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Happy Fourth of July

Parachutist with American flag

(A. Kotok)

Science & Enterprise is celebrating today’s Independence Day holiday in the U.S., and will return to regular posting on Monday, 7 July. Enjoy your day or holiday, as the case may be.

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Big Data Quickly Identify Foodborne Illness Sources

Pins on a map (CJ Sorg/Flickr)

(CJ Sorg/Flickr)

3 July 2014. Data analysts and public health experts at the IBM research center in San Jose, California developed techniques for faster identification of sources of foodborne diseases from available public health and retail sales data. The team led by IBM’s James Kaufman, the company’s public health research manager, published its findings today online in the journal PLOS Computational Biology.

Kaufman, with colleagues from IBM, Johns Hopkins University in Baltimore, and the Federal Institute for Risk Assessment in Berlin, Germany addressed a growing problem of finding the sources of contaminated food faster to prevent outbreaks from spreading. In the U.S. alone, Centers for Disease Control and Prevention estimates foodborne illnesses strike 1 in 6 Americans each year or 48 million people, causing 128,000 hospitalizations, and 3,000 deaths. The authors cite sources calculating medical costs worldwide for foodborne illnesses at $9 billion a year and indirect economic costs (e.g., lost work time) at $75 billion.

The techniques designed by the researchers start with reports of contaminated food illnesses and corresponding lab analyses issued by public health authorities, which when used alone can take days or weeks to identify sources of the outbreaks. The researchers added in sales data from food retailers, captured in standard product and packaging codes. When arrayed against geo-coded food-related illness reports, the combination of outbreak and sales data begins to form a clearer picture of potential sources. Up to now, food sales data, collected routinely by retailers, were not used in this way.

The team adapted a statistical technique called receiver-operating characteristic analysis first used in identifying radar blips in World War II, and since expanded into many fields including epidemiology and bioinformatics. The technique classifies subjects into one of two conditions — e.g., contaminated or not contaminated — which enables construction of statistical tests and graphical models.

Applying this technique enabled the team to estimate the likelihood of individual food items causing the outbreaks, in effect, learning from the data and recalculating the probability of each food item causing the outbreak, as new data were introduced. The results could then be displayed geographically.

The researchers tested the technique in a simulation with real-world data from a German retailer, providing weekly sales of 580 food items over a three-year period sold throughout Germany, matched against 60,000 food illness outbreaks. The results show it is possible with this technique to identify likely culprits in the sales data causing the outbreaks from as few as 10 outbreak reports, although the probabilities rise when the numbers increase to 20 or 50 reports.

“Predictive analytics based on location, content, and context are driving our ability to quickly discover hidden patterns and relationships from diverse public health and retail data,” says Kaufman in an IBM statement. “We are working with our public health clients and with retailers in the U.S. to scale this research prototype and begin focusing on the 1.7 billion supermarket items sold each week in the United States.”

In the following video, Kaufman tells more about the study.

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Trial: Insulin Pumps Better Control Glucose Than Injections

Paradigm Veo (Medtronic, U.K.)

Paradigm Veo (Medtronic, U.K.)

3 July 2014. An international clinical trial shows insulin pumps worn by people with type 2 diabetes do a better job of controlling blood glucose levels than multiple daily injections of insulin, the usual control treatment. Results from the post-marketing study funded by Medtronic Inc., a medical device developer in Minneapolis that makes insulin pumps, appear today online in the journal The Lancet (paid subscription required).

Type 2 diabetes is a chronic condition where the body fails to produce enough insulin that regulates the flow of glucose or sugar into cells, or resists the effects of insulin. For advanced cases of the disease where diet and exercise are not enough to control blood glucose, patients need medications or insulin therapy.

The usual method for providing insulin in these cases is with multiple daily injections, but insulin pumps — originally developed for people with inherited or type 1 diabetes — are being considered as an alternative. Insulin pumps are small, wearable computer-controlled devices that feed insulin in a continuous flow or short-term busts at meal time through a catheter into the body to emulate a normal body’s release of insulin. Controlled comparative effectiveness studies of insulin pumps versus injections, however, have so far not produced conclusive results.

This clinical trial, conducted after regulatory approval of Medtronic’s insulin pump, aimed to provide more solid evidence. The study enrolled 331 patients with type 2 diabetes and not able to adequately control their blood glucose levels despite receiving multiple daily injections of insulin.

Patients were recruited at 36 medical centers in the U.S., Canada, Europe, Israel, and South Africa, and selected at random to either wear a Medtronic insulin pump or continue with injections. The researchers looked primarily at patients’ ability to reduce blood glucose levels over 6 months in a standard test known as A1c, but also measured variability in glucose levels and weight loss, as well as safety issues such as episodes of severe hypoglycemia, where glucose levels fall too low.

The findings show on the main measure, patients with insulin pumps reduced their blood glucose levels an average of 1.1 percent after 6 months, compared to 0.4 percent for the injection patients, a statistically reliable difference. More than half (55%) of participants wearing insulin pumps were able to reduce their blood glucose levels to the target range, under 8 percent, compared to 28 percent of the participants receiving injections. In addition, patients wearing insulin pumps were able after 6 months to receive a daily amount of insulin 20 percent lower than patients receiving injections.

The amount of weight loss was about the same for both groups of patients. On safety issues, the number of adverse events during the trial were few and about the same between the two groups: 2 cases of blood sugar levels rising too high, requiring hospitalization, occurred in the insulin pump group, while 1 case of hypoglycemia occurred in the injection group.

“This patient population is sizable and difficult to manage, which frequently results in costly complications,” says study leader Yves Reznik of University Hospital in Caen, France in a Medtronic statement, “These trial results are important in showing that insulin pump therapy can safely reduce A1c without causing hypoglycemic episodes.”

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University Offers Tuberculosis Drug Technology for Licensing

Mycobacterium tuberculosis bacteria (CDC)

Mycobacterium tuberculosis bacteria (CDC)

2 July 2014. A new process for developing drugs for tuberculosis designed at ETH Zurich, the Swiss Federal Institute of Technology, is offered for licensing by the university to companies for commercialization. The technology that aims to overcome resistance to many current tuberculosis drugs is the result of research from the lab of Zurich pharmaceutical biology professor Karl-Heinz Altmann.

While the number of cases of tuberculosis is falling worldwide, World Health Organization reports in 2012, some 8.6 million new cases of TB with 1.3 million deaths. Many of the cases occur in people with HIV, with 320,000 deaths in 2012 reported among people who are HIV-positive. While TB occurs more often in men than women, the number of TB deaths among women with HIV were about the same as men in 2012.

A key problem in eradicating tuberculosis is the ability of the TB pathogen Mycobacterium tuberculosis to become resistant to many antibiotics given to patients. This resistance often arises from the lengthy course of treatment, about 6 months, patients are required to follow. For many patients, symptoms disappear after a few weeks, which tempts them to discontinue taking their medications. As a result, the TB pathogen remains in the body and builds a resistance to the drugs.

The growing resistance to antibiotics contributes to a reluctance among many pharmaceutical companies to develop new drugs. Altmann’s team takes a different approach to TB, but one that is based on an older drug, pyridomycin, first discovered in the 1950s. While the drug was derived from natural, non-pathogenic soil bacteria, it lacked the stability to effectively fight the disease, and was abandoned as a TB therapy.

The Zurich researchers, with colleagues from EPFL in Lausanne, Switzerland, discovered the crystalline structure of pyridomycin gave it an ability to block a key enzyme in the TB bacteria, called InhA, from working in two different ways, weakening the bacteria and making it easier to destroy. This double action reduces the risk of the bacteria becoming resistant, since it would need to adapt to both types of attack simultaneously.

The technology developed by Altmann and colleagues developed a synthetic scaffold resembling the crystal structure of pyridomycin, which their research shows maintains the ability to bind to the InhA target and weaken the TB bacteria. The researchers say this framework can be enhanced with other compounds for treating TB.

ETH Zurich’s technology transfer office says the university applied for a patent on the synthetic scaffold technology, which is available for development into TB treatments.

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Solar Process Converts CO2 to Source of Power, Chemicals

Andrew Bocarsly

Andrew Bocarsly (Brian Wilson, Princeton University)

2 July 2014. Chemists from Princeton University and spin-off company Liquid Light Inc. in Monmouth Junction, New Jersey created a process to use sunlight for converting carbon dioxide into formic acid, a source for electric power and industrial chemicals. Princeton chemistry professor Andrew Bocarsly, also a founder of Liquid Light, and colleagues published their findings last month in the Journal of CO2 Utilization (paid subscription required).

Formic acid, also known as methanoic acid, is a naturally occurring hydrocarbon used as a preservative and antibacterial agent, but also as a catalyst for industrial chemicals, and more recently studied as a potential source for hydrogen fuel cells. Bocarsly’s lab and Liquid Light are seeking ways to convert CO2 from waste processes into useful outputs, to reduce greenhouse gas emissions and  — for Liquid Light — as a commercial opportunity.

The researchers devised a stack of three cells with electrodes made of indium and iridium oxide. The cells were housed inside metal plates the size of lunch boxes, with channels to carry liquids. Public Service Electric and Gas, a New Jersey power company, provided a commercial solar panel used on its power line poles. The cells convert supplied CO2 into formic acid as an alternative transportation and stationary fuel source.

Tests of the cells show it could generate a solar-to-fuel conversion efficiency exceeding 1.8 percent. According to the authors, this is the highest efficiency rate yet recorded for a lab device and twice the rate of natural photosynthesis. In addition to the commercial solar panel, say the authors, the system’s conversion cells used easily obtained parts.

Liquid Light’s main business is low-energy and low-cost conversion of CO2 emitted in high concentrations from factories making fertilizers and cement into chemicals, such as ethylene glycol for producing polyester fibers and polyethylene resins in plastic bottles. In addition to feeding fuel cells, formic acid is easily converted into formate salts, a less corrosive and more environmentally friendly chemical for de-icing airport runways, providing another potential product line for the company.

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Health Quality Agency: Vaccines Safe, Adverse Effects Rare

Vaccination (U.S. Army Corps of Engineers)

(U.S. Army Corps of Engineers)

1 July 2014. The Agency for Healthcare Research and Quality, a division of the U.S. Department of Health and Human Services, issued a report today indicating a systematic review of published research shows that vaccines are safe and serious adverse reactions to vaccines are rare occurrences. The study, conducted by the Southern California Evidence-Based Practice Center, a consortium of the Rand Corporation in Santa Monica and four California universities, was also published online today in the journal Pediatrics.

Despite the record of vaccines preventing millions of occurrences diseases like polio and measles, increasing numbers of parents in the U.S. are opting out of having their children vaccinated. In addition, target immunization levels for adolescents, pregnant women, and adults overall have still not been reached. Despite voluminous evidence to the contrary, concerns among some parents persist over the safety of vaccines, particularly the link between the measles-mumps-rubella vaccine and autism.

The authors note that parental refusals to have their children vaccinated are associated with recent outbreaks of measles and whooping cough. In addition, Centers for Disease Control and Prevention reported in May that the number of measles cases reached a 20-year high, with nearly all cases the result of international travel by unvaccinated people.

The research team from Rand Corp., UCLA, and Boston Children’s Hospital compiled reports of published studies archived in PubMed, reviews of published studies, information packets from vaccine manufacturers, package inserts, and a 2011 report from the Institute of Medicine that reviewed 1,000 studies and found few health problems caused by or even associated with vaccines. The collection process yielded nearly 20,500 studies on vaccines, from which they identified 67 discussing adverse effects. The researchers then evaluated the adverse effects reported on a standard McMaster Quality Assessment of Harms, abbreviated McHarms scale.

The results show strong scientific evidence of no association between common vaccines and rumored adverse outcomes believed by some parents and circulating on the Internet. Among the findings with strong evidence are no connection found between the measles-mumps-rubella vaccine and autism. The researchers also found no connection between vaccines for pneumonia or influenza and cases of heart condition or stroke among the elderly. Likewise, the team found no association between a range of vaccines — including measles-mumps-rubella, diphtheria, tetanus, whooping cough, and hepatitis B — and childhood leukemia.

In addition, the researchers found strong evidence, but not quite as conclusive, that there are no connections between human papillomavirus (HPV) vaccines and stroke, seizures, appendicitis, deep vein thrombosis, and the onset of type 1 diabetes and juvenile arthritis. Similar strength of evidence was found showing no association between inactivated flu vaccines and adverse pregnancy outcomes, such as miscarriage, low birth weight, and premature birth, among women who are vaccinated while pregnant.

The literature did show rare occurrences of adverse effects from vaccines, such as cases of Guillain-Barré Syndrome resulting from the 2009 H1N1 flu vaccine. The number of cases reported, however, were low: only 1.6 cases per 1 million people vaccinated.

While the findings may allay some fears by parents about links between vaccines and adverse effects, the authors suggest instituting a stronger surveillance system, taking advantage of electronic health records and vaccine safety reports maintained by managed care organizations and other large health care providers.

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Univ at Buffalo Starting Advanced Materials Research Center

Graphene coated steel and uncoated steel (University at Buffalo)

Steel coated with a graphene compound, in foreground, remains rust-free, while and the uncoated steel in the background accumulates rust. (University at Buffalo)

1 July 2014. University at Buffalo in New York is establishing a new materials research department that aims to accelerate the process of bringing advanced materials to market. Buffalo’s Materials Design and Innovation department is a joint project of the university’s engineering and Arts and Science schools, and funded in part by donation of $1.5 million from former National Science Foundation director Erich Bloch.

A key part of the Materials Design and Innovation program is the application of computational tools to speed the design and lower the cost of developing new materials. The department plans to combine computational tools with bench science in its research, as well as train future materials scientists and engineers in these techniques. The connection between computational tools and materials is already found on campus in the New York State Center of Excellence in Materials Informatics, which has close ties to industry.

The Materials Design and Innovation department expects to draw from its current faculty in computer science, physics, chemistry, mechanical engineering, environmental engineering, electrical engineering, biomedical engineering, and chemical and biological engineering. The department will first grant master and Ph.D. degrees, and add undergraduate degrees later. The university says it plans to hire 12 tenure-track faculty for the department, but did not give a schedule for those hires.

The department chair will be an endowed position funded by Erich Bloch, a 1952 Buffalo engineering graduate and director of National Science Foundation from 1984 to 1990. Bloch is donating $1.5 million for the position. According to his official NSF biography, Bloch “made the improvement of U.S. economic competitiveness a major agenda item of the NSF. He encouraged funding for high-risk, but potentially revolutionary research.”

The Materials Design and Innovation research agenda is expected to study the design of new materials that apply nanotechnology for advances in electronics, wearable devices, and transportation. Faculty also anticipate studying reduction of costs of materials for manufacturing, and minimizing waste and environmental impact.

Part of the inspiration for the Materials Design and Innovation department is the federal Materials Genome Initiative that aims to at least double the pace of discovering advanced materials and bringing them to market, while lowering their costs. The department also plans to align its program with state initiatives aiming to increase economic development in western New York.

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Online Clinical Trial with Children Tests Autism Therapy

Three girls in front of a computer screen

(San José Library/Flicker)

30 June 2014. Researchers at University of California in San Francisco and Kennedy Krieger Institute in Baltimore completed a clinical trial conducted entirely online testing the ability of omega-3 fatty acids to control hyperactivity in children with autism. The team led by UC-San Francisco medical professor Stephen Bent published its findings in this month’s issue of Journal of the American Academy of Child & Adolescent Psychiatry (paid subscription required).

The intermediate-stage trial was designed to test the effects of omega-3 fatty acids on hyperactivity of children, age 5 to 8, diagnosed with autism. Omega-3 fatty acids are considered essential nutrients for many bodily functions, such as normal blood clotting and building cell membranes in the brain. The body does not make omega-3 fatty acids on it own, thus they’re provided in food.

Early, preclinical evidence shows a link between omega-3 fatty acids and symptoms of attention deficit/hyperactivity disorder, or ADHD. This trial tested that association among children with autism. Half of the sample of 57 children, selected at random, were given a daily pudding packet with 1.3 grams of omega-3 fatty acids for 6 weeks, while the other half of the sample received an identically flavored placebo with safflower oil.

The trial looked primarily for changes in hyperactivity, measured by a series of 16 items from a larger 58-item aberrant behavior checklist. The researchers measured other symptoms as well, such as lethargy, irritability, and inappropriate speech.

The 57 children from 28 states in the U.S. taking part in the trial were recruited in about 6 weeks from the Interactive Autism Network, an online community of parents of children with autism hosted by Kennedy Krieger Institute. The parents were alerted of the study and recruited by e-mail, with all screening, informed consent, and outcome measures conducted over the Internet. Screening was accomplished with a short questionnaire completed by parents that verified their children received a professional diagnosis of autism, which eliminated the need for children and parents making a preliminary clinical visit.

Both the children’s parents and teachers completed the behavior questionnaire items online, which captured the data immediately in a database. The results show children taking omega-3 fatty acids with lower hyperactivity scores than the comparable group taking a placebo, but the differences were not large enough to be statistically reliable.

Despite the the lack of unambiguous results, the researchers were pleased with conduct of an online clinical trial. “The entire study was completed in slightly more than three months from the start of enrollment,” says Bent in a university statement, “and demonstrates there are many advantages including low cost, rapid enrollment, high completion rate, convenience for participating families, and the ability to participate from virtually any location.”

Bent adds that the researchers received 100 percent completion of the outcome measures from parents and teachers, which he says engages parents at a higher rate than in traditional clinical trials.

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Spin-Off Licenses Genomic Technology from Wash. University

DNA strand (


30 June 2014. PierianDx, a new company formed by medical faculty and practitioners at Washington University in St. Louis, licensed genomic technology from the university to commercialize diagnostic tools for personalized medicine. Financial details of the licensing deal were not disclosed.

The start-up company plans to offer the technology in a system developed internally by Washington University’s medical labs for sequencing a patient’s DNA to determine an individualized course of treatment. The system, called the Clinical Genomicist Workstation, has been in use by Washington University since 2011.

The system, says PierianDx, combines high-throughput genomic sequencing with analytic software, access to bioinformatic databases, and integration with a patient’s electronic medical records. High-throughput sequencing uncovers the precise order of nucleotides, or organic molecules in DNA that make up an individual’s genome. This sequence of nucleotides can identify genes and mutations causing disease.

Advances in genomic research, along with access to greater computer power, are making sequencing of entire genomes less expensive, and thus more widely available for research and diagnostics. National Human Genome Research Institute estimates, as of January 2014, sequencing a single human genome costs about $4,000. Three years earlier, that cost was estimated $21,000, and three years before that about $3,000,000.

PierianDx aims to make the genomic workstation available to clinical labs seeking an in-house sequencing capability, rather than relying on an outside service. The system uses software to call on data in online genomic databases for review by the patient’s physician. The company says the system uses industry standard HL7 message connections, to enable a patient’s electronic health record to access the report.

PierianDx was founded by geneticists and medical practitioners from Washington University, including Rakesh Nagarajan, professor of pathology and genetics, and Catherine Cottrell, medical director of genomics and pathology services. Nagarajan is the company’s chief biomedical informatics officer, and Cottrell serves as a medical advisor to the company.

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Big Data Analytics ID People Risking Metabolic Syndrome

Calculator keys (


27 June 2014. Researchers from the insurance provider Aetna Inc. and GNS Healthcare, a data analytics company in the health care industry, developed statistical models that can identify population groups and individuals at risk for metabolic syndrome, a collection of conditions pointing to future heart disorders and diabetes. The team from Aetna’s Innovation Labs in Hartford, Connecticut and GNS Healthcare in Cambridge, Massachusetts published its findings yesterday online in the American Journal of Managed Care.

Metabolic syndrome is the name given to five related conditions which, when taken together, substantially raise the risk of an individual developing heart disease, stroke, or diabetes. The factors are a large waistline from excess fat in the stomach area, high triglyceride levels, low high-density lipoprotein (HDL or “good”) cholesterol, high blood pressure, and high fasting blood sugar considered an early indicator of diabetes.

Any one of the five metabolic syndrome factors increases the risk of heart disease, stroke, or diabetes, but individuals with more than one of these conditions are considered at higher risk, with the risk increasing as the number of factors increases. The authors cite recent studies showing one-third of U.S. adults — about 80 million people — meet the criteria for metabolic syndrome, with an additional 45 percent with 1 or 2 risk factors for metabolic syndrome.

The researchers analyzed some 37,000 medical records of workers from employers with Aetna health plans who voluntarily took part in metabolic syndrome screening programs in 2011 and 2012. Data collected include insurance eligibility records, medical claims, pharmacy claims, demographics, and lab tests, as well as metabolic syndrome screening results and health risk assessment responses.

With this data set, the researchers applied GNS Healthcare’s analytical platform it calls reverse engineering and forward simulation or Refs. GNS Healthcare says the reverse engineering part of Refs extracts network models from large sets of data with an algorithm that samples successively from a target population. Each sample taken is dependent on the previous sample, thus enabling the algorithm to learn more about the population with each subsequent sample. The company uses a variation of this technique, called the Metropolis algorithm (named after its inventor, not a location), that allows Refs to take random samples from complex distributions, such as those found in health care.

The forward simulation part of Refs tests these models for causation by asking questions of the data about specific interventions. The simulations return probabilities of success, thus the name Monte Carlo given by statisticians to this simulation technique. GNS Healthcare says its use of Monte Carlo simulations makes it possible to return confidence intervals — i.e., margins of error — for each probability.

The analysis focused on two major queries for the data set:

- Predict the probability of each of the five metabolic syndrome variables occurring in individual subjects, based only on claims data.

- Indicate the likelihood of individual subjects improving, staying the same, or getting worse on each metabolic syndrome variable.

The researchers report being able to construct detail risk profiles for the population as a whole and individual subjects, with the calculation of a percentage probability for members developing the five metabolic syndrome risk factors. Calculations include probabilities of developing specific risk factors in the future, based on an individual’s current risk profile.

The models developed in the study also made it possible to test possible interventions to reduce an individual’s risk of developing metabolic syndrome. The researchers found reducing waist size and blood glucose levels return the largest benefits in lowering risks of metabolic syndrome and cutting medical costs. In addition, scheduling a visit to a primary care physician lowers the probability of developing metabolic syndrome in the next year by almost 90 percent.

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