Wuhan University

About: Wuhan University is a education organization based out in Wuhan, China. It is known for research contribution in the topics: Computer science & Population. The organization has 92849 authors who have published 92882 publications receiving 1691049 citations. The organization is also known as: WHU & Wuhan College.

Single-crystal FeFe(CN)6 nanoparticles: a high capacity and high rate cathode for Na-ion batteries

Abstract: Prussian blue analogues are actively explored as low cost and high capacity cathodes for Na ion batteries; however, their applications are hindered by low capacity utilization and poor cyclability of these compounds. Here we show that this problem can be solved by controlling the purity and crystallinity of the Prussian blue lattices. As a model compound, single-crystal FeIIIFeIII(CN)6 nanoparticles are synthesized and found to have a sufficiently high capacity of 120 mA h g−1, an exceptional rate capability at 20 C and superior cyclability with 87% capacity retention over 500 cycles, showing great promise for Na ion battery applications. More significantly, these results provide a new insight into the intercalation chemistry of Prussian blue analogues and open new perspectives to develop Na storage cathodes for widespread applications of electric energy storage.

Multiscale Dynamic Graph Convolutional Network for Hyperspectral Image Classification

Abstract: Convolutional neural network (CNN) has demonstrated impressive ability to represent hyperspectral images and to achieve promising results in hyperspectral image classification. However, traditional CNN models can only operate convolution on regular square image regions with fixed size and weights, and thus, they cannot universally adapt to the distinct local regions with various object distributions and geometric appearances. Therefore, their classification performances are still to be improved, especially in class boundaries. To alleviate this shortcoming, we consider employing the recently proposed graph convolutional network (GCN) for hyperspectral image classification, as it can conduct the convolution on arbitrarily structured non-Euclidean data and is applicable to the irregular image regions represented by graph topological information. Different from the commonly used GCN models that work on a fixed graph, we enable the graph to be dynamically updated along with the graph convolution process so that these two steps can be benefited from each other to gradually produce the discriminative embedded features as well as a refined graph. Moreover, to comprehensively deploy the multiscale information inherited by hyperspectral images, we establish multiple input graphs with different neighborhood scales to extensively exploit the diversified spectral–spatial correlations at multiple scales. Therefore, our method is termed multiscale dynamic GCN (MDGCN). The experimental results on three typical benchmark data sets firmly demonstrate the superiority of the proposed MDGCN to other state-of-the-art methods in both qualitative and quantitative aspects.

Making a tooth: growth factors, transcription factors, and stem cells.

Abstract: Mammalian tooth development is largely dependent on sequential and reciprocal epithelial-mesenchymal interactions. These processes involve a series of inductive and permissive interactions that result in the determination, differentiation, and organization of odontogenic tissues. Multiple signaling molecules, including BMPs, FGFs, Shh, and Wnt proteins, have been implicated in mediating these tissue interactions. Transcription factors participate in epithelial-mesenchymal interactions via linking the signaling loops between tissue layers by responding to inductive signals and regulating the expression of other signaling molecules. Adult stem cells are highly plastic and multipotent. These cells including dental pulp stem cells and bone marrow stromal cells could be reprogrammed into odontogenic fate and participated in tooth formation. Recent progress in the studies of molecular basis of tooth development, adult stem cell biology, and regeneration will provide fundamental knowledge for the realization of human tooth regeneration in the near future.

Eleven faces of coronavirus disease 2019.

Abstract: BACKGROUND AND AIMS: The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has recently spread worldwide and been declared a pandemic. We aim to describe here the various clinical presentations of this disease by examining eleven cases. METHODS: Electronic medical records of 11 patients with COVID-19 were collected, and demographics, clinical manifestations, outcomes, key laboratory results, and radiological images are discussed. RESULTS: The clinical course of the eleven cases demonstrated the complexity of the COVID-19 profile with different clinical presentations. Clinical manifestations range from asymptomatic cases to patients with mild and severe symptoms, with or without pneumonia. Laboratory detection of the viral nucleic acid can yield false-negative results, and serological testing of virus-specific IgG and IgM antibodies should be used as an alternative for diagnosis. Patients with common allergic diseases did not develop distinct symptoms and severe courses. Cases with a pre-existing condition of chronic obstructive pulmonary disease or complicated with a secondary bacterial pneumonia were more severe. CONCLUSION: All different clinical characteristics of COVID-19 should be taken into consideration to identify patients that need to be in strict quarantine for the efficient containment of the pandemic.

Human telomeric DNA forms parallel-stranded intramolecular G-quadruplex in K+ solution under molecular crowding condition

Abstract: The G-rich strand of human telomeric DNA can fold into a four-stranded structure called G-quadruplex and inhibit telomerase activity that is expressed in 85-90% tumor cells. For this reason, telomere quadruplex is emerging as a potential therapeutic target for cancer. Information on the structure of the quadruplex in the physiological environment is important for structure-based drug design targeting the quadruplex. Recent studies have raised significant controversy regarding the exact structure of the quadruplex formed by human telomeric DNA in a physiological relevant environment. Studies on the crystal prepared in K+ solution revealed a distinct propeller-shaped parallel-stranded conformation. However, many later works failed to confirm such structure in physiological K+ solution but rather led to the identification of a different hybrid-type mixed parallel/antiparallel quadruplex. Here we demonstrate that human telomere DNA adopts a parallel-stranded conformation in physiological K+ solution under molecular crowding conditions created by PEG. At the concentration of 40% (w/v), PEG induced complete structural conversion to a parallel-stranded G-quadruplex. We also show that the quadruplex formed under such a condition has unusual stability and significant negative impact on telomerase processivity. Since the environment inside cells is molecularly crowded, our results obtained under the cell mimicking condition suggest that the parallel-stranded quadruplex may be the more favored structure under physiological conditions, and drug design targeting the human telomeric quadruplex should take this into consideration.