Georgetown University

About: Georgetown University is a education organization based out in Washington D.C., District of Columbia, United States. It is known for research contribution in the topics: Population & Cancer. The organization has 23377 authors who have published 43718 publications receiving 1748598 citations. The organization is also known as: GU & Georgetown.

Direct interaction of a ligand for the erbB2 oncogene product with the EGF receptor and p185erbB2.

Abstract: The erbB2 oncogene encodes a 185-kilodalton transmembrane protein whose sequence is similar to the epidermal growth factor receptor (EGFR). A 30-kilodalton factor (gp30) secreted from MDA-MB-231 human breast cancer cells was shown to be a ligand for p185erbB2. An antibody to EGFR abolished the tyrosine phosphorylation induced by EGF and transforming growth factor-alpha (TGF-alpha) but only partially blocked that produced by gp30 in SK-BR-3 breast cancer cells. In two cell lines that overexpress erbB2 but do not expresss EGFR (MDA-MB-453 breast cancer cells and a Chinese hamster ovary cell line that had been transfected with erbB2), phosphorylation of p185erbB2 was induced only by gp30. The gp30 specifically inhibited the growth of cells that overexpressed p185erbB2. An antibody to EGFR had no effect on the inhibition of SK-BR-3 cell colony formation obtained with gp30. Thus, it appeared that gp30 interacted directly with the EGFR and erbB2. Direct binding of gp30 to p185erbB2 was confirmed by binding competition experiments, where gp30 was found to displace the p185erbB2 binding of a specific antibody to p185erbB2. The evidence described here suggests that gp30 is a ligand for p185erbB2.

Artificial convolution neural network techniques and applications for lung nodule detection

Abstract: We have developed a double-matching method and an artificial visual neural network technique for lung nodule detection. This neural network technique is generally applicable to the recognition of medical image pattern in gray scale imaging. The structure of the artificial neural net is a simplified network structure of human vision. The fundamental operation of the artificial neural network is local two-dimensional convolution rather than full connection with weighted multiplication. Weighting coefficients of the convolution kernels are formed by the neural network through backpropagated training. In addition, we modeled radiologists' reading procedures in order to instruct the artificial neural network to recognize the image patterns predefined and those of interest to experts in radiology. We have tested this method for lung nodule detection. The performance studies have shown the potential use of this technique in a clinical setting. This program first performed an initial nodule search with high sensitivity in detecting round objects using a sphere template double-matching technique. The artificial convolution neural network acted as a final classifier to determine whether the suspected image block contains a lung nodule. The total processing time for the automatic detection of lung nodules using both prescan and convolution neural network evaluation was about 15 seconds in a DEC Alpha workstation.

Magnetic resonance studies of intramuscular interferon β-1a for relapsing multiple sclerosis

Abstract: The Multiple Sclerosis Collaborative Research Group trial was a double-blind, randomized, multicenter, phase III, placebo-controlled study of interferon beta-1a (IFNbeta-1a; AVONEX) in relapsing forms of multiple sclerosis. Initial magnetic resonance imaging results have been published; this report provides additional results. Treatment with IFNbeta-1a, 30 microg once weekly by intramuscular injection, resulted in a significant decrease in the number of new, enlarging, and new plus enlarging T2 lesions over 2 years. The median increase in T2 lesion volume in placebo and IFNbeta-1a patients was 455 and 152 mm3, respectively, at 1 year and 1,410 and 628 mm3 at 2 years, although the treatment group differences did not reach statistical significance. For active patients, defined as those with gadolinium enhancement at baseline, the median change in T2 lesion volume in placebo and IFNbeta-1a patients was 1,578 and -12 mm3 and 2,980 and 1,285 mm3 at 1 and 2 years, respectively. Except for a minimal correlation of 0.30 between relapse rate and the number of gadolinium-enhanced lesions, correlations between MR and clinical measures at baseline and throughout the study were in general poor. Once weekly intramuscular IFNbeta-1a appears to impede the development of multiple sclerosis lesions at an early stage and has a favorable impact on the long-term sequelae of these inflammatory events as indicated by the slowed accumulation of T2 lesions.

Asset and Health Dynamics Among the Oldest Old: An Overview of the AHEAD Study

Abstract: This chapter provides background information for the study of Asset and Health Dynamics Among the Oldest Old (AHEAD), a prospective panel survey of persons born in 1923 or earlier who were residing in the community at the time of the 1993 baseline. Interviews were sought with both spouses in married households, and an overall total of 8,222 were completed. We review the interdisciplinary scientific issues that motivated the study, describe the fundamental design decisions that structured AHEAD, and summarize the content in the core and experimental modules. The study provides unusually detailed data on cognition, family structure and transfers, and assets. Data are presented on sample selections, response rates, and oversamples of minority groups. Basic descriptive data on the demographic, health, and socioeconomic attributes of respondents also are presented. Plans for future waves of AHEAD are described, including a next-of-kin interview for decreased respondents.