Surface runoff and phosphorus (P) loss from bamboo (Phyllostachys pubescens) forest ecosystem in southeast China

The effect of different fertilization treatments on runoff and nutrient losses under field conditions was investigated through setting runoff plots in bamboo (Phyllostachys pubescens) forests in a catchment of Taihu Lake. The results showed that, the runoff loss reached 356, 361 and 342 m3/hm2, while the soil particle loss reached 393, 392 and 442 kg/hm2, respectively, in the period from June 2009 to May 2010, under the treatments of control (CK), site-specific nutrient management (SSNM) and farmers’ fertilizer practice (FFP). The runoff and soil particle losses were highly correlated with the precipitation during the period. The largest phosphorus losses happened in August, when it had the largest rainfall of that year. The total phosphorus (TP) concentration of the 95% of the observed runoff samples exceeded 0.10 mg/l. The average bioavailable phosphorus (BAP) concentration of the runoff was 0.23 mg/l and the various phosphorus forms lost was strongly inter-correlated. Compared with FFP, the SSNM treatment reduced total P (TP) by 5%, total dissolved phosphorus (DP) loss by 15% and total bioavailable phosphorus (BAP) loss by 8%.Key words: Phyllostachys pubescens, ecosystem, surface runoff, phosphorus (P) loss

Superderivations for Modular Graded Lie Superalgebras of Cartan-type

Superderivations for the eight families of finite or infinite dimensional graded Lie superalgebras of Cartan-type over a field of characteristic $p>3$ are completely determined by a uniform approach: The infinite dimensional case is reduced to the finite dimensional case and the latter is further reduced to the restrictedness case, which proves to be far more manageable. In particular, the outer superderivation algebras of those Lie superalgebras are completely determined

Recovery from Mercury Contamination in the Second Songhua River, China

Mercury pollution in the Second Songhua River (SSR) was serious in the last century due to effluent from a chemical corporation. Effects of riverine self-purification on mercury removal were studied by comparing monitoring data of mercury concentrations varieties in water, sediment, and fish in the past, about 30 years. The present work suggested that a river of such a size like the SSR possessed the potential ability to recover from mercury pollution under the condition that mercury sources were cut off, though it needs a very long time, which might be several decades or even a century of years. During the 30 years with no effluent containing mercury input, total mercury (T-Hg) of water and sediment in some typical segments, mostly near the past effluent outlet, had decreased radically but still higher than the background values, though the decrease amplitudes were over 90% compared with that in 1975. T-Hg had decreased by more than 90% in most fishes, but some were still not suitable for consumption. Methylmercury concentrations (MeHg) of water, sediment, and fish were higher or close to the background levels in 2004. In the coming decades, the purification processes in the SSR would be steady and slow for a long period

Chemosensitivity of radioresistant cells in the multicellular spheroids of A549 lung adenocarcinoma

<p>Abstract</p> <p>Background</p> <p>The relapse of cancer after radiotherapy is a clinical knotty problem. Previous studies have demonstrated that the elevation of several factors is likely in some way to lead to the development of treatment tolerance, so it is necessary to further explore the problem of re-proliferated radioresistant cells to chemotherapeutic agents. In the present study, we aimed to investigate the chemosensitivity of radioresistant cells originated from the multicellular spheroids of A549 lung adenocarcinoma.</p> <p>Methods</p> <p>After irradiated with 25 Gy of 6 MV X-ray to A549 multicellular spheroids, whose 10th re-proliferated generations were employed as radioresistant cells, and the control groups were A549 parental cells and MCF7/VCR resistant cells. The chemo-sensitivity test was made by six kinds of chemotherapeutic drugs which were DDP, VDS, 5-Fu, HCP, MMC and ADM respectively, while verapamil (VPL) was used as the reversal agent. Then the treatment effect was evaluated by MTT assay, and the multidrug resistant gene expressions of <it>mdr1 </it>and <it>MRP </it>were measured by RT-PCR.</p> <p>Results</p> <p>Both A549 parental cells and A549 derived radioresistant cells were resistant to DDP, but sensitive to VDS, 5-Fu, HCP, MMC and ADM. The inhibitory rates of VPL to these two types of cell were 98% and 25% respectively (P < 0.001). In addition, without drugs added, the absorbance value (A value) of A549 parental cells was 2-folds higher than that of their radioresistant cells (P < 0.001). As to the MCF7/VCR cells, they were resistant to DDP and VDS, but slight sensitive to MMC, ADM, 5-Fu, and HCP with 80% of inhibitory rate to VPL. The subsequent RT-PCR demonstrated that the <it>Mdr1</it>/β2-MG and <it>MRP</it>/β2-MG of all A549 cells were about 0 and 0.7 respectively, and those of MCF7/VCR cells were 35 and 4.36.</p> <p>Conclusion</p> <p>The chemosensitivity of A549 radioresistant cells had not changed markedly, and the decreased sensitivity to VPL could not be explained by the gene expression of <it>mdr1 </it>and <it>MRP</it>. It is possible that the changes in the cell membrane and decreased proliferate ability might be attributed to the resistance. Unlike multidrug resistance induced by chemotherapy, VPL may be not an ideal reverser to radioresistant cells. Therefore, the new biological strategy needs to be developed to treat recurring radioresistant tumor in combination with chemotherapy.</p

In situ epitaxial engineering of graphene and h-BN lateral heterostructure with a tunable morphology comprising h-BN domains

Graphene and hexagonal boron nitride (h-BN), as typical two-dimensional (2D) materials, have long attracted substantial attention due to their unique properties and promise in a wide range of applications. Although they have a rather large difference in their intrinsic bandgaps, they share a very similar atomic lattice; thus, there is great potential in constructing heterostructures by lateral stitching. Herein, we present the in situ growth of graphene and h-BN lateral heterostructures with tunable morphologies that range from a regular hexagon to highly symmetrical star-like structure on the surface of liquid Cu. The chemical vapor deposition (CVD) method is used, where the growth of the h-BN is demonstrated to be highly templated by the graphene. Furthermore, large-area production of lateral G-h-BN heterostructures at the centimeter scale with uniform orientation is realized by precisely tuning the CVD conditions. We found that the growth of h-BN is determined by the initial graphene and symmetrical features are produced that demonstrate heteroepitaxy. Simulations based on the phase field and density functional theories are carried out to elucidate the growth processes of G-h-BN flakes with various morphologies, and they have a striking consistency with experimental observations. The growth of a lateral G-h-BN heterostructure and an understanding of the growth mechanism can accelerate the construction of various heterostructures based on 2D materials

Scoring docking conformations using predicted protein interfaces

BACKGROUND: Since proteins function by interacting with other molecules, analysis of protein-protein interactions is essential for comprehending biological processes. Whereas understanding of atomic interactions within a complex is especially useful for drug design, limitations of experimental techniques have restricted their practical use. Despite progress in docking predictions, there is still room for improvement. In this study, we contribute to this topic by proposing T-PioDock, a framework for detection of a native-like docked complex 3D structure. T-PioDock supports the identification of near-native conformations from 3D models that docking software produced by scoring those models using binding interfaces predicted by the interface predictor, Template based Protein Interface Prediction (T-PIP). RESULTS: First, exhaustive evaluation of interface predictors demonstrates that T-PIP, whose predictions are customised to target complexity, is a state-of-the-art method. Second, comparative study between T-PioDock and other state-of-the-art scoring methods establishes T-PioDock as the best performing approach. Moreover, there is good correlation between T-PioDock performance and quality of docking models, which suggests that progress in docking will lead to even better results at recognising near-native conformations. CONCLUSION: Accurate identification of near-native conformations remains a challenging task. Although availability of 3D complexes will benefit from template-based methods such as T-PioDock, we have identified specific limitations which need to be addressed. First, docking software are still not able to produce native like models for every target. Second, current interface predictors do not explicitly consider pairwise residue interactions between proteins and their interacting partners which leaves ambiguity when assessing quality of complex conformations

Predicting protein-protein interface residues using local surface structural similarity

<p>Abstract</p> <p>Background</p> <p>Identification of the residues in protein-protein interaction sites has a significant impact in problems such as drug discovery. Motivated by the observation that the set of interface residues of a protein tend to be conserved even among remote structural homologs, we introduce <it>PrISE</it>, a family of local structural similarity-based computational methods for predicting protein-protein interface residues.</p> <p>Results</p> <p>We present a novel representation of the surface residues of a protein in the form of structural elements. Each structural element consists of a central residue and its surface neighbors. The <it>PrISE </it>family of interface prediction methods uses a representation of structural elements that captures the atomic composition and accessible surface area of the residues that make up each structural element. Each of the members of the <it>PrISE </it>methods identifies for each structural element in the query protein, a collection of <it>similar </it>structural elements in its repository of structural elements and weights them according to their similarity with the structural element of the query protein. <it>PrISE_L</it>relies on the similarity between structural elements (i.e. local structural similarity). <it>PrISE_G</it>relies on the similarity between protein surfaces (i.e. general structural similarity). <it>PrISE_C</it>, combines local structural similarity and general structural similarity to predict interface residues. These predictors label the central residue of a structural element in a query protein as an interface residue if a weighted majority of the structural elements that are similar to it are interface residues, and as a non-interface residue otherwise. The results of our experiments using three representative benchmark datasets show that the <it>PrISE_C</it>outperforms <it>PrISE_L</it>and <it>PrISE_G</it>; and that <it>PrISE_C</it>is highly competitive with state-of-the-art structure-based methods for predicting protein-protein interface residues. Our comparison of <it>PrISE_C</it>with <it>PredUs</it>, a recently developed method for predicting interface residues of a query protein based on the known interface residues of its (global) structural homologs, shows that performance superior or comparable to that of <it>PredUs </it>can be obtained using only local surface structural similarity. <it>PrISE_C</it>is available as a Web server at <url>http://prise.cs.iastate.edu/</url></p> <p>Conclusions</p> <p>Local surface structural similarity based methods offer a simple, efficient, and effective approach to predict protein-protein interface residues.</p