Identifying HER2 Inhibitors from Natural Products Database

The relationship between abnormal HER2 expression and cancer is important in cancer therapeutics. Formation and spread of cancer cells may be restricted by inhibiting HER2. We conducted ligand-based and structure-based studies to assess the potency of natural compounds as potential HER2 inhibitors. Multiple linear regression (MLR) and support vector machine (SVM) models were constructed to predict biological activities of natural compounds, and molecular dynamics (MD) was used to assess their stability with HER2 under a dynamic environment. Predicted bioactivities of the natural compounds ranged from 6.014–9.077 using MLR (r[superscript 2] = 0.7954) and 5.122–6.950 using SVM (r[superscript 2] = 0.8620). Both models were in agreement and suggest bioactivity based on candidate structure. Conformation changes caused by MD favored the formation of stabilizing H-bonds. All candidates had higher stability than Lapinatib, which may be due to the number and spatial distribution of additional H-bonds and hydrophobic interactions. Amino acids Lys724 and Lys736 are critical for binding in HER2, and Thr798, Cys805, and Asp808 are also important for increased stability. Candidates may block the entrance to the ATP binding site located within the inner regions and prevent downstream activation of HER2. Our multidirectional approach indicates that the natural compounds have good ligand efficacy in addition to stable binding affinities to HER2, and should be potent candidates of HER2 inhibitors. With regard to drug design, designing HER2 inhibitors with carboxyl or carbonyl groups available for H-bond formation with Lys724 and Lys736, and benzene groups for hydrophobic contact with Cys805 may improve protein-ligand stability.National Science Council of Taiwan (NSC 99-2221-E-039-013-)Committee on Chinese Medicine and Pharmacy (CCMP100-RD-030)China Medical University and Asia University (CMU98-TCM)China Medical University and Asia University (CMU99-TCM)China Medical University and Asia University (CMU99-S-02)China Medical University and Asia University (CMU99-ASIA-25)China Medical University and Asia University (CMU99-ASIA-26)China Medical University and Asia University (CMU99-ASIA-27)China Medical University and Asia University (CMU99-ASIA-28)Taiwan Department of Health. Clinical Trial and Research Center of Excellence (DOH100-TD-B-111-004)Taiwan Department of Health. Cancer Research Center of Excellence (DOH100-TD-C-111-005

Guaiacol producing Alicyclobacillus spp. differentiation, detection, and control

Alicyclobacillus spp. are thermoacidophilic sporeformers that have significant impact on the pasteurized juice industry. Better detection and control methods are needed to minimize Alicyclobacillus related spoilage. The objective of this research is to improve existing detection and control methods by (1) the investigation of basic characteristics of guaiacol producing Alicyclobacillus and development of a novel detection method; and (2) the evaluation of Alicyclobacillus control method during storage and processing. Differences in growth characteristics were observed but not significant between guaiacol producing and non-guaiacol producing Alicyclobacillus. Enzyme and carbohydrate utilization profiles were variable depending on test isolates. Guaiacol formation was detectable within 12 h at 43 C and further accelerated under microaerophilic conditions. The newly developed SK2 agar provides selective identification of guaiacol producing Alicyclobacillus with a 95% correct identification rate. SK2 agar is the first known media providing selective isolation of guaiacol producing Alicyclobacillus. The effectiveness of aqueous and gas chlorine dioxide against Alicyclobacillus spores has been demonstrated. Greater than five log reductions were observed following 1 min and 1 h exposures to 120 ppm ClO2(aq) and 4.32 ppm ClO2(g), respectively

A Robust RGBD Slam System for 3D Environment with Planar Surfaces

With the increasing popularity of RGB-depth (RGB-D) sensors such as the Microsoft Kinect, there have been much research on capturing and reconstructing 3D environments using a movable RGB-D sensor. The key process behind these kinds of simultaneous location and mapping (SLAM) systems is the iterative closest point or ICP algorithm, which is an iterative algorithm that can estimate the rigid movement of the camera based on the captured 3D point clouds. While ICP is a well-studied algorithm, it is problematic when it is used in scanning large planar regions such as wall surfaces in a room. The lack of depth variations on planar surfaces makes the global alignment an ill-conditioned problem. In this paper, we present a novel approach for registering 3D point clouds by combining both color and depth information. Instead of directly searching for point correspondences among 3D data, the proposed method first extracts features from the RGB images, and then back-projects the features to the 3D space to identify more reliable correspondences. These color correspondences form the initial input to the ICP procedure which then proceeds to refine the alignment. Experimental results show that our proposed approach can achieve better accuracy than existing SLAMs in reconstructing indoor environments with large planar surfaces

Reconstructing the properties of dark energy from recent observations

We explore the properties of dark energy from recent observational data, including the Gold Sne Ia, the baryonic acoustic oscillation peak from SDSS, the CMB shift parameter from WMAP3, the X-ray gas mass fraction in cluster and the Hubble parameter versus redshift. The $\Lambda CDM$ model with curvature and two parameterized dark energy models are studied. For the $\Lambda CDM$ model, we find that the flat universe is consistent with observations at the $1\sigma$ confidence level and a closed universe is slightly favored by these data. For two parameterized dark energy models, with the prior given on the present matter density, $\Omega_{m0}$, with $\Omega_{m0}=0.24$, $\Omega_{m0}=0.28$ and $\Omega_{m0}=0.32$, our result seems to suggest that the trend of $\Omega_{m0}$ dependence for an evolving dark energy from a combination of the observational data sets is model-dependent.Comment: 16 pages, 15 figures, To appear in JCA

A Fast and Robust Extrinsic Calibration for RGB-D Camera Networks

From object tracking to 3D reconstruction, RGB-Depth (RGB-D) camera networks play an increasingly important role in many vision and graphics applications. Practical applications often use sparsely-placed cameras to maximize visibility, while using as few cameras as possible to minimize cost. In general, it is challenging to calibrate sparse camera networks due to the lack of shared scene features across different camera views. In this paper, we propose a novel algorithm that can accurately and rapidly calibrate the geometric relationships across an arbitrary number of RGB-D cameras on a network. Our work has a number of novel features. First, to cope with the wide separation between different cameras, we establish view correspondences by using a spherical calibration object. We show that this approach outperforms other techniques based on planar calibration objects. Second, instead of modeling camera extrinsic calibration using rigid transformation, which is optimal only for pinhole cameras, we systematically test different view transformation functions including rigid transformation, polynomial transformation and manifold regression to determine the most robust mapping that generalizes well to unseen data. Third, we reformulate the celebrated bundle adjustment procedure to minimize the global 3D reprojection error so as to fine-tune the initial estimates. Finally, our scalable client-server architecture is computationally efficient: the calibration of a five-camera system, including data capture, can be done in minutes using only commodity PCs. Our proposed framework is compared with other state-of-the-arts systems using both quantitative measurements and visual alignment results of the merged point clouds

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

Identification of Potent EGFR Inhibitors from TCM Database@Taiwan

Overexpression of epidermal growth factor receptor (EGFR) has been associated with cancer. Targeted inhibition of the EGFR pathway has been shown to limit proliferation of cancerous cells. Hence, we employed Traditional Chinese Medicine Database (TCM Database@Taiwan) (http://tcm.cmu.edu.tw) to identify potential EGFR inhibitor. Multiple Linear Regression (MLR), Support Vector Machine (SVM), Comparative Molecular Field Analysis (CoMFA), and Comparative Molecular Similarities Indices Analysis (CoMSIA) models were generated using a training set of EGFR ligands of known inhibitory activities. The top four TCM candidates based on DockScore were 2-O-caffeoyl tartaric acid, Emitine, Rosmaricine, and 2-O-feruloyl tartaric acid, and all had higher binding affinities than the control Iressa®. The TCM candidates had interactions with Asp855, Lys716, and Lys728, all which are residues of the protein kinase binding site. Validated MLR (r² = 0.7858) and SVM (r² = 0.8754) models predicted good bioactivity for the TCM candidates. In addition, the TCM candidates contoured well to the 3D-Quantitative Structure-Activity Relationship (3D-QSAR) map derived from the CoMFA (q² = 0.721, r² = 0.986) and CoMSIA (q² = 0.662, r² = 0.988) models. The steric field, hydrophobic field, and H-bond of the 3D-QSAR map were well matched by each TCM candidate. Molecular docking indicated that all TCM candidates formed H-bonds within the EGFR protein kinase domain. Based on the different structures, H-bonds were formed at either Asp855 or Lys716/Lys728. The compounds remained stable throughout molecular dynamics (MD) simulation. Based on the results of this study, 2-O-caffeoyl tartaric acid, Emitine, Rosmaricine, and 2-O-feruloyl tartaric acid are suggested to be potential EGFR inhibitors.National Science Council of Taiwan (NSC 99-2221-E-039-013-)Committee on Chinese Medicine and Pharmacy (CCMP100-RD-030)China Medical University (CMU98-TCM)China Medical University (CMU99-TCM)China Medical University (CMU99-S-02)China Medical University (CMU99-ASIA-25)China Medical University (CMU99-ASIA-26)China Medical University (CMU99-ASIA-27)China Medical University (CMU99-ASIA-28)Asia UniversityTaiwan Department of Health. Clinical Trial and Research Center of Excellence (DOH100-TD-B-111-004)Taiwan Department of Health. Cancer Research Center of Excellence (DOH100-TD-C-111-005

Genomewide association study of leprosy.

BACKGROUND: The narrow host range of Mycobacterium leprae and the fact that it is refractory to growth in culture has limited research on and the biologic understanding of leprosy. Host genetic factors are thought to influence susceptibility to infection as well as disease progression. METHODS: We performed a two-stage genomewide association study by genotyping 706 patients and 1225 controls using the Human610-Quad BeadChip (Illumina). We then tested three independent replication sets for an association between the presence of leprosy and 93 single-nucleotide polymorphisms (SNPs) that were most strongly associated with the disease in the genomewide association study. Together, these replication sets comprised 3254 patients and 5955 controls. We also carried out tests of heterogeneity of the associations (or lack thereof) between these 93 SNPs and disease, stratified according to clinical subtype (multibacillary vs. paucibacillary). RESULTS: We observed a significant association (P<1.00x10(-10)) between SNPs in the genes CCDC122, C13orf31, NOD2, TNFSF15, HLA-DR, and RIPK2 and a trend toward an association (P=5.10x10(-5)) with a SNP in LRRK2. The associations between the SNPs in C13orf31, LRRK2, NOD2, and RIPK2 and multibacillary leprosy were stronger than the associations between these SNPs and paucibacillary leprosy. CONCLUSIONS: Variants of genes in the NOD2-mediated signaling pathway (which regulates the innate immune response) are associated with susceptibility to infection with M. leprae

Seismic Stratigraphic Features of the Late Miocene-Present Unconformities and Related Seismic Units, Northern Offshore Taiwan

We investigate the seismic stratigraphic features offshore northern Taiwan by using newly collected multichannel seismic data. Two significant regional unconformities U1 and U2 have been identified, which further subdivide the sedimentary sequence into three seismic units as SU I, SU II, and SU III. The lowermost seismic unit SU I is a pre-late Miocene sequence, while the middle and upper seismic unit SU II and SU III result from the interactions between the rapid fault-controlled subsidence and the stable thermal-controlled subsidence. We consider that the present-day offshore northern Taiwan is under a post-collisional state and the unconformities U1 and U2 represent a response to the mountain collapse and to the cessation of the regional volcano-tectonic activities. It is not until 1.5 Ma that northern offshore Taiwan became a post-collisional basin and started to receive sediments, with a rapid fault-controlled subsidence. Afterward, the basin became dominated by a stable thermal-controlled subsidence at 0.2 Ma. Although the main volcano-tectonic activities in the northern offshore Taiwan are ceased, modern geophysical and geochemical investigations have suggested that the tectonism and the volcanism are still active and represent potential threatening geohazard