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The novel approach relies on a new algorithm, developed by the researchers, that is more sensitive to detecting specific types of variation in DNA sequences. "It required a lot of persistence and the outcome wasn't what I had originally planned to investigate," said lead author Paul Bodily, PhD student in computer science. "I just continued down a path, not knowing where it was going to lead, until I found something shiny." Every person has two copies of the genome in each of their cells, one from each parent. The DNA sequence of the two copies is mostly identical, but there are occasionally places where one of the sequences gets reversed, called an inversion. Inversions are often biologically significant. Previous research has demonstrated an association between inversions and mental retardation, diabetes, epilepsy, schizophrenia and autism. The research, published in medical journal Bioinformatics, details how the new algorithm outperforms other methods and the unintended discovery of the algorithm's ability to detect inversions. Previously, inversions have been very difficult to detect, but the researchers believe their method can significantly enhance the process. "There are diseases, like autism, that we're really uncertain as to what causes them," said senior author Mark Clement, professor in computer science. "To at least have improved tools for detecting a possible cause is important." The group made the algorithm source freely available to any fellow researchers interested in applying it. Bodily is still a few years from graduation but anticipates the development of his research to apply the new module on a bigger scale. "You can make almost any algorithm look good if you craft the right data set, but ours is based on some pretty fundamental theory," said Bodily. "Theory and practice don't often agree, but I have a lot of hope that when applied to the bigger picture, our approach will work well."

EMPIAR provides raw 2-D data for datasets submitted to the EMDB, and is managed by the Protein Data Bank in Europe team at EMBL-EBI. Credit: Spencer Phillips, EMBL-EBI As the bioimaging revolution gives scientists ever-more detailed views on the inner workings of cells, there is growing demand for public infrastructure to store, share and link the massive datasets produced using high-resolution imaging techniques. Complementing large-scale, EMBL-led, intergovernmental initiatives such as Euro-BioImaging, the European Bioinformatics Institute (EMBL-EBI) has expanded its EMPIAR data service to accommodate new high-resolution imaging modalities such as Scanning Electron Microscopy (SEM). A correspondence published in Nature Methods today introduces the resource and gives a glimpse of future developments. EMPIAR, EMBL-EBI's global public data resource for raw 2D images, provides valuable data for developing new approaches to data processing, interpretation and validation - all essential activities for archiving and quality control. "The raw image data archived in EMPIAR is very useful for many things, including making original data related to controversial studies available publicly," explains Gerard Kleywegt, Head of Molecular and Cellular Structure services at EMBL-EBI. EMPIAR, part of the Electron Microscopy Data Bank (EMDB) at EMBL-EBI, is designed to handle very large datasets: the average entry is around 700 Gigabytes, and the largest is over 6 Terabytes. Recent datasets include four related 3D SEM entries showing different stages of infection of a red blood cell by a malaria parasite. EMPIAR is currently the only way to archive these data and make them available to other scientists. "EMPIAR allows us to share big raw datasets," says John Briggs of EMBL, whose group develops and applies advanced cryo-electron microscopy techniques to study enveloped viruses such as HIV. "These can then be looked at by other labs that might be interested in other aspects of the data, or used for testing or comparing new image-analysis pipelines." "EMPIAR is an exemplar of a very timely, community-driven archiving initiative, and fits perfectly with our mission to provide services that support life-science discovery," says EMBL Director General Iain Mattaj. "It supports cutting-edge imaging methods such as those developed at EMBL by giving a home to the data, and allowing the community to refine their interpretation. This enables us to gain an increasingly precise view on the processes of life." The EMPIAR team is working on ways to accommodate other imaging modalities, for example soft X-ray tomography - which bridges the scale and resolution gap between light microscopy and electron tomography - and Correlative Light and Electron Microscopy (CLEM). "In CLEM, researchers use fluorescent tags to detect interesting events in a cell, then take a closer look using high-resolution EM," says Ardan Patwardhan, Coordinator in EMBL-EBI's Protein Data Bank in Europe team. "We are working with pioneers in this field to find the best way to store and correlate these data types, which will provide a very powerful tool for research." More information: Iudin A, et al. (2016) EMPIAR: A public archive for raw electron microscopy image data. Nature Methods. DOI: 10.1038/nmeth.3806

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Site: techcrunch.com

If you get hurt and show up unconscious at the hospital, they likely have no idea what medications you’re on, your medical history, or where you’ve been treated. Medal wants to fix that so all your medical records are united in one place and can be securely accessed by your doctors whenever necessary. While insurance companies and hospitals have worked for years on so-called patient data interchanges, electronic medical records still aren’t universally transferrable. Competing networks don’t work together, and most records are still moved by fax or courier. The result is a fiasco, and a dangerous one. Records are lost, incomplete, or inaccessible. Doctors don’t know about a patient’s past care or medications, which can cause potentially fatal drug interactions. Doctors are sued for malpractice. It takes months for patients to get their bills. And the whole thing is grossly inefficient. Here’s just one example of how dire this problem is. Right now, 50% of patients that show up for care are taking a medication their doctor doesn’t know about. Of those, 39% are taking a medication with a moderate to severe harm potential if wrongly combined with other drugs. This causes millions of Americans each year to die, or get sick and spend longer in a hospital. It’s time for software to not only improve the medical record, but how it moves around. That way, no matter where you’re sick or hurt, you get the best possible care from a doctor that knows about you. Lonnie Rae Kurlander was practically a doctor. But deep down she knew there might be a way to heal more people by building technology than she ever could at a hospital. So despite almost finishing medical school at Boston University and having started her clinical rotations, she left to start Medal. “I believe it’s my opportunity to make the biggest impact on healthcare” she tells me. [Disclosure: Kurlander is also a friend of mine.] This is the first time Medal has spoken publicly about its plan. Medal is now running primarily on revenue after taking a small angel round from Lee Linden of Karma and Facebook Gifts, Justin Rosenstein of Asana [also a friend], and Dr. Anand Devaiah. That last one was Kurlander’s professor at Boston University who kept approving her petitions for leaves of absence to work on Medal. Once he understood why Kurlander thought it was more important than becoming a doctor, he invested. The goal of Medal’s software is to make it easy but secure for doctors to quickly retrieve a patient’s medical record, no matter where in the U.S. they’re from or who their primary care physician is. Medal installs in one minute on a doctor’s computer, and works with just about every medical record system. It analyzes the data, and turns structured and unstructured fields into an organized record that is both human and machine-readable on the other side. Insurance pays for when doctors receive these records. The current Medal product works within a referral network or accountable care organization — essentially all the medical professionals directly associated with your doctor. Medal makes sure all the patient’s data is synced and accessible to their primary physicians, specialists, in-patient and out-patient caretakers, and rehabilitation workers. It works for care coordination, referrals, and billing. Phase two will allow doctors on Medal to request medical records for any patient on any system. They’ll enter the available information on the patient’s identity and their own official care provider ID, Medal will confirm where the record is, and send a retrieval request via fax. The record can then be faxed back, or the doctor can sign up for Medal on the spot and send the record through the system. Medal also offers a patient information card people can carry in their wallet. “We’re completely agnostic” says Kurlander. Medal isn’t trying to preference one network of hospitals or insurers over another, upsell other health information technology, or drive up costs. Kurlander insists “We’re hoping to create true interoperability for the first time in this country.” The two core challenges for Medal will be security and adoption. The system only works if doctors and patients are confident their data is safe, and it can get enough caretakers and hospitals on board. This is why Medal has Andy McMurry as its co-founder and CTO, a PhD in Bioinformatics from Boston University. He spent six years as the lead architect of Shrine, Harvard’s research interchange that works with millions of patient records from over 60 health institutions. Medal has also brought on famed white hat hacker Dan Kaminsky to protect it from attacks. Kaminsky is known for discovering and patching a core flaw in DNS, and being one of the seven key holders who can assemble to essentially reset the Internet if necessary. Making Medal work everywhere is a monumental task because Kurlander says “Every medical record system is a like a unique snow flake.” Medal is building customizations for each system so it can always accurately interpret and organize the medical record. Other businesses are also pursuing interoperability, but they may not be as well tuned to the problem. RightFax accepts more kinds of data but isn’t healthcare specific. The CommonWell Health Alliance was started by several large health IT vendors, but comes from a slower, more traditional approach. There’s also Relay Health, Human API, and regional interchanges vying to become the connective tissue for medical records. Medal also faces entrenched institutions that see incompatibility and control of your data as a competitive advantage. But Kurlander insists that “It’s the law that that data belongs to you, the patient.” By acting as a bridge between the fragmented health networks, Medal aims to co-opt competitors and unite their data into a coordinated community. But with regulation, competitors, and the inherent caution and slowness of the health industry, Medal has a tough road ahead to getting us off clumsy paper records. Luckily, years of apathy have finally given way to real passion to reform the inefficiencies of the insanely expensive U.S. healthcare system. Medal now has over 800 hospitals lined up to use its product. “This is like Visa” Kurlander concludes. “Visa is the payments interchange. Medal is the medical data interchange.”

Machine learning algorithms power predictions about the coming season of the TV-series "Game of Thrones." Credit: Christian Dallago The rich worlds created in the TV series Game of Thrones (GoT) inspired a computer science class at the Technical University of Munich (TUM) in Germany: As part of their class project, the students developed applications that scour the web for data on Game of Thrones and crunch the numbers. Then they put together a website that reports which characters are most likely to die in the upcoming sixth season of the TV series. Just ahead of the kickoff for season six, the students have implemented a project that answers questions preoccupying fans of the series: Has Jon Snow survived season five? Who is going to die next? The students used an array of machine learning algorithms to answer these questions. The algorithm, which accurately predicted 74 percent of character deaths in the show and books, has many surprises in store, placing a number of characters thought to be relatively safe in grave danger. Based on these predictions, there is a good chance that the villainous Ramsay Snow (64 percent likelihood of death) will outlive his runaway captive and mortal enemy Theon Greyjoy (74 percent likelihood of death). The algorithm also gives a very clear answer on the fate of Jon Snow, who was betrayed by his friends in the season five finale. The website Got.show presents key data generated by the students' diverse machine learning tools compilation. The site also tracks and analyzes Twitter user sentiments on hundreds of GoT characters. Beyond these predictions, the students also programmed an interactive map that allows fans to explore the Game of Thrones world and chart the journeys taken by major characters. Game of Thrones Season 6 will premiere in USA on April 24th. It will also air in Germany in the night from April 24th to 25th on Sky, in both English and German. "This project has been a lot of fun for us," says Dr. Guy Yachdav, who led the class and conceived the project. "In its daily work, our research group focuses on answering complex biological questions using data mining and machine learning algorithms. For this project we used similar techniques. Only this time the subject matter was a popular TV show. The epic scale of the worlds created by George R. R. Martin provides an almost endless resource of raw multi-dimensional data. It provided the perfect setting for our class." "Data mining and machine learning are tools that enable digital medicine to benefit from modern biology for diagnosis, treatment and prevention of disease. Turning to such a 'real life' challenge created a didactical jewel, winning students for these subjects," summarizes Burkhardt Rost, Professor of Bioinformatics at the Technical University of Munich. "And the interactive visual maps created in the project might open a new approach to data visualization that we will follow up scientifically."

It was found that synthesized molecules could potentially be used as anticancer agents with good selectivity index. Hydantoin moiety and its derivatives can be found in many drug molecules, including nilutamide, which is used in chemotherapy for prostate cancer, and dantrolene, which helps to relax skeletal muscles and prevent cramps. Selenohydantoins are derivatives of hydantoins in which one of the oxygen atoms is replaced by selenium. It was found that drug molecules containing selenium possess anticancer activity and can be used as effective antioxidants. Selenium can be found in a number of known drug molecules, such as Ebselen, an antioxidant with a broad spectrum of therapeutic activity. In the study, the scientists have synthesized novel selenium-containing hydantoin derivatives. The structures of the molecules obtained were confirmed by NMR (Nuclear Magnetic Resonance) spectroscopy, high resolution mass spectrometry, and X-ray analysis. It was found that in the presence of Cu2+ copper cations, a spatial transformation is observed and a stable isomer is formed. Isomers are molecules with the same atomic composition, but different spatial structure. The interest lies in the fact that the isomers differ in terms of their properties and activity. The scientists used quantum-chemical calculations to explain the mechanism of the transformation they had discovered. The results of electromechanical studies showed that the synthesized molecules possess antioxidant activity, which means they are able to slow down the process of oxidation. They are also able to bind to receptors that protect the body from oxidation. "We have examined the effect of selenium on the activity of the synthesized molecules. The next step is to investigate the pharmacological potential of the most active molecules in vivo and in vitro," said Yan Ivanenkov, the head of the Laboratory of Medical Chemistry and Bioinformatics, when commenting on the prospects of the research. The results of the study highlighted the important role of selenium in the structure of hydantoin derivatives. Structural modification such as this has a significant influence on the spectrum of biological activity and properties of the molecules. Explore further: Scientists find new way to detect ortho-para conversion in water More information: Yan A. Ivanenkov et al. Synthesis, isomerization and biological activity of novel 2-selenohydantoin derivatives, Bioorganic & Medicinal Chemistry (2016). DOI: 10.1016/j.bmc.2015.12.050

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