Breaking the cycle : attacking the malaria parasite in the liver / / edited by Ute Frevert, Urszula Krzych, Thomas L. Richie

• Record Nr.: UNINA9910136802703321
• Autore: Richie Thomas
• Pubbl/distr/stampa: Frontiers Media SA, 2015; [Place of publication not identified] : , : Frontiers Media SA, , 2015
• Descrizione fisica: 1 online resource (173 pages) : illustrations, charts; digital, PDF file(s)
• Collana: Frontiers research topics; Frontiers in Human Neuroscience, , 1664-8714
• Soggetti: Plasmodium falciparum; Malaria - Immunological aspects; Malaria - Prevention; Malaria - Research; Liver - Immunology; Liver - Parasites; Hepatology; Plasmodis
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references.
• Sommario/riassunto: Despite significant progress in the global fight against malaria, this parasitic infection is still responsible for nearly 300 million clinical cases and more than half a million deaths each year, predominantly in African children less than 5 years of age. The infection starts when mosquitoes transmit small numbers of parasites into the skin. From here, the parasites travel with the bloodstream to the liver where they undergo an initial round of replication and maturation to the next developmental stage that infects red blood cells. A vaccine capable of blocking the clinically silent liver phase of the Plasmodium life cycle would prevent the subsequent symptomatic phase of this tropical disease, including its frequently fatal manifestations such as severe anemia, acute lung injury, and cerebral malaria. Parasitologists, ; immunologists, and vaccinologists have come to appreciate the complexity of the adaptive immune response against the liver stages of this deadly parasite. Lymphocytes play a central role in the elimination of Plasmodium infected hepatocytes, both in humans and animal models, but our understanding of the exact cellular interactions and molecular effector mechanisms that lead to parasite killing within the complex hepatic microenvironment of an immune host is still rudimentary. Nevertheless, recent collaborative efforts have led to promising vaccine approaches based on liver stages that have conferred sterile immunity in humans – the University of Oxford's Ad prime / MVA boost vaccine, the Naval Medical Research Center’s DNA prime / Ad boost vaccine, Sanaria, Inc.'s radiation-attenuated whole sporozoite vaccine, and Radboud University Nijmegen Medical Centre’s chemoprophylaxis with sporozoites vaccine. The aim of this Research Topic is to bring together researchers with expertise in malariology, immunology, hepatology, antigen discovery and vaccine development to provide a better understanding of the basic biology of Plasmodium in the liver and the host’s innate and adaptive immune responses. Understanding the conditions required to generate complete protection in a vaccinated individual will bring us closer to our ultimate goal, namely to develop a safe, scalable, and affordable malaria vaccine capable of inducing sustained high-level protective immunity in the large proportion of the world’s population constantly at risk of malaria.

Empirical evaluation methods in computer vision [[electronic resource] /] / editors, Henrik I. Christensen, P. Jonathon Phillips

• Record Nr.: UNINA9910784783003321
• Pubbl/distr/stampa: River Edge, N.J., : World Scientific, c2002
• ISBN: 981-277-742-3
• Descrizione fisica: 1 online resource (172 p.)
• Collana: Series in machine perception and artificial intelligence ; ; v. 50
• Altri autori (Persone): ChristensenH. I <1962-> (Henrik I.); PhillipsP. Jonathon
• Disciplina: 006.3/7
• Soggetti: Computer vision - Evaluation
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: All but two contributions are revised papers from a workshop held in 2000.
• Nota di bibliografia: Includes bibliographical references.
• Nota di contenuto: Contents ; Foreword ; Chapter 1 Automated Performance Evaluation of Range Image Segmentation Algorithms ; 1.1. Introduction ; 1.2. Scoring the Segmented Regions ; 1.3. Segmentation Performance Curves ; 1.4. Training of Algorithm Parameters ; 1.5. Train-and-Test Performance Evaluation; 1.6. Training Stage 1.7. Testing Stage ; 1.8. Summary and Discussion ; References ; Chapter 2 Training/Test Data Partitioning for Empirical Performance Evaluation ; 2.1. Introduction ; 2.2. Formal Problem Definition ; 2.2.1. Distance Function ; 2.2.2. Computational Complexity; 2.3. Genetic Search Algorithm 2.4. A Testbed ; 2.5. Experimental Results ; 2.6. Conclusions ; References ; Chapter 3 Analyzing PCA-based Face Recognition Algorithms: Eigenvector Selection and Distance Measures ; 3.1. Introduction ; 3.2. The FERET Database ; 3.3. Distance Measures; 3.3.1. Adding Distance Measures 3.3.2. Distance Measure Aggregation ; 3.3.3. Correlating Distance Metrics ; 3.3.4. When Is ; a Difference Significant ; 3.4. Selecting Eigenvectors ; 3.4.1. Removing the Last Eigenvectors ; 3.4.2. Removing the First Eigenvector; 3.4.3. Eigenvalue Ordered by Like-Image Difference 3.4.4. Variation Associated with Different Test/Training Sets ; 3.5. Conclusion ; References ; Chapter 4 Design of a Visual System for Detecting Natural Events by the Use of an Independent Visual Estimate: A Human Fall Detector; 4.1. Introduction
• Sommario/riassunto: This book provides comprehensive coverage of methods for the empirical evaluation of computer vision techniques. The practical use of computer vision requires empirical evaluation to ensure that the overall system has a guaranteed performance. The book contains articles that cover the design of experiments for evaluation, range image segmentation, the evaluation of face recognition and diffusion methods, image matching using correlation methods, and the performance of medical image processing algorithms. <i>Sample Chapter(s)</i><br>Foreword (228 KB)<br>Chapter 1: Introduction (505 KB)<br> <