Prevalence of Aflatoxin-Associated TP53R249S Mutation in Hepatocellular Carcinoma in Hispanics in South Texas

We aimed to determine whether aflatoxin dietary exposure plays a role in the high incidence of hepatocellular carcinoma (HCC) observed among Hispanics in South Texas. We measured TP53R249S somatic mutation, hallmark of aflatoxin etiology in HCC, using droplet digital PCR and RFLP. TP53R249S mutation was detected in 3 of 41 HCC tumors from Hispanics in South Texas (7.3%). We also measured TP53R249S mutation in plasma cell-free DNA (cfDNA) from 218 HCC patients and 96 Hispanic subjects with advanced fibrosis or cirrhosis, from South Texas. The mutation was detected only in Hispanic and Asian HCC patients, and patients harboring TP53R249S mutation were significantly younger and had a shorter overall survival. The mutation was not detected in any Hispanic subject with advanced fibrosis or cirrhosis. Genes involved in cell-cycle control of chromosomal replication and in BRCA1-dependent DNA damage response were enriched in HCCs with TP53R249S mutation. The E2F1 family members, E2F1 and E2F4, were identified as upstream regulators. TP53R249S mutation was detected in 5.7% to 7.3% of Hispanics with HCC in South Texas. This mutation was associated with a younger age and worse prognosis. TP53R249S was however not detected in Hispanics in South Texas with cirrhosis or advanced fibrosis. Aflatoxin exposure may contribute to a small number of HCCs in Hispanics in South Texas, but the detection of TP53R249S mutation in plasma cfDNA is not a promising biomarker of risk assessment for HCC in subjects with cirrhosis or advanced fibrosis in this population. Cancer Prev Res; 11(2); 103-12. ©2017 AACR

Vertebral fractures among breast cancer survivors in China: a cross-sectional study of prevalence and health services gaps

Abstract Background Breast cancer survivors are at high risk for fracture due to cancer treatment-induced bone loss, however, data is scarce regarding the scope of this problem from an epidemiologic and health services perspective among Chinese women with breast cancer. Methods We designed a cross-sectional study comparing prevalence of vertebral fractures among age- and BMI-matched women from two cohorts. Women in the Breast Cancer Survivors cohort were enrolled from a large cancer hospital in Beijing. Eligibility criteria included age 50–70 years, initiation of treatment for breast cancer at least 5 years prior to enrollment, and no history of metabolic bone disease or bone metastases. Data collected included sociodemographic characteristics; fracture-related risk factors, screening and preventive measures; breast cancer history; and thoracolumbar x-ray. The matched comparator group was selected from participants enrolled in the Peking Vertebral Fracture Study, an independent cohort of healthy community-dwelling postmenopausal women from Beijing. Results Two hundred breast cancer survivors were enrolled (mean age 57.5 ± 4.9 years), and compared with 200 matched healthy women. Twenty-two (11%) vertebral fractures were identified among breast cancer survivors compared with 7 (3.5%) vertebral fractures in the comparison group, yielding an adjusted odds ratio for vertebral fracture of 4.16 (95%CI 1.69–10.21, p < 0.01). The majority had early stage (85.3%) and estrogen and/or progesterone receptor positive (84.6%) breast cancer. Approximately half of breast cancer survivors reported taking calcium supplements, 6.1% reported taking vitamin D supplements, and only 27% reported having a bone density scan since being diagnosed with breast cancer. Conclusions Despite a four-fold increased odds of prevalent vertebral fracture among Chinese breast cancer survivors in our study, rates of screening for osteoporosis and fracture risk were low reflecting a lack of standardization of care regarding cancer-treatment induced bone loss

Positron Emission Tomography Imaging of CD105 Expression with a 64Cu-Labeled Monoclonal Antibody: NOTA Is Superior to DOTA

Optimizing the in vivo stability of positron emission tomography (PET) tracers is of critical importance to cancer diagnosis. In the case of 64Cu-labeled monoclonal antibodies (mAb), in vivo behavior and biodistribution is critically dependent on the performance of the bifunctional chelator used to conjugate the mAb to the radiolabel. This study compared the in vivo characteristics of 64Cu-labeled TRC105 (a chimeric mAb that binds to both human and murine CD105), through two commonly used chelators: 1,4,7-triazacyclononane-1,4,7-triacetic acid (NOTA) and 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA). Flow cytometry analysis confirmed that chelator conjugation of TRC105 did not affect its CD105 binding affinity or specificity. PET imaging and biodistribution studies in 4T1 murine breast tumor-bearing mice revealed that 64Cu-NOTA-TRC105 exhibited better stability than 64Cu-DOTA-TRC105 in vivo, which resulted in significantly lower liver uptake without compromising the tumor targeting efficiency. In conclusion, this study confirmed that NOTA is a superior chelator to DOTA for PET imaging with 64Cu-labeled TRC105

Prediction of CO2 Emission in China’s Power Generation Industry with Gauss Optimized Cuckoo Search Algorithm and Wavelet Neural Network Based on STIRPAT model with Ridge Regression

Power generation industry is the key industry of carbon dioxide (CO2) emission in China. Assessing its future CO2 emissions is of great significance to the formulation and implementation of energy saving and emission reduction policies. Based on the Stochastic Impacts by Regression on Population, Affluence and Technology model (STIRPAT), the influencing factors analysis model of CO2 emission of power generation industry is established. The ridge regression (RR) method is used to estimate the historical data. In addition, a wavelet neural network (WNN) prediction model based on Cuckoo Search algorithm optimized by Gauss (GCS) is put forward to predict the factors in the STIRPAT model. Then, the predicted values are substituted into the regression model, and the CO2 emission estimation values of the power generation industry in China are obtained. It’s concluded that population, per capita Gross Domestic Product (GDP), standard coal consumption and thermal power specific gravity are the key factors affecting the CO2 emission from the power generation industry. Besides, the GCS-WNN prediction model has higher prediction accuracy, comparing with other models. Moreover, with the development of science and technology in the future, the CO2 emission growth in the power generation industry will gradually slow down according to the prediction results

Effective contact texture region aware pavement skid resistance prediction via convolutional neural network

The surface texture of asphalt pavement has a significant effect on skid resistance performance. However, its contribution to the performance of skid resistance is non-homogeneous and subjects to local validity. There are also a few deep learning models that take into account the effective contact texture region. This paper proposes a convolutional neural network model based on the effective contact texture region, containing macro- and micro-scale awareness sub-modules. In this study, the asphalt mixture with varying gradations was designed to accurately obtain the effective contact texture region. Then, the textures were disentangled into macro- and micro-texture scales by applying the fast Fourier transform and fed into the model for training. Finally, the area of effective contact texture region was calculated, and the effective contact ratio parameter was then proposed using the triangulation algorithm. The results showed that the effective contact texture area of pavement varies by the asphalt mixture type. The effective contact ratio parameter exhibited a significant positive correlation (Pearson correlation coefficient is 0.901, R2= 0.8129) with skid resistance performance and was also influenced by key sieve aggregate content from 2.36 to 4.75 mm. The data of effective contact texture region following disentanglement significantly released the model performance (the relative error dropped to 1.81%). The model exhibited improved precision and performance, which can be utilized as an efficient, non-contact alternative method for skid resistance analysis.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport and Plannin

Effect of coordination number of particle contact force on rutting resistance of asphalt mixture

Optimizing asphalt mix design at the indoor stage is of significant importance for enhancing the rutting resistance of asphalt mixture, which is affected by its structural characteristics. In this work, the coordination number of particle contact force (CNpcf) was proposed as an indicator to represent contact characteristics of skeleton structure aggregates in asphalt mixture. Nine asphalt mixtures with different gradations were designed, and the relationship of CNpcf with the number of aggregate contact zones (CZ) was established by combining rutting tests and digital image processing technique (DIP). The Mann-Whitney U test was implemented to analyze the distribution properties of inter-particle contacts before and after the rutting test. In addition, the resistance to the further expansion of rutting was analyzed. The results revealed a significant positive correlation (PCCs = 0.843, R2 = 0.711) between CNpcf and CZ. The content of coarse aggregates in the dominant structure did not exhibit monotonic related to anti-rutting performance of the asphalt mixture. Therefore, an optimum aggregate content of 57% was utilized. The Mann-Whitney U test revealed that the mesoscale skeleton structure of the asphalt mixes before and after rutting exhibited excellent stability. This study further indicated the applicability of combining CNpcf to adjust the mix design to enhance the rutting resistance of asphalt mixture and to prevent rutting expansion in flexible pavement.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Pavement Engineerin

Performance and emissions of a diesel engine fueled by coal-based diesel fuels and their blends with polyoxymethylene dimethyl ethers

Abstract The objective of this study was to investigate the performance and emissions of a diesel engine fueled by coal-based diesel fuels and their blends with oxygenated fuel polyoxymethylene dimethyl ethers (PODEn). First, coal-based Fischer–Tropsch (FT) diesel fuel was blended with hydrogenated diesel fuel at three volume ratios of 40%/60%, 50%/50%, and 60%/40%, denoted as T6W4, T5W5, and T4W6, respectively. Then, PODEn were added into the T4W6 fuel with the volume ratios of 10%, 20%, and 30% to evaluate its effects on the performance and emissions of a coal-based diesel engine. The results showed that the output torques and powers of the three coal-based diesel blends were slightly lower than those of the petroleum diesel fuel. The brake specific fuel consumption (BSFC) of the coal-based diesel fuels was almost the same as that of the petroleum diesel fuel. The brake thermal efficiencies (BTE) of the coal-based diesel blends were slightly lower than that of the petroleum diesel fuel, and the maximum reduction was 1.59%. The pollutant emissions of T5W5 were the closest to those of petroleum diesel fuel. The nitrogen oxides (NOx) emissions of T4W6 were lower, with a maximum decrease of 11.18% compared with the petroleum diesel. The carbon monoxide (CO) and hydrocarbon (HC) emissions of T6W4 were the highest, with maximum increases of 36.79% and 29.05%, respectively. The smoke emissions of T4W6 and T6W4 were higher than those of petroleum diesel fuel. Adding PODEn into T4W6 lowered the engine power and torque but increased the BSFC and BTE. The output torque and power of the diesel engine were further reduced when PODEn were blended with T4W6, with the maximum reductions of 17.76% and 16.96%, respectively. With an increase in the PODEn blending ratio, BSFC and BTE increased gradually, and the maximum increase in the BTE was 1.57%. Blending PODEn with the fuel effectively improved the emission characteristics of the coal-based diesel fuels. The NOx emissions increased slightly, but the emissions of HC, CO, and smoke were reduced significantly, with maximum reductions of 24.42%, 31.67%, and 82.35%, respectively