Case Western Reserve University

About: Case Western Reserve University is a education organization based out in Cleveland, Ohio, United States. It is known for research contribution in the topics: Population & Cancer. The organization has 54617 authors who have published 106568 publications receiving 5071613 citations. The organization is also known as: Case & Case Western.

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Abstract: Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumoris a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses thestate-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross tota lresection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset.

Design and Testing of a Generalized Reduced Gradient Code for Nonlinear Programming

Abstract: : The purpose of this paper is to describe a Generalized Reduced Gradient (GRG) algorithm for nonlinear programming, its implementation as a FORTRAN program for solving small to medium size problems, and some computational results. Our focus is more on the software implementation of the algorithm than on its mathematical properties. This is in line with the premise that robust, efficient, easy to use NLP software must be written and made accessible if nonlinear programming is to progress, both in theory and in practice.

Global Challenge of Multidrug-Resistant Acinetobacter baumannii

Abstract: We may soon be facing the end of the “antibiotic era.” The initial and seemingly unstoppable success of antibiotics, the fruit of human ingenuity, has been countered by an escalation of resistance mechanisms in bacteria. This crisis has been described as an “unwinnable war” (www.wellcome.org). The statistics compiled as a result of surveillance efforts illustrate the emergence of many genera of bacteria that are resistant to all antibiotics (57, 60). The genus Acinetobacter epitomizes this trend and deserves close attention. Acinetobacter spp. display mechanisms of resistance to all existing antibiotic classes as well as a prodigious capacity to acquire new determinants of resistance (7). The increasing recovery in the clinic of multidrug-resistant (MDR) Acinetobacter baumannii is a frightening reality (112). This review summarizes the worldwide emergence of antibiotic-resistant A. baumannii as a nosocomial pathogen and focuses on its mechanisms of resistance against selected antibiotics. It concludes with a summary of current strategies in the treatment of MDR A. baumannii and offers perspectives on the control of this global public health threat.

Rapid Hematopoietic Recovery After Coinfusion of Autologous-Blood Stem Cells and Culture-Expanded Marrow Mesenchymal Stem Cells in Advanced Breast Cancer Patients Receiving High-Dose Chemotherapy

Abstract: PURPOSE: Multipotential mesenchymal stem cells (MSCs) are found in human bone marrow and are shown to secrete hematopoietic cytokines and support hematopoietic progenitors in vitro. We hypothesized that infusion of autologous MSCs after myeloablative therapy would facilitate engraftment by hematopoietic stem cells, and we investigated the feasibility, safety, and hematopoietic effects of culture-expanded MSCs in breast cancer patients receiving autologous peripheral-blood progenitor-cell (PBPC) infusion. PATIENTS AND METHODS: We developed an efficient method of isolating and culture-expanding a homogenous population of MSCs from a small marrow-aspirate sample obtained from 32 breast cancer patients. Twenty-eight patients were given high-dose chemotherapy and autologous PBPCs plus culture-expanded MSC infusion and daily granulocyte colony-stimulating factor. RESULTS: Human MSCs were successfully isolated from a mean ± SD of 23.4 ± 5.9 mL of bone marrow aspirate from all patients. Expansion cultures generat...