The research focused on patients with the disease known as non-Hodgkin lymphoma of the stomach, which accounts for 5% of all gastric neoplasms. This disease is believed to be caused by a chronic Helicobacter pylori infection.
The proper diagnosis and medical treatment of this type of cancer depends on the use of uncertain information. To further their knowledge of this disease, physicians have to resort to data tables. Data tables give a broad overview of a set of factors within a group of patients for pattern extraction. These patterns are helpful for preventing, diagnosing and treating this lymphoma.
These decision-making processes, which affect the health and lives of many people, are complicated: the size of the tables used is massive, which is an obstacle for analysing and interpreting their contents.
What the research team proposed in the article was to introduce what are known as KBM2L Lists to support clinical decision making in patients suffering from this disease. These lists are dynamic knowledge representations that are capable of representing the analysed system knowledge in a summarized and understandable form.
As they explain in their article, this proposal is an attractive alternative to today’s clinical decision-making methods, as the system is able to extract and present patterns from an influence diagram for physicians to interpret. Influence diagrams are a way of representing decision-making problems as they are perceived by the decision maker, in this case the physician.
In a preliminary evaluation of this technique, the researchers generated KBM2L lists specific to non-Hodgkin lymphoma of the stomach that one of the authors, both a computer scientist and experience physician, interpreted. The KBM2L lists could be applied to other diseases.
The authors of this research are Concha Bielza and Juan Fernández del Pozo, from the Decision Analysis and Statistics Group at the UPM’s School of Computing, and Peter F. Lucas, from Radboud University Nijmegen’s Information Science and Computing Institute in Holland.
Eduardo Martínez | alfa
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Researchers from the Department of Atomically Resolved Dynamics of the Max Planck Institute for the Structure and Dynamics of Matter (MPSD) at the Center for Free-Electron Laser Science in Hamburg, the University of Hamburg and the European Molecular Biology Laboratory (EMBL) outstation in the city have developed a new method to watch biomolecules at work. This method dramatically simplifies starting enzymatic reactions by mixing a cocktail of small amounts of liquids with protein crystals. Determination of the protein structures at different times after mixing can be assembled into a time-lapse sequence that shows the molecular foundations of biology.
The functions of biomolecules are determined by their motions and structural changes. Yet it is a formidable challenge to understand these dynamic motions.
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Researchers from the Department of Atomically Resolved Dynamics of the Max Planck Institute for the Structure and Dynamics of Matter (MPSD) at the Center for Free-Electron Laser Science in Hamburg, the University of Potsdam (both in Germany) and the University of Toronto (Canada) have pieced together a detailed time-lapse movie revealing all the major steps during the catalytic cycle of an enzyme. Surprisingly, the communication between the protein units is accomplished via a water-network akin to a string telephone. This communication is aligned with a ‘breathing’ motion, that is the expansion and contraction of the protein.
This time-lapse sequence of structures reveals dynamic motions as a fundamental element in the molecular foundations of biology.
Two research teams have succeeded simultaneously in measuring the long-sought Thorium nuclear transition, which enables extremely precise nuclear clocks. TU Wien (Vienna) is part of both teams.
If you want to build the most accurate clock in the world, you need something that "ticks" very fast and extremely precise. In an atomic clock, electrons are...
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