The Ventilation Efficiency of Urban Built Intensity and Ventilation Path Identification: A Case Study of Wuhan

Urban ventilation is being hampered by rough surfaces in dense urban areas, and the microclimate and air quality of the urban built environment are not ideal. Identifying urban ventilation paths is helpful to save energy, reduce emissions, and improve the urban ecological environment. Wuhan is the capital city of Hubei, and it has a high urban built intensity and hot summers. Taking Wuhan city, with a size of 35 km ×50 km, as an example, the built environment was divided into grids of 100 m × 100 m and included the building density, floor area ratio, and average building height. The ventilation mechanism of the urban built intensity index has previously been explained. The decrease in building density is not the sole factor causing an increase in wind speed; the enclosure and width of the ventilation path and the height of the front building are also influential. Twelve urban built units were selected for CFD numerical simulation. The ventilation efficiency of each grid was evaluated by calculating the wind speed ratio, maximum wind speed, average wind speed, and area ratio of strong wind. The relationship between the urban built intensity index and ventilation efficiency index was established using the factor analysis method and the Pearson correlation coefficient; building density and average building height are the most critical indexes of ventilation potential. In addition, the layout of the building also has an important impact on ventilation. A suitable built environment is that in which the building density is less than 30%, the average building height is greater than 15 m, and the floor area ratio is greater than 1.5. The urban built intensity map was weighted to identify urban ventilation paths. The paper provides a quantitative reference for scientific planning and design of the urban spatial form to improve ventilation.

[Study of abnormal lipid metabolism analysis and significance of fatty acid binding protein expression in patients with hepatocellular carcinoma]

Objective: Hepatocellular carcinoma (HCC) is the fourth most dominant cancer in the world and the second leading cause of cancer-related deaths in the China. With the increase in the incidence of metabolic syndrome (MS) in the population, the correlation between MS and HCC has gradually been recognized. MS manifests as non-alcoholic fatty liver disease (shortly known as NAFLD) in the liver. A large number of research results has shown that the development of fatty liver is closely related to the occurrence of HCC, in which lipid metabolism plays a key regulatory role, and lipid metabolism is regulated by fatty acid binding protein (FABP). This study signifies the lipid metabolism analysis and the key FABP expression conditions in HCC. Methods: Data of patients who were first diagnosed with primary HCC between January 2016 to July 2019 were collected, and were divided into two groups according to the etiology, namely the viral and non-viral hepatitis-related HCC group. The relationship between MS-related factors and HCC was analyzed by t-test and chi square test. The expressions of FABP1, FABP4 and FABP5 were detected in cancer and adjacent tissues by immunohistochemistry, and the expressions of FABP1, FABP4 and FABP5 in HCC with fatty liver were detected by immunofluorescence. Finally, the expressional characteristics of the above-mentioned FABPs in HCC patients were analyzed with different clinicopathological features. Results: There were statistically significant differences in the rate of abnormal lipid metabolism and the number of abnormalities in MS-related factors between the viral and non-viral hepatitis-related HCC group. FABP1, FABP4, and FABP5 expression in HCC tissues were lower than the corresponding adjacent tumor tissues. Compared with simple HCC, FABP1, FABP4, FABP5 expression were increased in HCC tissues with steatosis, and the expression of FABP was closely related to the clinical characteristics of patients. Conclusion: Abnormal lipid metabolism is closely related to non-viral hepatitis-related HCC. The expression of lipid metabolism regulatory proteins FABP1, FABP4, and FABP5 are down-regulated in HCC tissues, but up-regulated in HCC with fatty liver, suggesting that the relationship between MS, especially dyslipidemia, and HCC should be paid attention to in clinical practice for early intervention. FABP1, FABP4, FABP5 may regulate HCC occurrence and development.

P–165 Using Artificial Intelligence to Classify Embryo Shape: An International Perspective

Study question

Is a pre-trained machine learning algorithm able to accurately detect cellular arrangement in 4-cell embryos from a different continent?

Summary answer

Artificial Intelligence (AI) analysis of 4-cell embryo classification is transferable across clinics globally with 79% accuracy.

What is known already

Previous studies observing four-cell human embryo configurations have demonstrated that non-tetrahedral embryos (embryos in which cells make contact with fewer than 3 other cells) are associated with compromised blastulation and implantation potential. Previous research by this study group has indicated the efficacy of AI models in classification of tetrahedral and non-tetrahedral embryos with 87% accuracy, with a database comprising 2 clinics both from the same country (Brazil). This study aims to evaluate the transferability and robustness of this model on blind test data from a different country (France).

Study design, size, duration

The study was a retrospective cohort analysis in which 909 4-cell embryo images (“tetrahedral”, n = 749; “non-tetrahedral”, n = 160) were collected from 3 clinics (2 Brazilian, 1 French). All embryos were captured at the central focal plane using Embryoscope™ time-lapse incubators. The training data consisted solely of embryo images captured in Brazil (586 tetrahedral; 87 non-tetrahedral) and the test data consisted exclusively of embryo images captured in France (163 tetrahedral; 72 non-tetrahedral).

Participants/materials, setting, methods

The embryo images were labelled as either “tetrahedral” or “non-tetrahedral” at their respective clinics. Annotations were then validated by three operators. A ResNet–50 neural network model pretrained on ImageNet was fine-tuned on the training dataset to predict the correct annotation for each image. We used the cross entropy loss function and the RMSprop optimiser (lr = 1e–5). Simple data augmentations (flips and rotations) were used during the training process to help counteract class imbalances.

Main results and the role of chance

Our model was capable of classifying embryos in the blind French test set with 79% accuracy when trained with the Brazilian data. The model had sensitivity of 91% and 51% for tetrahedral and non-tetrahedral embryos respectively; precision was 81% and 73%; F1 score was 86% and 60%; and AUC was 0.61 and 0.64. This represents a 10% decrease in accuracy compared to when the model both trained and tested on different data from the same clinics.

Limitations, reasons for caution

Although strict inclusion and exclusion criteria were used, inter-operator variability may affect the pre-processing stage of the algorithm. Moreover, as only one focal plane was used, ambiguous cases were interpoloated and further annotated. Analysing embryos at multiple focal planes may prove crucial in improving the accuracy of the model.

Wider implications of the findings: Though the use of machine learning models in the analysis of embryo imagery has grown in recent years, there has been concern over their robustness and transferability. While previous results have demonstrated the utility of locally-trained models, our results highlight the potential for models to be implemented across different clinics.

Trial registration number

Not applicable

A cooled city? Comparing human activity changes on the impact of urban thermal environment before and after city-wide lockdown

The outbreak of the COVID-19 epidemic in early 2020 reduced human outdoor activities and changed the spatial-temporal distribution of the population. To find its changes on the impact of urban thermal environment, we applied Pearson correlation analysis and OLS linear regression model from the perspective of urban land use and the local climate zone (LCZ) scheme, and selected Wuhan City in China as a case study. The results showed that the population size decreased in most urban land use and LCZ classes due to the Spring Festival and epidemic effects, which caused residents to leave Wuhan City. As a result, the normalized surface urban heat island changes (SUHI_nc) decreased by 9.41% at the city level, and a larger SUHI_nc occurred in commercial and industrial land. Among the LCZ classes, the built-up classes also tended to have a larger SUHI_nc than the natural land cover classes. However, the population size and human outdoor activity changes did not modify the spatial distribution of the urban thermal environment, because the same trends were observed for various urban land use and LCZ classes, which illustrated that the contribution of anthropogenic heat discharge on the urban thermal environment is relatively weaker. The above findings imply that it is necessary to apply different methods for various urban land uses and alleviate urban heat island.

Utility of Contrast-Enhanced T2 FLAIR for Imaging Brain Metastases Using a Half-dose High-Relaxivity Contrast Agent

BACKGROUND AND PURPOSE

Efficient detection of metastases is important for patient' treatment. This prospective study was to explore the clinical value of contrast-enhanced T2 FLAIR in imaging brain metastases using half-dose gadobenate dimeglumine.

MATERIALS AND METHODS

In vitro signal intensity of various gadolinium concentrations was explored by spin-echo T1-weighted imaging and T2 FLAIR. Then, 46 patients with lung cancer underwent nonenhanced T2 FLAIR before administration of half-dose gadobenate dimeglumine and 3 consecutive contrast-enhanced T2 FLAIR sequences followed by 1 spin-echo T1WI after administration of half-dose gadobenate dimeglumine. After an additional dose of 0.05 mmol/kg, 3D brain volume imaging was performed. All brain metastases were classified as follows: solid-enhancing, ≥ 5 mm (group A); ring-enhancing, ≥ 5 mm (group B); and lesion diameter of <5 mm (group C). The contrast ratio of the lesions on 3 consecutive phases of contrast-enhanced T2 FLAIR was measured, and the percentage increase of contrast-enhanced T2 FLAIR among the 3 groups was compared.

RESULTS

In vitro, the maximal signal intensity was achieved in T2 FLAIR at one-eighth to one-half of the contrast concentration needed for maximal signal intensity in T1WI. In vivo, the mean contrast ratio values of metastases on contrast-enhanced T2 FLAIR for the 3 consecutive phases ranged from 63.64% to 83.05%. The percentage increase (PI) values of contrast-enhanced T2 FLAIR were as follows: PI_A < PI_B (P = .001) and PI_A < PI_C (P < .001). The degree of enhancement of brain metastases on contrast-enhanced T2 FLAIR was lower than on 3D brain volume imaging (P < .001) in group A, and higher than on 3D brain volume imaging (P < .001) in group C.

CONCLUSIONS

Small or ring-enhancing metastases can be better visualized on delayed contrast-enhanced T2 FLAIR using a half-dose high-relaxivity contrast agent.

The Diversified Impacts of Urban Morphology on Land Surface Temperature among Urban Functional Zones

Local warming induced by rapid urbanization has been threatening residents' health, raising significant concerns among urban planners. Local climate zone (LCZ), a widely accepted approach to reclassify the urban area, which is helpful to propose planning strategies for mitigating local warming, has been well documented in recent years. Based on the LCZ framework, many scholars have carried out diversified extensions in urban zoning research in recent years, in which urban functional zone (UFZ) is a typical perspective because it directly takes into account the impacts of human activities. UFZs, widely used in urban planning and management, were chosen as the basic unit of this study to explore the spatial heterogeneity in the relationship between landscape composition, urban morphology, urban functions, and land surface temperature (LST). Global regression including ordinary least square regression (OLS) and random forest regression (RF) were used to model the landscape-LST correlations to screen indicators to participate in following spatial regression. The spatial regression including semi-parametric geographically weighted regression (SGWR) and multiscale geographically weighted regression (MGWR) were applied to investigate the spatial heterogeneity in landscape-LST among different types of UFZ and within each UFZ. Urban two-dimensional (2D) morphology indicators including building density (BD); three-dimensional (3D) morphology indicators including building height (BH), building volume density (BVD), and sky view factor (SVF); and other indicators including albedo and normalized difference vegetation index (NDVI) and impervious surface fraction (ISF) were used as potential landscape drivers for LST. The results show significant spatial heterogeneity in the Landscape-LST relationship across UFZs, but the spatial heterogeneity is not obvious within specific UFZs. The significant impact of urban morphology on LST was observed in six types of UFZs representing urban built up areas including Residential (R), Urban village (UV), Administration and Public Services (APS), Commercial and Business Facilities (CBF), Industrial and Manufacturing (IM), and Logistics and Warehouse (LW). Specifically, a significant correlation between urban 3D morphology indicators and LST in CBF was discovered. Based on the results, we propose different planning strategies to settle the local warming problems for each UFZ. In general, this research reveals UFZs to be an appropriate operational scale for analyzing LST on an urban scale.

Coupling mobile phone data with machine learning: How misclassification errors in ambient PM2.5 exposure estimates are produced?

BACKGROUND

Most studies relying on time-activity diary or traditional air pollution modelling approach are insufficient to suggest the impacts of ignoring individual mobility and air pollution variations on misclassification errors in exposure estimates. Moreover, very few studies have examined whether such impacts differ across socioeconomic groups.

OBJECTIVES

We aim to examine how ignoring individual mobility and PM2.5 variations produces misclassification errors in ambient PM2.5 exposure estimates.

METHODS

We developed a geo-informed backward propagation neural network model to estimate hourly PM2.5 concentrations in terms of remote sensing and geospatial big data. Combining the estimated PM2.5 concentrations and individual trajectories derived from 755,468 mobile phone users on a weekday in Shenzhen, China, we estimated four types of individual total PM2.5 exposures during weekdays at multi-temporal scales. The estimate ignoring individual mobility, PM2.5 variations or both was compared with the hypothetical error-free estimate using paired sample t-test. We then quantified the exposure misclassification error using Pearson correlation analysis. Moreover, we examined whether the misclassification error differs across different socioeconomic groups. Taking findings of ignoring individual mobility as an example, we further investigated whether such findings are robust to the different selections of time.

RESULTS

We found that the estimate ignoring PM2.5 variations, individual mobility or both was statistically different from the hypothetical error-free estimate. Ignoring both factors produced the largest exposure misclassification error. The misclassification error was larger in the estimate ignoring PM2.5 variations than that ignoring individual mobility. People with high economic status suffered from a larger exposure misclassification error. The findings were robust to the different selections of time.

CONCLUSIONS

Ignoring individual mobility, PM2.5 variations or both leads to misclassification errors in ambient PM2.5 exposure estimates. A larger misclassification error occurs in the estimate neglecting PM2.5 variations than that ignoring individual mobility, which is seldom reported before.

How Did Distribution Patterns of Particulate Matter Air Pollution (PM2.5 and PM10) Change in China during the COVID-19 Outbreak: A Spatiotemporal Investigation at Chinese City-Level

Due to the suspension of traffic mobility and industrial activities during the COVID-19, particulate matter (PM) pollution has decreased in China. However, rarely have research studies discussed the spatiotemporal pattern of this change and related influencing factors at city-scale across the nation. In this research, the clustering patterns of the decline rates of PM_2.5 and PM₁₀ during the period from 20 January to 8 April in 2020, compared with the same period of 2019, were investigated using spatial autocorrelation analysis. Four meteorological factors and two socioeconomic factors, i.e., the decline of intra-city mobility intensity (dIMI) representing the effect of traffic mobility and the decline rates of the secondary industrial output values (drSIOV), were adopted in the regression analysis. Then, multi-scale geographically weighted regression (MGWR), a model allowing the particular processing scale for each independent variable, was applied for investigating the relationship between PM pollution reductions and influencing factors. For comparison, ordinary least square (OLS) regression and the classic geographically weighted regression (GWR) were also performed. The research found that there were 16% and 20% reduction of PM_2.5 and PM₁₀ concentration across China and significant PM pollution mitigation in central, east, and south regions of China. As for the regression analysis results, MGWR outperformed the other two models, with R² of 0.711 and 0.732 for PM_2.5 and PM₁₀, respectively. The results of MGWR revealed that the two socioeconomic factors had more significant impacts than meteorological factors. It showed that the reduction of traffic mobility caused more relative declines of PM_2.5 in east China (e.g., cities in Jiangsu), while it caused more relative declines of PM₁₀ in central China (e.g., cities in Henan). The reduction of industrial operation had a strong relationship with the PM₁₀ drop in northeast China. The results are crucial for understanding how the decline pattern of PM pollution varied spatially during the COVID-19 outbreak, and it also provides a good reference for air pollution control in the future.

Spatiotemporal Variations of Particulate and Gaseous Pollutants and Their Relations to Meteorological Parameters: The Case of Xiangyang, China

High air pollution levels have become a nationwide problem in China, but limited attention has been paid to prefecture-level cities. Furthermore, different time resolutions between air pollutant level data and meteorological parameters used in many previous studies can lead to biased results. Supported by synchronous measurements of air pollutants and meteorological parameters, including PM_2.5, PM₁₀, total suspended particles (TSP), CO, NO₂, O₃, SO₂, temperature, relative humidity, wind speed and direction, at 16 urban sites in Xiangyang, China, from 1 March 2018 to 28 February 2019, this paper: (1) analyzes the overall air quality using an air quality index (AQI); (2) captures spatial dynamics of air pollutants with pollution point source data; (3) characterizes pollution variations at seasonal, day-of-week and diurnal timescales; (4) detects weekend effects and holiday (Chinese New Year and National Day holidays) effects from a statistical point of view; (5) establishes relationships between air pollutants and meteorological parameters. The principal results are as follows: (1) PM_2.5 and PM₁₀ act as primary pollutants all year round and O₃ loses its primary pollutant position after November; (2) automobile manufacture contributes to more particulate pollutants while chemical plants produce more gaseous pollutants. TSP concentration is related to on-going construction and road sprinkler operations help alleviate it; (3) an unclear weekend effect for all air pollutants is confirmed; (4) celebration activities for the Chinese New Year bring distinctly increased concentrations of SO₂ and thereby enhance secondary particulate pollutants; (5) relative humidity and wind speed, respectively, have strong negative correlations with coarse particles and fine particles. Temperature positively correlates with O₃.

How Do the Multi-Temporal Centroid Trajectories of Urban Heat Island Correspond to Impervious Surface Changes: A Case Study in Wuhan, China

Conspicuous expansion and intensification of impervious surfaces accompanied by rapid urbanization are widely recognized to have exerted evident impacts on the urban thermal environment. Investigating the spatially and temporally varying relationships between Land Surface Temperature (LST) and impervious surfaces (IS) at multiple scales is of great significance for steering IS expansion and intensification. This study proposes an analytical framework to investigate the spatiotemporal variations of LST and its responses to IS in Wuhan, China at both city scale and sub-region scale. The summer LST patterns in 2002-2017 are extracted by Multi-Task Gaussian Process (MTGP) model from raw 8-day synthesized MODerate-resolution Imaging Spectroradiometer (MODIS) LST data. At the city scale, the weighted center of LST (LSTWC) and impervious surface fraction (ISFWC), multi-temporal trajectories and coupling indicators are utilized to comprehensively examine the spatial and temporal dynamics of LST and IS within Wuhan. At the sub-region scale, urban heat island ratio index (URI), impervious surfaces contribution index (ISCI) and sprawl rate are introduced for further quantifying the relationships of LST and IS. The results reveal that IS and hot thermal landscapes expanded by 407.43 km2 and 255.82 km2 in Wuhan in 2002-2017 at city scale. The trajectories of LSTWCs and ISFWCs are visually coherent and both heading to southeast direction in general. At the sub-region scale, the specific cardinal directions with the highest ISCI variations are examined to be the exact directions of ISFWC trajectories in 2002-2017. The results reveal that the spatiotemporal variations of LST and IS are highly correlated at both city and sub-region scales within Wuhan, thus testifying the significance of steering IS expansion and renewal for controlling urban thermal environment deterioration.

How to quantify the relationship between spatial distribution of urban waterbodies and land surface temperature?

Urban waterbodies can effectively mitigate the increasing UHI effects and thus enhance climate resilience of urban areas. To contribute to our limited understanding in cooling effect of waterbodies on surrounding thermal environments, we examine the quantitative relationship between the spatial distribution of urban waterbodies and the land surface temperature (LST) in Wuhan, China. This paper 1) applies two indicators, the fractional water cover and the gravity water index, for measuring the spatial distribution of urban waterbodies; 2) conducts simple linear regression and spatial regression analyses to explore the LST-water relationship at multiple scales; and 3) compares the individual regression results from different land use types. The results show that the spatial distribution of urban waterbodies affects the LST significantly, and the gravity water index sufficiently explains the LST variation at various scales. Furthermore, the impact of urban waterbody distribution on the LST does vary across different land use types. Conclusions from this study provide insights of the cooling effect of urban waterbodies, which can further assist city planners and decision makers in utilizing cooling effects of waterbodies to improve the thermal environment of urban areas.

Association of serum uric acid change with mortality, renal function and diuretic dose administered in treatment of acute heart failure

BACKGROUND AND AIMS

Hyperuricemia is reportedly associated with poor outcome in acute heart failure (AHF). The association between changes in Uric acid (UA) levels with renal function change, diuretic doses, and mortality in patients with AHF were studied.

METHODS AND RESULTS

Consecutive patients hospitalized with AHF were reviewed (n = 535). UA levels were measured at admission and either at discharge or on approximately the seventh day of admission. Patients with an UA change in the top tertile were defined as having an increase (UA-increase) and were compared to those outside the top tertile (non-UA-increase). The endpoint was all-cause mortality, with a mean follow-up duration of 22.2 months. Patients in the UA-increase group presented with greater creatine increase (P < 0.001), and were administered a higher average daily dose of loop diuretic (P = 0.016) compared with the non-UA-increase group. In-hospital UA-increase was associated with higher risk of mortality even after adjusting for confounding variables including creatine change and diuretic dosage [harzard ratio (HR) 1.53, 95% confidence interval (CI) 1.02-2.30, P = 0.042]. In patients with hyperuricemia on admission, UA-increase was associated with increased mortality (adjusted HR 2.21, 95% CI 1.38-3.52, P = 0.001). Whereas, in those without admission hyperuricemia, UA-increase had no significant association with mortality.

CONCLUSIONS

An increase in UA during in-hospital treatment is associated with an increase in creatine levels and daily diuretic dose. Mortality associated with increased UA is restricted to patients who already have hyperuricemia at admission. A combination of UA levels at admission and UA changes on serial assessment during hospitalization may be additional value in the risk stratification of AHF patients.

[Research progress of microRNAs in regulation of lipid metabolism-related proteins for influencing the pathogenesis of hepatocellular carcinoma]

The incidence of metabolic syndrome gradually multiplied with the change of dietary structure of high fat- high sugar in the population, bringing it as independent risk factors for tumors. Liver is an important organ of lipid metabolism. The main manifestations of metabolic syndrome are obesity and abnormal lipid metabolism, which are closely related to hepatocellular carcinoma occurrence. MicroRNA (miRNA) is an endogenous non-coding RNA that participates in the post-transcriptional regulation of target genes by binding to the 3'-UTR of mRNA. Research studies have found that abnormal miRNA expression can influence the pathogenesis of hepatocellular carcinoma via regulating lipid metabolism-related proteins in the liver. This article reviews and discusses the characteristics and pathogenesis of lipid metabolism disorder in hepatocellular carcinoma, and the mechanism by which miRNA regulates the occurrence and development of hepatocellular carcinoma through lipid metabolism-related proteins. Furthermore, it also provides a reliable theoretical foundation for the study of the pathogenesis of hepatocellular carcinoma.

The multi-timescale temporal patterns and dynamics of land surface temperature using Ensemble Empirical Mode Decomposition

Temporal variation patterns of Land Surface Temperature (LST) under different time scales are crucial in understanding the response of urban thermal environment to different forcings. However, there is no integrated toolset to extract such patterns from satellite remotely sensed time series LST (TSLST) data. This paper presents a workflow to extract the multi-timescale temporal patterns and dynamics from nonlinear and non-stationary TSLST data by taking Wuhan, China as case study. The 8-day MODerate-resolution Imaging Spectroradiometer (MODIS) satellite image products spanning the 2003-2017 period are used to generate a TSLST dataset with continuous and smooth surfaces on the monthly basis through the non-parametric Multi-Task Gaussian Process Modeling (MTGP). The study area is segmented into multiple time series clusters by k-means to bridge with urban planning in terms of research and implementation scale. Then, temporal patterns including annual, interannual components, and overall trends are reconstructed based on the components with characteristic time scales decomposed by the adaptive Ensemble Empirical Mode Decomposition (EEMD) method. The generated patterns of the 17 time series clusters are interpreted from the perspective of earth revolution, meteorological cycles and urbanization. Specifically, the annual components which are mainly generated by earth revolution reveal consistent rhythmic patterns among the time series. The interannual components preserve similar shapes although they differ in amplitudes. The overall shape is basically consistent with that of air temperature of Central China, which may be mainly induced by the El Niño-Southern Oscillation (ENSO) phenomenon. The overall trends which exert considerable differences are grouped into three types by shape. Such differences may be potentially caused by the inconsistent levels of localized urbanization, afforestation or circular economy development. This study facilitates the understanding of TSLST patterns and human-environment interactions. The proposed workflow can be utilized for other cities and potentially used for comparison among different cities.

[Mechanism of lung injury of rats induced by inhalation of white smoke from burning smoke pot]

Objective: To explore mechanism of lung injury of rats induced by inhalation of white smoke from burning smoke pot. Methods: Forty-eight Sprague Dawley rats were divided into control group (n=12) and injury group (n=36) according to the random number table. Rats in injury group were placed in smoke-induced injury experimental equipment fulled with white smoke from burning smoke pot for 5 minutes to make lung injury, and rats in control group were placed in smoke-induced injury experimental equipment fulled with air for 5 minutes to make sham injury. Six rats in injury group at post injury hour (PIH) 6, 24, and 72 and six rats in control group at PIH 72 were collected to observe pathological changes of lung tissue and pathological score of rats in the two groups by hematoxylin-eosin staining, to detect expression of nuclear factor-κB (NF-κB) p65 mRNA in lung tissue of rats by reverse transcriptional polymerase chain reaction, and to detect content of tumor necrosis factor α (TNF-α), interleukin 1β (IL-1β), and IL-6 in lung tissue of rats by enzyme-linked immunosorbent assay. Data were processed with one-way analysis of variance and t test. Results: At PIH 72, lung tissue structure of rats in control group was clear and complete, with no inflammatory cell infiltration. At PIH 6, there was edema, hemorrhage, and inflammatory cell infiltration in lung tissue of rats in injury group. At PIH 24, edema, hemorrhage, and inflammatory cell infiltration in lung tissue of rats in injury group aggravated. At PIH 72, area of edema in lung tissue of rats in injury group was enlarged, with obvious hemorrhage and inflammatory cell infiltration. At PIH 6, 24, and 72, pathological score of lung tissue of rats in injury group was (3.43±0.86), (5.39±0.93), and (9.99±0.84) points, respectively, obviously higher than that of rats in control group at PIH 72 [(2.11±0.20) points, t=3.659, 8.450, 22.355, P<0.05]. As time post injury prolonged, pathological scores of lung tissue of rats in injury group were significantly increased (F=121.244, P<0.01). At PIH 6, 24, and 72, expression of NF-κB p65 mRNA in lung tissue of rats in injury group was 15.5±4.3, 25.9±1.8, 30.9±3.5 respectively, significantly higher than that of rats in control group at PIH 72 (7.8±0.8, t=4.315, 20.445, 14.408, P<0.01). As time post injury prolonged, expression of NF-κB p65 mRNA in lung tissue of rats in injury group gradually increased (F=32.691, P<0.01). At PIH 6, 24, and 72, content of TNF-α, IL-1β, and IL-6 in lung tissue of rats in injury group was significantly higher than that of rats in control group at PIH 72, respectively (t=7.650, 8.968, 6.827, 6.726, 8.978, 3.460, 5.420, 13.289, 16.438, P<0.01). At PIH 24, content of TNF-α and IL-1β in lung tissue of rats in injury group was higher than that of rats in the same group at PIH 6 and 72, respectively (t=3.409, -2.549, 4.047, -4.100, P<0.05). At PIH 24 and 72, content of IL-6 in lung tissue of rats in injury group was respectively higher than that of rats in the same group at PIH 6 (t=8.273, 9.711, P<0.05). Conclusions: After inhaling white smoke from burning smoke pot, rats are inflicted with lung injury by increasing expression of NF-κB p65 mRNA and content of TNF-α, IL-1β, and IL-6, and induce pathological changes of edema, hemorrhage, and inflammatory cell infiltration of lung tissue.

An IHS-Based Pan-Sharpening Method for Spectral Fidelity Improvement Using Ripplet Transform and Compressed Sensing

Pan-sharpening aims at integrating spectral information from a multi-spectral (MS) image and spatial information from a panchromatic (PAN) image in a fused image with both high spectral and spatial resolutions. Numerous pan-sharpening methods are based on intensity-hue-saturation (IHS) transform, which may cause evident spectral distortion. To address this problem, an IHS-based pan-sharpening method using ripplet transform and compressed sensing is proposed. Firstly, the IHS transform is applied to the MS image to separate intensity components. Secondly, discrete ripplet transform (DRT) is implemented on the intensity component and the PAN image to obtain multi-scale sub-images. High-frequency sub-images are fused by a local variance algorithm and, for low-frequency sub-images, compressed sensing is introduced for the reconstruction of the intensity component so as to integrate the local information from both the intensity component and the PAN image. The specific fusion rule is defined by local difference. Finally, the inverse ripplet transform and inverse IHS transform are coupled to generate the pan-sharpened image. The proposed method is compared with five state-of-the-art pan-sharpening methods and also the Gram-Schmidt (GS) method through visual and quantitative analysis of WorldView-2, Pleiades and Triplesat datasets. The experimental results reveal that the proposed method achieves relatively higher spatial resolution and more desirable spectral fidelity.

[A retrospective analysis of clinical characteristics and outcomes of heart failure patients with different left ventricular ejection fractions]

Objective: To compare the clinical characteristics, and outcomes of patients with heart failure with different left ventricular ejection fractions (LVEF). Methods: A total of 1 182 hospitalized patients with heart failure (HF) were enrolled and retrospectively studied in the present study. The patients were stratified by LVEF as reduced (HFrEF, LVEF<40%, n=313), mid-range (HFmrEF, 40% ≤LVEF <50%, n=287) and preserved (HFpEF, LVEF≥50%, n=582) ejection fraction groups. Among the 1 182 cases, 941 of them (81.3%, 84.9%, and 84.0% inHFrEF, HFmrEF and HFpEF groups, respectively) were followed up for an median duration of 27.3 months. Results: (1) Among the study patients, 26.5% were in HFrEF, 24.3% in HFmrEF, and 49.2% in HFpEF groups. (2) Ischemic heart disease with HFmrEF was more frequent than that in patients with HFrEF. The average age, percentage of female subjects, systolic blood pressure, uric acid, N terminal B-type natriuretic peptide precursor (NT-proBNP), hemoglobin, and the incidence of hypertensive heart disease, anemia, atrial fibrillation in patients with HFmrEF were higher than those in patients with HFrEF, but lower than those in patients with HFpEF (all P<0.01). (3) The all-cause cumulative mortality was 10.8% at 1 year, 20.6% at 2 years and 35.9% at 5 years. No difference was observed in the all-cause cumulative mortality at 1 year, 2 years, 5 years among the three groups (all P>0.05). Conclusions: The HFmrEF patients, as a new and distinct group, were with many intermediate characteristics compared with HFrEF and HFpEF subjects. However, the all-cause mortality was not significantly different among HF patients with different LVEF.

Piccolo mediates EGFR signaling and acts as a prognostic biomarker in esophageal squamous cell carcinoma

The presynaptic cytomatrix protein Piccolo, encoded by PCLO, is frequently mutated and amplified in esophageal squamous cell carcinoma (ESCC), but its exact roles in ESCC remain unclear. Here we report that Piccolo expression correlates significantly with clinical stage, patient survival and tumor embolus. Functional studies demonstrate that PCLO knockdown remarkably attenuates ESCC malignancy in vitro and in vivo, and ectopic EGFR expression partially compensates for Piccolo loss. PCLO knockdown promotes ubiquitination and degradation of EGFR, which is associated with the negative regulatory effect of Piccolo on E3 ligase Siah1. An anti-Piccolo monoclonal antibody inhibited tumor proliferation in a mouse model of ESCC. These results demonstrate that Piccolo contributes to tumor aggressiveness in ESCC, likely by stabilizing EGFR and promoting EGFR-dependent signaling. Our results further suggest that Piccolo may represent a novel prognostic biomarker and therapeutic target for patients with ESCC.

Upregulation of long noncoding RNA ZEB1-AS1 promotes tumor metastasis and predicts poor prognosis in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality worldwide. Despite progress in diagnostics and treatment of HCC, its prognosis remains poor. Emerging studies showed that long noncoding RNAs (lncRNAs) have crucial regulatory roles in cancer biology. In the current study, differentially expressed lncRNAs between HCC and paired non-tumor tissues were identified using microarrays. The effects of a specific differentially expressed lncRNA (termed ZEB1-AS1) on tumor progression were investigated in vitro and in vivo. We found that ZEB1-AS1 is frequently upregulated in HCC samples, especially in metastatic tumor tissues. DNA methylation analysis shows a tumor-specific ZEB1-AS1 promoter hypomethylation. Aberrant methylation is tightly correlated with overexpression of ZEB1-AS1 in HCC. Patients with ZEB1-AS1 hypomethylation or with high ZEB1-AS1 expression have poor recurrence-free survival. Functionally, ZEB1-AS1 promotes tumor growth and metastasis, acts as an oncogene in HCC. The ZEB1-AS1 gene is located in physical contiguity with ZEB1 and positively regulates the ZEB1 expression. ZEB1 inhibition partially abrogates ZEB1-AS1-induced epithelial to mesenchymal transition (EMT) and cancer metastasis. Our results provide novel insights into the function of lncRNA-driven hepatocarcinogenesis, highlight the important role of ZEB1-AS1 and ZEB1 in HCC progression, and indicate that ZEB1-AS1 may be served as a valuable prognostic biomarker for HCC.

Platelet-activating factor receptor-mediated PI3K/AKT activation contributes to the malignant development of esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the most common malignancies worldwide and occurs at a relatively high frequency in China, yet the mechanisms underlying its devastating outcome remain unclear. Here we report that platelet-activating factor receptor (PAFR), a type of G-protein-coupled receptor, was upregulated in ESCC tumors and cell lines, compared with controls; PAFR levels were positively correlated with ESCC clinical stages and survival time. Overexpression of PAFR promoted the malignant development of ESCC in vitro and in vivo, whereas depletion of PAFR suppressed these effects. Interestingly, PAFR was observed to activate PI3K/AKT (phosphatidylinositol 3-kinase/AKT) through the upregulation of FAK kinase activity. AKT-triggered nuclear factor-κB transcriptionally activated PAFR expression. This mutual positive regulation between PAFR and AKT was required for the aggressiveness of ESCC cells both in vitro and in vivo. Furthermore, treating mice bearing ESCC tumors with cholesterol-conjugated PAFR small interfering RNA effectively inhibited tumor progression and the expression of AKT-mediated oncogenic proteins. Taken together, we made the first demonstration that dysregulation of PAFR and the positive regulatory loop between PAFR and pAKT contribute to malignant progression of ESCC.

A case-control study indicates that the TRIB1 gene is associated with pancreatic cancer

Pancreatic cancer is a malignant neoplasm originating from transformed cells arising in tissues that form the pancreas. To investigate whether the tribbles homolog 1 (Drosophila) gene (TRIB1) is associated with pancreatic cancer in the Chinese Han population, we conducted this case-control study and genotyped 3 single nucleotide polymorphisms (rs2980879, rs2980874, and rs2235108) of the TRIB1 gene in 182 patients and 359 normal controls of Chinese Han origin and analyzed their association. The results showed that the rs2980879 polymorphism was associated with pancreatic cancer [allele: P = 0.023434, genotype: P = 0.03005; odds ratio (OR) and 95% confidence interval (CI) = 0.727788 (0.552664-0.958404)], whereas the rs2980874 polymorphism had no association with pancreatic cancer [allele: P = 0.749885, genotype: P = 0.699533; OR and 95%CI = 1.041981 (0.809196-1.341734)], and the rs2235108 polymorphism was not associated with the disease [allele: P = 0.629475, genotype: P = 0.547534, OR and 95%CI = 1.128290 (0.690829-1.842770)]. Haplotype analyses and linkage disequilibrium tests were also conducted, and the results showed that these 3 loci are not in the same block. In conclusion, our study indicated that the TRIB1 gene is associated with pancreatic cancer. More studies with larger samples are needed in order to support this finding.