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News Article | April 20, 2017
Site: www.biosciencetechnology.com

“Inhale deeply ... and exhale.” This is what a test for lung cancer could be like in future. Scientists at the Max Planck Institute for Heart and Lung Research in Bad Nauheim have developed a method that can detect the disease at an early stage. To this effect, they investigated the presence of traces of RNA molecules that are altered by cancer growth. In a study on healthy volunteers and cancer patients, the breath test correctly determined the health status of 98 percent of the participants. The method will now be refined in cooperation with licensing partners so that it can be used for the diagnosis of lung cancer. Most lung cancer patients die within five years of diagnosis. One of the main reasons for this is the insidious and largely symptom-free onset of the disease, which often remains unnoticed. In the USA, high-risk groups, such as heavy smokers, are therefore routinely examined by CAT scan. However, patients can be wrongly classified as having the disease. Together with cooperation partners, researchers at the Max Planck Institute for Heart and Lung Research have now developed a breath test that is much more accurate. In their research, the diagnosis of lung cancer was correct in nine out of ten cases. The method is therefore reliable enough to be used for the routine early detection of lung cancer. The researchers analyzed RNA molecules released from lung tissue into expired breath, noting differences between healthy subjects and lung cancer patients. Unlike DNA, the RNA profile is not identical in every cell. Several RNA variants, and therefore different proteins, can arise from one and the same DNA segment. In healthy cells, such variants are present in a characteristic ratio. The scientists discovered that cancerous and healthy cells contain different amounts of RNA variants of the GATA6 and NKX2 genes. Cancer cells resemble lung cells in the embryonic stage. The researchers developed a method to isolate RNA molecules. Not only is their concentration in expired breath extremely low, but they are also frequently highly fragmented. The researchers then investigated the RNA profile in subjects with and without lung cancer and from these data established a model for diagnosing the disease. In a test of 138 subjects whose health status was known, the test was able to identify 98 percent of the patients with lung cancer. 90 percent of the detected abnormalities were in fact cancerous. “The breath test could make the detection of early-stage lung cancer easier and more reliable, but it will not completely supplant conventional techniques,” says Guillermo Barreto, a Working Group Leader at the Max Planck Institute in Bad Nauheim. “However, it can complement other techniques for detecting early cancer stages and reduce false-positive diagnoses.” The scientists will contribute to future large-scale clinical trials. Together with the technology transfer organization Max Planck Innovation, they are seeking licensing partners to develop the breath test to maturity and market it. They also hope to use RNA profiles for the early detection of other diseases. Tiny changes could produce tissue profiles, akin to an RNA fingerprint, that reveal diseased cells and allow for rapid treatment.


News Article | April 21, 2017
Site: www.rdmag.com

A new potential early-stage lung cancer detection method has emerged, which focuses on changes in the composition of the breath In a Max Planck Institute for Heart and Lung Research study comprised of 138 healthy volunteers and cancer patients, a breath test—which detected the presence of traces of RNA molecules that are altered by cancer growth— correctly determined the health status of 98 percent of participants. “The breath test could make the detection of early-stage lung cancer easier and more reliable, but it will not completely supplant conventional techniques,” Guillermo Barreto, a Working Group Leader at the Max Planck Institute, said in a statement. “However, it can complement other techniques for detecting early cancer stages and reduce false-positive diagnoses.” The researchers analyzed RNA molecules from lung tissue into expired breath, which is not identical in every cell. The research team observed that cancerous and healthy cells contain different amounts of GATA6 and NKX2 genes, RNA variants. The researchers were able to isolate RNA molecules, which have an extremely low concentration in expired breath but are also frequently highly fragmented. Lung cancer is known for its insidious and largely symptom-free onset, which often remains unnoticed, causing the majority of lung cancer patients to pass away within five years of the diagnosis. According to the study, lung cancer is the leading cause of cancer-related deaths worldwide. High-risk groups, including heavy smokers, are routinely given CAT scans in the U.S., but patients can also be wrongly classified as having the disease from this method. Scientists will now contribute to future clinical trials, while seeking licensing partners to develop the breath test to maturity and market it with the Max Planck Innovation, a technology transfer organization. The researchers will also attempt to use RNA profiles for the early detection of other diseases, making tiny changes to produce tissue profiles that reveal diseased cells and allow for rapid treatment. The study was published in EMBO Molecular Medicine.


News Article | April 21, 2017
Site: www.rdmag.com

A new potential early-stage lung cancer detection method has emerged, which focuses on changes in the composition of the breath In a Max Planck Institute for Heart and Lung Research study comprised of 138 healthy volunteers and cancer patients, a breath test—which detected the presence of traces of RNA molecules that are altered by cancer growth— correctly determined the health status of 98 percent of participants. “The breath test could make the detection of early-stage lung cancer easier and more reliable, but it will not completely supplant conventional techniques,” Guillermo Barreto, a Working Group Leader at the Max Planck Institute, said in a statement. “However, it can complement other techniques for detecting early cancer stages and reduce false-positive diagnoses.” The researchers analyzed RNA molecules from lung tissue into expired breath, which is not identical in every cell. The research team observed that cancerous and healthy cells contain different amounts of GATA6 and NKX2 genes, RNA variants. The researchers were able to isolate RNA molecules, which have an extremely low concentration in expired breath but are also frequently highly fragmented. Lung cancer is known for its insidious and largely symptom-free onset, which often remains unnoticed, causing the majority of lung cancer patients to pass away within five years of the diagnosis. According to the study, lung cancer is the leading cause of cancer-related deaths worldwide. High-risk groups, including heavy smokers, are routinely given CAT scans in the U.S., but patients can also be wrongly classified as having the disease from this method. Scientists will now contribute to future clinical trials, while seeking licensing partners to develop the breath test to maturity and market it with the Max Planck Innovation, a technology transfer organization. The researchers will also attempt to use RNA profiles for the early detection of other diseases, making tiny changes to produce tissue profiles that reveal diseased cells and allow for rapid treatment. The study was published in EMBO Molecular Medicine.


Today, it is not clear how the impact of research on other areas of society than science should be measured. While peer review and bibliometrics have become standard methods for measuring the impact of research in science, there is not yet an accepted framework within which to measure societal impact. Alternative metrics (called altmetrics to distinguish them from bibliometrics) are considered an interesting option for assessing the societal impact of research, as they offer new ways to measure (public) engagement with research output. Altmetrics is a term to describe web-based metrics for the impact of publications and other scholarly material by using data from social media platforms (e.g. Twitter or Mendeley). This overview of studies explores the potential of altmetrics for measuring societal impact. It deals with the definition and classification of altmetrics. Furthermore, their benefits and disadvantages for measuring impact are discussed. © 2014 Elsevier Ltd.


Mueller-Langer F.,Max Planck Innovation
Health Economics, Policy and Law | Year: 2013

Infectious diseases are among the main causes of death and disability in developing countries, and they are a major reason for the health disparity between rich and poor countries. One of the reasons for this public health tragedy is a lack of lifesaving essential medicines, which either do not exist or badly need improvements. In this article, we analyse which of the push and pull mechanisms proposed in the recent literature may serve to promote research into neglected infectious diseases. A combination of push programmes that subsidise research inputs through direct funding and pull programmes that reward research output rather than research input may be the appropriate strategy to stimulate research into neglected diseases. On the one hand, early-stage (basic) research should be supported through push mechanisms, such as research grants or publicly financed research institutions. On the other hand, pull mechanisms, such as prize funds that link reward payments to the health impacts of effective medicines, have the potential to stimulate research into neglected diseases. Copyright © Cambridge University Press 2013.


Bornmann L.,Max Planck Innovation | Leydesdorff L.,University of Amsterdam
Journal of Informetrics | Year: 2013

The data of F1000 and InCites provide us with the unique opportunity to investigate the relationship between peers' ratings and bibliometric metrics on a broad and comprehensive data set with high-quality ratings. F1000 is a post-publication peer review system of the biomedical literature. The comparison of metrics with peer evaluation has been widely acknowledged as a way of validating metrics. Based on the seven indicators offered by InCites, we analyzed the validity of raw citation counts (Times Cited, 2nd Generation Citations, and 2nd Generation Citations per Citing Document), normalized indicators (Journal Actual/Expected Citations, Category Actual/Expected Citations, and Percentile in Subject Area), and a journal based indicator (Journal Impact Factor). The data set consists of 125 papers published in 2008 and belonging to the subject category cell biology or immunology. As the results show, Percentile in Subject Area achieves the highest correlation with F1000 ratings; we can assert that for further three other indicators (Times Cited, 2nd Generation Citations, and Category Actual/Expected Citations) the "true" correlation with the ratings reaches at least a medium effect size. © 2012 Elsevier Ltd.


Bornmann L.,Max Planck Innovation
Journal of Informetrics | Year: 2013

Bibliometrics has become an indispensable tool in the evaluation of institutions (in the natural and life sciences). An evaluation report without bibliometric data has become a rarity. However, evaluations are often required to measure the citation impact of publications in very recent years in particular. As a citation analysis is only meaningful for publications for which a citation window of at least three years is guaranteed, very recent years cannot (should not) be included in the analysis. This study presents various options for dealing with this problem in statistical analysis. The publications from two universities from 2000 to 2011 are used as a sample dataset (n= 2652, univ 1= 1484 and univ 2= 1168). One option is to show the citation impact data (percentiles) in a graphic and to use a line for percentiles regressed on 'distant' publication years (with confidence interval) showing the trend for the 'very recent' publication years. Another way of dealing with the problem is to work with the concept of samples and populations. The third option (very related to the second) is the application of the counterfactual concept of causality. © 2013 Elsevier Ltd.


Bornmann L.,Max Planck Innovation
Journal of the American Society for Information Science and Technology | Year: 2013

Since the 1990s, the scope of research evaluations becomes broader as the societal products (outputs), societal use (societal references), and societal benefits (changes in society) of research come into scope. Society can reap the benefits of successful research studies only if the results are converted into marketable and consumable products (e.g., medicaments, diagnostic tools, machines, and devices) or services. A series of different names have been introduced which refer to the societal impact of research: third stream activities, societal benefits, societal quality, usefulness, public values, knowledge transfer, and societal relevance. What most of these names are concerned with is the assessment of social, cultural, environmental, and economic returns (impact and effects) from results (research output) or products (research outcome) of publicly funded research. This review intends to present existing research on and practices employed in the assessment of societal impact in the form of a literature survey. The objective is for this review to serve as a basis for the development of robust and reliable methods of societal impact measurement. © 2012 ASIS&;T.


Bornmann L.,Max Planck Innovation
Journal of the American Society for Information Science and Technology | Year: 2013

According to current research in bibliometrics, percentiles (or percentile rank classes) are the most suitable method for normalizing the citation counts of individual publications in terms of the subject area, the document type, and the publication year. Up to now, bibliometric research has concerned itself primarily with the calculation of percentiles. This study suggests how percentiles (and percentile rank classes) can be analyzed meaningfully for an evaluation study. Publication sets from four universities are compared with each other to provide sample data. These suggestions take into account on the one hand the distribution of percentiles over the publications in the sets (universities here) and on the other hand concentrate on the range of publications with the highest citation impact - that is, the range that is usually of most interest in the evaluation of scientific performance. © 2013 ASIS&T.


Bornmann L.,Max Planck Innovation
Journal of Informetrics | Year: 2014

Can altmetric data be validly used for the measurement of societal impact? The current study seeks to answer this question with a comprehensive dataset (about 100,000 records) from very disparate sources (F1000, Altmetric, and an in-house database based on Web of Science). In the F1000 peer review system, experts attach particular tags to scientific papers which indicate whether a paper could be of interest for science or rather for other segments of society. The results show that papers with the tag "good for teaching" do achieve higher altmetric counts than papers without this tag - if the quality of the papers is controlled. At the same time, a higher citation count is shown especially by papers with a tag that is specifically scientifically oriented ("new finding"). The findings indicate that papers tailored for a readership outside the area of research should lead to societal impact.If altmetric data is to be used for the measurement of societal impact, the question arises of its normalization. In bibliometrics, citations are normalized for the papers' subject area and publication year. This study has taken a second analytic step involving a possible normalization of altmetric data. As the results show there are particular scientific topics which are of especial interest for a wide audience. Since these more or less interesting topics are not completely reflected in Thomson Reuters' journal sets, a normalization of altmetric data should not be based on the level of subject categories, but on the level of topics. © 2014 Elsevier Ltd.

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