link between CO2 emissions and urban structures, and pursued low-carbon development from the standpoint of urban spatial planning. However, most of previous efforts only focused on urban structures in term of two-dimensional space, whereas the vertical influence of urban buildings (three-dimensional space) plays an important role in CO2 emissions. To address this issue, we took the cities in mainland China as study case to quantitatively explore how the three-dimensional urban structure affects CO2 emissions. First, we collected the city-level CO2 emission data from a greenhouse gas emission dataset released by the China City Greenhouse Gas Working Group. Then, a series of spatial metrics were established to quantify three-dimensional urban structures based on urban building data derived from Baidu Map. On the strength of the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, an extended approach and ridge regression analysis were finally utilized to investigate the consequences of three-dimensional urban structures on CO2 emissions at the city level. The results indicate that the total building volume is the largest driving force accelerating CO2 emissions due to the massive consumption of energies for human activities during rapid urbanization. Besides, urban buildings with taller height and large heat dissipation area also have significant positive effects on promoting CO2 emissions. Although a compact coverage of urban buildings at a two-dimensional scale contributes to the reduction of CO2 emissions, urban structure characterized by an intense and congested pattern in three-dimensional space can lead to more CO2 emissions because of the adverse impacts from surrounding environment and traffic congestion. Additionally, an irregular pattern of three-dimensional urban structure would help reduce CO2 emissions to some extent. Such study results highlight the importance of urban planning for the development of a low-carbon city, and suggest the compact patterns of three-dimensional urban structures should be controlled within a reasonable range to avoid more CO2 emissions caused by excessive centralization and aggregation.

Sulforaphane suppresses the viability and metastasis, and promotes the apoptosis of bladder cancer cells by inhibiting the expression of FAT­1.

FAT atypical cadherin 1 (FAT1) regulates complex mechanisms for the promotion of oncogenesis or the suppression of malignancies. Sulforaphane (SFN) has antioxidant and anti­tumor activities. The present study investigated the roles of SFN and FAT1 in bladder cancer (BC). The expression of FAT1 in BC cell lines and tissues was measured by western blot analysis and reverse transcription­quantitative PCR (RT­qPCR). The association between FAT1 expression and the 5­year survival rate of patients with BC was evaluated. The viability of and FAT1 expression in T24 and SW780 cells exposed to various concentrations of SFN were detected by MTT assay, and western blot analysis and RT­qPCR, respectively. Furthermore, the viability, migration, invasion and apoptosis of and FAT1 expression in BC cells subjected to FAT1 overexpression or knockdown, and with or without SFN stimulation, were examined. The results revealed that FAT1 expression in BC cells and tissues was increased, and patients with a high FAT­1 expression had a shorter 5­year survival time than those with a low FAT­1 expression. BC cell viability and FAT1 expression were suppressed by SFN in a concentration­dependent manner. The knockdown of FAT1 inhibited the viability, migration and invasion, and promoted the apoptosis of BC cells, whereas the overexpression of FAT1 produced opposite effects. In addition, cells exposed to SFN exhibited a reduced viability, migration, invasion and an increased apoptosis, effects which were promoted by FAT1 knockdown; however, the overexpression of FAT1 blocked the above­mentioned effects of SFN on the cells. On the whole, the present study demonstrates that SFN suppresses the progression of BC by inhibiting the expression of FAT­1; thus, SFN may be used as a potential drug for the treatment of BC.

The longitudinal relationship between exposure to air pollution and depression in older adults.

BACKGROUND: Air pollution, especially PM2.5 (particulate matter with a diameter of below 2.5 µm), has been recognized as a key environmental factor that affects mental health, but few studies have focused on its influence on older adults, who are a vulnerable group. OBJECTIVE: This study focused on the influence of PM2.5 on health-related behaviors, such as physical activities and social contact, to assess their role as mediators of depression among older adults in China. METHODS: We used data (N = 24 623) from the CHARLS (China Health and Retirement Longitudinal Study) of 2011-2015. CES-D 10 (Center for Epidemiology Studies of Depression scale) was used to measure depression. Using multilevel linear models, we examined the relationships between the variables, with different times nested within the same individual and individuals nested within the cities. RESULTS: Before mediators were added, depression symptoms among older adults increased with annual concentration of PM2.5 (Coeff = 0.57, SE = 0.11). However, after the mediators were added, the coefficient of the annual concentration of PM2.5 decreased (Coeff = 0.37, SE = 0.10). While both physical activities (Sobel test Z score = 2.37, P value = .02) and social contact (Z score = 7.33, P value = .00) mediated the relationship between PM2.5 and depression, the mediating effects decreased with increasing PM2.5 . CONCLUSIONS: Exposure to PM2.5 , therefore, increases depressive symptoms in older Chinese adults by decreasing their physical activities and social contact. Also, the positive effects of physical activities and social contact on depression decreased with increasing PM2.5 concentrations.

Residential greenness, air pollution and psychological well-being among urban residents in Guangzhou, China.

China's rapid urbanization has led to an increasing level of exposure to air pollution and a decreasing level of exposure to vegetation among urban populations. Both trends may pose threats to psychological well-being. Previous studies on the interrelationships among greenness, air pollution and psychological well-being rely on exposure measures from remote sensing data, which may fail to accurately capture how people perceive vegetation on the ground. To address this research gap, this study aimed to explore relationships among neighbourhood greenness, air pollution exposure and psychological well-being, using survey data on 1029 adults residing in 35 neighbourhoods in Guangzhou, China. We used the Normalized Difference Vegetation Index (NDVI) and streetscape greenery (SVG) to assess greenery exposure at the neighbourhood level, and we distinguished between trees (SVG-tree) and grasses (SVG-grass) when generating streetscape greenery exposure metrics. We used two objective (PM2.5 and NO2 concentrations) measures and one subjective (perceived air pollution) measure to quantify air pollution exposure. We quantified psychological well-being using the World Health Organization Well-Being Index (WHO-5). Results from multilevel structural equation models (SEM) showed that, for parallel mediation models, while the association between SVG-grass and psychological well-being was completely mediated by perceived air pollution and NO2, the relationship between SVG-tree and psychological well-being was completely mediated by ambient PM2.5, NO2 and perceived air pollution. None of three air pollution indicators mediated the association between psychological well-being and NDVI. For serial mediation models, measures of air pollution did not mediate the relationship between NDVI and psychological well-being. While the linkage between SVG-grass and psychological well-being scores was partially mediated by NO2-perceived air pollution, SVG-tree was partially mediated by both ambient PM2.5-perceived air pollution and NO2-perceived air pollution. Our results suggest that street trees may be more related to lower air pollution levels and better mental health than grasses are.

Using street view data and machine learning to assess how perception of neighborhood safety influences urban residents' mental health.

Previous studies have shown that perceptions of neighborhood safety are associated with various mental health outcomes. However, scant attention has been paid to the mediating pathways by which perception of neighborhood safety affects mental health. In addition, most previous studies have evaluated perception of neighborhood safety with questionnaires or field audits, both of which are labor-intensive and time-consuming. This study is the first attempt to measure perception of neighborhood safety using street view data and a machine learning approach. Four potential mediating pathways linking perception of neighborhood safety to mental health were explored for 1029 participants from 35 neighborhoods of Guangzhou, China. The results of multilevel regression models confirm that perception of neighborhood safety is positively associated with mental health. More importantly, physical activity, social cohesion, stress and life satisfaction mediate this relationship. The results of a moderation analysis suggest that the beneficial effects of physical activity and social cohesion on mental health are strengthened by a perception of neighborhood safety. Our findings suggest the need to increase residents' perception of neighborhood safety to maintain mental health in urban areas of China.

The linkage between the perception of neighbourhood and physical activity in Guangzhou, China: using street view imagery with deep learning techniques.

BACKGROUND: Neighbourhood environment characteristics have been found to be associated with residents' willingness to conduct physical activity (PA). Traditional methods to assess perceived neighbourhood environment characteristics are often subjective, costly, and time-consuming, and can be applied only on a small scale. Recent developments in deep learning algorithms and the recent availability of street view images enable researchers to assess multiple aspects of neighbourhood environment perceptions more efficiently on a large scale. This study aims to examine the relationship between each of six neighbourhood environment perceptual indicators-namely, wealthy, safe, lively, depressing, boring and beautiful-and residents' time spent on PA in Guangzhou, China. METHODS: A human-machine adversarial scoring system was developed to predict perceptions of neighbourhood environments based on Tencent Street View imagery and deep learning techniques. Image segmentation was conducted using a fully convolutional neural network (FCN-8s) and annotated ADE20k data. A human-machine adversarial scoring system was constructed based on a random forest model and image ratings by 30 volunteers. Multilevel linear regressions were used to examine the association between each of the six indicators and time spent on PA among 808 residents living in 35 neighbourhoods. RESULTS: Total PA time was positively associated with the scores for "safe" [Coef. = 1.495, SE = 0.558], "lively" [1.635, 0.789] and "beautiful" [1.009, 0.404]. It was negatively associated with the scores for "depressing" [- 1.232, 0.588] and "boring" [- 1.227, 0.603]. No significant linkage was found between total PA time and the "wealthy" score. PA was further categorised into three intensity levels. More neighbourhood perceptual indicators were associated with higher intensity PA. The scores for "safe" and "depressing" were significantly related to all three intensity levels of PA. CONCLUSIONS: People living in perceived safe, lively and beautiful neighbourhoods were more likely to engage in PA, and people living in perceived boring and depressing neighbourhoods were less likely to engage in PA. Additionally, the relationship between neighbourhood perception and PA varies across different PA intensity levels. A combination of Tencent Street View imagery and deep learning techniques provides an accurate tool to automatically assess neighbourhood environment exposure for Chinese large cities.

Urban greenery and mental wellbeing in adults: Cross-sectional mediation analyses on multiple pathways across different greenery measures.

BACKGROUND: Multiple mechanisms have been proposed to explain how greenery in the vicinity of people's homes enhances their mental health and wellbeing. Mediation studies, however, focus on a limited number of mechanisms and rely on remotely sensed greenery measures, which do not accurately capture how neighborhood greenery is perceived on the ground. OBJECTIVE: To examine: 1) how streetscape and remote sensing-based greenery affect people's mental wellbeing; 2) whether and, if so, to what extent the associations are mediated by physical activity, stress, air quality and noise, and social cohesion; and 3) whether differences in the mediation across the streetscape greenery and NDVI exposure metrics occurred. METHODS: We used a population sample of 1029 adult residents of the metropolis of Guangzhou, China, from 2016. Mental wellbeing was quantified by the World Health Organization Well-Being Index (WHO-5). Two objective greenery measures were extracted at the neighborhood level: 1) streetscape greenery from street view data via a convolutional neural network, and 2) the normalized difference vegetation index (NDVI) from Landsat 8 remote sensing images. Single and multiple mediation analyses with multilevel regressions were conducted. RESULTS: Streetscape and NDVI greenery were weakly and positively, but not significantly, correlated. Our regression results revealed that streetscape greenery and NDVI were, individually and jointly, positively associated with mental wellbeing. Significant partial mediators for the streetscape greenery were physical activity, stress, air quality and noise, and social cohesion; together, they explained 62% of the association. For NDVI, only physical activity and social cohesion were significant partial mediators, accounting for 22% of the association. CONCLUSIONS: Mental health and wellbeing and both streetscape and satellite-derived greenery seem to be both directly correlated and indirectly mediated. Our findings signify that both greenery measures capture different aspects of natural environments and may contribute to people's wellbeing by means of different mechanisms.

Cross-sectional associations between long-term exposure to particulate matter and depression in China: The mediating effects of sunlight, physical activity, and neighborly reciprocity.

BACKGROUND: Although numerous studies have speculated about the direct and indirect linkage between long-term air pollution (i.e., PM2.5) concentrations and mental health in developed countries, evidence for developing countries is limited. Our aim was to examine the mediation effects of sunlight, physical activity, and neighborly reciprocity on the association between air pollution and depression. METHODS: In a sample of 20,861 individuals in China in 2016, depression was measured using the Center for Epidemiological Studies Depression screener (CES-D) and linked to annual city-wide PM2.5 data. We used multilevel regression models to assess the associations between depressive symptoms and PM2.5 and tested the mediation of sunlight, physical activity, and neighborly reciprocity in this association. Propensity score matching was used to evaluate whether selection bias may affect the association between CES-D scores and PM2.5. RESULTS: PM2.5 concentration was positively associated with depression symptoms. All mediators were significantly and negatively associated with PM2.5. Our mediation analyses indicated that physical activity, neighborly reciprocity, and exposure to sunlight are important mechanisms through which PM2.5 affects depressive symptoms. LIMITATIONS: The limitations of the present study were the cross-sectional nature of the data and modifiable areal unit problem. CONCLUSIONS: Our findings suggest not only that PM2.5 is directly associated with depression, but also that this association seems to be partially mediated by physical activity, neighborly reciprocity, and sunlight.

Using deep learning to examine street view green and blue spaces and their associations with geriatric depression in Beijing, China.

BACKGROUND: Residential green and blue spaces may be therapeutic for the mental health. However, solid evidence on the linkage between exposure to green and blue spaces and mental health among the elderly in non-Western countries is scarce and limited to exposure metrics based on remote sensing images (i.e., land cover and vegetation indices). Such overhead-view measures may fail to capture how people perceive the environment on the site. OBJECTIVE: This study aimed to compare streetscape metrics derived from street view images with satellite-derived ones for the assessment of green and blue space; and to examine associations between exposure to green and blue spaces as well as geriatric depression in Beijing, China. METHODS: Questionnaire data on 1190 participants aged 60 or above were analyzed cross-sectionally. Depressive symptoms were assessed through the shortened Geriatric Depression Scale (GDS-15). Streetscape green and blue spaces were extracted from Tencent Street View data by a fully convolutional neural network. Indicators derived from street view images were compared with a satellite-based normalized difference vegetation index (NDVI), a normalized difference water index (NDWI), and those derived from GlobeLand30 land cover data on a neighborhood level. Multilevel regressions with neighborhood-level random effects were fitted to assess correlations between GDS-15 scores and these green and blue spaces exposure metrics. RESULTS: The average cumulative GDS-15 score was 3.4 (i.e., no depressive symptoms). Metrics of green and blue space derived from street view images were not correlated with satellite-based ones. While NDVI was highly correlated with GlobeLand30 green space, NDWI was moderately correlated with GlobeLand30 blue space. Multilevel regressions showed that both street view green and blue spaces were inversely associated with GDS-15 scores and achieved the highest model goodness-of-fit. No significant associations were found with NDVI, NDWI, and GlobeLand30 green and blue space. Our results passed robustness tests. CONCLUSION: Our findings provide support that street view green and blue spaces are protective against depression for the elderly in China, yet longitudinal confirmation to infer causality is necessary. Street view and satellite-derived green and blue space measures represent different aspects of natural environments. Both street view data and deep learning are valuable tools for automated environmental exposure assessments for health-related studies.

The Relationship between Air Pollution and Depression in China: Is Neighbourhood Social Capital Protective?

There is increasing evidence from the developed world that air pollution is significantly related to residents' depressive symptoms; however, the existence of such a relationship in developing countries such as China is still unclear. Furthermore, although neighbourhood social capital is beneficial for health, whether it is a protective factor in the relationship between health and environment pollution remains unclear. Consequently, we examined the effects of cities' PM2.5 concentrations on residents' depressive symptoms and the moderating effects of neighbourhood social capital, using data from the 2016 wave of China Labourforce Dynamics Survey and the real-time remote inquiry website of Airborne Fine Particulate Matter and Air Quality Index. Results showed that PM2.5 concentrations and neighbourhood social capital may increase and decrease respondents' depressive symptoms, respectively. Notably, neighbourhood social capital decreased the negative effect of PM2.5 concentrations on respondents' depressive symptoms. These analyses contributed to the understanding of the effect of air pollution on mental health in China and confirmed that neighbourhood social capital were protective factors in the relationship between health and environment hazards.

[Efficacy observation on acupoint catgut embedding therapy combined medication for treatment of chronic urticaria induced by Helicobacter pylori infection].

OBJECTIVE: To observe the efficacy of acupoint catgut embedding therapy combined medication on chronic urticaria induced by Helicobacter pylori (HP) infection. METHODS: Ninety-two cases were randomly divided into 3 groups, named a medication group (group A, 31 cases), an acupoint catgut embedding group (group B, 30 cases) and a medication combined acupoint catgut embedding group (group C, 31 cases). In group A, the medication was administered orally for antihistamine and anti-HP infection. In group B, catgut embedding was applied on Quchi (LI 11), Xuehai (SP 10), Zusanli (ST 36), etc. In group C, acupoint catgut embedding therapy was applied in combination with medication (medication as group A, acupoint catgut embedding as group B). After 3-month treatment, the efficacy, recurrence rate and HP negative rate were compared among 3 groups. RESULTS: Separately, the effective rates of group A, B, C were 61.3% (19/31), 53.3% (16/30) and 90.3% (28/31); the recurrence rates were 27.3% (3/11), 33.3% (3/9) and 5.9% (1/17); and HP negative rates were 31.3% (10/31), 26.7% (9/30) and 77.4% (24/31). The clinical efficacy and HP negative rate in group C were superior to those in group A and B (P < 0.01, P < 0.05). CONCLUSION: Acupoint catgut embedding therapy combined medication is significant in efficacy and low in recurrence rate in treatment of chronic urticaria caused by HP infection.