Homogeneity in terrestrial land cover is reflected in fish diversity patterns in a Chinese river system

In river systems worldwide, land cover changes have been identified as major drivers of biodiversity change. Quantifying how terrestrial land cover impacts riverine diversity requires local biodiversity assessments. In this study, we investigated the association of terrestrial land cover and the corresponding riverine fish species communities using eDNA‐metabarcoding in the Chinese Shaying River basin. This basin is home to about 37 million people and is largely dominated by a mix of intense agriculture and urban areas, creating a relatively homogeneous, intensely used landscape. We investigated whether the homogeneous landscape is mirrored in the composition and structure of fish communities in the river network. We sampled eDNA in spring and fall of 2018, amplified it with a primer designed for local fish species and used operational taxonomic units (OTU) assigned to fish as proxy for diversity. Furthermore, we used redundancy analysis, general linear models, and distance decay curves to assess the effects of land cover on fish communities. We found that the Shaying River showed relatively high basin‐wide richness (63 OTU) and seasonal differences in local richness, but limited community differentiation. Variations in alpha‐ and beta‐diversity, measured as local OTU richness and pairwise distance‐decay across the basin were low. Redundancy analysis showed only a weak association between observed aquatic communities and their terrestrial surroundings in a 10 km buffer upstream. The lack of community differentiation assessed by eDNA metabarcoding reflects the homogeneous and intense land‐use in this basin

Learning-Assisted Inversion for Solving Nonlinear Inverse Scattering Problem

Solving inverse scattering problems (ISPs) is challenging because of its intrinsic ill-posedness and the nonlinearity. When dealing with highly nonlinear ISPs, i.e., those scatterers with high contrast and/or electrically large size, the traditional iterative nonlinear inversion methods converge slowly and take lots of computation time, even maybe trapped into local wrong solution. To alleviate the above challenges, a learning-assisted (LA) inversion approach termed as the LA inversion method (LAIM) with advanced generative adversarial network (GAN) in virtue of a new recently established contraction integral equation for inversion (CIE-I) is proposed to achieve a good balance between the computational efficiency and the accuracy of solving highly nonlinear ISPs. The preliminary profiles composed of only small amount of low-frequency components can be got efficiently by the Fourier bases expansion of CIE-I inversion (FBE-CIE-I). The physically exacted information can be taken as the input of the neural network to recover super-resolution image with more high-frequency components. A weighted loss function composed of the adversarial loss, mean absolute percentage error (MAPE), and structural similarity (SSIM) is used under the pix2pix GAN framework. In addition, the self-attention module is used at the end of the generator network to capture the physical distance information between two pixels and enhance the inversion accuracy of the feature scatterers. To further improve the inversion efficiency, the data-driven method (DDM) is used to achieve real-time imaging by cascading U-net and pix2pix GAN, where U-net is used to replace FBE-CIE-I in the LAIM. Compared with other LA inversion, both the synthetic and experimental examples have validated the merits of the proposed LAIM and DDM

An Experimental Study on Diesel Spray Injection into a Non-Quiescent Chamber

[EN] Visualization of single-hole nozzles into quiescent ambient has been used extensively in the literature to characterize spray mixing and combustion. However in-cylinder flow may have some meaningful impact on the spray evolution. In the present work, visualization of direct diesel injection spray under both non-reacting and reacting operating conditions was conducted in an optically accessible two-stroke engine equipped with a single-hole injector. Two different high-speed imaging techniques, Schlieren and UV-Light Absorption, were applied here to quantify vapor penetration for non-reacting spray. Meanwhile, Mie-scattering was used to measure the liquid length. As for reacting conditions, Schlieren and OH* chemiluminescence were simultaneously applied to obtain the spray tip penetration and flame lift-off length under the same TDC density and temperature. Additionally, PIV was used to characterize in-cylinder flow motion. Results were compared with those from the Engine Combustion Network database obtained under quiescent ambient conditions in a high pressure high temperature vessel. Because of the air flow induced by piston movement, in-cylinder conditions in the two-stroke engine during the spray injection are highly unsteady, which has a significant impact on the spray development and interference on the spray visualization. From the comparison with quiescent data from the Engine Combustion Network, air flow induced by piston movement was found to slow down tip penetration. Moreover, both ignition delay and lift-off length under unsteady flow conditions show less sensitivity with ambient temperature than that of quasi-steady conditions.This work was partially funded by the Government of Spain through COMEFF Project (TRA2014-59483-R). In addition, the authors acknowledge that some equipment used in this work has been partially supported by FEDER project funds (FEDER-ICTS-2012-06), framed in the operational program of unique scientific and technical infrastructure of the Ministry of Science and Innovation of Spain. The authors want also to express their gratitude to CONVERGENT SCIENCE Inc for their kind support for this research.Pastor, JV.; García-Oliver, JM.; García Martínez, A.; Zhong, W.; Micó Reche, C.; Xuan, T. (2017). An Experimental Study on Diesel Spray Injection into a Non-Quiescent Chamber. SAE International Journal of Fuel and Lubricants. 10(2):1-13. https://doi.org/10.4271/2017-01-0850S11310

No evidence of a causal relationship between ankylosing spondylitis and cardiovascular disease: a two-sample Mendelian randomization study

ObjectiveObservational studies have suggested an increased risk of cardiovascular disease in individuals with ankylosing spondylitis. However, these studies are prone to confounding factors and reverse causality. To address these limitations, we conducted a Mendelian randomization study to assess the causal relationship between AS and CVD.MethodsThe study population comprises 9,069 individuals with ankylosing spondylitis and 509,093 individuals with either of six common cardiovascular diseases and a related indicator. Causal analysis using summary effect estimates and inverse variance weighting were employed as the main methods.ResultsThe CAUSE analysis showed no evidence of a causal relationship between AS and CVD. The odds ratios for total CVD, heart failure, myocardial infarction, valvular heart disease, ischemic heart disease, and venous thromboembolism, Arterial stiffness index, were as follows: OR, 1.01; 95% confidence interval, 0.96–1.05; P = 0.91; OR, 1.03; 95% CI, 0.99–1.08; P = 0.50; OR, 0.94; 95% CI, 0.86–1.03; P = 0.53; OR, 0.99; 95% CI, 0.94–1.04; P = 0.99; OR, 0.98; 95% CI, 0.91–1.04; P = 0.94; OR, 0.98; 95% CI, 0.91–1.04; P = 0.99; β, −0.0019; 95% CI, 0.97–1.01; P = 0.99. The IVW and weighted median methods also yielded consistent results, and no heterogeneity or pleiotropy was found. Likewise, a reverse Mendelian randomization analysis did not uncover a heritable causal relationship between AS and CVD.ConclusionThis Mendelian randomization study does not support a causal relationship between AS and CVD. Further research is needed to confirm this association

Albumin Binding Function: The Potential Earliest Indicator for Liver Function Damage

Background. Currently there is no indicator that can evaluate actual liver lesion for early stages of viral hepatitis, nonalcoholic fatty liver disease (NAFLD), and cirrhosis. Aim of this study was to investigate if albumin binding function could better reflect liver function in these liver diseases. Methods. An observational study was performed on 193 patients with early NAFLD, viral hepatitis, and cirrhosis. Cirrhosis patients were separated according to Child-Pugh score into A, B, and C subgroup. Albumin metal ion binding capacity (Ischemia-modified albumin transformed, IMAT) and fatty acid binding capacity (total binding sites, TBS) were detected. Results. Both IMAT and TBS were significantly decreased in patients with NAFLD and early hepatitis. In hepatitis group, they declined prior to changes of liver enzymes. IMAT was significantly higher in cirrhosis Child-Pugh class A group than hepatitis patients and decreased in Child-Pugh class B and class C patients. Both IMAT/albumin and TBS/albumin decreased significantly in hepatitis and NAFLD group patients. Conclusions. This is the first study to discover changes of albumin metal ion and fatty acid binding capacities prior to conventional biomarkers for liver damage in early stage of liver diseases. They may become potential earliest sensitive indicators for liver function evaluation

Distinguishing Emission-Associated Ambient Air PM2.5 Concentrations and Meteorological Factor-Induced Fluctuations

Although PM2.5 (particulate matter with aerodynamic diameters less than 2.5 μm) in the air originates from emissions, its concentrations are often affected by confounding meteorological effects. Therefore, direct comparisons of PM2.5 concentrations made across two periods, which are commonly used by environmental protection administrations to measure the effectiveness of mitigation efforts, can be misleading. Here, we developed a two-step method to distinguish the significance of emissions and meteorological factors and assess the effectiveness of emission mitigation efforts. We modeled ambient PM2.5 concentrations from 1980 to 2014 based on three conditional scenarios: realistic conditions, fixed emissions, and fixed meteorology. The differences found between the model outputs were analyzed to quantify the relative contributions of emissions and meteorological factors. Emission-related gridded PM2.5 concentrations excluding the meteorological effects were predicted using multivariate regression models, whereas meteorological confounding effects on PM2.5 fluctuations were characterized by probabilistic functions. When the regression models and probabilistic functions were combined, fluctuations in the PM2.5 concentrations induced by emissions and meteorological factors were quantified for all model grid cells and regions. The method was then applied to assess the historical and future trends of PM2.5 concentrations and potential fluctuations on global, national, and city scales. The proposed method may thus be used to assess the effectiveness of mitigation actions

Impacts of air pollutants from rural Chinese households under the rapid residential energy transition

Rural residential energy consumption in China is experiencing a rapid transition towards clean energy, nevertheless, solid fuel combustion remains an important emission source. Here we quantitatively evaluate the contribution of rural residential emissions to PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm) and the impacts on health and climate. The clean energy transitions result in remarkable reductions in the contributions to ambient PM2.5, avoiding 130,000 (90,000-160,000) premature deaths associated with PM2.5 exposure. The climate forcing associated with this sector declines from 0.057 ± 0.016 W/m2 in 1992 to 0.031 ± 0.008 W/m2 in 2012. Despite this, the large remaining quantities of solid fuels still contributed 14 ± 10 μg/m3 to population-weighted PM2.5 in 2012, which comprises 21 ± 14% of the overall population-weighted PM2.5 from all sources. Rural residential emissions affect not only rural but urban air quality, and the impacts are highly seasonal and location dependent

E6 Protein Expressed by High-Risk HPV Activates Super-Enhancers of the EGFR and c-MET Oncogenes by Destabilizing the Histone

The high-risk (HR) human papillomaviruses (HPV) are causative agents of anogenital tract dysplasia and cancers and a fraction of head and neck cancers. The HR HPV E6 oncoprotein possesses canonical oncogenic functions, such as p53 degradation and telomerase activation. It is also capable of stimulating expression of several oncogenes, but the molecular mechanism underlying these events is poorly understood. Here, we provide evidence that HPV16 E6 physically interacts with histone H3K4 demethylase KDM5C, resulting in its degradation in an E3 ligase E6AP- and proteasome-dependent manner. Moreover, we found that HPV16-positive cancer cell lines exhibited lower KDM5C protein levels than HPV-negative cancer cell lines. Restoration of KDM5C significantly suppressed the tumorigenicity of CaSki cells, an HPV16-positive cervical cancer cell line. Whole genome ChIP-seq and RNA-seq results revealed that CaSki cells contained super-enhancers in the proto-oncogenes EGFR and c-MET. Ectopic KDM5C dampened these super-enhancers and reduced the expression of proto-oncogenes. This effect was likely mediated by modulating H3K4me3/H3K4me1 dynamics and decreasing bidirectional enhancer RNA transcription. Depletion of KDM5C or HPV16 E6 expression activated these two super-enhancers. These results illuminate a pivotal relationship between the oncogenic E6 proteins expressed by HR HPV isotypes and epigenetic activation of super-enhancers in the genome that drive expression of key oncogenes like EGFR and c-MET. Significance: This study suggests a novel explanation for why infections with certain HPV isotypes are associated with elevated cancer risk by identifying an epigenetic mechanism through which E6 proteins expressed by those isotypes can drive expression of key oncogenes.</p