Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Protein Subcellular Localization with Gaussian Kernel Discriminant Analysis and Its Kernel Parameter Selection

Kernel discriminant analysis (KDA) is a dimension reduction and classification algorithm based on nonlinear kernel trick, which can be novelly used to treat high-dimensional and complex biological data before undergoing classification processes such as protein subcellular localization. Kernel parameters make a great impact on the performance of the KDA model. Specifically, for KDA with the popular Gaussian kernel, to select the scale parameter is still a challenging problem. Thus, this paper introduces the KDA method and proposes a new method for Gaussian kernel parameter selection depending on the fact that the differences between reconstruction errors of edge normal samples and those of interior normal samples should be maximized for certain suitable kernel parameters. Experiments with various standard data sets of protein subcellular localization show that the overall accuracy of protein classification prediction with KDA is much higher than that without KDA. Meanwhile, the kernel parameter of KDA has a great impact on the efficiency, and the proposed method can produce an optimum parameter, which makes the new algorithm not only perform as effectively as the traditional ones, but also reduce the computational time and thus improve efficiency

Unexpected Odd–Even Oscillation in the Enhanced Chemical Activities of the Ru_<i>n</i> (<i>n</i> = 2–14) Nanoclusters for H₂O Splitting

Nanoclusters usually display exotic physical and chemical properties due to their intriguing geometric structures in contrast to their bulk counterparts. In general, the more energetically stable the nanocluster, the weaker the reagent reacts with it; however, to date, it is still open whether all reactions are subject to such a fundamental constraint. Here, using first-principles calculations within density functional theory in consideration of van der Waals corrections and Gaussian 09 program, we investigate the energetic and kinetic properties of water molecules adsorption on small Ru_<i>n</i> (<i>n</i> = 2–14) clusters. It is found that almost all of the studied Ru_<i>n</i> clusters possess superior activities toward H₂O adsorption and dissociation, due to the enlarged desorption energies and reduced dissociation barriers when compared with the bulk Ru(0001) counterpart. More interestingly, though the stabilities of Ru_<i>n</i> clusters exhibit significant odd–even oscillation behavior, i.e., the even-numbered nanoclusters are distinctly more stable than their neighboring odd-numbered cases, the H₂O molecule adsorption on the even-numbered Ru_<i>n</i> clusters (such as <i>n</i> = 4, 6, 8, 10) leads to larger adsorption energies. We reveal that such intriguing activity can be explicated by a geometric effect, namely, the lowly coordinated atoms contribute the lowest-unoccupied molecular orbital protruding out of the cluster to capture the lone-pair electrons from H₂O molecule and determine the size-dependent chemical activities. These findings shed new insight into highly efficient and economic nanocatalysts design for the field of water splitting

Lentivirus-Mediated Nox4 shRNA Invasion and Angiogenesis and Enhances Radiosensitivity in Human Glioblastoma

Radioresistance remains a significant therapeutic obstacle in glioblastoma. Reactive oxygen species (ROS) are associated with multiple cellular functions such as cell proliferation and apoptosis. Nox4 NADPH oxidase is abundantly expressed and has proven to be a major source of ROS production in glioblastoma. Here we investigated the effects of Nox4 on GBM tumor cell invasion, angiogenesis, and radiosensitivity. A lentiviral shRNA vector was utilized to stably knockdown Nox4 in U87MG and U251 glioblastoma cells. ROS production was measured by flow cytometry using the fluorescent probe DCFH-DA. Radiosensitivity was evaluated by clonogenic assay and survival curve was generated. Cell proliferation activity was assessed by a cell counting proliferation assay and invasion/migration potential by Matrigel invasion assay. Tube-like structure formation assay was used to evaluate angiogenesis ability in vitro and VEGF expression was assessed by MTT assay. Nox4 knockdown reduced ROS production significantly and suppressed glioblastoma cells proliferation and invasion and tumor associated angiogenesis and increased their radiosensitivity in vitro. Our results indicate that Nox4 may play a crucial role in tumor invasion, angiogenesis, and radioresistance in glioblastoma. Inhibition of Nox4 by lentivirus-mediated shRNA could be a strategy to overcome radioresistance and then improve its therapeutic efficacy for glioblastoma

Local Magnetic Effect-Induced Electron Configuration Regulation: Spin Flipping of Iron Centers for Molecular Catalysis

Efficient oxygen reduction reactions (ORRs) rely on the appropriate chemical adsorption of triplet oxygen (O2) on the surface of the catalyst and rapid conversion to doublet intermediate species, accelerating the ORR process. However, overcoming the energy barrier of this spin-forbidden transition via spin coupling with a catalyst remains a major challenge. Herein, iron phthalocyanine (FePc) was attached to the intrinsic atomic step sites on semiconductor TiO2 nanotubes (FePc@TiO2). The inherent magnetic field of these TiO2 atomic step sites induced a spin flip within the Fe 3d near the Fermi level, resulting in enhanced Fe–O covalent bonding as a result of the spin-antiparallel alignment of the electrons in the Fe 3d and the electrons in the π antibonding orbital of the key oxygen intermediate. This process effectively accelerated the protonation step from *OO to *OOH and activated adsorbed O2 to promote efficient ORR. Compared with the half-wave potential of the original FePc molecule, the half-wave potential of FePc@TiO2 greatly increased by 67 mV, up to 0.921 V in 0.1 M KOH. We confirm that the magnetic flipping of single-molecule magnet catalysts is an effective approach for reducing the spin activation barrier of O2, providing a strategy for the rational design of spin-based catalysts in oxygen-involved reactions for energy conversion devices

MoS₂/NiSe₂/rGO Multiple-Interfaced Sandwich-like Nanostructures as Efficient Electrocatalysts for Overall Water Splitting

Constructing a heterogeneous interface using different components is one of the effective measures to achieve the bifunctionality of nanocatalysts, while synergistic interactions between multiple interfaces can further optimize the performance of single-interface nanocatalysts. The non-precious metal nanocatalysts MoS2/NiSe2/reduced graphene oxide (rGO) bilayer sandwich-like nanostructure with multiple well-defined interfaces is prepared by a simple hydrothermal method. MoS2 and rGO are layered nanostructures with clear boundaries, and the NiSe2 nanoparticles with uniform size are sandwiched between both layered nanostructures. This multiple-interfaced sandwich-like nanostructure is prominent in catalytic water splitting with low overpotential for oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) and almost no degradation in performance after a 20 h long-term reaction. In order to simulate the actual overall water splitting process, the prepared nanostructures are assembled into MoS2/NiSe2/rGO||MoS2/NiSe2/rGO modified two-electrode system, whose overpotential is only 1.52 mV, even exceeded that of noble metal nanocatalyst (Pt/C||RuO2~1.63 mV). This work provides a feasible idea for constructing multi-interface bifunctional electrocatalysts using nanoparticle-doped bilayer-like nanostructures

Interface Modulation for the Heterointegration of Diamond on Si

Abstract Along with the increasing integration density and decreased feature size of current semiconductor technology, heterointegration of the Si‐based devices with diamond has acted as a promising strategy to relieve the existing heat dissipation problem. As one of the heterointegration methods, the microwave plasma chemical vapor deposition (MPCVD) method is utilized to synthesize large‐scale diamond films on a Si substrate, while distinct structures appear at the Si‐diamond interface. Investigation of the formation mechanisms and modulation strategies of the interface is crucial to optimize the heat dissipation behaviors. By taking advantage of electron microscopy, the formation of the epitaxial β‐SiC interlayer is found to be caused by the interaction between the anisotropically sputtered Si and the deposited amorphous carbon. Compared with the randomly oriented β‐SiC interlayer, larger diamond grain sizes can be obtained on the epitaxial β‐SiC interlayer under the same synthesis condition. Moreover, due to the competitive interfacial reactions, the epitaxial β‐SiC interlayer thickness can be reduced by increasing the CH4/H2 ratio (from 3% to 10%), while further increase in the ratio (to 20%) can lead to the broken of the epitaxial relationship. The above findings are expected to provide interfacial design strategies for multiple large‐scale diamond applications