The Use of Proteomic Technologies to Identify Serum Glycoproteins for the Early Detection of Liver and Prostate Cancers

The application of proteomic technologies to identify serum glycoproteins is an emerging technique to identify new biomarkers indicative of disease severity. Many of these newly evolving protein-profiling methodologies have evolved from previous global protein expression profiling studies such as those involving SELDI-TOF-MS technologies. Though the SELDI approach could distinguish disease from normal by utilizing protein patterns as shown herein with the HCC study of chapter II, it was unable to offer sequence information on the selected peaks, and did not have the ability to analyze the entire dynamic range of the serum/plasma proteome. To address these deficiencies, new strategies that incorporate the use of differential lectin-based glycoprotein capture and targeted immuno-based assays have been developed. The carbohydrate binding specificities of different lectins offers a biological affinity approach that both complements existing mass spectrometer capabilities and retains automated throughput options. A prostate cancer study using disease stratified samples is utilized herein to determine whether lectin capture can identify glycoproteins, which are indicative of different stages of prostate disease. By utilizing upfront lectin fractionation we show here evidence of glycoproteins and glycoprotein isoforms, which are specific to cancer progression. In addition, the incorporation of lectin fractionation followed by albumin depletion allows for a more in depth analysis of the entire dynamic range of the human serum and plasma proteome. Taken together we believe this approach is an attractive strategy for the discovery of proteins indicative of the early detection of liver and prostate cancers

EXPANSÃO E APRIMORAMENTO DE SOFTWARE DE GESTÃO PECUÁRIA NO BRASIL

O objetivo foi difundir o uso de ferramentas de gerenciamento eficientes para facilitar tomadas de decisões. Foi realizado estudo de mercado sobre formas de gerenciamento e coleta de dados produtivos em 907 propriedades rurais para detectar pontos críticos do sistema e posteriormente desenvolver um software para gerenciamento. A coleta/armazenamento de dados foram por Excel® (52,4%, n=475), seguido por caderno de campo (42,2%, n=383) e softwares pagos (5,4%, n=49). Logo viabiliza desenvolver com a fábrica de softwares do IFC Araquari um programa para propriedades direcionadas a pecuária de corte