The B apoprotein is thought to be essential for the synthesis and secretion of triglyceriderich lipoproteins from mammalian liver. Antibodies were prepared against rat low density lipoproteins (LDL, density 1.025-1.045) and very low density lipoproteins (VLDL). By Ouchterlony immunodiffusion and Immunoelectrophoresis, the major determinant shared by these antisera had the characteristics of the B apoprotein. Fab fragments were prepared by the method of Porter and conjugated to horseradish peroxidase (HRP) by the two step method of Avrameas and Ternynck. Male Long-Evans rats (250-300 gm) were fasted overnight, anesthetized with Brevital (Lilly), and perfused through the portal vein with fresh 4% formaldehyde in 0.135 M sodium phosphate buffer.

Introduction: Acute myocardial infarction (heart attack) is one of the deadliest diseases patients face. The key to cardiovascular disease management is to evaluate large scores of datasets, compare and mine for information that can be used to predict, prevent, manage and treat chronic diseases such as heart attacks. Big Data analytics, known in the corporate world for its valuable use in controlling, contrasting and managing large datasets can be applied with much success to the prediction, prevention, management and treatment of cardiovascular disease. Data mining, visualization and Hadoop are technologies or tools of big data in mining the voluminous datasets for information.

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Big Data can unify all patient related data to get a 360-degree view of the patient to analyze and predict outcomes. It can improve clinical practices, new drug development and health care financing process. It offers a lot of benefits such as early disease detection, fraud detection and better healthcare quality and efficiency. This paper introduces the Big Data concept and characteristics, health care data and some major issues of Big Data. These issues include Big Data benefits, its applications and opportunities in medical areas and health care. Methods and technology progress about Big Data are presented in this study. Big Data challenges in medical applications and health care are also discussed.

Big Data helps improve visibility throughout the supply chain, provides an integrated view of operational performance and customer interaction and gives businesses real-time insights that help make critical decisions. Big Data also has a potential to yield new management principles. This paper introduces the Big Data concept, its characteristics and some major issues of Big Data in supply chain management and business administration. These issues include supply chain and business data, Big Data benefits and its applications and opportunities. Methods and technology progress about Big Data are presented in this study. General challenges of Big Data and Big Data challenges in supply chain management and business administration are also discussed.

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Big Data analytics can improve patient outcomes, advance and personalize care, improve provider relationships with patients, and reduce medical spending. This paper introduces healthcare data, big data in healthcare systems, and applications and advantages of Big Data analytics in healthcare. We also present the technological progress of big data in healthcare, such as cloud computing and stream processing. Challenges of Big Data analytics in healthcare systems are also discussed.

Big Data helps facilitate information visibility and process automation in design and manufacturing engineering. It also helps analyze trends through analytics and predict inventory, manufacturing output and equipment lifespan and cycles, etc. This paper introduces Big Data, its characteristics and a number of issues of Big Data in design and manufacturing engineering. These issues include design and manufacturing data, Big Data benefits and impacts and its applications and opportunities. Methods, technologies and some technology progress around Big Data are presented in this study. General challenges of Big Data and Big Data challenges in design and manufacturing engineering are also discussed.