Safety and Allele-Specific Immunogenicity of a Malaria Vaccine in Malian Adults: Results of a Phase I Randomized Trial

OBJECTIVES: The objectives were to evaluate the safety, reactogenicity, and allele-specific immunogenicity of the blood-stage malaria vaccine FMP1/AS02A in adults exposed to seasonal malaria and the impact of natural infection on vaccine-induced antibody levels. DESIGN: We conducted a randomized, double-blind, controlled phase I clinical trial. SETTING: Bandiagara, Mali, West Africa, is a rural town with intense seasonal transmission of Plasmodium falciparum malaria. PARTICIPANTS: Forty healthy, malaria-experienced Malian adults aged 18–55 y were enrolled. INTERVENTIONS: The FMP1/AS02A malaria vaccine is a 42-kDa recombinant protein based on the carboxy-terminal end of merozoite surface protein-1 (MSP-1(42)) from the 3D7 clone of P. falciparum, adjuvanted with AS02A. The control vaccine was a killed rabies virus vaccine (Imovax). Participants were randomized to receive either FMP1/AS02A or rabies vaccine at 0, 1, and 2 mo and were followed for 1 y. OUTCOME MEASURES: Solicited and unsolicited adverse events and allele-specific antibody responses to recombinant MSP-1(42) and its subunits derived from P. falciparum strains homologous and heterologous to the 3D7 vaccine strain were measured. RESULTS: Transient local pain and swelling were more common in the malaria vaccine group than in the control group (11/20 versus 3/20 and 10/20 versus 6/20, respectively). MSP-1(42) antibody levels rose during the malaria transmission season in the control group, but were significantly higher in malaria vaccine recipients after the second immunization and remained higher after the third immunization relative both to baseline and to the control group. Immunization with the malaria vaccine was followed by significant increases in antibodies recognizing three diverse MSP-1(42) alleles and their subunits. CONCLUSIONS: FMP1/AS02A was well tolerated and highly immunogenic in adults exposed to intense seasonal malaria transmission and elicited immune responses to genetically diverse parasite clones. Anti-MSP-1(42) antibody levels followed a seasonal pattern that was significantly augmented and prolonged by the malaria vaccine

Overview of BioCreative II gene mention recognition.

Nineteen teams presented results for the Gene Mention Task at the BioCreative II Workshop. In this task participants designed systems to identify substrings in sentences corresponding to gene name mentions. A variety of different methods were used and the results varied with a highest achieved F1 score of 0.8721. Here we present brief descriptions of all the methods used and a statistical analysis of the results. We also demonstrate that, by combining the results from all submissions, an F score of 0.9066 is feasible, and furthermore that the best result makes use of the lowest scoring submissions

The Genomic Data Mine

The genomic data mine represents a fundamental shift from genetics to genomics, essentially from the study of one gene at a time to the study of entire genetic metabolic networks and whole genomes. Experimental laboratory data are deposited into large public repositories and a wealth of computational data mining algorithms and tools are applied to mine the data. The integration of different types of data in the genomic data mine will contribute towards an understanding of the systems biology of living organisms, contributing to improved diagnoses and individualized medicine. This chapter focuses on the genomic data mine consisting of text data, map data, sequence data, and expression data, and concludes with a case study of the Gene Expression Omnibus (GEO). Keywords genomics; text mining; data mining; gene expression data “ … Medical schools, slow to recognize the profound implications of genomics for clinical medicine, have been lurching, if not stumbling, forward to embrace the genomification of medicine…

Overview of BioCreative II gene mention recognition

Nineteen teams presented results for the Gene Mention Task at the BioCreative II Workshop. In this task participants designed systems to identify substrings in sentences corresponding to gene name mentions. A variety of different methods were used and the results varied with a highest achieved F1 score of 0.8721. Here we present brief descriptions of all the methods used and a statistical analysis of the results. We also demonstrate that, by combining the results from all submissions, an F score of 0.9066 is feasible, and furthermore that the best result makes use of the lowest scoring submissions

Edgar: Extraction of drugs, genes and relations from the biomedical literature

EDGAR (Extraction of Drugs, Genes and Relations) is a natural language processing system that extracts information about drugs and genes relevant to cancer from the biomedical literature. This automatically extracted information has remarkable potential to facilitate computational analysis in the molecular biology of cancer, and the technology is straightforwardly generalizable to many areas of biomedicine. This paper reports on the mechanisms for automatically generating such assertions and on a simple application, conceptual clustering of documents. The system uses a stochastic part of speech tagger, generates an underspecified syntactic parse and then uses semantic and pragmatic information to construct its assertions. The system builds on two important existing resources: the MEDLINE database of biomedical citations and abstracts and the Unified Medical Language System, which provides syntactic and semantic information about the terms found in biomedical abstracts.