Exploring the Role of Calcium Ions in Biological Systems by Computational Prediction and Protein Engineering

Ca2+, a signal for death and life, is closely involved in the regulation of numerous important cellular events. Ca2+ carries out its function through its binding to Ca2+-receptors or Ca2+-binding proteins. The EF-hand protein, with a helix-loop-helix Ca2+-binding motif, constitutes one of the largest protein families. To facilitate our understanding of the role of Ca2+ in biological systems (denoted as calciomics) using genomic information, an improved pattern search method (http://www.chemistry.gsu.edu/faculty/Yang/Calciomics.htm) for the identification of EF-hand and EF-like Ca2+-binding proteins was developed. This fast and robust method allows us to analyze putative EF-hand proteins at the genome-wide level and further visualize the evolutionary scenario of the EF-hand protein family. This prediction method further enables us to locate a putative viral EF-hand Ca2+-binding motif within the rubella virus nonstructural protease that cleaves the nonstructural protein precursor into two active replicase components. A novel grafting approach has been used to probe the metal-binding properties of this motif by engineering the predicted 12-residue Ca2+-coordinating loop into a non-Ca2+-binding scaffold protein, CD2 domain 1. Structural and conformational studies were further performed on a purified, bacterially-expressed NS protease minimal metal-binding domain spanning the Zn2+- and EF-hand Ca2+-binding motif. It was revealed that Ca2+ binding induced local conformational changes and increased thermal stability. Furthermore, functional studies were carried out using RUB infectious cDNA clone and replicon constructs. Our studies have shown that the Ca2+ binding loop played a structural role in the NS protease and was specifically required for optimal stability under physiological conditions. In addition, we have predicted and characterized a calmodulin-binding domain in the gap junction proteins connexin43 and connexin44. Peptides encompassing the CaM binding motifs were synthesized and their ability to bind CaM was determined using various biophysical approaches. Transient expression in HeLa cells of two mutant Cx43-EYFP constructs without the putative CaM-binding site eliminated the Ca2+-dependent inhibition of gap junction permeability. These results provide the first direct evidence that CaM binds to a specific region of the ubiquitous gap junction protein Cx43 and Cx44 in a Ca2+-dependent manner, providing a molecular basis for the well-characterized Ca2+-dependent inhibition of Cx43-containing gap junctions

Evolution and control of the phase competition morphology in a manganite film

The competition among different phases in perovskite manganites is pronounced since their energies are very close under the interplay of charge, spin, orbital and lattice degrees of freedom. To reveal the roles of underlying interactions, many efforts have been devoted towards directly imaging phase transitions at microscopic scales. Here we show images of the charge-ordered insulator (COI) phase transition from a pure ferromagnetic metal with reducing field or increasing temperature in a strained phase-separated manganite film, using a home-built magnetic force microscope. Compared with the COI melting transition, this reverse transition is sharp, cooperative and martensitic-like with astonishingly unique yet diverse morphologies. The COI domains show variable-dimensional growth at different temperatures and their distribution can illustrate the delicate balance of the underlying interactions in manganites. Our findings also display how phase domain engineering is possible and how the phase competition can be tuned in a controllable manner.Comment: Published versio

Giant congenital diaphragmatic hernia in an adult

Bochdalek hernia is the most common type of congenital diaphragmatic hernia. It appears frequently in infants but rarely in adults. We present the case of a 50-year-old female han patient with tremendous left-sided congenital posterolateral diaphragmatic hernia (Bochdalek hernia) who also has a pair of supernumerary breasts and pulmonary hypoplasia of the lower-left lobe. The patient had an experience of misdiagnosis and she was treated for bronchitis for one year until being admitted to our hospital. This case study emphasizes the rare presentation of Bochdalek hernia in adults and the necessity of high clinical attention to similar cases

Fibroblast phenotypes in different lung diseases

BACKGROUND: The “seed and soil” hypothesis emphasizes the importance of interactions between tumor cells and their microenvironment. CAFs (Cancer associated fibroblasts) are important components of the tumor microenvironment. They were widely involved in cancer cells growth and metastasis. Fibroblasts may also play a role in inflammatory disease. The phenotype conversion of fibroblasts in lung diseases has not been investigated previously. We hypothesized that fibroblasts phenotypes may vary among different types of lung disease. METHODS: The study included six types of lung tissues, ranging from normal lung to lung adenocarcinoma with lymphatic metastasis. Para-carcinoma tissues which were 2-cm-away from the tumor focus were also included in the analysis. The expression of target proteins including alpha-SMA (smooth muscle actin), FAP (fibroblast activation protein), vimentin, E-cadherin, and CK-19 (cytokeratin-19) were examined by immunohistochemistry. TGF-beta(transforming growth factor) and Twist were detected simultaneously in all samples. RESULTS: A progressive increase in the levels of alpha-SMA, vimentin and CK-19 was observed in correlation to the degree of malignancy from normal lung tissue to lung adenocarcinoma with lymphatic metastasis, whereas E-cadherin expression showed the opposite trend. TGF-beta and Twist were detected in cancer tissues and inflammatory pseudotumors. None of the proteins were detected in para-carcinoma tissues. CONCLUSIONS: Fibroblast phenotypes varied according to the type and degree of lung malignancy and fibroblasts phenotypic conversion occurs as a gradual process with specific spatiotemporal characteristics. Similar fibroblast phenotypes in inflammatory diseases and cancer tissues suggested a correlation between inflammation and cancer and implied a common mechanism underlying the formation of fibroblasts in inflammatory diseases and lung cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13019-014-0147-z) contains supplementary material, which is available to authorized users

Deep Imaging of the HCG 95 Field.I.Ultra-diffuse Galaxies

We present a detection of 89 candidates of ultra-diffuse galaxies (UDGs) in a 4.9 degree$^2$ field centered on the Hickson Compact Group 95 (HCG 95) using deep $g$- and $r$-band images taken with the Chinese Near Object Survey Telescope. This field contains one rich galaxy cluster (Abell 2588 at $z$=0.199) and two poor clusters (Pegasus I at $z$=0.013 and Pegasus II at $z$=0.040). The 89 candidates are likely associated with the two poor clusters, giving about 50 $-$ 60 true UDGs with a half-light radius $r_{\rm e} > 1.5$ kpc and a central surface brightness $\mu(g,0) > 24.0$ mag arcsec$^{-2}$. Deep $z$'-band images are available for 84 of the 89 galaxies from the Dark Energy Camera Legacy Survey (DECaLS), confirming that these galaxies have an extremely low central surface brightness. Moreover, our UDG candidates are spread over a wide range in $g-r$ color, and $\sim$26% are as blue as normal star-forming galaxies, which is suggestive of young UDGs that are still in formation. Interestingly, we find that one UDG linked with HCG 95 is a gas-rich galaxy with H I mass $1.1 \times 10^{9} M_{\odot}$ detected by the Very Large Array, and has a stellar mass of $M_\star \sim 1.8 \times 10^{8}$ $M_{\odot}$. This indicates that UDGs at least partially overlap with the population of nearly dark galaxies found in deep H I surveys. Our results show that the high abundance of blue UDGs in the HCG 95 field is favored by the environment of poor galaxy clusters residing in H I-rich large-scale structures.Comment: Published in Ap

Synthesis and Biological Evaluation of Ezetimibe Analogs as Possible Cholesterol Absorption Inhibitors

In order to investigate the SAR of Ezetimibe analogs for cholesterol absorption inhibitions, amide group and electron-deficient pyridine ring were introduced to the C-(3) carbon chain of Ezetimibe. Eight new derivatives of the 2-azetidinone cholesterol absorption inhibitors have been synthesized, and all of them were enantiomerically pure. All the new compounds were evaluated for their activity to inhibit cholesterol absorption in hamsters, and most of them showed comparable effects in lowering the levels of total cholesterol in the serum

Curriculum Proximal Policy Optimization with Stage-Decaying Clipping for Self-Driving at Unsignalized Intersections

Unsignalized intersections are typically considered as one of the most representative and challenging scenarios for self-driving vehicles. To tackle autonomous driving problems in such scenarios, this paper proposes a curriculum proximal policy optimization (CPPO) framework with stage-decaying clipping. By adjusting the clipping parameter during different stages of training through proximal policy optimization (PPO), the vehicle can first rapidly search for an approximate optimal policy or its neighborhood with a large parameter, and then converges to the optimal policy with a small one. Particularly, the stage-based curriculum learning technology is incorporated into the proposed framework to improve the generalization performance and further accelerate the training process. Moreover, the reward function is specially designed in view of different curriculum settings. A series of comparative experiments are conducted in intersection-crossing scenarios with bi-lane carriageways to verify the effectiveness of the proposed CPPO method. The results show that the proposed approach demonstrates better adaptiveness to different dynamic and complex environments, as well as faster training speed over baseline methods.Comment: 7 pages, 4 figure

Numerical Approximation of Stochastic Time-Fractional Diffusion

We develop and analyze a numerical method for stochastic time-fractional diffusion driven by additive fractionally integrated Gaussian noise. The model involves two nonlocal terms in time, i.e., a Caputo fractional derivative of order $\alpha\in(0,1)$, and fractionally integrated Gaussian noise (with a Riemann-Liouville fractional integral of order $\gamma \in[0,1]$ in the front). The numerical scheme approximates the model in space by the standard Galerkin method with continuous piecewise linear finite elements and in time by the classical Gr\"unwald-Letnikov method, and the noise by the $L^2$-projection. Sharp strong and weak convergence rates are established, using suitable nonsmooth data error estimates for the deterministic counterpart. One- and two-dimensional numerical results are presented to support the theoretical findings

Shape-Aware Fine-Grained Classification of Erythroid Cells

Fine-grained classification and counting of bone marrow erythroid cells are vital for evaluating the health status and formulating therapeutic schedules for leukemia or hematopathy. Due to the subtle visual differences between different types of erythroid cells, it is challenging to apply existing image-based deep learning models for fine-grained erythroid cell classification. Moreover, there is no large open-source datasets on erythroid cells to support the model training. In this paper, we introduce BMEC (Bone Morrow Erythroid Cells), the first large fine-grained image dataset of erythroid cells, to facilitate more deep learning research on erythroid cells. BMEC contains 5,666 images of individual erythroid cells, each of which is extracted from the bone marrow erythroid cell smears and professionally annotated to one of the four types of erythroid cells. To distinguish the erythroid cells, one key indicator is the cell shape which is closely related to the cell growth and maturation. Therefore, we design a novel shape-aware image classification network for fine-grained erythroid cell classification. The shape feature is extracted from the shape mask image and aggregated to the raw image feature with a shape attention module. With the shape-attended image feature, our network achieved superior classification performance (81.12\% top-1 accuracy) on the BMEC dataset comparing to the baseline methods. Ablation studies also demonstrate the effectiveness of incorporating the shape information for the fine-grained cell classification. To further verify the generalizability of our method, we tested our network on two additional public white blood cells (WBC) datasets and the results show our shape-aware method can generally outperform recent state-of-the-art works on classifying the WBC. The code and BMEC dataset can be found on https://github.com/wangye8899/BMEC