Determination of material parameters of the two-dimensional Holzapfel–Weizsäcker type model based on uniaxial extension data of arterial walls

Soft tissues are anisotropic materials yet a majority of mechanical property tests have been uniaxial, which often failed to recapitulate the tensile response in other directions. This paper aims to study the feasibility of determining material parameters of anisotropic tissues by uniaxial extension with a minimal loss of anisotropic information. We assumed that by preselecting a certain constitutive model, we could give the constitutive parameters based on uniaxial extension data from orthogonal strip samples. In our study, the Holzapfel–Weizsäcker type strain energy density function (H–W model) was used to determine the material parameters of arterial walls from two fresh donation bodies. The key points we applied were the relationships between strain components in uniaxial tensile tests and the methods of stochastic optimisation. Further numerical experiments were taken. The estimate–effect ratio, defined by the number of data with the precision of estimation less than 0.5% over whole size of data, was calculated to demonstrate the feasibility of our method. The material parameters for Chinese aorta and pulmonary artery were given with the maximum root mean square (RMS) errors 0.042, and the minimal estimate–effect ratio in numerical experiments was 90.79%. Our results suggest that the constitutive parameters of arterial walls can be determined from uniaxial extension data, given the passive mechanical behaviour governed by H–W model. This method may apply to other tissues using different constitutive models.     

Complex Interaction and Adsorption of Glyphosate and Lead in Soil

Glyphosate [N-(phosphonomethyl)-glycine] is a herbicide widely used in large quantities in agricultural applications. It is also known to form complexes with metal ions, although its influence on metal behavior, such as lead (Pb) in soil, is not well understood. In this study, the adsorption and co-adsorption of Pb and glyphosate were determined on two soils [a red (RS) soil, Udic Ferrisol, and a yellow-brown (YB) soil, Udic Luvisol] of distinctly different chemical characteristics at varying pH conditions. Results indicate that the adsorption of lead and glyphosate strongly depends on soil types: the RS soil, characterized by a relatively high iron/aluminum content but a low pH and organic matter content, shows a much lower adsorption capacity for Pb but a higher sorption for glyphosate than the YB soil. The co-existence of Pb and glyphosate in soils resulted in complex interactions among Pb, glyphosate, Pb-glyphosate complexes, and soil minerals. The presence of glyphosate decreased Pb adsorption on the two soils, which was attributed primarily to the formation of soluble Pb-glyphosate complexes having relatively low affinities to soil surfaces. On the other hand, addition of Pb increased the adsorption of glyphosate on both soils, which was attributed to: (1) a decreased solution pH due to the ion exchange between Pb²⁺ and H⁺ on soil surfaces; and (2) increased sorption sites where Pb was adsorbed and acted as a bridge between glyphosate and the soil. The present study illustrates that the complex interactions among glyphosate, Pb, and soil may have important implications for the mobility and bioavailability of Pb in soil and should thus be considered in future environmental risk assessments.     

MicroRNAs-1614-3p gene seed region polymorphisms and association analysis with chicken production traits

In the present study, a total of 860 chickens from a Gushi–Anka F₂ resource population were used to evaluate the genetic effect of the gga-miR-1614-3p gene. A novel, silent, single nucleotide polymorphism (SNP, +5 C>T) was detected in the gga-miR-1614-3p gene seed region through AvaII polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) and PCR products sequencing methods. Associations between the SNP and chicken growth, meat quality and carcass traits were performed by association analysis. The results showed that the SNP was significantly associated with breast muscle shear force and leg muscle water loss rate, wing weight, liver weight and heart weight (p?<?0.05), and highly significantly associated with the weight of the abdominal fat (p?<?0.01). The secondary structure of gga-miR-1614 and the free energy were altered due to the variation predicted by the M-fold program.     

Development of rapid and highly sensitive HSPA1A promoter-driven luciferase reporter system for assessing oxidative stress associated with low-dose photodynamic therapy

Photodynamic therapy (PDT) is a regulatory-approved modality for treating a variety of malignant tumors. It induces tumor tissue damage via photosensitizer-mediated oxidative cytotoxicity. The heat shock protein 70 (HSP70-1) is a stress protein encoded by the HSPA1A gene and is significantly induced by oxidative stress associated with PDT. The aim of this study was to identify the functional region of the HSPA1A promoter that responds to PDT-induced oxidative stress and uses the stress responsiveness of HSPA1A expression to establish a rapid and cost-effective photocytotoxic assessment bioassay to evaluate the photodynamic potential of photosensitizers. By constructing luciferase vectors with a variety of hspa1a promoter fractions and examining their relative luciferase activity, we demonstrated that the DNA sequence from −218 to +87 of the HSPA1A gene could be used as a functional promoter to detect the PDT-induced oxidative stress. The maximal relative luciferase activity level of HSPA1A (HSP70-1) induced by hypericin-PDT was nearly nine times that of the control. Our results suggest that the novel reporter gene assay using a functional region of the HSP70A1A promoter has significant advantages for the detection of photoactivity in terms of both speed and sensitivity, when compared with a cell viability test based on ATP quantification and ROS levels. Furthermore, phthalocyanine zinc and methylene blue both induced significantly elevated levels of relative luciferase activity in a dose-dependent manner.     

Net greenhouse gas balance in response to nitrogen enrichment: perspectives from a coupled biogeochemical model

Increasing reactive nitrogen (N) input has been recognized as one of the important factors influencing climate system through affecting the uptake and emission of greenhouse gases (GHG). However, the magnitude and spatiotemporal variations of N‐induced GHG fluxes at regional and global scales remain far from certain. Here we selected China as an example, and used a coupled biogeochemical model in conjunction with spatially explicit data sets (including climate, atmospheric CO₂, O₃, N deposition, land use, and land cover changes, and N fertilizer application) to simulate the concurrent impacts of increasing atmospheric and fertilized N inputs on balance of three major GHGs (CO₂, CH₄, and N₂O). Our simulations showed that these two N enrichment sources in China decreased global warming potential (GWP) through stimulating CO₂ sink and suppressing CH₄ emission. However, direct N₂O emission was estimated to offset 39% of N‐induced carbon (C) benefit, with a net GWP of three GHGs averaging ?376.3 ± 146.4 Tg CO₂ eq yr^?1 (the standard deviation is interannual variability of GWP) during 2000–2008. The chemical N fertilizer uses were estimated to increase GWP by 45.6 ± 34.3 Tg CO₂ eq yr^?1 in the same period, and C sink was offset by 136%. The largest C sink offset ratio due to increasing N input was found in Southeast and Central mainland of China, where rapid industrial development and intensively managed crop system are located. Although exposed to the rapidly increasing N deposition, most of the natural vegetation covers were still showing decreasing GWP. However, due to extensive overuse of N fertilizer, China's cropland was found to show the least negative GWP, or even positive GWP in recent decade. From both scientific and policy perspectives, it is essential to incorporate multiple GHGs into a coupled biogeochemical framework for fully assessing N impacts on climate changes.