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Search Results: 1 - 10 of 54458 matches for " Guang-Jer Wu "
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Dual Roles of METCAM in the Progression of Different Cancers
Guang-Jer Wu
Journal of Oncology , 2012, DOI: 10.1155/2012/853797
Abstract: METCAM, an integral membrane cell adhesion molecule (CAM) in the Ig-like gene superfamily, is capable of performing typical functions of CAMs, such as mediating cell-cell and cell-extracellular interactions, crosstalk with intracellular signaling pathways, and modulating social behaviors of cells. METCAM is expressed in about nine normal cells/tissues. Aberrant expression of METCAM has been associated with the progression of several epithelial tumors. Further in vitro and in vivo studies show that METCAM plays a dual role in the progression of different tumors. It can promote the malignant progression of several tumors. On the other hand, it can suppress the malignant progression of other tumors. We suggest that the role of METCAM in the progression of different cancer types may be modulated by different intrinsic factors present in different cancer cells and also in different stromal microenvironment. Many possible mechanisms mediated by this CAM during early tumor development and metastasis are suggested. 1. Introduction Human METCAM (huMETCAM), a CAM in the immunoglobulin-like gene superfamily, is an integral membrane glycoprotein. Alternative names for METCAM are MUC18 [1], CD146 [2], MCAM [3], MelCAM [4], A32 [5], and S-endo 1 [6]. To avoid confusion with mucins and to reflect its biological functions, we have renamed MUC18 as METCAM (metastasis CAM), which means an immunoglobulin-like CAM that affects or regulates metastasis, [7]. The huMETCAM has 646 aminoacids that include a N-terminal extracellular domain of 558 aminoacids, which has 28 aminoacids characteristics of a signal peptide sequence at its N-terminus, a transmembrane domain of 24 aminoacids (amino acid number 559–583), and a cytoplasmic domain of 64 aminoacids at the C-terminus. HuMETCAM has eight putative N-glycosylation sites (Asn-X-Ser/Thr), of which six are conserved, and are heavily glycosylated and sialylated resulting in an apparent molecular weight of 113,000–150,000. The extracellular domain of the protein comprises five immunoglobulin-like domains (V-V-C2-C2-C2) [1, 7] and an X domain [7]. The cytoplasmic tail contains peptide sequences that will potentially be phosphorylated by protein kinase A (PKA), protein kinase C (PKC), and casein kinase 2 (CK 2) [1, 7, 8]. My lab has also cloned and sequenced the mouse METCAM (moMETCAM) cDNA, which contains 648 aminoacids with a 76.2% identity with huMETCAM, suggesting that moMETCAM is likely to have biochemical properties and biological functions similar to the human counterpart [9]. The structure of the huMETCAM protein is depicted
Up-regulation of METCAM/MUC18 promotes motility, invasion, and tumorigenesis of human breast cancer cells
Guo-fang Zeng, Shao-xi Cai, Guang-Jer Wu
BMC Cancer , 2011, DOI: 10.1186/1471-2407-11-113
Abstract: Three breast cancer cell lines were used for the tests: one luminal-like breast cancer cell line, MCF7, which did not express any METCAM/MUC18, and two basal-like breast cancer cell lines, MDA-MB-231 and MDA-MB-468, which expressed moderate levels of the protein.MCF7 cells were transfected with the human METCAM/MUC18 cDNA to obtain G418-resistant clones which expressed the protein and were used for testing effects of human METCAM/MUC18 expression on in vitro motility and invasiveness, and in vitro and in vivo tumorigenesis. Both MDA-MB-231 and MDA-MB-468 cells already expressed METCAM/MUC18. They were directly used for in vitro tests in the presence and absence of an anti-METCAM/MUC18 antibody.In MCF7 cells, enforced METCAM/MUC18 expression increased in vitro motility, invasiveness, anchorage-independent colony formation (in vitro tumorigenesis), and in vivo tumorigenesis. In both MDA-MB-231 and MDA-MB-468 cells, the anti-METCAM/MUC18 antibody inhibited both motility and invasiveness. Though both MDA-MB-231 and MDA-MB-468 cells established a disorganized growth in 3D basement membrane culture assay, the introduction of the anti-METCAM/MUC18 antibody completely destroyed their growth in the 3D culture.These findings support the notion that human METCAM/MUC18 expression promotes the progression of human breast cancer cells by increasing their motility, invasiveness and tumorigenesis.METCAM (alternative names as MUC18, CD146, S-endo 1, MelCAM, and MCAM), an integral membrane cell adhesion molecule (CAM) in the Ig-like gene super-family, has an immunoglobulin-like extra-cellular domain and a cytoplasmic domain, which contains five consensus sequences potentially phosphorylated by PKA, PKC, and CK2 [1,2]. Thus METCAM/MUC18 is capable of performing the typical functions of CAMs: adhesion (cell-cell and cell-extracellular matrix interactions), response to extra-cellular stimuli, intra-cellular interactions with cytoskeleton, and cross-talk with signaling pathways. In addit
Determination of inter- and intra-subtype/species varia-tions in polymerase acidic protein from influenza A virus using amino-acid pair predictability  [PDF]
Shaomin Yan, Guang Wu
Journal of Biomedical Science and Engineering (JBiSE) , 2009, DOI: 10.4236/jbise.2009.24041
Abstract: The polymerase acidic protein is an important family of proteins from influenza A virus, which is classified as many different subtypes or spe-cies. Thus, an important question is if these classifications are numerically distinguishable with respect to the polymerase acidic protein. The amino-acid pair predictability was used to transfer 2432 polymerase acidic proteins into 2432 scalar data. The one-way ANOVA found these polymerase acidic proteins distinguish-able in terms of subtypes and species. However, the large residuals in ANOVA suggested a pos-sible large intra-subtype/species variation. Therefore, the inter- and intra-subtype/species variations were studied using the model II ANOVA. The results showed that the in-tra-subtype/species variations accounted most of variation, which was 100% in total for both inter- and intra- subtype/species variations. Our analysis threw lights on the issue of how to de-termine a wide variety of patterns of antigenic variation across space and time, and within and between subtypes as well as hosts.
Application of random walk model to fit temperature in 46 gamma world cities from 1901 to 1998  [PDF]
Shaomin Yan, Guang Wu
Natural Science (NS) , 2010, DOI: 10.4236/ns.2010.212174
Abstract: Very recently, we have applied the random walk model to fit the global temperature anomaly, CRUTEM3. With encouraging results, we apply the random walk model to fit the temperature walk that is the conversion of recorded tem-perature and real recorded temperature in 46 gamma world cities from 1901 to 1998 in this study. The results show that the random walk model can fit both temperature walk and real recorded temperature although the fitted results from other climate models are unavailable for comparison in these 46 cities. Therefore, the random walk model can fit not only the global temperature anomaly, but also the real recorded temperatures in various cities around the world.
Fitting of precipitation in 49 European capitals from 1901 to 1998 using random walk  [PDF]
Shaomin Yan, Guang Wu
Natural Science (NS) , 2011, DOI: 10.4236/ns.2011.36059
Abstract: Mathematical modeling of precipitation is an important step to understand the precipitation patterns, and paves the way to possibly predict the precipitation. In this study, we attempt to use the random walk model to fit the annual precipitation in 49 European capitals from 1901 to 1998. At first, we used the simplest random walk model to fit the precipitation walk, which is the conversion of recorded precipitations into ±1 format, and then we used a more complex random walk model to fit the recorded precipi-tations. The results show that the random walk models can fit both precipitation walk and re-corded precipitation. Thus this study provides a model to describe the precipitation patterns during this period in these cities.
Adaptation in polymerase basic protein 1 family from influenza A virus to climate change  [PDF]
Shaomin Yan, Guang Wu
Health (Health) , 2012, DOI: 10.4236/health.2012.430148
Abstract: Global climate changes affect the functioning of ecosystems, in particular host-pathogen interactions, with major consequences in health ecology, however, it is less addressed how the change in global temperature affects the protein family of influenza virus. In this study, we studied the adaptation of polymerase basic protein 1 (PB1) family from influenza A virus to temperature change. 3841 PB1 proteins sampled from 1956-2011 were quantified by the amino-acid pair predictability and then compared their general changes with the temperature changes (Had-CRUT3v and CRUTEM4v data sets) of corresponding years on a 5? by 5? grid-box basis. Also, point-to-point comparisons were conducted from 1956 to 1998 in all and different species. The results showed that both changes in the temperature and unpredictable portion of PB1 proteins had similar trends from 1956 to 2011, which provides the evidence of virus adaptation at protein level to climate change.
2-Dimensional HP Foldings of Dermaseptin-J2  [PDF]
Shaomin Yan, Guang Wu
Engineering (ENG) , 2013, DOI: 10.4236/eng.2013.510B016

Although the hydrophobic-polar (HP) model is a simple model to study protein folding, it is an approximation to the real-life case. Dermaseptin is a subfamily of frog skin active peptide family, which has various antimicrobial activities, and dermaseptin-J2 is a newly found peptide composed of 26 amino acids. In this study, the 2-dimensional HP model was used to analyze the foldings of dermaseptin-J2 and its nine mutants, which were converted to different HP sequences according to the normalized amino acid hydrophobicity index with respect to pH levels and the conversion of glycine as hydrophobic or polar, and each has 847,288,609,443 possible foldings. The results show that the foldings with minimal energy have different native states, which are chiral and can be numerically distinguished and ranked according to the normalized amino acid hydrophobicity index. The nine mutants of dermaseptin-J2 do not affect the minimal energy but affect their native states at pH 7. The results demonstrate that two pH levels and conversion of glycine as hydrophobic or polar affect the native state and minimal energy, suggesting these are two ways to modify dermaseptin-J2.

Selection of Influential Microfabric Properties of Anisotropic Amphibolite Rocks on Its Uniaxial Compressive Strength (UCS): A Comprehensive Statistical Study  [PDF]
Esamaldeen Ali, Guang Wu
Journal of Applied Mathematics and Physics (JAMP) , 2014, DOI: 10.4236/jamp.2014.212132

Occasionally, in complex inherent characteristics of certain rocks, especially anisotropic rocks it may be difficult to measure the uniaxial compressive strength UCS. However, the use of empirical relationships to evaluate the UCS of rock can be more practical and economical. Consequently, this study carried out to predict UCS from microfabrics properties of banded amphibolite rocks using multiple regression analysis. Based on statistical results, rock microfabric parameters, which adequately represent the UCS of a given rock type have been selected. The results show that grain size, shape factor and quartz content have high significant correlation with UCS at 95% confidence level. From multiple regression model, approximately 84% of the variance of the UCS can be estimated by the linear combination of these three parameters. However, according to model performance criteria: correlation coefficient (R = 0.919), variance account for (VAF = 97%) and root mean square error (RMSE = 4.16) the study clearly indicates that the developed model is reliable to predict the UCS. Finally, this approach can be easily extended to the modeling of rock strength in the absence of adequate geological information or abundant data.

Spontaneous Unfolding and Refolding of Plantaricin α-Helix in Molecular Dynamics Simulation  [PDF]
Shaomin Yan, Guang Wu
Computational Molecular Bioscience (CMB) , 2019, DOI: 10.4236/cmb.2019.91003
Abstract: Antimicrobial peptides are promising therapeutic agents in view of increasing resistance to conventional antibiotics. Antimicrobial peptides usually fold in α-helical, β-sheet, and extended/random-coil structures. The α-helical antimicrobial peptides are often unstructured in aqueous solution but become structured on bacterial membrane. The α-helical structure allows the partitioning into bacterial membrane. Therefore it is important to understand the mechanism of unfolding and refolding of α-helical structure in antimicrobial peptides. It is not very easy to obverse and study the process of unfolding and refolding of α-helical antimicrobial peptides because of their rapidity. Therefore, molecular simulation provides a way to observe and explain this phenomenon. Plantaricin A is a 26 amino-acid antimicrobial pheromone peptide and can spontaneously unfold and refold under physiological condition. This study demonstrated the unfolding and refolding of plantaricin A by means of molecular simulation, and its mechanism was discussed with its implication to the Levinthal paradox.
Correlation of Combined Characters of Amino Acid and Whole Protein with Success Rate of Crystallization of Lactobacillus Proteins  [PDF]
Shaomin Yan, Guang Wu
Journal of Biomedical Science and Engineering (JBiSE) , 2019, DOI: 10.4236/jbise.2019.124017
Abstract: Crystallization of proteins is a very delicate process, which is influenced by many known and unknown factors. Of tested factors, many factors are exclusively related to individual amino-acid characters such as molecular weight or protein characters such as protein length. It is considered necessary to test factors that combine both individual amino-acid characters and protein characters with respect to success rate of crystallization. In this study, two combined characters characterizing individual amino-acid character and protein character, amino acid distribution probability and future composition, were used to correlate the success rate of crystallization of proteins from Lactobacillus via modeling. The results obtained from logistic regression and neural network were compared against the results obtained from each of 533 individual amino-acid characters. This study demonstrated that the combined characters are involved in crystallization process and should be taken into account for predicting the success rate of crystallization process.
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