Deletion of the thrombin cleavage domain of osteopontin mediates breast cancer cell adhesion, proteolytic activity, tumorgenicity, and metastasis

<p>Abstract</p> <p>Background</p> <p>Osteopontin (OPN) is a secreted phosphoprotein often overexpressed at high levels in the blood and primary tumors of breast cancer patients. OPN contains two integrin-binding sites and a thrombin cleavage domain located in close proximity to each other.</p> <p>Methods</p> <p>To study the role of the thrombin cleavage site of OPN, MDA-MB-468 human breast cancer cells were stably transfected with either wildtype OPN (468-OPN), mutant OPN lacking the thrombin cleavage domain (468-ΔTC) or an empty vector (468-CON) and assessed for <it>in vitro </it>and <it>in vivo </it>functional differences in malignant/metastatic behavior.</p> <p>Results</p> <p>All three cell lines were found to equivalently express thrombin, tissue factor, CD44, αvβ5 integrin and β1 integrin. Relative to 468-OPN and 468-CON cells, 468-ΔTC cells expressing OPN with a deleted thrombin cleavage domain demonstrated decreased cell adhesion (p < 0.001), decreased mRNA expression of MCAM, maspin and TRAIL (p < 0.01), and increased uPA expression and activity (p < 0.01) <it>in vitro</it>. Furthermore, injection of 468-ΔTC cells into the mammary fat pad of nude mice resulted in decreased primary tumor latency time (p < 0.01) and increased primary tumor growth and lymph node metastatic burden (p < 0.001) compared to 468-OPN and 468-CON cells.</p> <p>Conclusions</p> <p>The results presented here suggest that expression of thrombin-uncleavable OPN imparts an early tumor formation advantage as well as a metastatic advantage for breast cancer cells, possibly due to increased proteolytic activity and decreased adhesion and apoptosis. Clarification of the mechanisms responsible for these observations and the translation of this knowledge into the clinic could ultimately provide new therapeutic opportunities for combating breast cancer.</p

Utilization of Recently Enhanced Simulation Tools and Empirical Ground Motion Databases to Improve Ground Motion Prediction Capabilities

My research was strongly influenced by ongoing Next Generation Attenuation projects (NGA), which is sponsored by Pacific Earthquake Engineering Research Center (PEER). This far, PEER has sponsored two landmark national projects for developing NGA relationship in active tectonic regions. The result of these two projects will be incorporated into national hazard maps developed by United States Geological Survey (USGS). However, since the national seismic hazard maps include stable continental regions and subduction zones, it is desired to ex- tend those studies to other tectonic regions. NGA-Subduction project has recently been initiated to address Subduction Zones (SZ).For this project, I collaborated with PEER researcher for processing the data of main shock recordings of the Tohoku earthquake. I also analyzed the data to evaluate the implications of this data set with respect to magnitude-, distance-, and site-scaling in existing GMPEs for SZs. The Mw = 9.0 Tohoku-oki Japan earthquake produced approximately 2000 ground motion recordings. We consider 1238 three-component accelerograms corrected with component-specific low-cut filters. The recordings have rupture distances between 44 and 1000km, time-veraged shear wave velocities of Vs30 = 90 to 1900ms−1, and usable response spectral periods of 0.01 to &gt; 10 s. The data support the notion that the increase of ground motions with magnitude saturates at large magnitudes. High frequency ground motions demonstrate faster attenuation with distance in backarc than in forearc regions, which is only captured by one of the four considered ground motion prediction equations for subduction earthquakes. Recordings within 100 km of the fault are used to estimate event terms, which are generally positive (indicating model under-prediction) at short periods and zero or negative (over-prediction) at long periods. We find site amplification to scale minimally with Vs30 at high frequencies, in contrast with other active tectonic regions, but to scale strongly with Vs30 at low frequencies.It is envisioned that the research outlined herein could help earthquake engi- neering community to design infrastructures which are more resistant to earth- quakes by improving ground motion prediction capabilities

Scattering of mechanical waves from the perspective of open systems

In this paper, we consider the problem of mechanical wave scattering from a spatially finite system into an infinite surrounding environment. The goal is to illuminate why the scattering spectrum undergoes peaks and dips (resonances) at specific locations and how these locations connect to the vibrational properties of the scatterer. The resonance locations are connected to the eigenvalues of a finite dimensional effective operator, $H_{eff}$, corresponding to the scatterer. The developments are presented from the perspective of open systems, which seeks to convert the infinite dimensional scattering problem (scatterer+environment) into a finite dimensional effective problem involving only the finite scatterer. This is achieved through a projection operator formalism which allows us to formally calculate $H_{eff}$. An interesting corollary of our analysis is the deep connection between resonance locations in the scattering spectrum and the eigenfrequencies of the scatterer under Neumann boundary condition. We bring out this point further by considering 3D scattering from an elastic shell, connecting our results to classical results in acousto-elastic scattering theory

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هدف اصلی پژوهش حاضر پیشبینی عملکرد تحصیلی بر اساس خودکارآمدی تحصیلی، خودنظمدهیفراشناختی و تفکر انتقادی بود. بدین منظور 294 نفر از دانشآموزان مقطع دبیرستان به روش نمونهگیریتصادفی خوشهای چندمرحلهای انتخاب شدند. برای سنجش متغیرهای پژوهش از سه خردهمقیاسپرسشنامهی راهبردهای انگیزشی برای یادگیری (پینتریج و دگروت، 1990 ) استفاده شد. دادهها با استفادهاز شاخصهای آمار توصیفی، ضریب همبستگی پیرسون و تحلیل رگرسیون چندگانه به شیوه ورود تحلیلشدند. نتایج پژوهش نشان داد که بین نمره متغیرهای خودکارآمدی تحصیلی، خودنظمدهی فراشناختی وتفکر انتقادی با نمرة عملکرد تحصیلی رابطۀ مستقیم و معنادار وجود دارد. همچنین، نتایج تحلیلرگرسیون نشان داد که متغیرهای مذکور میتوانند درمجموع 16 درصد از واریانس متغیر عملکرد تحصیلیرا تبیین نمایند و خودکارآمدی تحصیلی بهترین پیشبینیکنندة عملکرد تحصیلی میباشد

Cluster-based network model for time-course gene expression data

We propose a model-based approach to unify clustering and network modeling using time-course gene expression data. Specifically, our approach uses a mixture model to cluster genes. Genes within the same cluster share a similar expression profile. The network is built over cluster-specific expression profiles using state-space models. We discuss the application of our model to simulated data as well as to time-course gene expression data arising from animal models on prostate cancer progression. The latter application shows that with a combined statistical/bioinformatics analyses, we are able to extract gene-to-gene relationships supported by the literature as well as new plausible relationships