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"Superbug" bacterial infections that are resistant to common antibiotics are increasing at an alarming rate. But traditional antibiotics aren't the only way to battle dangerous germs. Biomedical scientists are investigating new additions to their arsenal. 
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Phillip Trotter's insight:
In our bodies every cell contains the same genetic code, however the active or expressed genes determine cell function. Which genes are expressed is controlled by tiny bits of the genome called promoters and enhancers and different cell types are determined by different combinations of promoters and enhancers. Now an international consortium of researchers known as FANTOM, led by the RIKEN institute in Japan have created the clearest map yet of how genes control cells to make our bodies function. The map is already challenging ideas about what our genes do and how they interact and may accelerate the development of gene-based therapies. The team examined more than 800 human tissue samples, covering nearly all cell types, and found 44,000 enhancers and 180,000 promoters that control gene expression.
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The new Mers virus, which has killed half of those infected, is "unlikely" to reach the same scale as Sars, ministers in Saudi Arabia say.
Phillip Trotter's insight:
The source of the Mers virus is still unknown. Given that Mers is from the same group of viruses as Sars and Common Cold - understanding the genotype and phenotype differences and how they relate to pathogenic and vector pathways in its related family could help to better understand both Mers and related groups and perhaps indicate a source. Viral evolution is something we still know relatively little about - and understanding of how they coevolve and relate to microbial habitat are becoming increasingly important to health planning and treatments.
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Researchers from Johns Hopkins and Northwestern universities have discovered how to control the shape of nanoparticles that move DNA through the body and have shown that the shapes of these carriers may make a big difference in how well they work in treating cancer and other diseases. The use of computer models allowed Luijten’s team to mimic traditional lab experiments at a far faster pace. These molecular dynamic simulations were performed on Quest, Northwestern’s high-performance computing system. The computations were so complex that some of them required 96 computer processors working simultaneously for one month. “Our computer simulations and theoretical model have provided a mechanistic understanding, identifying what is responsible for this shape change,” Associate Professor Eric Luijten said. “We now can predict precisely how to choose the nanoparticle components if one wants to obtain a certain shape.”. Click on the image or the title to learn more.
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Phillip Trotter's insight:
Dr.Stefan Gruenwalds scoop-it list of bioinformatics databases is an essential resource for anyone looking to discover which datasets are available and accessible. Awesome.
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ECAL 2013, the twelfth European Conference on Artificial Life, presents the current state of the art of a mature and autonomous discipline collocated at the intersection of a theoretical perspective (the scientific explanations of different levels of life organizations, e.g., molecules, compartments, cells, tissues, organs, organisms, societies, collective and social phenomena) and advanced technological applications (bio-inspired algorithms and techniques to building-up concrete solutions such as in robotics, data analysis, search engines, gaming).
Advances in Artificial Life, ECAL 2013 Proceedings of the Twelfth European Conference on the Synthesis and Simulation of Living Systems Edited by Pietro Liò, Orazio Miglino, Giuseppe Nicosia, Stefano Nolfi and Mario Pavone http://mitpress.mit.edu/books/advances-artificial-life-ecal-2013 Via Complexity Digest
Phillip Trotter's insight:
I have a big soft spot for artificial life research - partly because i was a young researcher shortly after Chris Langton coined the term and a lot of my early hacking was around games of life, vants and cellular automata but also because over the years I have found many of the techniques discussed in ALIFE circles applicable to other fields such as machine learning, control architectures, and emergent simulation etc so this is definitely one for the reading list.
luiy's curator insight,
September 9, 2013 4:35 PM
About the Editors
Pietro Liò is Reader in Computational Biology at the University of Cambridge and a member of the Artificial Intelligence group of the University's Computer Laboratory. He researches on Predictive models in Personalized medicine and Multiscale modelling of molecules-cell-tissue-organ interactions.
Orazio Miglino is a full Professor of Psychology at University of Naples Federico II where he leads the Natural and Artificial Cognition Lab. He is also an associate researcher at the Institute of Cognitive Sciences and Technologies of Italian National Research Council (ISTC-CNR) in Rome.
Giuseppe Nicosia is an Associate Professor in Computational Systems and Synthetic Biology in the Dept. of Mathematics and Computer Science of the University of Catania, Italy. His research activities focus on the design of biological systems, neuroinformatics, system design, design automation, optimization, solar cells, circuit and semiconductor design.
Stefano Nolfi is Research Director at the Italian National Research Council (CNR), director of the Laboratory of Autonomous Robots and Artificial Life of the Institute of Cognitive Sciences and Technologies. His research activities focus on the evolution and development of behavioural and cognitive skills in natural and artificial embodied agents (robots).
Mario Pavone is an Assistant Professor in computer science at the Department of Mathematics and Computer Science of the University of Catania. He is co-founder of TaoScience Research center, and he is also a member of the EURO association (The Association of European Operational Research Societies)
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From
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How the blistering pace of technological change could have a profound impact on healthcare.
Phillip Trotter's insight:
The combination of sensors and automated tests in areas of genetics and proteomics enable collection of largescale comprehensive health data for the first time. That data will generate insights into human biology, our bacterial biome and how our health systems work. Advances in large scale data processing, correlation and machine learning will help over the next decade to radically change our understanding of human biology. As data is collected and in silico experimentation mapped to invitrio understanding data will change our healthcare systems over the next 30 years. This BBC article gives a good insight into how and why this is starting to happen now.
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Given the WHO announcement that antibacterial resistance is now a global threat - article on popular mechanic outlines some of the alternate treatments to antibiotics.