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Archive for the ‘Statistical Methods for Research Evaluation’ Category

Larry H Bernstein, MD, FACP, Reporter

Clinical Trials
Dr. Eric Topol, Director of the Scripps Translational Science Institute and Editor-in-Chief of Medscape Genomic Medicine and the heart.org.
In our series The Creative Destruction of Medicine, I’m trying to get into critical aspects of how we can Schumpeter or reboot the future of healthcare by leveraging the big innovations that are occurring in the digital world, including digital medicine.

But one of the things that has been missed along the way is that how we do clinical research will be radically affected as well. We have this big thing about evidence-based medicine and, of course, the sanctimonious randomized, placebo-controlled clinical trial. Well, that’s great if one can do that, but often we’re talking about needing thousands, if not tens of thousands, of patients for these types of clinical trials. And things are changing so fast with respect to medicine and, for example, genomically guided interventions that it’s going to become increasingly difficult to justify these very large clinical trials.

For example, there was a drug trial for melanoma and the mutation of BRAF, which is the gene that is found in about 60% of people with malignant melanoma. When that trial was done, there was a placebo control, and there was a big ethical charge asking whether it is justifiable to have a body count. This was a matched drug for the biology underpinning metastatic melanoma, which is essentially a fatal condition within 1 year, and researchers were giving some individuals a placebo.

Would we even do that kind of trial in the future when we now have such elegant matching of the biological defect and the specific drug intervention? A remarkable example of a trial of the future was announced in May.[1] For this trial, the National Institutes of Health is working with [Banner Alzheimer’s Institute] in Arizona, the University of Antioquia in Colombia, and Genentech to have a specific mutation studied in a large extended family living in the country of Colombia in South America. There is a family of 8000 individuals who have the so-called Paisa mutation, a presenilin gene mutation, which results in every member of this family developing dementia in their 40s.

Clinical Trials (journal)

Clinical Trials (journal) (Photo credit: Wikipedia)

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Reporter: Aviva Lev-Ari, PhD, RN

October 24, 2012

Sequoia Supercomputer Pumps Up Heart Research

Tiffany Trader


Cardioid code imageThe Cardioid code developed by a team of Livermore and IBM scientists divides the heart into a large number of manageable pieces, or subdomains. The development team used two approaches, called Voronoi (left) and grid (right), to break the enormous computing challenge into much smaller individual tasks.Source: LLNLThe world’s fastest computer has created the fastest computer simulation of the human heart.

The Lawrence Livermore National Laboratory‘s Sequoia supercomputer, a TOP500 chart topper, was built to handle top secret nuclear weapons simulations, but before it goes behind the classified curtain, it is pumping out sophisticated cardiac simulations.

Earlier this month, Sequoia, which currently ranks number one on the TOP500 list of the world’s fastest computer systems, received a 2012 Breakthrough Award from Popular Mechanics magazine. Now the magazine is reporting on Sequoia’s ground-breaking heart simulations.

Clocking in at 16.32 sustained petaflops (20 PF peak), Sequoia is taking modeling and simulation to new heights, enabling researchers to capture greater complexity in a shorter time frame. With this advanced capability, LLNL scientists have been able to simulate the human heart down to the cellular level and use the resulting model to predict how the organ will respond to different drug compounds.

Principal investigator Dave Richards couldn’t resist a little showboating: “Other labs are working on similar models for many body systems, including the heart,” he told Popular Mechanics. “But Lawrence Livermore’s model has one major advantage: It runs on Sequoia, the most powerful supercomputer in the world and a recent PM Breakthrough Award winner.”

The simulations were made possible by an advanced modeling program, calledCardioid, that was developed by a team of scientists from LLNL and the IBM T. J. Watson Research Center. The highly scalable code simulates the electrophysiology of the heart. It works by breaking down the heart into units; the smaller the unit, the more accurate the model.

Until now the best modeling programs could achieve 0.2 mm in each direction. Cardioid can get down to 0.1 mm. Where previously researchers could run the simulations for tens of heartbeats, Cardioid executing on Sequoia captures thousands of heartbeats.

Scientists are seeing 300-fold speedups. It used to take 45 minutes to simulate just one beat, but now researchers can simulate an hour of heart activity – several thousand heartbeats – in seven hours.

With the less sophisticated codes, it was impossible to model the heart’s response to a drug or perform an electrocardiogram trace for a particular heart disorder. That kind of testing requires longer run times, which just wasn’t possible before Cardioid.

The model could potentially test a range of drugs and devices like pacemakers to examine their affect on the heart, paving the way for safer and more effective human testing. But it is especially suited to studying arrhythmia, a disorder of the heart in which the organ does not pump blood efficiently. Arrhythmias can lead to congestive heart failure, an inability of the heart to supply sufficient blood flow to meet the needs of the body.

There are various types of medications that disrupt cardiac rhythms. Even those designed to prevent arrhythmias can be harmful to some patients, and researchers do not yet fully understand exactly what causes these negative side effects. Cardioid will enable LLNL scientists to examine heart function as an anti-arrhythmia drug enters the bloodstream. They’ll be able to identify when drug levels are highest and when they drop off.

“Observing the full range of effects produced by a particular drug takes many hours,” noted computational scientist Art Mirin of LLNL. “With Cardioid, heart simulations over this timeframe are now possible for the first time.”

The Livermore–IBM team is also working on a mechanical model that simulates the contraction of the heart and pumping of blood. The electrical and mechanical simulations will be allowed to interact with each other, adding more realism to the heart model.

It’s not entirely clear why a national defense lab took on this heart simulation work. Fred Streitz, director of the Institute for Scientific Computing Research at LLNL, would say only that “there are legitimate national security implications for understanding how drugs affect human organs,” adding that the project stretched the limits of supercomputing in a manner that is relatable to the American people.

The cardiac modeling work was performed during the system’s “shakedown period” – the set-up and testing phase – and the team had to hurry to finish in the allotted time span. Once Sequoia becomes classified, it’s unclear if it will still be available to run Cardioid and other unclassified programs, although access will certainly be more difficult since the machine’s principle mission is running nuclear weapons codes.

Sequoia is an integral part of the NNSA’s Advanced Simulation and Computing (ASC) program, which is run by partner organizations LLNL, Los Alamos National Laboratory and Sandia National Laboratories. With 96 racks, 98,304 compute nodes, 1.6 million cores, and 1.6 petabytes of memory, Sequoia will help the NNSA fulfill its mission to “maintain and enhance the safety, security, reliability and performance of the U.S. nuclear weapons stockpile without nuclear testing.”

The Cardioid simulation has been named as a finalist in the 2012 Gordon Bell Prize competition, awarded each year to recognize supercomputing’s crowning achievements. Research partners, Streitz, Richards, and Mirin, will reveal their results at the Supercomputing Conference in Salt Lake City, Utah, on November 13.

SOURCE:

http://www.hpcwire.com/hpcwire/2012-10-24/sequoia_supercomputer_pumps_up_heart_research.html

Human heart simulated on world’s fastest supercomputer

October 29, 2012 | By 

Before the U.S. government cloaks the operations of the Sequoia supercomputer for classified nuclear arms analyses, scientists have tapped the world’s fastest computer for an unprecedented simulation of the human heart. With the aid of the supercomputer, according to an HPC Wire report, researchers have been able to model the heart down to the cellular level and simulate how the organ would react to certain drugs.

The supercomputer has been performing simulations of the heart with a modeling program, Cardioid, from researchers at Lawrence Livermore National Laboratory (LLNL) and IBM’s T.J. Watson Research Center, HPC Wire reported. The computing power and capabilities of the modeling program have advanced heart modeling from simulations of a handful of heartbeats to thousands. It enables researchers to get closer to the real thing as they boost their capacity to capture activities in the heart at finer levels of detail and complexity.

Drugmakers have spent billions of dollars on studies to improve their understanding of the heart, and computer simulations offer a way for researchers to gauge the potential impacts of a compound before testing it in living subjects. Researchers believe that Cardioid could help them understand the activity and potential side effects of drugs for an inefficient heart-pumping condition known as an arrhythmia, which can trigger congestive heart failure and other medical problems.

“Observing the full range of effects produced by a particular drug takes many hours,” Art Mirin, an LLNL computational scientist, noted, as quoted by HPC Wire. “With Cardioid, heart simulations over this timeframe are now possible for the first time.”

SOURCE:

http://www.fiercebiotechit.com/story/human-heart-simulated-worlds-fastest-supercomputer/2012-10-29

 

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Benefits of Open Data for Economic Research

By Angela Guess on October 24, 2012 6:00 PM

Guo of OpenEconomics.net recently discussed the benefits of open data for economic research. He writes, “There used to be a time when data was costly: There was not much data around. Comparable GDP data, for example, has only been collected starting in the early mid 20th Century. Computing power was expensive and costly: Data and commands were stored on punch cards, and researchers only had limited hours to run their statistical analyses at the few computers available at hand.”

He goes on, “Today, however, statistics and econometric analysis has arrived in every office: Open Data initiatives at the World Bank and governments have made it possible to download cross-country GDP and related data using a few mouse-clicks. The availability of open source statistical packages such as R allows virtually everyone to run quantitative analyses on their own laptops and computers. Consequently, the number of empirical papers have increased substantially. The [above] figure (taken from Espinosa et al. 2012) plots the number of econometric (statistical) outputs per article in a given year: Quantitative research has really taken off since the 1960s. Where researchers used datasets with a few dozens of observations, modern applied econometricians now often draw upon datasets boasting millions of detailed micro-level observations.”

Image: Courtesy OpenEconomics

SOURCE:

http://semanticweb.com/benefits-of-open-data-for-economic-research_b32917

The Benefits of Open Data (part II) – Impact on Economic Research

October 21, 2012 in Open Economics

A couple of weeks ago, I wrote the first part of the three part series on Open Data in Economics. Drawing upon examples from top research that focused on how providing information and data can help increase the quality of public service provision, the article explored economic research on open data. In this second part, I would like to explore the impact of openness on economic research.

We live in a data-driven age

There used to be a time when data was costly: There was not much data around. Comparable GDP data, for example, has only been collected starting in the early mid 20th Century. Computing power was expensive and costly: Data and commands were stored on punch cards, and researchers only had limited hours to run their statistical analyses at the few computers available at hand.

Today, however, statistics and econometric analysis has arrived in every office: Open Data initiatives at the World Bank and governments have made it possible to download cross-country GDP and related data using a few mouse-clicks. The availability of open source statistical packages such as R allows virtually everyone to run quantitative analyses on their own laptops and computers. Consequently, the number of empirical papers have increased substantially. The left figure (taken from Espinosa et al. 2012) plots the number of econometric (statistical) outputs per article in a given year: Quantitative research has really taken off since the 1960s. Where researchers used datasets with a few dozens of observations, modern applied econometricians now often draw upon datasets boasting millions of detailed micro-level observations.

Why we need open data and access

The main economic argument in favour of open data is gains from trade. These gains come in several dimensions: First, open data helps avoid redundancy. As a researcher, you may know there are often same basic procedures (such as cleaning datasets, merging datasets) that have been done thousands of times, by hundreds of different researchers. You may also have experienced the time wasted compiling a dataset someone else already put together, but was unwilling to share: Open data in these cases can save a lot of time, allowing you to build upon the work of others. By feeding your additions back to the ecosystem, you again ensure that others can build on your data work. Just like there is no need to re-invent the wheel several times, the sharing of data allows researchers to build on existing data work and devote valuable time to genuinely new research.

Second, open data ensures the most efficient allocation of scarce resources – in this case datasets. Again, as a researcher, you may know that academics often treat their datasets as private gold mines. Indeed, entire research careers are often built on possessing a unique dataset. This hoarding often results in valuable data lying around on a forgotten harddisk, not fully used and ultimately wasted. What’s worse, the researcher – even though owning a unique dataset – may not be the most skilled to make full use of the dataset, while someone else may possess the necessary skills but not the data. Only recently, I had the opportunity to talk to a group of renown economists who – over the past decades – have compiled an incredibly rich dataset. During the conversation, it was mentioned that they themselves may have only exploited 10% of the data – and were urgently looking for fresh PhDs and talented researchers to unlock the full potential of the their data. But when data is open, there is no need to search, and data can be allocated to the most skilled researcher.

Finally, and perhaps most importantly, open data – by increasing transparency – also fosters scientific rigour: When datasets and statistical procedures are made available to everyone, a curious undergraduate student may be able to replicate and possibly refute the results of a senior researcher. Indeed, journals are increasingly asking researchers to publish their datasets along with the paper. But while this is a great step forward, most journals still keep the actual publication closed, asking for horrendous subscription fees. For example, readers of my first post may have noticed that many of the research articles linked could not be downloaded without a subscription or university affiliation. Since dissemination, replication and falsification are key features of science, the role of both open data and open access become essential to knowledge generation.

But there are of course challenges ahead: For example, while a wider access to data and statistical tools is a good thing, the ease of running regressions with a few mouse-clicks also results in a lot of mindless data mining and nonsensical econometric outputs. Quality control, hence, is and remains important. There are and in some cases also should be some barriers to data sharing. In some cases, researchers have invested a substantial time of their lives to construct their datasets, in which case it is understandable why some are uncomfortable to share their “baby” with just anyone. In addition, releasing (even anonymized) micro-level data often raises concerns of privacy protection. These issues – and existing solutions – will be discussed in the next post.

SOURCE:

http://openeconomics.net/2012/10/21/the-benefits-of-open-data-part-ii-impact-on-economic-research/

Advocacy for Open Access Publishing and the Economic Synergy obtained from Open Data

Anatomy of open access publishing: a study of longitudinal development and internal structure

Mikael Laakso* and Bo-Christer Björk

Author Affiliations

Hanken School of Economics, Helsinki, Finland

BMC Medicine 2012, 10:124 doi:10.1186/1741-7015-10-124

The electronic version of this article is the complete one and can be found online at:http://www.biomedcentral.com/1741-7015/10/124

Received: 27 July 2012
Accepted: 28 September 2012
Published: 22 October 2012

© 2012 Laakso and Björk; licensee BioMed Central Ltd.

This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background

Open access (OA) is a revolutionary way of providing access to the scholarly journal literature made possible by the Internet. The primary aim of this study was to measure the volume of scientific articles published in full immediate OA journals from 2000 to 2011, while observing longitudinal internal shifts in the structure of OA publishing concerning revenue models, publisher types and relative distribution among scientific disciplines. The secondary aim was to measure the share of OA articles of all journal articles, including articles made OA by publishers with a delay and individual author-paid OA articles in subscription journals (hybrid OA), as these subsets of OA publishing have mostly been ignored in previous studies.

Methods

Stratified random sampling of journals in the Directory of Open Access Journals (n = 787) was performed. The annual publication volumes spanning 2000 to 2011 were retrieved from major publication indexes and through manual data collection.

Results

An estimated 340,000 articles were published by 6,713 full immediate OA journals during 2011. OA journals requiring article-processing charges have become increasingly common, publishing 166,700 articles in 2011 (49% of all OA articles). This growth is related to the growth of commercial publishers, who, despite only a marginal presence a decade ago, have grown to become key actors on the OA scene, responsible for 120,000 of the articles published in 2011. Publication volume has grown within all major scientific disciplines, however, biomedicine has seen a particularly rapid 16-fold growth between 2000 (7,400 articles) and 2011 (120,900 articles). Over the past decade, OA journal publishing has steadily increased its relative share of all scholarly journal articles by about 1% annually. Approximately 17% of the 1.66 million articles published during 2011 and indexed in the most comprehensive article-level index of scholarly articles (Scopus) are available OA through journal publishers, most articles immediately (12%) but some within 12 months of publication (5%).

Conclusions

OA journal publishing is disrupting the dominant subscription-based model of scientific publishing, having rapidly grown in relative annual share of published journal articles during the last decade.

Keywords:

Open access; scientific publishing

Background

Open access (OA) has expanded the possibilities for disseminating one’s own research and accessing that of others [1,2]. OA, in the context of scholarly publishing, is a term widely used to refer to unrestricted online access to articles published in scholarly journals. There are two distinct ways for scholarly articles to become available OA, either directly provided by the journal publisher (gold OA), or indirectly by being uploaded and made freely available somewhere else on the Web (green OA). Both options increase the potential readership of any article to over a billion individuals with Internet access and indirectly speed up the spread of new research ideas. While the majority of OA journals do not charge authors anything for the services provided, a growing minority of professionally operating journals charge authors fees ranging from 20 to 3800 USD, with an estimated average of 900 USD [3].

OA is closely related to developments in other media content delivery businesses, and its ethos is well aligned with the fundamental openness principle of science itself as well as the ideologies behind Wikipedia and open source software. However, what makes scientific publishing distinct is the influence journal prestige and rankings have on journal selection for authors submitting article manuscripts [4]. There are also vested interests to preserve the status quo of the current subscription market among stakeholders, with dominant publishers seeing OA as a potential threat to the bottom-line. Friction caused by these and other factors can be argued to slow down the process of OA adoption because journals are not direct substitutes for each other and subscription-based journal copyright agreements can prohibit parallel distribution of published content. However, following in the footsteps of the National Institutes of Health in the US, public research funders in the UK have recently launched strategies to increase OA to publicly funded research [5]. While the ultimate goal of increasing access to publicly funded research is known and widely accepted it is difficult to reach compromises that balance the long- and short-term interests of the stakeholders involved [6].

Important changes in policy facilitating growth of OA happen on many levels, influencing research publishing both upstream and downstream. The examples from the public funders in the US and UK are merely the most ambitious movements so far: public and private research funders large and small, universities, publishers and research institutes all contribute to forming the evolving OA landscape. The problem that has persisted with OA since the start is the lack of readily available data for how this particular subset of journal publishing is developing over time, an aspect which is described in closer detail in the Methods section. Policymakers should have an interest in knowing how common OA is today, how fast the share of OA has increased and what proportion of journal articles are currently OA? The purpose of this study is to provide answers to these types of questions.

Aim of the study

This study focuses on providing measurement of the longitudinal development gold OA publication volume for the years 2000 to 2011 as a whole and by subtype: full immediate journal OA, delayed OA and hybrid OA. As will be described in more detail further on, earlier studies have mostly ignored the subset of delayed OA journals. This is partly because there is no comprehensive index of such journals similar to the service the Directory of Open Access Journals (DOAJ) provides for immediate OA journals, and partly because of the divisive acceptance of delayed OA as a valid form of OA. However, the subset of delayed OA journals is both substantial in volume and is populated with many high-quality journals; five of the 10 most-cited journals within Thomson Reuters Web of Knowledge in the period from 1999 to 2009 are currently delayed OA while the others are subscription-access only [7]. Hybrid OA is the term commonly used for describing individual articles being provided openly within subscription-only journals through an optional author payment; it is only recently that this type of OA has been properly studied [8].

The chosen research aim is related to some existing areas of OA research that warrant mention to clarify the specific contribution of this study. Green OA is not part of the scope of this study as that is a wholly different research problem and one that requires its own set of methods, as different versions of articles are scattered around on the Web. Furthermore, this study does not extensively discuss or evaluate the pros or cons of OA, since there is already a well-developed body of literature focusing on issues such as relationships between OA and readership, citation or impact [912]. In summary, the aim is to provide comprehensive and up-to-date quantitative measurement of gold OA journals and articles. The results and data of this study can then potentially act as a foundation for more targeted research enquiries.

Previous studies

Researchers have applied different methods to cope with the lack of readily available quantitative data to study the OA phenomenon, ranging from labor-intensive manual article-counting [1315] to automated Web-crawling [16,17]. What is known about the early years of OA, both gold and green, is mostly through a series of independent studies providing snapshots for individual years based on sampling various publication indexes. The fact that studies have been based around OA prevalence within different publication indexes and the diverse adopted sampling methods makes comparisons or composition of longitudinal development inexact. Nevertheless, these are the best figures currently available. The earliest comprehensive study suggests the 2003 share for gold OA to have been 2.9% for articles included in the Thomson Reuters Web of Knowledge [18]. The next study was performed for the 2006 publication volume based on data from UlrichsWeb [19] and the DOAJ [20], where a gold OA share of 8.1% and a green OA share of 11.3% resulted in a combined OA share of 19.4% [14]. For 2008 articles, the Thomson Reuters Web of Knowledge gold OA share was measured to be 6.6% and green OA 14%, resulting in a figure of total OA of 20.6% [21]. Also for 2008, a large-scale study based on English-language journals listed in the DOAJ calculated that 120,000 articles were published OA either through full immediate OA journals or as individual hybrid OA articles [22]. The first comprehensive longitudinal study on the volume of articles published by full immediate OA journals in the DOAJ resulted in an average annual year-on-year growth rate of 30% from 2000 to 2009, with some 191,000 articles published during 2009 [13]. Another longitudinal study, including both gold and green OA, produced a total OA share of 23.1% for Thomson Reuters Web of Knowledge indexed articles published during 2010 [16]. Outside of this 2010 study of Thomson Reuters Web of Knowledge, there are no comprehensive measurements for OA volume since 2009. This study is designed to provide a longitudinal study implementing a well-documented and easily replicable methodology, producing results applicable to multiple publication indexes, producing results that are easy to follow-up and compare with future measurements.

Methods

Sampling

The study is founded on the assumption that the full population of OA journals is listed in the DOAJ. There are OA journals not indexed in this database, but systematically identifying them is not feasible. Because the majority of the 7,372 journals listed in the DOAJ on 1 January 2012 were not included in any indexing service that would reliably keep track of their article output, nor the exact year previously subscription-based journals have converted to OA, gathering data is largely a manual task and one of the major practical challenges for the execution of studies of this type. To strike a balance between feasibility and reliability, stratified random sampling with unequal probabilities was utilized, a sampling method that has proven suitable for similar studies in the past [13]. An argument for adopting this approach in favor of fully random sampling is that the population of OA journals is highly heterogeneous, where a small number of titles output a large proportion of the total article volume [22]. The fact that large journals can be identified with a high degree of certainty through various indexing services also means that reliable, readily available article count information can be used for journals responsible for a major part of the total OA output. A visualization of the sampling is provided in Figure 1A cross-analysis of data available from SCImago [23], Thomson Reuters Web of Knowledge [24] and the DOAJ identified 103 OA journals that had published over 200 articles annually during 2009, 2010 or 2011; these were included in the large journal stratum. The rest of the 7,269 DOAJ journals were represented by a second stratum with a sample of 684 journals selected at random among them, each given an observation weight of 10.62719 (684 × 10.62719 = 7269). The stratum of large journals was only applied an observation weight of 1 since the population of that stratum is exhaustively sampled.

thumbnailFigure 1. Visualization of the sampling.

Data collection

Through a previous study using identical sampling and data collection methodology [13], data for 565 journals spanning publication volumes for 2000 to 2009 could be re-used, with only the need to gather publication volumes for two additional years. Since the existing data material lacked coverage for journals added to the DOAJ during 2010 and 2011, an additional randomly selected sample was drawn out of the journals added within the two missing years adhering to the same sampling probability as the pre-existing sample (0.1011), with 222 new journals added to the existing sample of 565 journals.

Where journal publication volumes could be retrieved from either SCImago or Thomson Reuters Web of Knowledge, such data was used. For the majority of journals, the individual journal websites were visited and the annual entries collected manually. It is worthwhile to note that journals often include editorials, news, book reviews, obituaries and other non-research content. Such material was excluded from all measurements in this study. To provide an accurate representation of retrospective OA volume, articles were not collected for subscription-only journals prior to publishing OA. Determining when a journal has initiated OA publishing often requires manual investigation as the information is not always made explicit on the webpages, and the data concerning this is often incorrect in the journal metadata available in the DOAJ. To support the analysis of the sampled journals, additional data from Scopus [25] and Thomson Reuters Web of Knowledge was utilized in addition to the data that is already available through the DOAJ.

Results

The longitudinal development of full immediate OA article volume spanning 2000 to 2011 is presented visually in Figure 2 and numerically in Table 1, where a breakdown of the total volume is provided for articles split into three different categories: online-only journals that require an article-processing charge, online-only journals that do not require an article-processing charge, and journals that still output print versions for subscribers but have all articles available OA online. It is important to point out that journals still producing a print version might also require an article-processing charge in addition to having income from subscriptions. However, such differentiation is not provided here due to the relative rarity of such journals as well as a desire to focus on these three mutually exclusive business models specifically.

thumbnailFigure 2. Annual volumes of articles in full immediate open access journals, split by type of open access journal.

Table 1. Estimated annual article and journal counts in full immediate open access journals

Overall there has been growth in the annual output among all three categories since the year 2000, going from a total volume of 20,700 articles in 2000 to 340,000 in 2011. Not depicted in Figure 2 but provided in Table 1 is the number of active OA journals for each respective year (journals with at least one article published during the respective year), which has increased from 744 journals in the year 2000 to 6,713 in 2011. The average number of articles per journal has also seen a constant increase, with an average of 26 articles per journal in 2000, 33 in 2005, and 51 for 2011. However, a reminder about the skewed nature of article distribution among journals is relevant here. There is a handful of journals publishing more than 1,000 articles per year and thousands of journals publishing only a few articles annually.

Inspecting the internal structure of the total article mass reveals some major shifts that have happened over the course of a decade. Journals that also publish a parallel print version, which are often old, established journals that decided to make the online version free when they started putting their content on the Web, provided the majority of the OA content up until the year 2008 where, for the first time, online-only journals took the lead in terms of output volume. Since 2008, the online-only journals have sustained a much stronger growth while the OA output provided by journals outputting a print version has plateaued to annual volumes between 100,000 and 110,000 articles. The latter group includes a lot of society journals registered with dedicated portals like SciELO [26], Redalyc [27] and J-Stage [28] providing the technical platform for electronic publishing. Journals with author-processing charges have seen breakout growth during the last three years, going from 80,700 articles in 2009 to 166,700 articles in 2011.

Cross-analysis of the sample with the titles listed in Thomson Reuters Web of Knowledge index and Elsevier’s Scopus index was performed, only including the titles present in the respective index to calculate the share of OA articles of all peer-reviewed articles. Table 2 provides the main results of this analysis, presented as longitudinal breakdowns of publisher-provided OA in the two indexing services. Nearly half of all full immediate OA articles published during 2011 were outside of Scopus and two thirds outside of Thomson Reuters Web of Knowledge, meaning that a large portion of article OA article volume lacks coverage in major publication indexes. This issue highlights the importance of using manual data collection methods in OA studies because data available from indexes only provide part of the total picture. In addition to the results concerning full immediate OA journals, Table 2 also contains volume data for two other types of publisher-provided OA in each respective index: delayed OA and hybrid OA.

Table 2. Proportion of publisher-provided (gold) open access in major indexes

Of the 1.66 million articles indexed by Scopus in 2011, 11% were published in full immediate OA journals, 0.7% as hybrid OA and 5.2% in journals that have a maximum OA delay of 12 months. Together, these account for almost 17% of the total article volume in the whole index. The figures for articles indexed by Thomson Reuters Web of Knowledge are comparable to those of Scopus, with a total publisher-provided OA rate of 16.2% for 2011. Of the 1.29 million articles indexed by Thomson Reuters Web of Knowledge, 7.9% are available in full immediate OA journals, 0.7% as hybrid OA and 6.4% in journals that have a maximum OA delay of 12 months. Overall the results suggest that there has been an increase of about one percentage point annually in relative OA volume in both Scopus and Thomson Reuters Web of Knowledge during 2008 to 2011.

Figure 3 presents the longitudinal development of OA publisher output as measured by the number of articles output by publishers based in different regions of the world. This figure, and all that follow, only includes full immediate OA journals, excluding delayed and hybrid OA. Prior to interpretation it needs to be noted that this is a publisher-centric analysis. In some cases, the publisher is not registered within the same country, or even region of the world, as the journal. The results suggest that Latin American countries were early to have substantial OA output, possibly due to the early availability of the SciELO portal. However, the region has not increased its output at a similar rate as North America, Asia or Europe, who have multiplied their outputs between 2005 and 2011.

thumbnailFigure 3. Open access publisher output across geographic regions.

Figure 4 presents the total OA article volume for 2000, 2005 and 2011 split according to publisher type. The analysis shows that the early years of OA publishing were largely driven by scientific societies, professional associations, universities and their departments as well as individual scientists. Scientific societies and universities have maintained strong growth throughout the decade, while scientist-driven publication has been overshadowed by the article volume produced by the more formally organized publisher types. The most dramatic development since 2005 is the rapid increase in articles published by commercial publishers, jumping from 13,400 articles in 2005 to 119,900 in 2011, resulting in commercial publishers currently being the most common publisher of OA articles. The category of professional non-commercial publishers is a new type of publisher that has rapidly emerged during the last few years, largely attributed to the journals published by the Public Library of Science.

thumbnailFigure 4. Open access publisher type analysis.

Figure 5 presents the OA article volumes for the years 2000, 2005 and 2011 split across the major scientific disciplines, with an additional category for general science journals. Throughout the decade, articles in journals broadly related to biomedicine have held the lead in terms of article volume, and since 2005 the gap to the other disciplines has been further extended. Biomedical journals published 120,900 articles in 2011, constituting 35.5% of the total OA article output for the year. In second place in terms of volume for 2011 is the social sciences and humanities, almost tied with earth and environmental sciences in third place, publishing 56,000 and 54,900 articles respectively. Coming in fourth place in terms of size is engineering, which is the discipline that has seen the most dramatic relative growth between 2005 and 2011, from publishing only 4,800 articles in 2005 to 37,500 articles in 2011. In fifth place for 2011 is physics and astronomy with 16,000 articles; however, previous studies have shown there to be particularly strong practice and supporting infrastructure for parallel publication within this discipline, potentially lessening the demand for OA journals [21]. Chemistry and chemical engineering is sixth in terms of size with 12,700 articles in 2011, followed by general science journals and mathematics at the tail end with 12,600 and 7,200 articles respectively. The category of general science journals is a relatively new one with only marginal volume until recently. Journals belonging to this category have little or no limitations with regards to research subject or scope. Though it could be argued that PLOS ONE is a general science journal, the vast majority of actual articles published so far have been within the scope of biomedicine, thus that specific journal was placed within the biomedicine category for this coarse disciplinary breakdown.

thumbnailFigure 5. Open access across major scientific disciplines.

Discussion

Over the course of the last decade, OA journal publishing has grown universally across diverse types of journal publishers, geographical regions and scientific disciplines. This has resulted in a continuously growing proportion of journal articles being published OA for each year that has passed, with the most recent measurement from this study being 17% when delayed OA articles with a maximum embargo of 12 months are included. However, despite all the studied dimensions showing increases in annual article output over the decade, the results of the study show that growth has not been uniform across the board. OA publishing seems to be in a very dynamic growth phase, with major shifts in the internal composition happening in a relatively short span of time.

A major strength of the study is associated with the labor-intensive manual approach to data collection, where the annual article volumes for each journal included in the sample was registered for the years 2000 to 2011. This approach reduces the risk of using incorrect, skewed or incomplete source data. The methodological transparency should also enable others to produce comparable numbers to follow-up and compare with the measurements provided here. What can be held as a weakness is the reliance on sampling rather than complete population coverage, however, such an approach is not feasible with the indexing tools currently available and manually collecting the data for over 7,000 journals is a very labor-intensive task.

In comparison with existing studies, this is not only the first study to provide comprehensive gold OA measurement for 2010 and 2011, but the results for the earlier years studied are also more accurate and representative of the actual volumes published at the time. The previous directly comparable study suggested that 191,000 articles were published by full immediate OA journals during 2009 [13], whereas this study suggests the volume for the same year to actually be 225,600. The discrepancy in retrospective annual volumes between these two studies, or any other earlier study using data from the DOAJ, is influenced by the time-lag between the time journals actually start publishing OA and the time they get registered to the DOAJ. In part, this is because journals have to submit a request to the DOAJ to be added, meaning that journals rarely are registered from the first issue they publish, if at all. Another issue is the time the DOAJ takes to process new addition requests; as of September 2012 the backlog of journals currently in queue for evaluation is described as being ‘huge’ on the DOAJ contact page [20]. Exploring this issue more closely through the sampled journals, it appears that over half of the sampled journals added to the DOAJ during 2010 and 2011 had been publishing OA already prior to 2010, with a handful of cases publishing OA for over a decade prior to DOAJ registration. As was noted in the introduction, most other earlier studies have been limited by only looking at specific OA subsets for specific years, and are thus not directly comparable. However, despite this inability to compare our estimates directly with earlier studies because of methodological incompatibilities, all the results nevertheless speak for the notion of a strong longitudinal growth for OA, particularly so for the biomedical research field.

The results, in particular the finding that approximately 17% of scholarly journal articles are already now made openly available on the Web within a year by the publishers, should be an important input for the policy discussions on OA in venues like the US Congress, the European Commission and the UK Finch Committee that recently published its report with OA-guidelines for British research funders [6]. This study also sheds new light on the relative contributions of the two complementary routes for achieving OA, the publisher-provided gold route and the author-provided green route, indicating that the contribution of gold (both immediate and articles withheld for short embargo periods) is much larger than many earlier estimates. The results should also be considered together with two other recent studies [3,9]. These studies suggest that the level of article-processing charges paid is on average around 900 USD, which is lower than generally believed, and that the scientific impact of OA journals founded in the last decade, and in particular in biomedicine, is on par with similar subscription journals, as measured by average number of citations.

It no longer seems to be a question whether OA is a viable alternative to the traditional subscription model for scholarly journal publishing; the question is rather when OA publishing will become the mainstream model. What remains to be seen is whether the growth will continue at a similar rate as measured during last few years, or if it will accelerate to an even steeper part of the S-shaped adoption pattern typical of many innovations [29]. As in many other markets where the Internet has thoroughly rewritten the rules of the game, an interesting question is if new entrants, like Public Library of Science and BioMed Central, will take over the market or if the old established actors, commercial and society publishers with subscription-based revenue models, will be able to adapt their business models and regain the ground they have so far lost. Future studies on the internal structure of OA publishing are likely to witness the anatomy transforming yet again. Most of the major internal shifts in OA journal publishing have only happened fairly recently during the last few years and, judging by the momentum at which things are moving, it is hard to imagine the internal dynamics settling down any time soon.

Competing interests

The authors declare that they have no competing financial interests. B-CB founded an OA journal in the 1990s and is emeritus Editor-in-Chief. B-CB is a current board member of the Open Access Scholarly Publishers Association.

Authors’ contributions

ML and B-CB conceived, designed and coordinated the study. ML handled most of the data collection and analysis. Both authors participated equally to interpretation of the results and writing of the manuscript. Both authors have read and approved the final manuscript.

Authors’ information

ML is a doctoral student in Information Systems Science at the Hanken School of Economics, Helsinki, Finland. B-CB is professor of Information Systems Science at the Hanken School of Economics, Helsinki, Finland.

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Endothelial Function and Cardiovascular Disease

Pathologist and AuthorLarry H Bernstein, MD, FCAP 

 

This discussion is a continuation of a series on Nitric Oxide, vascular relaxation, vascular integrity, and systemic organ dysfunctions related to inflammatory and circulatory disorders. In some of these, the relationships are more clear than others, and in other cases the vascular disorders are aligned with serious metabolic disturbances. This article, in particular centers on the regulation of NO production, NO synthase, and elaborates more on the assymetrical dimethylarginine (ADMA) inhibition brought up in a previous comment, and cardiovascular disease, including:

Recall, though, that in SIRS leading to septic shock, that there is a difference between the pulmonary circulation, the systemic circulation and the portal circulation in these events. The comment calls attention to:
Böger RH. Asymmetric dimethylarginine, an endogenous inhibitor of nitric oxide synthase, explains the ‘L-arginine paradox’ and acts as a novel cardiovascular risk factor. J Nutr 2004; 134: 2842S–7S.

This observer points out that ADMA inhibits vascular NO production at concentrations found in pathophysiological conditions (i.e., 3–15 μmol/l); ADMA also causes local vasoconstriction when it is infused intra-arterially. ADMA is increased in the plasma of humans with hypercholesterolemia, atherosclerosis, hypertension, chronic renal failure, and chronic heart failure.

Increased ADMA levels are associated with reduced NO synthesis as assessed by impaired endothelium-dependent vasodilation. We’ll go into that more with respect to therapeutic targets – including exercise, sauna, and possibly diet, as well as medical drugs.

It is remarkable how far we have come since the epic discovery of 17th century physician, William Harvey, by observing the action of the heart in small animals and fishes, proved that heart receives and expels blood during each cycle, and argued for the circulation in man. This was a huge lead into renaissance medicine. What would he think now?

Key Words: eNOS, NO, endothelin, ROS, oxidative stress, blood flow, vascular resistance, cardiovascular disease, chronic renal disease, hypertension, diabetes, atherosclerosis, MI, exercise, nutrition, traditional chinese medicine, statistical modeling for targeted therapy.

Endothelial Function
The endothelium plays a crucial role in the maintenance of vascular tone and structure by means of eNOS, producing the endothelium-derived vasoactive mediator nitric oxide (NO), an endogenous messenger molecule formed in healthy vascular endothelium from the amino acid precursor L-arginine. Nitric oxide synthases (NOS) are the enzymes responsible for nitric oxide (NO) generation. The generation and actions of NO under physiological and pathophysiological conditions are exquisitely regulated and extend to almost every cell type and function within the circulation. While the molecule mediates many physiological functions, an excessive presence of NO is toxic to cells.

The enzyme NOS, constitutively or inductively, catalyses the production of NO in several biological systems. NO is derived not only from NOS isoforms but also from NOS-independent sources. In mammals, to date, three distinct NOS isoforms have been identified:

  1. neuronal NOS (nNOS),
  2. inducible NOS (iNOS), and
  3. endothelial NOS (eNOS).

The molecular structure, enzymology and pharmacology of these enzymes have been well defined, and reveal critical roles for the NOS system in a variety of important physiological processes. The role of NO and NOS in regulating vascular physiology, through neuro-hormonal, renal and other non-vascular pathways, as well as direct effects on arterial smooth muscle, appear to be more intricate than was originally thought.

Vallance et al. described the presence of asymmetric dimethylarginine (ADMA) as an endogenous inhibitor of eNOS in 1992. Since then, the role of this molecule in the regulation of eNOS has attracted increasing attention.
Endothelins are 21-amino acid peptides, which are active in almost all tissues in the body. They are potent vasoconstrictors, mediators of cardiac, renal, endocrine and immune functions and play a role in bronchoconstriction, neurotransmitter regulation, activation of inflammatory cells, cell proliferation and differentiation.

Endothelins were first characterised by Yanagisawa et al. (1988). The three known endothelins ET-1, -2 and -3 are structurally similar to sarafotoxins from snake venoms. ET-1 is the major isoform generated in blood vessels and appears to be the isoform of most importance in the cardiovascular system with a major role in the maintenance of vascular tone.

The systemic vascular response to hypoxia is vasodilation. However, reports suggest that the potent vasoconstrictor endothelin-1 (ET-1) is released from the vasculature during hypoxia. ET-1 is reported to augment superoxide anion generation and may counteract nitric oxide (NO) vasodilation. Moreover, ET-1 was proposed to contribute to increased vascular resistance in heart failure by increasing the production of asymmetric dimethylarginine (ADMA).

A study investigated the role of ET-1, the NO pathway, the potassium channels and radical oxygen species in hypoxia-induced vasodilation of large coronary arteries and found NO contributes to hypoxic vasodilation, probably through K channel opening, which is reversed by addition of ET-1 and enhanced by endothelin receptor antagonism. These latter findings suggest that endothelin receptor activation counteracts hypoxic vasodilation.

Endothelial dysfunction
Patients with Raynaud’s Phemonenon had abnormal vasoconstrictor responses to cold pressor tests (CPT) that were similar in primary and secondary RP. There were no differences in median flow-mediated and nitroglycerin mediated dilation or CPT of the brachial artery in the 2 populations. Patients with secondary RP were characterized by abnormalities in microvascular responses to reactive hyperemia, with a reduction in area under the curve adjusted for baseline perfusion, but not in time to peak response or peak perfusion ratio.

Plasma ET-1, ADMA, VCAM-1, and MCP-1 levels were significantly elevated in secondary RP compared with primary RP. There was a significant negative correlation between ET-1 and ADMA values and measures of microvascular perfusion but not macrovascular endothelial function. Secondary RP is characterized by elevations in plasma ET-1 and ADMA levels that may contribute to alterations in cutaneous microvascular function.

ADMA inhibits vascular NO production within the concentration range found in patients with vascular disease. ADMA also causes local vasoconstriction when infused intra-arterially, and increases systemic vascular resistance and impairs renal function when infused systemically. Several recent studies have supplied evidence to support a pathophysiological role of ADMA in the pathogenesis of vascular dysfunction and cardiovascular disease. High ADMA levels were found to be associated with carotid artery intima-media-thickness in a study with 116 clinically healthy human subjects. Taking this observation further, another study performed with hemodialysis patients reported that ADMA prospectively predicted the progression of intimal thickening during one year of follow-up.

In a nested, case-control study involving 150 middle-aged, non-smoking men, high ADMA levels were associated with a 3.9-fold elevated risk for acute coronary events. Clinical and experimental evidence suggests elevation of ADMA can cause a relative L-arginine deficiency, even in the presence of “normal” L-arginine levels. As ADMA is a competitive inhibitor of eNOS, its inhibitory action can be overcome by increasing the concentration of the substrate, L-arginine. Elevated ADMA concentration is one possible explanation for endothelial dysfunction and decreased NO production in these diseases.
Metabolic Regulation of L-arginine and NO Synthesis 
Methylation of arginine residues within proteins or polypeptides occurs through N-methyltransferases, which utilize S-adenosylmethionine as a methyl donor. After proteolysis of these proteins or polypeptides, free ADMA is present in the cytoplasm. ADMA can also be detected in circulating blood plasma. ADMA acts as an inhibitor of eNOS by competing with the substrate of this enzyme, L-arginine. The ensuing reduction in nitric oxide synthesis causes vascular endothelial dysfunction and, subsequently, atherosclerosis. ADMA is eliminated from the body via urinary excretion and via metabolism by the enzyme DDAH to citrulline and dimethylamine.
Supplementation with L-arginine in animals with experimentally-induced vascular dysfunction atherosclerosis improves endothelium-dependent vasodilation. Moreover, L-arginine supplementation results in enhanced endothelium-dependent inhibition of platelet aggregation, inhibition of monocyte adhesion, and reduced vascular smooth muscle proliferation. One mechanism that explains the occurrence of endothelial dysfunction is the presence of elevated blood levels of asymmetric dimethylarginine (ADMA) – an L-arginine analogue that inhibits NO formation and thereby can impair vascular function. Supplementation with L-arginine has been shown to restore vascular function and to improve the clinical symptoms of various diseases associated with vascular dysfunction.

Beneficial Effects of L-Arginine

  • Angina
  • Congestive Heart Failure
  • Hypertension
  • Erectile dysfunction
  • Sickle Cell Disease and Pulmonary Hypertension

The ratio of L-arginine to ADMA is considered to be the most accurate measure of eNOS substrate availability. This ratio will increase during L-arginine supplementation, regardless of initial ADMA concentration. Due to the pharmacokinetics of oral L-arginine and the positive results from preliminary studies, it appears supplementation with a sustained-release L-arginine preparation will achieve positive therapeutic results at lower dosing levels.

Many prospective clinical trials have shown that the association between elevated ADMA levels and major cardiovascular events and total mortality is robust and extends to diverse patient populations. However, we need to define more clearly in the future who will profit from ADMA determination, in order to use this novel risk marker as a more specific diagnostic tool.
Elimination of ADMA by way of DDAH
Asymmetric dimethylarginine (ADMA) and monomethyl arginine (L-NMMA) are endogenously produced amino acids that inhibit all three isoforms of nitric oxide synthase (NOS). ADMA accumulates in various disease states, including renal failure, diabetes and pulmonary hypertension, and its concentration in plasma is strongly predictive of premature cardiovascular disease and death. Both LNMMA and ADMA are eliminated largely through active metabolism by dimethylarginine dimethylaminohydrolase (DDAH) and thus DDAH dysfunction may be a crucial unifying feature of increased cardiovascular risk. These investigators ask whether ADMA is the underlying issue related to the pathogenesis of the vascular disorder.
They identified the structure of human DDAH-1 and probed the function of DDAH-1 both by deleting the Ddah1 gene in mice and by using DDAH-specific inhibitors that is shown by crystallography, bind to the active site of human DDAH-1. The loss of DDAH-1 activity leads to accumulation of ADMA and reduction in NO signaling. This in turn causes vascular pathophysiology, including endothelial dysfunction, increased systemic vascular resistance and elevated systemic and pulmonary blood pressure. The results suggest that DDAH inhibition could be harnessed therapeutically to reduce the vascular collapse associated with sepsis.
Methylarginines are formed when arginine residues in proteins are methylated by the action of protein arginine methyltransferases (PRMTs), and free methylarginines are liberated following proteolysis. Clear demonstration of an effect of endogenous ADMA and L-NMMA on cardiovascular physiology would be of importance, not only because of the implications for disease, but also because it would expose a link between post-translational modification of proteins and signaling through a proteolytic product of these modified proteins.
Which is it? ADMA or DDHA: Intrusion of a Genetic alteration.
The study showed that loss of DDAH expression or activity causes endothelial dysfunction, we believe that DDAH inhibition could potentially be used therapeutically to limit excessive NO production, which can have pathological effects. They then showed treated cultured isolated blood vessels with lipopolysaccharide (LPS) induced expression of the inducible isoform of NO synthase (iNOS) and generated high levels of NO, which were blocked by the iNOS-selective inhibitor 1400W and by DDAH inhibitors. Treatment of isolated blood vessels with DDAH inhibitors significantly increased ADMA accumulation in the culture medium. Treatment of isolated blood vessels with bacterial LPS led to the expected hyporeactivity to the contractile effects of phenylephrine, which was reversed by treatment with a DDAH inhibitor. The effect of the DDAH inhibitor was large and stereospecific, and was reversed by the addition of L-arginine.
In conclusion, genetic and chemical-biology approaches provide compelling evidence that loss of DDAH-1 function results in increased ADMA concentrations and thereby disrupts vascular NO signaling. A broader implication of this study is that post-translational methylation of arginine residues in proteins may have downstream effects by affecting NO signaling upon hydrolysis and release of the free methylated amino acid. This signaling pathway seems to have been highly conserved through evolution.

The crucial role of nitric oxide (NO) for normal endothelial function is well known. In many conditions associated with increased risk of cardiovascular diseases such as hypercholesterolemia, hypertension, abdominal obesity, diabetes and smoking, NO biosynthesis is dysregulated, leading to endothelial dysfunction. The growing evidence from animal and human studies indicates that endogenous inhibitors of endothelial NO synthase such as asymmetric dimethylarginine (ADMA) and NG-monomethyl-L-arginine (L-NMMA) are associated with the endothelial dysfunction and potentially regulate NO synthase.

Nitric Oxide Synthase

Asymmetric dimethylarginine (ADMA) is one of three known endogenously produced circulating methylarginines (i.e. ADMA, NG-monomethyl-L-arginine (L-NMMA) and symmetrically methylated NG, NG-dimethyl-L-arginine). ADMA is formed by the action of protein arginine methyltransferases that methylate arginine residues in proteins and after which free ADMA is released. ADMA and L-NMMA can competitively inhibit NO elaboration by displacing L-arginine from NO synthase (NOS). The amount of methylarginines is related to overall metabolic activity and the protein turnover rate of cells. Although methylarginines are excreted partly by the kidneys, the major route of elimination of ADMA in humans is metabolism by the dimethylarginine dimethylaminohydrolase enzymes[ dimethylarginine dimethylaminohydrolase-1 and -2 (DDAH)] enzymes. Inhibition of DDAH leads to the accumulation of ADMA and consequently to inhibition of NO-mediated endothelium dependent relaxation of blood vessels.
The potential role of ADMA in angina pectoris has been evaluated by Piatti and co-workers, who reported ADMA levels to be higher in patients with cardiac syndrome X (angina pectoris with normal coronary arteriograms) than in controls. According to preliminary results from the CARDIAC (Coronary Artery Risk Determination investigating the influence of ADMA Concentration) study, patients with coronary heart disease (n 816) had a higher median ADMA plasma concentration than age and sex matched controls (median 0.91 vs. 0.70 mol/l; p 0.0001). Further, in a prospective Chinese study, a high plasma ADMA level independently predicted subsequent cardiovascular adverse events (cardiovascular death, myocardial infarction, and repeated revascularization of a target vessel).

Protein detoxification pathway.

Protein detoxification pathway. (Photo credit: Wikipedia)

There are only few published findings concerning variations in human DDAH. However, polymorphisms in other genes potentially related to risk factors for endothelial dysfunction and cardiovascular events have been studied. Reduced NO synthesis has been implicated in the development of atherosclerosis. For example, there are some functionally important variants of the NOS that could affect individual vulnerability to atherosclerosis by changing the amount of NO generated by the endothelium.
There are probably several functional variations in genes coding DDAH enzymes in different populations. Some of them could confer protection against the harmful effects of elevated ADMA and others impair enzyme function causing accumulation of ADMA in cytosol and/or blood.
In a study of 16 men with either low or high plasma ADMA concentrations were screened to identify DDAH polymorphisms that could potentially be associated with increased susceptibility to cardiovascular diseases. In that study a novel functional mutation of DDAH-1 was identified; the mutation carriers had a significantly elevated risk for cardiovascular disease and a tendency to develop hypertension. These results confirmed the clinical role of DDAH enzymes in ADMA metabolism. Furthermore, it is possible that more common variants of DDAH genes contribute more widely to increased cardiovascular risk.
We found a rare variation in the DDAH-1 gene, which is associated with elevated plasma concentrations of ADMA in heterozygous mutation carriers. There was also an increased prevalence of CHD and a tendency to hypertension among individuals with this DDAH-1 mutation. These observations highlight the importance of ADMA as a possible risk factor and emphasize the essential role of DDAH in regulating ADMA levels.

ADMA Elevation and Coronary Artery Disease
Endothelial dysfunction may be considered as a systemic disorder and involves different vascular beds. Coronary endothelial dysfunction (CED) precedes the development of coronary. Endothelial dysfunction is characterized by a reduction in endogenous nitric oxide (NO) activity, which may be accompanied by elevated plasma asymmetric dimethylarginine (ADMA) levels. ADMA is a novel endogenous competitive inhibitor of NO synthase (NOS), an independent marker for cardiovascular risk.

English: Structure of asymmetric dimethylargin...

English: Structure of asymmetric dimethylarginine; ADMA; N,N-Dimethylarginine Deutsch: Asymmetrisches Dimethylarginin; N,N-Dimethyl-L-arginin; Guanidin-N,N-dimethylarginin (Photo credit: Wikipedia)

In a small study fifty-six men without obstructive coronary artery disease (CAD) who underwent coronary endothelial function testing were studied. Men with CED had significant impairment of erectile function (P ¼ 0.008) and significantly higher ADMA levels (0.50+0.06 vs. 0.45+0.07 ng/mL, P ¼ 0.017) compared with men with normal endothelial function. Erectile function positively correlated with coronary endothelial function. This correlation was independent of age, body mass index, high-density lipoprotein, C-reactive protein, homeostasis model assessment of insulin resistance index, and smoking status, suggesting that CED is independently associated with ED and plasma ADMA concentration in men with early coronary atherosclerosis.

ADMA and Chronic Renal Failure in Hepatorenal Syndrome
The concentration of SDMA was significantly higher in the patients with HRS compared to the patients without HRS and it was also higher than the values obtained from the healthy participants (1.76 ± 0.3 μmol/L; 1.01 ± 0.32 and 0.520 ± 0.18 μmol/L, respectively; p < 0.01). The concentrations of ADMA were higher in the cirrhotic patients with HRS than in those without this serious complication of cirrhosis. The concentration of ADMA in all the examined cirrhotic patients was higher than those obtained from healthy volunteers (1.35 ± 0.27 μmol/L, 1.05 ± 0.35 μmol/L and 0.76 ± 0.21 μmol/L, respectively). In the patients with terminal alcoholic liver cirrhosis, the concentrations
of ADMA and SDMA correlated with the progress of cirrhosis as well as with the development of cirrhosis complications. In the patients with HRS there was a positive correlation between creatinine and SDMA in plasma (r2 = 0.0756, p < 0.001) which was not found between creatinine and ADMA. The results demonstrate that the increase in SDMA concentration is proportionate to the progression of chronic damage of the liver and kidneys. Increased ADMA concentration can be a causative agent of renal insufficiency in patients with cirrhosis.

In patients with cirrhosis, ADMA, as well as SDMA could be markers for kidney insufficiency development. Accumulation of ADMA in plasma causes kidney
vasoconstriction and thereby retention of SDMA. Considering that ADMA has several damaging effects, it can be concluded that modulation of the activity of enzyme which participates in ADMA catabolism may represent a new therapeutic goal which is intended to reduce the progress of liver and kidney damage and thus the development of HRS.

ADMA Therapeutic Targets
Elevated plasma concentrations of the endogenous nitric oxide synthase
inhibitor asymmetric dimethylarginine (ADMA) are found in various clinical settings, including

  • renal failure,
  • coronary heart disease,
  • hypertension,
  • diabetes and
  • preeclampsia.

In healthy people acute infusion of ADMA promotes vascular dysfunction,
and in mice chronic infusion of ADMA promotes progression of atherosclerosis.
Thus, ADMA may not only be a marker but also an active player in cardiovascular disease, which makes it a potential target for therapeutic interventions.

This review provides a summary and critical discussion of the presently available data concerning the effects on plasma ADMA levels of cardiovascular drugs, hypoglycemic agents, hormone replacement therapy, antioxidants, and vitamin supplementation.
We assess the evidence that the beneficial effects of drug therapies on vascular function can be attributed to modification of ADMA levels. To develop more specific ADMA-lowering therapies, mechanisms leading to elevation of plasma ADMA concentrations in cardiovascular disease need to be better understood.

ADMA is formed endogenously by degradation of proteins containing arginine residues that have been methylated by S-adenosylmethionine-dependent methyltransferases (PRMTs). There are two major routes of elimination: renal excretion and enzymatic degradation by the dimethylarginine dimethylaminohydrolases (DDAH-1 and -2).

Oxidative stress causing upregulation of PRMT expression and/or attenuation of DDAH activity has been suggested as a mechanism and possible drug target in clinical conditions associated with elevation of ADMA. As impairment of DDAH activity or capacity is associated with substantial increases in plasma ADMA concentrations, DDAH is likely to emerge as a prime target for specific therapeutic interventions.

Cardiovascular diseases (CVD) in diabetic patients have endothelial dysfunction as a key pathogenetic event. Asymmetric dimethylarginine (ADMA), an endogenous inhibitor of nitric oxide synthase (NOS), plays a pivotal role in endothelial dysfunction. Different natural polyphenols have been shown to preserve endothelial function and prevent CVD. Another study assessed the effect of silibinin, a widely used flavonolignan from milk thistle, on ADMA levels and endothelial dysfunction in db/db mice.

Plasma and aorta ADMA levels were higher in db/db than in control lean mice. Silibinin administration markedly decreased plasma ADMA; consistently, aorta ADMA was reduced in silibinin-treated animals. Plasma and aorta ADMA levels exhibited a positive correlation, whereas liver ADMA was inversely correlated with both plasma and aorta ADMA concentrations. Endothelium-(NO)-dependent vasodilatation to ACh was impaired in db/db mice and was restored in the silibinin group, in accordance with the observed reduction of plasma and vascular levels of ADMA. Endothelium-independent vasodilatation to SNP was not modified by silibinin administration.

Endothelin Inhibitors
Endothelins are potent vasoconstrictors and pressor peptides and are important mediators of cardiac, renal andendocrine functions. Increased ET-1 levels in disease states such as congestive heart failure, pulmonary hypertension, acute myocardial infarction, and renal failure suggest the endothelin system as an attractive target for pharmacotherapy. A non-peptidic, selective, competitive endothelin receptor antagonist with an affinity for the ETA receptor in the subnanomolar range was administered by continuous intravenous infusion to beagle dogs, rats, and Goettingen minipigs. It caused mild arteriopathy characterised by segmental degeneration in the media of mid- to large-size coronary arteries in the heart of dog, but not rat or minipig.

The lesions only occurred in the atrium and ventricle. Frequency and severity of the vascular lesions was not sex or dose related. No effects were noted in blood vessels in other organs or tissue. Plasma concentrations at steady state, and overall exposure in terms of AUC(0–24h) were higher in minipig and rat than the dog but did not cause cardiac arteriopathy. These findings concur with those caused by other endothelin anatagonists, vasodilators and positive inotropic: vasodilating drugs such as potassium channel openers, phosphodiesterase inhibitors and peripheral vasodilators.

Results by echocardiography indicate treatment-related local vasodilatation in the coronary arteries. These data suggest that the coronary arteriopathy may be the result of exaggerated pharmacology. Sustained vasodilatation in the coronary vascular bed may alter flow dynamics and lead to increased shear stress and tension on the coronary wall with subsequent microscopic trauma. In our experience with a number of endothelin receptor antagonists, the cardiac arteriopathy was only noted in studies with multiple daily or continuous intravenous infusion inviting speculation that sustained high plasma levels are needed for development of the lesions.

Up-regulation of vascular endothelin type B (ETB) receptors is implicated in the
pathogenesis of cardiovascular disease. Culture of intact arteries has been shown to induce similar receptor alterations and has therefore been suggested as a suitable method for, ex vivo, in detail delineation of the regulation of endothelin receptors. We hypothesize that mitogen-activated kinases (MAPK) and protein kinase C (PKC) are involved in the regulation of endothelin ETB receptors in human internal mammary arteries.

The endothelin-1-induced contraction (after endothelin ETB receptor desensitization) and the endothelin ETA receptor mRNA expression levels were not altered by culture. The sarafotoxin 6c contraction, endothelin ETB receptor protein and mRNA expression levels were increased. This increase was antagonized by;

PKC inhibitors (10 μM bisindolylmaleimide I and 10 μM Ro-32-0432), and
inhibitors of the p38, extracellular signal related kinases 1 and 2 (ERK1/2) and C-jun terminal kinase (JNK) MAPK pathways
Endothelin Receptor Antagonist Tezosentan
The effects of changes in the mean (Sm) and pulsatile (Sp) components of arterial wall shear stress on arterial dilatation of the iliac artery of the anaesthetized dog were examined in the absence and presence of the endothelin receptor antagonist tezosentan (10 mg kg_1 I.V.; Ro 61-0612; [5-isopropylpyridine-2-sulphonic acid 6-(2-hydroxy-ethoxy)-5-(2-methoxy-phenoxy)-2-(2-1H-tetrazol-5-ylpyridin-4-yl)-pyrimidin-4-ylamide]).

Changes in shear stress were brought about by varying local peripheral resistance and stroke volume using a distal infusion of acetylcholine and stimulation of the left ansa subclavia. An increase in Sm from 1.81 ± 0.3 to 7.29 ± 0.7 N m_2 (means ± S.E.M.) before tezosentan caused an endothelium-dependent arterial dilatation which was unaffected by administration of tezosentan for a similar increase in Sm from 1.34 ± 0.6 to 5.76 ± 1.4 N m_2 (means ± S.E.M.).

In contrast, increasing the Sp from 7.1 ± 0.8 to a maximum of 11.5 ± 1.1 N m_2 (means ± S.E.M.) before tezosentan reduced arterial diameter significantly. Importantly, after administration of tezosentan subsequent increases in Sp caused arterial dilatation for the same increase in Sp achieved prior to tezosentan, increasing from a baseline of 4.23 ± 0.4 to a maximum of 9.03 ± 0.9 N m_2 (means ± S.E.M.; P < 0.001). The results of this study provide the first in vivo evidence that pulsatile shear stress is a stimulus for the release of endothelin from the vascular endothelium.

Exercise and Diet
Vascular endotheliumis affected by plasma asymmetric dimethylarginine (ADMA), and it is induced by inflammatory cytokines of tumour necrosis factor (TNF)-a in vitro. Would a tight glycemic control restore endothelial function in patients with type-2 diabetes mellitus (DM) with modulation of TNF-a and/or reduction of ADMA level? In 24 patients with type-2 DM, the flow-mediated, endothelium-dependent dilation (FMD: %) of brachial arteries during reactive hyperaemia was determined by a high-resolution ultrasound method. Blood samples for glucose, cholesterol, TNF-a, and ADMA analyses were also collected from these patients after fasting. No significant glycemic or FMD changes were observed in 10 patients receiving the conventional therapy.

In 14 patients who were hospitalized and intensively treated, there was a significant decrease in glucose level after the treatment [from 190+55 to 117+21 (mean+SD) mg/dL, P , 0.01]. After the intensive control of glucose level, FMD increased significantly (from 2.5+0.9 to 7.2+3.0%), accompanied by a significant (P , 0.01) decrease in TNF-a (from 29+16 to 11+9 pg/dL) and ADMA (from 4.8+1.5 to 3.5+1.1 mM/L) levels. The changes in FMD after treatment correlated inversely with those in TNF-a (R ¼ 20.711, P , 0.01) and ADMA (R ¼ 20.717, P , 0.01) levels.
The exaggerated blood pressure response to exercise (EBPR) is an independent predictor of hypertension. Asymmetric dimethylarginine (ADMA) is an endogenous nitric oxide inhibitor and higher plasma levels of ADMA are related to increased cardiovascular risk. The aim of this study is to identify the relationship between ADMA and EBPR.

A total of 66 patients (36 with EBPR and 30 as controls) were enrolled in the study. EBPR is defined as blood pressure (BP) measurements ≥200/100 mmHg during the treadmill test. All the subjects underwent 24-h ambulatory BP monitoring. L-arginine and ADMA levels were measured using a high performance lipid chromatography technique.

The serum ADMA levels were increased in the EBPR group compared to the healthy controls (4.0±1.4 vs 2.6±1.1 μmol/L respectively, P=0.001), but L-arginine levels were similar in the 2 groups (P=0.19). The serum ADMA levels were detected as an independent predictor of EBPR (odds ratio 2.28; 95% confidence interval 1.22–4.24; P=0.002). Serum ADMA levels might play a role in EBPR to exercise.

Endothelial dysfunction occurs early in atherosclerosis in response to cardiovascular risk factors. The occurrence of endothelial dysfunction is primarily the result of reduced nitric oxide (NO) bioavailabilty. It represents an independent predictor of cardiovascular events and predicts the prognosis of the patient. Therefore, endothelial function has been identified as a target for therapeutic intervention. Regular exercise training is a nonpharmacological option to improve endothelial dysfunction in patients with cardiovascular disease by increasing NO bioavailability.

Peripheral Arterial Disease (PAD) is a cause of significant morbidity and mortality in the Western world. risk factor modification and endovascular and surgical revascularisation are the main treatment options at present. However, a significant number of patients still require major amputation. There is evidence that nitric oxide (NO) and its endogenous inhibitor asymmetric dimethylarginine (ADMA) play significant roles in the pathophysiology of PAD.

This paper reviews experimental work implicating the ADMA-DDAH-NO pathway in PAD, focusing on both the vascular dysfunction and both the vascular dysfunction and effects within the ischaemic muscle, and examines the potential of manipulating this pathway as a novel adjunct therapy in PAD.

In patients with CHF, the peripheral vascular resistance is increased via activation of the neurohormonal system, namely by autonomous sympathetic nervous system, rennin -angiotensin- aldosterone system (RAAS), and endothelin system. The vascular endothelial function in patients with CHF, mainly represented by the endothelium-dependent vasodilation, is altered.

Such alteration leads to increased vascular tone and remodeling of the blood vessels, reducing the peripheral blood flow. Hence, the amount of oxygen for the skeletal muscles is compromised, with progressive exercise intolerance. The vascular endothelial dysfunction in the CHF is mainly due to the decrease of the nitric oxide production induced by the reduced gene expression of eNOS and increased oxidative stress.

The endothelium-dependent vasodilation alteration has been virtually reported in all cardiovascular diseases. Using sauna bath as therapeutic option for CHF is not very recent, since in the 1950’s the first studies with CHF patients were conducted and the potential beneficial effect of sauna was suggested. However, some time later the studies emphasized especially its risks and recommended caution in its use for cardiac patients.

Frequently, sports medicine physicians are invited to evaluate the impact of the sauna on diseases and on health in general. Sauna can be beneficial or dangerous depending on its use. In the past few years the sauna is considered beneficial for the cardiovascular diseases’ patients, as the heart failure and lifestyle-related diseases, mainly by improving the peripheral endothelial function through the increase in cardiac output and peripheral vasodilation.

It is widely known that the vasodilators, such as angiotensin converting enzyme inhibitors, improve the CHF and increase the peripheral perfusion. Since the endothelial function is altered in CHF, the endothelium is considered as a new therapeutic target in heart failure. Hence, the angiotensin converting enzyme inhibitors and physical training improve the endothelial function in CHF patients. One of the proposed mechanisms for the alteration of the endothelium-dependent vasodilation would be through the decrease of the NO production in the peripheral vessels in CHF patients. The decrease of peripheral perfusion would decrease the shear stress. The shear stress is an important stimulus for NO production and eNOS expression. On the other hand, the heat increases the cardiac output and improves the peripheral perfusion in CHF patients. Consequently, with the cardiac output improvement in CHF patients, an increase of the shear stress, NO production and eNOS expression are expected.

Sauna bath
The sauna bath represents a heat load of 300-600 W/m2 of body surface area. The skin temperature rapidly increases to ± 40o-41oC and the thermoregulatory mechanisms are triggered. Evaporative heat transfer by sweating is the only effective body heat loss channel in dry sauna. The sweating begins rapidly and reaches its maximum level in ± 15 min. The total sweat secretion represents a heat loss of about 200 W/m2 of the body surface area. The body cannot compensate for the heat load and causing elevation of internal temperature. The skin circulation increases substantially. The skin blood flow, in the thermo-neutral condition (± 20oC) and in rest corresponding to ± 5-10% of the cardiac output, can reach ± 50-70% of the cardiac output.

Thermal therapy in 60oC produced systemic arterial, pulmonary arterial and venous vasodilation, reduced the preload and afterload and improved the cardiac output and the peripheral perfusion, clinical symptoms, life quality, and cardiac arrhythmias in CHF patients. In infants with severe CHF secondary to ventricular septal defect, the sauna therapy decreased the systemic vascular resistance and increased the cardiac output. The sauna benefits in CHF patients are possibly caused by the improvement of the vascular endothelial function and normalization of the neurohormonal system .

Ikeda et al. discovered that the observed improvements in the sauna therapy are due to the eNOS expression increase in the arterial endothelium. They later showed that the thermal therapy with sauna improves the survival of the TO-2 cardiomyopathic hamsters with CHF and, more recently, showed that the repetitive therapy with sauna increases the eNOS expression and the nitric oxide production in artery endothelium of TO-2 cardiomyopathic hamsters with CHF.
Whether n-3 polyunsaturated fatty acid (PUFA) supplementation and/or diet intervention might have beneficial influence on endothelial function was assessed using plasma levels of ADMA and L-arginine. A male population (n = 563, age 70 ± 6 yrs) with long-standing hyperlipidemia, characterized as high risk individuals in 1970–72, was included, randomly allocated to receive placebo n-3 PUFA capsules (corn oil) and no dietary advice (control group), dietary advice (Mediterranean type), n-3 PUFA capsules, or dietary advice and n-3 PUFA combined and followed for 3 years. Fasting blood samples were drawn at baseline and the end of the study.

Compliance with both intervention regimens were demonstrated by changes in serum fatty acids and by recordings from a food frequency questionnaire. No influence of either regimens on ADMA levels were obtained. However, n-3 PUFA supplementation was accompanied by a significant increase in L-arginine levels, different from the decrease observed in the placebo group (p < 0.05). In individuals with low body mass index (<26 kg/m2), the decrease in L-arginine on placebo was strengthened (p = 0.01), and the L-arginine/ADMA ratio was also significantly reduced (p = 0.04). In this rather large randomized intervention study, ADMA levels were not influenced by n-3 PUFA supplementation or dietary counselling. n-3 PUFA did, however, counteract the age related reduction in L-arginine seen on placebo, especially in lean individuals, which might be considered as an improvement of endothelial function.

Traditional Chinese Medicine

Traditional Chinese Medicine (TCM) involves a broad range of empirical testing and refinement and plays an important role in the health maintenance for people all over the world. However, due to the complexity of Chinese herbs, a full understanding of TCM’s action mechanisms is still unavailable despite plenty of successful applications of TCM in the treatment of various diseases, including especially cardiovascular diseases (CVD), one of the leading causes of death.

An integrated system of TCM has been constructed to uncover the underlying action mechanisms of TCM by incorporating the chemical predictors, target predictors and network construction approaches from three representative Chinese herbs, i.e., Ligusticum chuanxiong Hort., Dalbergia odorifera T. Chen and Corydalis yanhusuo WT Wang widely used in CVD treatment, by combined use of drug absorption, distribution, metabolism and excretion (ADME) screening and network pharmacology techniques. These studies have generated 64 bioactive ingredients and identified 54 protein targets closely associated with CVD, to clarify some of the common conceptions in TCM, and provide clues to modernize such specific herbal medicines.

Ligusticum chuanxiong Hort., Dalbergia odorifera T. Chen and Corydalis yanhusuo WT Wang
Twenty-two of 194 ingredients in Ligusticum chuanxiong demonstrate good bioavailability (60%) after oral administration. Interestingly, as the most abundant bioactive compound of Chuanxiong, Ligustilide (M120) only has an adequate OB of 50.10%, although it significantly inhibits the vasoconstrictions induced by norepinephrine bitartrate (NE) and calcium chloride (CaCl2). Indeed, this compound can be metabolized to butylidenephthalide, senkyunolide I (M156), and senkyunolide H (M155) in vivo.

The three natural ingredients produce various pharmacological activities in cerebral blood vessels, the general circulatory system and immune system including spasmolysis contraction effects, inhibitory effects of platelet aggregation and anti-proliferative activity, and thus improve the therapeutic effect on patients. Cnidilide (M93, OB = 77.55%) and spathulenol (M169, OB = 82.37%) also closely correlate with the smooth muscle relaxant action, and thereby have the strongest spasmolytic activity. Carotol (M8) and Ferulic acid (M105) with an OB of 149.03% and 86.56%, respectively, demonstrate better bioavailability compared with cnidilide and spathulenol, which show strong antifungal, antioxidant and anti-inflammatory activity.

The pharmacological activity of ferulic acid results in the improvement of blood fluidity and the inhibition of platelet aggregation, which may offer beneficial effects against cancer, CVD, diabetes and Alzheimer’s disease. As for 3-n-butylphthalide (M85, OB = 71.28%), this compound is not only able to inhibit platelet aggregation, but also decreases the brain infarct volume and enhances microcirculation, thus benefiting patients with ischemic stroke. Platelet aggregation represents a multistep adhesion process involving distinct receptors and adhesive ligands, with the contribution of individual receptor-ligand interactions to the aggregation process depending on the prevailing blood flow conditions, implying that the rheological (blood flow) conditions are an important impact factor for platelet aggregation. Moreover, thrombosis, the pathological formation of platelet aggregates and one of the biggest risk factors for CVD, occludes blood flow causing stroke and heart attack. This explains why the traditional Chinese herb Ligusticum chuanxiong that inhibits platelet aggregates forming and promotes blood circulation can be used in treatment of CVD.

Twenty-six percent (24 of 93) of the ingredients in Dalbergia odorifera meet the OB > 60% criterion irrespective of the pharmacological activity. Relatively high bioavailability values were predicted for the mainly basic compounds odoriflavene (M275, OB = 84.49%), dalbergin (M247, OB = 78.57%), sativanone (M281, OB = 73.01%), liquiritigenin (M262, OB = 67.19%), isoliquiritigenin (M259, OB = 61.38%) and butein (M241, OB = 78.38%). Interestingly, all of the six ingredients show obvious anti-inflammatory property. Butein, liquiritigenin and isoliquiritigenin inhibit cell inflammatory responses by suppressing the NF-κB activation induced by various inflammatory agents and carcinogens, and by decreasing the NF-κB reporter activity. Inflammation occurs with CVD, and Dalbergia odorifera, one of the most potent anti-cardiovascular and anti-cerebrovascular agents, exerts great anti-inflammatory activity.

Corydalis yanhusuo has gained ever-increasing popularity in today’s world because of its therapeutic effects for the treatment of cardiac arrhythmia disease, gastric and duodenal ulcer and menorrhalgia. In our work, 21% (15 of 73) of chemicals in this Chinese herb display good OB (60% or even high), and the four main effective ingredients are natural alkaloid agents.

Dehydrocorydaline blocks the release of noradrenaline from the adrenergic nerve terminals in both the Taenia caecum and pulmonary artery, and thereby inhibits the relaxation or contraction of adrenergic neurons. As for dehydrocavidine with an OB of 47.59%, this alkaloid exhibits a significant spasmolytic effect, which acts via relaxing smooth muscle.

In recent years, CVD has been at the top list of the most serious health problems. Many different types of therapeutic targets have already been identified for the management and prevention of CVD, such as endothelin and others. The key question asked is

  • what the interactions of the active ingredients of the Chinese herbs are with their protein targets in a systematic manner and
  • how do the corresponding targets change under differential perturbation of the chemicals?

The study used an unbiased approach to probe the proteins that bind to the small molecules of interest in CVD on the basis of the Random Forest (RF) and Support Vector Machine (SVM) methods combining the chemical, genomic and pharmacological information for drug targeting and discovery on a large scale. Applied to 64 ingredients derived from the three traditional Chinese medicines Dalbergia odorifera, Ligusticum chuanxiong and Corydalis yanhusuo, which show good OB, 261 ligand-target interactions have been constructed, 221 of which are enzymes, receptors, and ion channels. This indicates that chemicals with multiple relative targets are responsible for the high interconnectedness of the ligand-target interactions. The promiscuity of drugs has restrained the advance in recent TCM, because they were thought to be undesirable in favor of more target-specific drugs.

Target Identification and Validation
To validate the reliability of these target proteins, the researchers performed a docking analysis to select the ligand-protein interactions with a binding free energies of ≤−5.0 kcal/mol, which leads to the sharp reduction of the interaction number from 5982 to 760. These drug target candidates were subsequently subject to PharmGkb (available online: http://www.pharmgkb.org; accessed on 1 December 2011), a comprehensive disease-target database, to investigate whether they were related to CVD or not, and finally, 54 proteins were collected and retained.

Fourty-two proteins (76%) were identified as the targets of Ligusticum chuanxiong, such as dihydrofolate reductase (P150), an androgen receptor (P210) and angiotensin-converting enzyme (P209) that were involved in the development of CVD. Of the proteins, seven and two were recognized as those of Dalbergia odorifera and Corydalis yanhusuo, respectively. For Dalbergia odorifera, this Chinese herb has 48 potential protein targets, 13 of which have at least one link to other drugs.

The three herbs share 29 common targets, accounting for 52.7% of the total number. Indeed, as one of the most important doctrines of TCM
abstracted from direct experience and perception, “multiple herbal drugs for one disease” has played an undeniable role. These studies explored the targets of the three Chinese herbs, indicating that these drugs target the same targets simultaneously and exhibit similar pharmacological effects on CVD. This is consistent with the theory of “multiple herbal drugs for one disease”.

The three Chinese herbs possess specific targets. The therapeutic efficacy of a TCM depends on multiple components, targets and pathways. The complexity becomes a huge obstacle for the development and innovation of TCM. For example, the Chinese herb Ligusticum chuanxiong identifies the protein caspase-3 (P184), a cysteinyl aspartate-specific protease, as one of its specific targets, and exhibits inhibitory effects on the activity of this protease. In fact, connective tissue growth factor enables the activation of caspase-3 to induce apoptosis in human aortic vascular smooth muscle cells.

Thus, modulation of the activity of caspase-3 with Ligusticum chuanxiong suggests an efficient therapeutic approach to CVD. The Chinese herb Dalbergia odorifera has the α-2A adrenergic receptor (P216) as its specific target and probably blocks the release of this receptor, and thus influences its action. As for Corydalisyanhusuo, the protein tyrosine-protein kinase JAK2 (P9) is the only specific target of this Chinese herb. The results indicate different specific targets possessed by the three Chinese herbs.

Ligand-Candidate Target and Ligand-Potential Target Networks
Previous studies have already reported the relationships of the small molecules with CVD, which indicates the reliability of our results [45,46]. Regarding the candidate targets, we have found that prostaglandin G/H synthase 2 (P46) and prostaglandin G/H synthase 1 (P47) possess the largest number of connected ingredients. Following are nitric-oxide synthase, endothelial (P66) and tyrosine-protein phosphatase non-receptor type 1 (P8), which have 62 and 61 linked chemicals, respectively.
The 29 targets shared by the three traditional Chinese herbs exhibit a high degree of correlations with CVD, which further verifies their effectiveness for the treatment of CVD. These results provide a clear view of the relationships of the target proteins with CVD and other related diseases, which actually link the Chinese herbs and the diseases via the protein targets. This result further explains the theory of “multiple herbal drugs for one disease” based on molecular pharmacology.

Target-Pathway Network
Cells communicate with each other using a “language” of chemical signals. The cell grows, divides,or dies according to the signals it receives. Signals are generally transferred from the outside of the cell. Specialized proteins are used to pass the signal—a process known as signal transduction. Cells have a number of overlapping pathways to transmit signals to multiple targets. Ligand binding in many of the signaling proteins in the pathway can change the cellular communication and finally affect cell growth and proliferation. The authors extracted nine signal pathways closely associated with CVD in PharmGkb (available online: http://www.pharmgkb.org; accessed on 1 December 2011).

As the main components in the VEGF system, proto-oncogene tyrosine-protein kinase Src, eNOS, and hsp90-α is also recognized as common targets of Dalbergia odorifera, Ligusticum chuanxiong and Corydalis yanhusuo, which are efficient for the treatment of CVD. This implies that the candidate drugs can target different target proteins involved in the same or different signal pathways, and thereby have potential effects on the whole signal system.

Target Prediction
In search of the candidate targets, the model that efficiently integrates the chemical, genomic and pharmacological information for drug targeting and discovery on a large scale is based on the two powerful methods Random Forest (RF) and Support Vector Machine (SVM). The model is supported by a large pharmacological database of 6511 drugs and 3999 targets extracted from the DrugBank database (available online: http://drugbank.ca/; accessed on 1 June 2011), and shows an impressive performance of prediction for drug-target interaction, with a concordance of 85.83%, a sensitivity of 79.62% and a specificity of 92.76%. the candidate targets were selected according to the criteria that the possibility of interacting with potential candidate targets was higher than 0.6 for the RF model and 0.7 for the SVM model. The obtained candidate targets were finally reserved and were further predicted for their targets.

Target Validation
Molecular docking analysis was carried out using the AutoDock software (available online: http://autodock.scripps.edu/; accessed on 1 February 2012). This approach performs the docking of the small, flexible ligand to a set of grids describing the target protein. During the docking process, the protein was considered as rigid and the molecules as flexible. The crystal structures of the candidate targets were downloaded from the RCSB Protein Data Bank (available online: http://www.pdb.org/; accessed on 1 December 2011), and the proteins without crystal structures were performed based on homology modeling using the Swiss-Model Automated Protein Modelling Server (available online: http://swissmodel.expasy.org/; accessed on 1 February 2012).

TCM is a heritage that is thousands of years old and is still used by millions of people all over the world—even after the development of modern scientific medicine. Chinese herbal combinations generally include one or more plants and even animal products.

The study identified 54 protein targets, which are closely associated with CVD for the three Chinese herbs, of which 29 are common targets (52.7%), which clarifies the mechanism of efficiency of the herbs for the treatment of CVD.

Activation of NFkB

Extracellular stimuli for NFkB activation and NFkB regulated genes
Extracellular stimuli                       Regulated genes
TNFa                                         Growth factors (G/M-CSF)
Interleukin 1                            G/M CSF, M CSF, G CSF
ROS                                              Cell adhesion molecules
UV light                            ICAM-1, VCAM, E-Selectin, P-selectin
Ischaemia                                   Cytokines
Lipopolysaccharide               TNFa, IL-1, IL-2, IL-6, interferon
Bacteria                                        Transcription regulators
Viruses                                         P53, IkB, c-rel, c-myc
Amyloid                                      Antiapoptotic proteins
Glutamate                              TRAF-1, TRAF-2, c-IAP1, c-IAP2
Pathophysiology
Reactive oxygen species (ROS) are toxic and in conditions of a dysbalance between their overproduction and the diminished activity of various antioxidant enzymes and other molecules induce cellular injury termed oxidative stress. ROS are often related to a number of diseases like atherosclerosis. However, the mechanism is not clear at all. Latest years of research have brought the idea of connection between ROS and NFkB. And indeed, in vitro studies showed a rapid activation of NFkB after exposure of certain cell types to ROS. Today, no specific receptor for ROS has been found, thus, the details of the ROS induced activation of NFkB are missing.

Natural occurring agents which actions are still a matter of debate in the theory and nouvelle small molecular derivates activate or inhibit the transcriptional factor. Synthetic oligo and polypeptide inhibitors of NFkB can penetrate the cell membrane and directly act on the Rel proteins. The most sophisticated approaches towards inhibiting the activation and translocation of NFkB into the nucleus represent gene deliveries, using plasmids or adenoviruses containing genes for various super repressors—modified IkB proteins, or so called NFkB decoys, which interact with activated NFkB and thus, inhibit the interaction between the transcription factor and nuclear DNA enhancers.

A simplified scheme of the activation of NFkB by the degradation of IkB. IkB is phosphorylated by IKK and ubiquinatated by the ubiquitine ligase system (ULS). IkB is further degradated by the 26S proteasome (26S).Activated NFkB can pass the nuclear membrane and interact with kB binding sequences in enhancers of NFkB regulated genes. LPS, lipopolysaccharide; ROS, reactive oxygen species; FasL, Fas ligand; TRAF, TNFa receptor associated factor; NIK, NFkB inducing kinase; MEKK, mitogen activated protein kinase/extracellular signal regulated kinases kinases.

The medicine of this century is a medicine of molecules, the diagnostic procedure and the therapy moves further from the “clinical picture” to the use of achievements in molecular biology and genetics. However, sober scepticism and awareness are indicated. Especially the role of NFkB in multiple signal transducing pathways and the tissue dependent variability of responses to alternations in NFkB pathway may be the reasons for unwanted side effects of the therapy that are after in vitro or in vivo experiments hardly to expect in the clinical use.

Therapeutic Targets
Modern drug discovery is primarily based on the search and subsequent testing of drug candidates acting on a preselected therapeutic target. Progress in genomics, protein structure, proteomics, and disease mechanisms has led to a growing interest in an effort for finding new targets and more effective exploration of existing targets. The number of reported targets of marketed and investigational drugs has significantly increased in the past 8 years. There are 1535 targets collected in the therapeutic target database.
Knowledge of these targets is helpful for molecular dissection of the mechanism of action of drugs and for predicting features that guide new drug design and the
search for new targets. This article summarizes the progress of target exploration and investigates the characteristics of the currently explored targets to analyze their sequence, structure, family representation, pathway association, tissue distribution, and genome location features for finding clues useful for searching for new targets. Possible “rules” to guide the search for druggable proteins and the feasibility of using a statistical learning method for predicting druggable proteins directly from their sequences are discussed.

Current Trends in Exploration of Therapeutic Targets
There are 395 identifiable targets described in 1606 patents. Of these targets, 264 have been found in more than one patent and 50 appear in more than 10 patents. The number of patents associated with a target can be considered to partly correlate with the level of effort and intensity of interest currently being directed to it. Approximately one third of the patents with an identifiable target were approved in the past year. This suggests that the effort for the exploration of these targets is ongoing, and there has been steady progress in the discovery of new investigational agents directed to these targets.

Various degrees of progress have been made toward discovery and testing of agents directed at these targets. However, for some of these targets, many difficulties remain to be resolved before viable drugs can be derived. The appearance of a high number of patents associated with these targets partly reflects the intensity of efforts for finding effective drug candidates against these targets.

There are 62 targets being explored for the design of subtype-specific drugs, which represents 15.7% of the 395 identifiable targets in U.S. patents approved in 2000 through 2004. Compared with the 11 targets of FDA approved subtype-specific drugs during the same period, a significantly larger number of targets are being explored for the design of subtype-specific drugs.

What Constitutes a Therapeutic Target?
The majority of clinical drugs achieve their effect by binding to a cavity and regulating the activity, of its protein target. Specific structural and physicochemical properties, such as the “rule of five” (Lipinski et al., 2001), are required for these drugs to have sufficient levels of efficacy, bioavailability, and safety, which define target sites to which drug-like molecules can bind. In most cases, these sites exist out of functional necessity, and their structural architectures accommodate target-specific drugs that minimally interact with other functionally important but structurally similar sites.
These constraints limit the types of proteins that can be bound by drug-like molecules, leading to the introduction of the concept of druggable proteins (Hopkins and Groom, 2002; Hardy and Peet, 2004). Druggable proteins do not necessarily become therapeutic targets (Hopkins and Groom, 2002); only those that play key roles in diseases can be explored as potential targets.

 Prediction of Druggable Proteins by a Statistical Learning Method

Currently, the support vector machine (SVM) method seems to be the most accurate statistical learning method for protein predictions. SVM is based on the structural risk minimization principle from statistical learning theory. Known proteins are divided into druggable and nondruggable classes; each of these proteins is represented by their sequence-derived physicochemical features.

These features are then used by the SVM to construct a hyperplane in a higher dimensional hyperspace that maximally separates druggable proteins and nondruggable ones. By projecting the sequence of a new protein onto this hyperspace, it can be determined whether this protein is druggable from its location with respect to the hyperplane. It is a druggable protein if it is located on the side of druggable class.
References

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Lev-Ari, A. Stem cells create new heart cells in baby mice, but not in adults, study shows

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Lev-Ari, A. Cardiovascular Disease (CVD) and the Role of agent alternatives in endothelial Nitric Oxide Synthase (eNOS) Activation and Nitric Oxide Production

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Lev-Ari, A. Bystolic’s generic Nebivolol – positive effect on circulating Endothelial Progenitor Cells endogenous augmentation

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Lev-Ari, A. Macrovascular Disease – Therapeutic Potential of cEPCs: Reduction Methods for CV Risk

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 Nitric Oxide and Sepsis, Hemodynamic Collapse, and the Search for Therapeutic Options

Congestive Heart Failure & Personalized Medicine: Two-gene Test predicts response to Beta Blocker Bucindolol

Mediterranean Diet is BEST for patients with established Heart Disorders

NO Nutritional remedies for hypertension and atherosclerosis. It’s 12 am: do you know where your electrons are?

Endothelin Receptors in Cardiovascular Diseases: The Role of eNOS Stimulation
Inhibition of ET-1, ETA and ETA-ETB, Induction of NO production, stimulation of eNOS and Treatment Regime with PPAR-gamma agonists (TZD): cEPCs

Endogenous Augmentation for Cardiovascular Risk Reduction – A Bibliography

Reveals from ENCODE project will invite high synergistic collaborations to discover specific targets

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Pancreatic cancer genomes reveal aberrations in axon guidance pathway genes

Nature (2012) 

doi:10.1038/nature11547 Received 09 January 2012  Accepted 04 September 2012 

Published online 24 October 2012

Pancreatic cancer is a highly lethal malignancy with few effective therapies. We performed exome sequencing and copy number analysis to define genomic aberrations in a prospectively accrued clinical cohort (n = 142) of early (stage I and II) sporadic pancreatic ductal adenocarcinoma. Detailed analysis of 99 informative tumours identified substantial heterogeneity with 2,016 non-silent mutations and 1,628 copy-number variations. We define 16 significantly mutated genes, reaffirming known mutations (KRASTP53CDKN2A, SMAD4MLL3TGFBR2, ARID1A andSF3B1), and uncover novel mutated genes including additional genes involved in chromatin modification (EPC1 and ARID2), DNA damage repair (ATM) and other mechanisms (ZIM2,MAP2K4NALCNSLC16A4 and MAGEA6). Integrative analysis with in vitro functional data and animal models provided supportive evidence for potential roles for these genetic aberrations in carcinogenesis. Pathway-based analysis of recurrently mutated genes recapitulated clustering in core signalling pathways in pancreatic ductal adenocarcinoma, and identified new mutated genes in each pathway. We also identified frequent and diverse somatic aberrations in genes described traditionally as embryonic regulators of axon guidance, particularly SLIT/ROBO signalling, which was also evident in murine Sleeping Beauty transposon-mediated somatic mutagenesis models of pancreatic cancer, providing further supportive evidence for the potential involvement of axon guidance genes in pancreatic carcinogenesis.

Figures at a glance

Contributions

The research network comprising the Australian Pancreatic Cancer Genome Initiative, the Baylor College of Medicine Cancer Genome Project and the Ontario Institute for Cancer Research Pancreatic Cancer Genome Study (ABO collaboration) contributed collectively to this study as part of the International Cancer Genome Consortium. Biospecimens were collected at affiliated hospitals and processed at each biospecimen core resource centre. Data generation and analyses were performed by the genome sequencing centres, cancer genome characterization centres and genome data analysis centres. Investigator contributions are as follows: S.M.G., A.V.B., J.V.P., R.L.S., R.A.G., D.A.W., M.-C.G., J.D.M., L.D.S and T.J.H. (project leaders); A.V.B., S.M.G. and R.L.S. (writing team); A.L.J., J.V.P., P.J.W., J.L.F., C.L., M.A., O.H., J.G.R., D.T., C.X., S.Wo., F.N., S.So., G.K. and W.K. (bioinformatics/databases); D.K.M., I.H., S.I., C.N., S.M., A.Chr., T.Br., S.Wa., E.N., B.B.G., D.M.M., Y.Q.W., Y.H., L.R.L., H.D., R. E. D., R.S.M. and M.W. (sequencing); N.W., K.S.K., J.V.P., A.-M.P., K.N., N.C., M.G., P.J.W., M.J.C., M.P., J.W., N.K., F.Z., J.D., K.C., C.J.B., L.B.M., D.P., R.E.D., R.D.B., T.Be. and C.K.Y. (mutation, copy number and gene expression analysis); A.L.J., D.K.C., M.D.J., M.P., C.J.S., E.K.C., C.T., A.M.N., E.S.H., V.T.C., L.A.C., E.N., J.S.S., J.L.H., C.T., N.B. and M.Sc. (sample processing and quality control); A.J.G., J.G.K., R.H.H., C.A.I.-D., A.Cho., A.Mai., J.R.E., P.C. and A.S. (pathology assessment); J.W., M.J.C., M.P., C.K.Y. and mutation analysis team (network/pathway analysis and functional data integration); K.M.M., N.A.J., N.G.C., P.A.P.-M., D.J.A., D.A.L., L.F.A.W., A.G.R., D.A.T., R.J.D., I.R., A.V.P., E.A.M., R.L.S., R.H.H. and A.Maw. (functional screens); E.N., A.L.J., J.S.S., A.J.G., J.G.K., N.D.M., A.B., K.E., N.Q.N., N.Z., W.E.F., F.C.B., S.E.H., G.E.A., L.M., L.T., M.Sam., K.B., A.B., D.P., A.P., N.B., R.D.B., R.E.D., C.Y., S.Se., N.O., D.M., M-S.T., P.A.S., G.M.P., S.G., L.D.S., C.A.I.-D., R.D.S., C.L.W., R.A.M., R.T.L., S.B., V.C., M.Sca., C.B., M.A.T., G.T., A.S. and J.R.E. (sample collection and clinical annotation); D.K.C., M.P., C.J.S., E.S.H., J.A.L., R.J.D., A.V.P. and I.R. (preclinical models).

Competing financial interests

The authors declare no competing financial interests.

International Team Reports on Large-Scale Pancreatic Cancer Analysis

October 24, 2012

NEW YORK (GenomeWeb News) – A whole-exome sequencing and copy number variation study of pancreatic cancer published online today in Nature suggests that the disease sometimes involves alterations to genes and pathways best known for their role in axon guidance during embryonic development.

The work was conducted as part of the International Cancer Genome Consortium effort by researchers with the BCM Cancer Genome Project, the Australian Pancreatic Cancer Genome Initiative, and the Ontario Institute for Cancer Research Pancreatic Cancer Genome Study.

As they reported today, the investigators identified thousands of somatic mutations and copy number alterations in pancreatic ductal adenocarcinoma cancer, the most common form of pancreatic cancer. Some of the mutations affected known cancer genes and/or pathways implicated in pancreatic cancer in the past. Other genetic glitches pointed to processes not previously linked to the disease including mutations to axon guidance genes such as SLIT2, ROBO1, and ROBO2.

“This is a category of genes not previously linked to pancreatic cancer,” Baylor College of Medicine researcher William Fisher, a co-author on the new paper, said in a statement. “We are poised to jump on this gene list and do some exciting things.”

Pancreatic cancer is among the deadliest types of cancer, he and his colleagues explained, with a grim five-year survival rate of less than 5 percent. But despite its clinical importance, direct genomic studies of primary tumors had been stymied in the past due to difficulties obtaining large enough samples for such analyses.

“Genomic characterization of pancreatic ductal adenocarcinoma, which accounts for over 90 [percent] of pancreatic cancer, has so far focused on targeted polymerase chain reaction-based exome sequencing of primary and metastatic lesions propagated as xenografts or cell lines,” the study authors noted.

“A deeper understanding of the underlying molecular pathophysiology of the clinical disease is needed to advance the development of effective therapeutic and early detection strategies,” they added.

For the current study, researchers started with a set of tumor-normal samples from 142 individuals with stage I or stage II sporadic pancreatic ductal adenocarcinoma. Following a series of experiments to assess tumor cellularity and other features that can impact tumor analyses, they selected 99 patients whose samples were assessed in detail.

For whole-exome sequencing experiments, the investigators nabbed coding sequences from matched tumor and normal samples using either Agilent SureSelectII or Nimblegen capture kits before sequencing the exomes on SOLiD 4 or Illumina sequencing platforms. They also used Ion Torrent and Roche 454 platforms to validate apparent somatic mutations in the samples.

For its copy number analyses, meanwhile, the team tested the pancreatic cancer and normal tissue samples using Illumina HumanOmni1 Quad genotyping arrays.

When they sifted through data for the 99 most completely characterized pancreatic tumors, researchers uncovered 1,628 CNVs and roughly 2,000 non-silent, somatic coding mutations. More than 1,500 of the non-silent mutations were subsequently verified through additional sequencing experiments.

On average, each of the tumors contained 26 coding mutations. And despite the variability in mutations present from one tumor to the next, researchers identified 16 genes that were mutated in multiple tumor samples.

Some were well-known cancer players such as KRAS, which was mutated in more than 90 percent of the 142 pancreatic tumors considered initially. Several other genes belonged to cell cycle checkpoint, apoptosis, blood vessel formation, and cell signaling pathways, researchers reported, or to pathways involved in chromatin remodeling or DNA damage repair.

For example, some 8 percent of tumors contained mutations to ATM, a gene participating in a DNA damage repair pathway that includes the ovarian/breast cancer risk gene BRCA1.

Genes falling within axon guidance pathways turned up as well. That pattern was supported by the researchers analyses of data from published pancreatic cancer studies — including two studies based on mutagenesis screens in mouse models of the disease — and by their own gene expression experiments in mice.

The team also tracked down a few more pancreatic ductal adenocarcinoma cases involving mutations to axon guidance genes such as ROBO1, ROBO2, and SLIT2 through targeted testing on 30 more pancreatic cancer patients.

The findings are consistent with those found in some other cancer types, according to the study’s authors, who noted that there is evidence indicating that some axon guidance components feed into signaling pathways related to cancer development, such as the WNT signaling pathway. If so, they explained, it’s possible that mutations to axon guidance genes might influence the effectiveness of therapies targeting such downstream pathways or serve as potential treatment targets themselves.

Still, those involved in the study cautioned that more research is needed not only to explore such possibilities but also to distinguish between driver and passenger mutations in pancreatic cancer.

“The potential therapeutic strategies identified will … require testing in appropriate clinical trials that are specifically designed to target subsets of patients stratified according to well-defined molecular markers,” the study’s authors concluded.

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Reporter: Aviva Lev-Ari, PhD, RN 

Mining the Unknown: A Systems Approach to Metabolite Identification Combining Genetic and Metabolic Information

Jan Krumsiek1, Karsten Suhre1,2, Anne M. Evans3, Matthew W. Mitchell3, Robert P. Mohney3, Michael V. Milburn3, Brigitte Wägele1,4, Werner Römisch-Margl1, Thomas Illig5,6, Jerzy Adamski7,8, Christian Gieger9, Fabian J. Theis1,10, Gabi Kastenmüller1*

 

1 Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Neuherberg, Germany, 2 Department of Physiology and Biophysics, Weill Cornell Medical College in Qatar, Education City, Qatar Foundation, Doha, Qatar, 3 Metabolon, Research Triangle Park, North Carolina, United States of America, 4 Department of Genome-Oriented Bioinformatics, Life and Food Science Center Weihenstephan, Technische Universität München, Freising, Germany, 5 Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany, 6 Biobank of the Hanover Medical School, Hanover Medical School, Hanover, Germany, 7 Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, Neuherberg, Germany, 8 Lehrstuhl für Experimentelle Genetik, Technische Universität München, Freising-Weihenstephan, Germany, 9 Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany, 10 Department of Mathematics, Technische Universität München, Garching, Germany

Abstract 

Recent genome-wide association studies (GWAS) with metabolomics data linked genetic variation in the human genome to differences in individual metabolite levels. A strong relevance of this metabolic individuality for biomedical and pharmaceutical research has been reported. However, a considerable amount of the molecules currently quantified by modern metabolomics techniques are chemically unidentified. The identification of these unknown metabolites is still a demanding and intricate task, limiting their usability as functional markers of metabolic processes. As a consequence, previous GWAS largely ignored unknown metabolites as metabolic traits for the analysis. Here we present a systems-level approach that combines genome-wide association analysis and Gaussian graphical modeling with metabolomics to predict the identity of the unknown metabolites. We apply our method to original data of 517 metabolic traits, of which 225 are unknowns, and genotyping information on 655,658 genetic variants, measured in 1,768 human blood samples. We report previously undescribed genotype–metabotype associations for six distinct gene loci (SLC22A2, COMT, CYP3A5, CYP2C18, GBA3, UGT3A1) and one locus not related to any known gene (rs12413935). Overlaying the inferred genetic associations, metabolic networks, and knowledge-based pathway information, we derive testable hypotheses on the biochemical identities of 106 unknown metabolites. As a proof of principle, we experimentally confirm nine concrete predictions. We demonstrate the benefit of our method for the functional interpretation of previous metabolomics biomarker studies on liver detoxification, hypertension, and insulin resistance. Our approach is generic in nature and can be directly transferred to metabolomics data from different experimental platforms.

Introduction 

Recently, genome-wide association studies (GWAS) on metabolic quantitative traits have proven valuable tools to uncover the genetically determined metabolic individuality in the general population [1][5]. Interestingly, a great portion of the genetic loci that were found to significantly associate with levels of specific metabolites are within or in close proximity to metabolic enzymes or transporters with known disease or pharmaceutical relevance. Moreover, compared to GWAS with clinical endpoints the effect sizes of the genotypes are exceptionally high.

The number and type of the metabolic features that went into these GWAS was mainly defined by the metabolomics techniques used: Gieger et al. [1] and Illig et al. [2] used a targeted mass spectrometry (MS)-based approach giving access to the concentrations of 363 and 163 metabolites, respectively. Suhre et al. [3] and Nicholson et al. [4] applied untargeted nuclear magnetic resonance (NMR) based metabolomics techniques, yielding 59 metabolites that had been identified in the spectra prior to the GWAS and 579 manually selected peaks from the spectra, respectively. In Suhre et al. [5], 276 metabolites from an untargeted MS-based approach were analyzed.

While these previous GWAS focused on metabolic features with known identity, untargeted metabolomics approaches additionally provide quantifications of so-called “unknown metabolites”. An unknown metabolite is a small molecule that can reproducibly be detected and quantified in a metabolomics experiment, but whose chemical identity has not been elucidated yet. In an experiment using liquid chromatography (LC) coupled to MS, such an unknown would be defined by a specific retention time, one or multiple masses (e.g. from adducts), and a characteristic fragmentation pattern of the primary ion(s). An unknown observed by NMR spectroscopy would correspond to a pattern in the chemical shifts. Unknowns may constitute previously undocumented small molecules, such as rare xenobiotics or secondary products of metabolism, or they may represent molecules from established pathways which could not be assigned using current libraries of MS fragmentation patterns [6], [7] or NMR reference spectra [8].

The impact of unknown metabolites for biomedical research has been shown in recent metabolomics-based discovery studies of novel biomarkers for diseases and various disease-causing conditions. This includes studies investigating altered metabolite levels in blood for insulin resistance [9], type 2 diabetes [10], and heart disorders [11]. A considerable number of high-ranking hits reported in these biomarker studies represent unknown metabolites. As long as their chemical identities are not clarified the usability of unknown metabolites as functional biomarkers for further investigations and clinical applications is rather limited.

In mass-spectrometry-based metabolomics approaches, the assignment of chemical identity usually involves the interpretation and comparison of experiment-specific parameters, such as accurate masses, isotope distributions, fragmentation patterns, and chromatography retention times [12][14]. Various computer-based methods have been developed to automate this process. For example, Rasche and colleagues [15] elucidated structural information of unknown metabolites in a mass-spectrometry setup using a graph-theoretical approach. Their approach attempts to reconstruct the underlying fragmentation tree based on mass-spectra at varying collision energies. Other authors excluded false candidates for a given unknown by comparing observed and predicted chromatography retention times [16], [17], or by the automatic determination of sum formulas from isotope distributions [18]. Furthermore, Gipson et al. [19] and Weber et al. [20] integrated public metabolic pathway information with correlating peak pairs in order to facilitate metabolite identification. However, these methods might not be applicable for high-throughput metabolomics datasets that have been produced in a fee-for-service manner, since the mass spectra as such might not be readily available.

Approaching the problem from a conceptually different perspective, we here present a novel functional metabolomics method to predict the identities of unknown metabolites using a systems biological framework. By combining high-throughput genotyping data, metabolomics data, and literature-derived metabolic pathway information, we generate testable hypotheses on the metabolite identities based solely on the obtained metabolite quantifications (Figure 1). No further experiment-specific data such as retention times, isotope patterns and fragmentation patterns are required for this analysis.

 

Figure 1. Data integration workflow for the systematic classification of unknown metabolites.

We combine high-throughput metabolomics and genotyping data in Gaussian graphical models (GGMs) [21] and in genome-wide association studies (GWAS) [5] in order to produce testable predictions of the unknown metabolites’ identities. These hypotheses are then subject to experimental verification by mass-spectrometry. Six such cases have been fully worked through and are presented in Table 3. doi:10.1371/journal.pgen.1003005.g001

 http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003005?imageURI=info:doi/10.1371/journal.pgen.1003005.g001#pgen-1003005-g001

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Discussion 

We developed and validated a novel integrative approach for the biochemical characterization of “unknown metabolites” from high-throughput metabolomics and genotyping datasets. Our method allows for the functional annotation of previously unidentified metabolites and, as a consequence, enhances the interpretability of metabolomics data in genome-wide association studies and biomarker discovery. For the first time, we systematically evaluated genetic associations of unknown metabolites, thereby discovering seven new loci of metabolic individuality. By classifying a series of unknown metabolites, we gained new insights into the functional interplay between genetic variation and the metabolome both for previously reported and new loci. Furthermore, several of the unknown compounds that we identified as well as their newly associated loci were independently reported in disease-related studies. In the following, we discuss three genetic loci and their associated phenotypes.

COMT and hepatic detoxification

The first example is a recent biomarker study, where Milburn et al. [34] reported an association of X-11593 with hepatic detoxification. In our GWAS, we find a strong association of X-11593 with the COMT locus, which encodes the catechol-O-methyltransferase enzyme. COMT is responsible for the inactivation of catecholamines such as L-dopa and various neuroactive drugs by O-methylation [35]. Following our identification approach, we experimentally confirmed the identity of X-11593 as O-methylascorbate. Notably, O-methylascorbate is a known product of ascorbate (vitamin C) O-methylation by COMT [36], [37]. Thus, our observations establish a link between O-methylascorbate blood levels, common genetic variation in the COMT locus and COMT-mediated liver detoxification processes.

ACE and hypertension

The second example relates to the ACE gene locus, which is a known risk locus for cardiovascular disease, hypertension and kidney failure. The protein encoded by the ACE locus, angiotensin-converting enzyme, is an exopeptidase which cleaves dipeptides from vasoactive oligopeptides, and plays a central role in the blood pressure-controlling renin-angiotensin system [38]. Moreover, the ACE protein is a target for various pharmaceuticals (ACE inhibitors), especially in the treatment of hypertension [39]. In our study, we identified three unknowns as dipeptides (X-14205, X-14208 and X-14478), two of which also associated with the ACE locus. These dipeptides could thus represent novel, interesting biomarkers for the activity of ACE. Moreover, Steffens et al. [11] reported a connection between heart failure and X-11805, which is in close proximity to angiontensin-related peptides in the GGM. This connection might be revisited after a successful identification of X-11805 in a future study.

UGT1A/ACADM and insulin resistance

The third example is an explorative study to detect biomarkers for insulin sensitivity. Gall et al. [9] reported several known metabolites (most prominently α-hydroxybutyrate) as biomarkers for insulin resistance. They also reported a series of unknown metabolites among their top hits. In the present study, we investigated three of these unknowns: X-11793 associates with UGT1A (UDP glucuronosyltransferase 1) and represents a bilirubin-related substance. Moreover, we experimentally validated X-11421 and X-13431, which display a strong association with ACADM (acyl-Coenzyme A dehydrogenase, C-4 to C-12 straight chain), as acylcarnitines containing 10 and 9 carbon atoms, respectively. The identification of these latter two unknown metabolites as medium-chain length acylcarnitines is coherent with reports by Adams et al. [40]. The authors found elevated blood plasma acylcarnitine levels in women with type 2 diabetes. Functionally, they attributed this finding to incomplete β-oxidation. Thus, our identification of X-11421 and X-13431 now suggests incomplete β-oxidation as an explanation for the associations found by Gall et al. and implies that acylcarnitines containing 10 and 9 carbon atoms are potential biomarkers for insulin resistance.

Conclusion

In summary, we integrated high-throughput metabolomics and genotyping data from a large population cohort for elucidating the biochemical identities of unknown metabolites. To this end, we applied metabolomics genome-wide association studies and Gaussian graphical modeling in order to link these unknown metabolites with known metabolic classes and biological processes. For six specific scenarios, we went from systematic hypothesis generation over detailed investigation and identity prediction to direct experimental confirmation. Similar validations may now be undertaken for the remaining predictions that we report in Table S1. Finally, we demonstrated the benefit of our method by discussing several of these newly identified metabolites in the context of existing biomarker discovery studies on liver detoxification, hypertension and insulin resistance.

It is to be noted that our method does not specifically require genotyping data. Even metabolomics measurements alone, analyzed through the GGMs, may provide sufficient information for the classification and even precise identity prediction. The unknowns with GGM evidence but without GWAS hits in Figure 4 as well as the HETE scenario represent examples for this approach.

One limitation of our approach is the requirement for associations with functionally described loci or known metabolites. Certain metabolite groups might thus systematically not be identifiable. For instance, if the identity of a whole class of biochemically related molecules is unknown (which might be due to experimental reasons), then the GGM associations between those compounds will not aid in identity elucidation. The 118 unknown compounds for which we could not derive any classification might represent such cases. Thus, our functionally oriented method should be regarded as a complementary extension to the existing identity determination methods.

Accordingly, our approach can be extended in several directions. It can be combined with method-specific, automated techniques that further exclude sets of metabolites. Previously mentioned methods relying on mass-spectra [15] or chromatographic properties [17] are suitable candidates here. Moreover, the method can be directly transferred to other types of metabolomics datasets not specifically originating from MS experiments, such as NMR-based metabolomics.

Beyond the application to metabolite identification, our study demonstrates the general potential of functional metabolomics in the context of genome-wide association studies. The comprehensive metabolic picture provided by GGMs in combination with GWAS allows for the detailed analysis of metabolic functions, chemical classes, enzyme-metabolite relationships and metabolic pathways.

Author Contributions 

Conceived and designed the experiments: JK KS FJT GK. Performed the experiments: AME MWM RPM MVM. Analyzed the data: JK GK. Contributed reagents/materials/analysis tools: BW WR-M TI JA CG. Wrote the paper: JK KS FJT GK.

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Chambers JC, Zhang W, Lord GM, van der Harst P, Lawlor DA, et al. (2010) Genetic loci influencing kidney function and chronic kidney disease. Nat Genet 42: 373–375. FIND THIS ARTICLE ONLINE

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Chen G, Ramos E, Adeyemo A, Shriner D, Zhou J, et al. (2012) UGT1A1 is a major locus influencing bilirubin levels in African Americans. Eur J Hum Genet 20: 463–468. FIND THIS ARTICLE ONLINE

Jylhava J, Lyytikainen LP, Kahonen M, Hutri-Kahonen N, Kettunen J, et al. (2012) A genome-wide association study identifies UGT1A1 as a regulator of serum cell-free DNA in young adults: The Cardiovascular Risk in Young Finns Study. PLoS ONE 7: e35426 doi:10.1371/journal.pone.0035426.

Source:

http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1003005

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Reporter: Alan F. Kaul, Pharm.D., M.S., M.B.A., FCCP

 

Centers for Medicare and Medicaid (CMS) Targets Hospital Readmissions – Update on Practices and Policy

 

An earlier post on June 8, 2012 in Pharmaceutical Intelligence presented an overview of the Hospital Readmissions Reduction Program (HRRP) and its requirement to reduce payments under the Inpatient Prospective Payment System (IPPS) to hospitals reporting excess readmissions commencing with discharges on October 1, 2012.  As CMS moved forward with HRRP, hospitals readiness for population based accountable care seemed questionable based on a 34 percent survey response or 1,672 hospitals.

http://pharmaceuticalintelligence.com/2012/06/12/centers-for-medicare-and-medicaid-cms-targets-hospital-readmissions-a-disconnect-among-the-hospitals-or-poor-education/

 

According to Medicare Payment Advisory Commission (MedPAC) report, approximately two-thirds of hospitals will be penalized (capped at 1 percent) for above average readmissions commencing October 1, 2012. This penalty will escalate to 2% in 2014 and 3 percent in 2015.  Looking at the hospital readmission measures for Acute Myocardial Infarction (AMI), Heart Failure (HF), and Pneumonia (PN), this penalty will average $125,000 per hospital. Overall, the CMS payment to all hospitals will be reduced by 0.24 percent.  A preliminary analysis indicated little variation by hospital type (i.e., urban, rural, teaching, non-teaching, profit, non-profit).

 

MedPAC pointed out several long-term issues with the readmission reduction program including:

 

  • Computing the penalty multiple – Penalty increases as readmission rate decreases and the penalty multiplier differs for each condition. Solutions could include using a fixed multiplier, using all-condition readmissions, and eliminating the multiplier and setting a lower target readmission rate to maintain budget neutrality
  • Random variation and small number of observations – Solutions could include using all-condition readmissions, using more than the 3 years of data currently used, and allowing hospitals to aggregate performance within a system for penalty purposed while continuing to report individual hospital performance
  • Unrelated and planned readmissions – Solutions could include switching to a-condition measures that have exceptions for planned and unrelated readmissions such as the Yale all condition model or the 3M all-condition model.
  • Socio-economic status and risk-reduction- Possible situations may include allow current incentives to close the gap, comparing hospitals against similar hospitals to compute the penalty, and providing financial assistance to hospitals with a disproportionate share of low-income patients

 

Moving forward in refining the policy several objectives were noted: maintaining or increasing average hospitals’ incentive to reduce readmissions; increasing the share of hospitals with an incentive to reduce readmissions; making any penalty a consistent multiple of the cost of readmissions; being at least budget neutral to current policy, with a preference for lower readmission rates rather than higher penalties. Any policy refinements will require a change in law and must proceed carefully.

http://www.medpac.gov/transcripts/readmissions Sept 12 presentation.pdf

 

On October 3, 2012, CMS issues a notice indicating that errors were discovered in its initial calculation for readmissions penalties under the Inpatient Prospective Payment Systems (IPPS) that went into effect the beginning of October. The revisions were in part to implement capital and operating related costs to acute care hospitals arising from CMS’s continued experience with the systems. Also updated were payment policies and rate of increase limits for certain hospitals excluded from IPPS and paid under Medicare’s Prospective Payment System such as Long Term Acute Care Hospitals (LTACHs).

 

Based on a Kaiser analysis of the miscalculation, 1,422 hospitals will lose more and 55 hospitals will lose less than originally projected. The changes were tiny averaging 0.002 percent of a hospital’s regular Medicare reimbursement. A total of 2,217 hospitals are being punished in the first year of the program which began on October 1, 2012. Of those punished, 307 (14%) will be penalized the maximum 1% of their regular Medicare reimbursement.

 

http://cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/FY-2013-IPPS-Final-Rule-Home-Page-Items/CMS-1588-F-Text-Version.html

http://www.kaiserhealthnews.org/Stories/2012/October/03/medicare-revises-hospitals-readmissions-penalties.aspx

 

As reported in the Napa Valley Register on October 14, 2012, variations in local practices patterns are already being noticed. For example in Napa Valley, Queen of Valley Medical Center has a 18 percent readmission rate, St. Helena Hospital a 13 percent readmission rate, and Kaiser Permanente Vallejo Medical Center a 7 percent readmission rate. Local hospital officials are claiming that reduced readmissions incorrectly assumes better care and that not making exceptions for unavoidable readmissions are policy flaws.  While officials at Kaiser Permanente of Northern California indicated that they had no concerns about the policy change because “it promotes co-ordianation of care, individuals at Queen of Valley Medical Center and St Helena’s Hospital expressed a variety of concerns from the fragile natur of patients in certain of the included diagnoses and the 30-day time fram to evaluate readmissions.  Moving forward to lower readmission rates at Queen and St. Helena indicated that they will pay more attention as patients are discharged from the hospitals during transitions of care, Professionals will coach patients in self-management through home visits and phone-calls after they have been discharged from the hospital.

 

http://napavalleyregister.com/news/local/local-hospitals-challenged-to-cut-medicare-readmissions/article_1827ecfc-159c-11e2-8ad2-001a4bcf887a.html?comment_form=true

 

 

 

 

 

 

 

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Reporter: Aviva Lev-Ari, PhD, RN

 

‘We Have a Problem in Science’

October 02, 2012

A recent study in the Proceedings of the National Academy of Sciences found that more than two-thirds of 2,000 retractions in the life science literature were attributable to some form of misconduct, including fraud, duplicate publication, and plagiarism.

The study, led by Arturo Casadevall of Albert Einstein College of Medicine, estimates that the percentage of scientific papers retracted because of fraud has increased more than 10-fold since 1975.

Carl Zimmer notes in The New York Times that previous studies have concluded that most retractions were attributable to “honest errors,” but the new study “challenges that comforting assumption.”

The authors compiled more than 2,000 retraction notices published before May 3, 2012, and then dug into the reasons behind each retraction. Some reasons were cited by the journals, but the authors also found that the retraction notices for some papers did not cite fraud as the reason for the retraction.

The rise in fraudulent papers “is a sign of a winner-take-all culture in which getting a paper published in a major journal can be the difference between heading a lab and facing unemployment,” Zimmer says.

According to Casadevall, the fact that “some fraction of people are starting to cheat” should not be taken lightly, even if the overall number of fraudulent papers is relatively low. “It convinces me more that we have a problem in science,” he says.

 Source:

 http://www.genomeweb.com//node/1133746?hq_e=el&hq_m=1361468&hq_l=1&hq_v=09187c3305

Misconduct accounts for the majority of retracted scientific publications

  1. Ferric C. Fanga,b,1,
  2. R. Grant Steenc,1, and
  3. Arturo Casadevalld,1,2

+Author Affiliations


  1. Departments of aLaboratory Medicine and

  2. bMicrobiology, University of Washington School of Medicine, Seattle, WA 98195;

  3. cMediCC! Medical Communications Consultants, Chapel Hill, NC 27517; and

  4. dDepartment of Microbiology and Immunology, Albert Einstein College of Medicine, Bronx, NY 10461
  1. Edited by Thomas Shenk, Princeton University, Princeton, NJ, and approved September 6, 2012 (received for review July 18, 2012)

Abstract

A detailed review of all 2,047 biomedical and life-science research articles indexed by PubMed as retracted on May 3, 2012 revealed that only 21.3% of retractions were attributable to error. In contrast, 67.4% of retractions were attributable to misconduct, including fraud or suspected fraud (43.4%), duplicate publication (14.2%), and plagiarism (9.8%). Incomplete, uninformative or misleading retraction announcements have led to a previous underestimation of the role of fraud in the ongoing retraction epidemic. The percentage of scientific articles retracted because of fraud has increased ∼10-fold since 1975. Retractions exhibit distinctive temporal and geographic patterns that may reveal underlying causes.

Footnotes

  • Author contributions: F.C.F., R.G.S., and A.C. designed research, performed research, analyzed data, and wrote the paper.

  • The authors declare no conflict of interest.

  • This article is a PNAS Direct Submission.

  • This article contains supporting information online atwww.pnas.org/lookup/suppl/doi:10.1073/pnas.1212247109/-/DCSupplemental.

    Source:

    http://www.pnas.org/content/early/2012/09/27/1212247109.abstract

     

    Misconduct Widespread in Retracted Science Papers, Study Finds

    By CARL ZIMMER
    Published: October 1, 2012

    Last year the journal Nature reported an alarming increase in the number of retractions of scientific papers — a tenfold rise in the previous decade, to more than 300 a year across the scientific literature.

    Other studies have suggested that most of these retractions resulted from honest errors. But a deeper analysis of retractions, being published this week, challenges that comforting assumption.

    In the new study, published in the Proceedings of the National Academy of Sciences, two scientists and a medical communications consultant analyzed 2,047 retracted papers in the biomedical and life sciences. They found that misconduct was the reason for three-quarters of the retractions for which they could determine the cause.

    “We found that the problem was a lot worse than we thought,” said an author of the study, Dr. Arturo Casadevall of Albert Einstein College of Medicine in the Bronx.

    Dr. Casadevall and another author, Dr. Ferric C. Fang of the University of Washington, have been outspoken critics of the current culture of science. To them, the rising rate of retractions reflects perverse incentives that drive scientists to make sloppy mistakes or even knowingly publish false data.

    “We realized we would really like more hard data for what the reasons were for retractions,” Dr. Fang said.

    They began collaborating with R. Grant Steen, a medical communications consultant in Chapel Hill, N.C., who had already published a study on 10 years of retractions. Together they gathered all the retraction notices published before May 2012 by searching PubMed, a database of scientific literature maintained by the National Library of Medicine.

    “I guess our O.C.D. kicked in and we started trying to look at every paper we could look at,” Dr. Fang said.

    The researchers analyzed the reasons for retractions cited by the scientific journals. But they also looked beyond the journals for the full story.

    In the mid-2000s, for example, Boris Cheskis, then a senior scientist at Wyeth Research, and his colleagues published two papers on estrogen. Later, the scientists retracted both papers, explaining that some of the data in them were “unreliable.” In 2010, the Office of Research Integrity at the federal Department of Health and Human Services ruled that Dr. Cheskis had engaged in misconduct, having falsified the figures.

    Dr. Cheskis settled with the government. Although he neither accepted nor denied the charges, he agreed not to serve on any advisory boards for the United States Public Health Service and agreed to be supervised on any Public Health Service-financed research for two years.

    Neither of the notices for the two retracted papers has been updated to reflect the finding of fraud. Dr. Cheskis could not be reached for comment.

    Dr. Fang and his colleagues dug through other reports from the Office of Research Integrity, as well as newspaper articles and the blog Retraction Watch. All told, they reclassified 158 papers as fraudulent based on their extra research.

    “We haven’t seen this level of analysis before,” said Dr. Ivan Oransky, an author of Retraction Watch and the executive editor at Reuters Health. “It confirms what we suspected.”

    Dr. Oransky said he expected the rise to continue in the near future. He and his co-author, Adam Marcus, have been scrambling to keep up with new cases of fraud.

    In July, for example, the Japanese Society of Anesthesiologists reported that Dr. Yoshitaka Fujii had falsified data in 172 papers. Most of those papers have yet to be officially retracted. “They’re headed for the fraud pile,” Dr. Oransky said.

    Dr. Benjamin G. Druss, a professor of health policy of Emory University, said he found the statistics in the paper to be sound but added that they “need to be kept in perspective.” Only about one in 10,000 papers in PubMed have been officially retracted, he noted. By contrast, 112,908 papers have had published corrections.

    Dr. Casadevall disagreed. “It convinces me more that we have a problem in science,” he said.

    While the fraudulent papers may be relatively few, he went on, their rapid increase is a sign of a winner-take-all culture in which getting a paper published in a major journal can be the difference between heading a lab and facing unemployment. “Some fraction of people are starting to cheat,” he said.

    Better policing techniques, like plagiarism-detecting software, might help slow the rise in misconduct, Dr. Casadevall said, but the most important thing the scientific community can do is change its culture.

    “I don’t think this problem is going to go away as long as you have this disproportionate system of rewards,” he said.

    <nyt_correction_bottom>

    This article has been revised to reflect the following correction:

    Correction: October 1, 2012

     

    An earlier version of this story misstated the federal agency housing the Office of Research Integrity. It is the Department of Health and Human Services, not the National Institutes of Health. The earlier version also misstated the reason cited in the study for three-quarters of the retractions for which researchers could determine the cause. It was misconduct, not fraud. (Fraud or suspected fraud accounted for 41.3 percent of retractions; other forms of misconduct made up the rest.)

    Source:

    http://www.nytimes.com/2012/10/02/science/study-finds-fraud-is-widespread-in-retracted-scientific-papers.html?_r=1 

 

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Reporter: Larry Bernstein, MD

Bioinformatics  refers to the creation and maintenance of a database to store biological information such as nucleotide sequences and amino acid sequences. Development of this type of database involved not only design issues but the development of complex interfaces whereby researchers could access existing data as well as submit new or revised data.

In order to study how normal cellular activities are altered in different disease states, the biological data must be combined to form a comprehensive picture of these activities. Therefore, the field of bioinformatics This includes nucleotide and amino acid sequences, protein domains, and protein structures. The actual process of analyzing and interpreting data is referred to as computational biology.

The primary goal of bioinformatics is to increase the understanding of biological processes. What sets it apart from other approaches, however, is its focus on developing and applying computationally intensive techniques to achieve this goal.

Bioinformatics elements for NGS data analysis

4 – 5 – 6 – 7 Dicembre 2012
c/o Polo Scientifico e Tecnologico di Careggi
Viale Morgagni 40, Firenze
Inscription Deadline: 3 November 2012

The high level training in “Bioinformatics for NGS data analysis” is oriented for students and PhD students in mathematics, physics, natural science, medicine, biotechnology, pharmacy and ingenering as well as employees of public institutions, industry and university researchers interested in problems of NGS bioinformatics.

The primary object of the course is to introduce the participants to the basic theory and the technical knowledge of NGS data analysis for the identification of single nucleotide polymorphism, insertion/deletion, genomic variants and for the study of gene expression.

The course will span four days structured in seminars and hands-on sessions at the computer given by docents and professionals.

Contacts
For more information visit: http://sites.google.com/site/corsobioinformatica/
e-mai: corsobioinformatica@gmail.com
telephone: (+39) 055 7949036

 

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typical changes in CK-MB and cardiac troponin ...

typical changes in CK-MB and cardiac troponin in Acute Myocardial Infarction (Photo credit: Wikipedia)

Reporter and curator:

Larry H Bernstein, MD, FCAP

This posting is a followup on two previous posts covering the design and handling of HIT to improve healthcare outcomes as well as lower costs from better workflow and diagnostics, which is self-correcting over time.

The first example is a non technology method designed by Lee Goldman (Goldman Algorithm) that was later implemented at Cook County Hospital in Chicago with great success.     It has been known that there is over triage of patients to intensive care beds, adding to the costs of medical care.  If the differentiation between acute myocardial infarction and other causes of chest pain could be made more accurate, the quantity of scare resources used on unnecessary admissions could be reduced.  The Goldman algorithm was introduced in 1982 during a training phase at Yale-New Haven Hospital based on 482 patients, and later validated at the BWH (in Boston) on 468 patients.They demonstrated improvement in sensitivity as well as specificity (67% to 77%), and positive predictive value (34% to 42%).  They modified the computer derived algorithm in 1988 to achieve better results in triage of patients to the ICU of patients with chest pain based on a study group of 1379 patients.  The process was tested prospectively on 4770 patients at two university and 4 community hospitals.  The specificity improved by 74% vs 71% in recognizing absence of AMI by the algorithm vs physician judgement. The sensitivity was not different for admission (88%).  Decisions based solely on the protocol would have decreased admissions of patients without AMI by 11.5% without adverse effects.  The study was repeated by Qamar et al. with equal success.

Pain in acute myocardial infarction (front)

Pain in acute myocardial infarction (front) (Photo credit: Wikipedia)

An ECG showing pardee waves indicating acute m...

An ECG showing pardee waves indicating acute myocardial infarction in the inferior leads II, III and aVF with reciprocal changes in the anterolateral leads. (Photo credit: Wikipedia)

Acute myocardial infarction with coagulative n...

Acute myocardial infarction with coagulative necrosis (4) (Photo credit: Wikipedia)

Goldman L, Cook EF, Brand DA, Lee TH, Rouan GW, Weisberg MC, et al. A computer protocol to predict myocardial infarction in emergency department patients with chest pain. N Engl J Med. 1988;318:797-803.

A Qamar, C McPherson, J Babb, L Bernstein, M Werdmann, D Yasick, S Zarich. The Goldman algorithm revisited: prospective evaluation of a computer-derived algorithm versus unaided physician judgment in suspected acute myocardial infarction. Am Heart J 1999; 138(4 Pt 1):705-709. ICID: 825629

The usual accepted method for determining the decision value of a predictive variable is the Receiver Operator Characteristic Curve, which requires a mapping of each value of the variable against the percent with disease on the Y-axis.   This requires a review of every case entered into the study.  The ROC curve is done to validate a study to classify data on leukemia markers for research purposes as shown by Jay Magidson in his demonstation of  Correlated Component Regression (2012)(Statistical Innovations, Inc.)  The test for the contribution of each predictor is measured by Akaike Information Criteria and Bayes Information Criteria, which have proved to be critically essential tests over the last 20 years.

I go back 20 years and revisit the application of these principles in clinical diagnostics, but the ROC was introduced to medicine in radiology earlier.   A full rendering of this matter can be found in the following:
R A Rudolph, L H Bernstein, J Babb. Information induction for predicting acute myocardial infarction.Clin Chem 1988; 34(10):2031-2038. ICID: 825568.

Rypka EW. Methods to evaluate and develop the decision process in the selection of tests. Clin Lab Med 1992; 12:355

Rypka EW. Syndromic Classification: A process for amplifying information using S-Clustering. Nutrition 1996;12(11/12):827-9.

Christianson R. Foundations of inductive reasoning. 1964.  Entropy Publications. Lincoln, MA.

Inability to classify information is a major problem in deriving and validating hypotheses from PRIMARY data sets necessary to establish a measure of outcome effectiveness.  When using quantitative data, decision limits have to be determined that best distinguish the populations investigated.   We are concerned with accurate assignment into uniquely verifiable groups by information in test relationships.  Uncertainty in assigning to a supervisory classification can only be relieved by providing suffiuciuent data.

A method for examining the endogenous information in the data is used to determine decision points.  The reference or null set is defined as a class having no information.  When information is present in the data, the entropy (uncertainty in the data set) is reduced by the amount of information provided.  This is measureable and may be referred to as the Kullback-Liebler distance, which was extended by Akaike to include statistical theory.   An approach is devised using EW Rypka’s S-Clustering has been created to find optimal decision values that separate the groups being classified.  Further, it is possible to obtain PRIMARY data on-line and continually creating primary classifications (learning matrices).  From the primary classifications test-minimized sets of features are determined with optimal useful and sufficient information for accurately distinguishing elements (patients).  Primary classifications can be continually created from PRIMARY data.  More recent and complex work in classifying hematology data using a 30,000 patient data set and 16 variables to identify the anemias, moderate SIRS, sepsis, lymphocytic and platelet disorders has been  published and recently presented.  Another classification for malnutrition and stress hypermetabolism is now validated and in press in the journal Nutrition (2012), Elsevier.
G David, LH Bernstein, RR Coifman. Generating Evidence Based Interpretation of Hematology Screens via Anomaly Characterization. Open Clinical Chemistry Journal 2011; 4 (1):10-16. 1874-2416/11 2011 Bentham Open.  ICID: 939928

G David; LH Bernstein; RR Coifman. The Automated Malnutrition Assessment. Accepted 29 April 2012.
http://www.nutritionjrnl.com. Nutrition (2012), doi:10.1016/j.nut.2012.04.017.

Keywords: Network Algorithm; unsupervised classification; malnutrition screening; protein energy malnutrition (PEM); malnutrition risk; characteristic metric; characteristic profile; data characterization; non-linear differential diagnosis

Summary: We propose an automated nutritional assessment (ANA) algorithm that provides a method for malnutrition risk prediction with high accuracy and reliability. The problem of rapidly identifying risk and severity of malnutrition is crucial for minimizing medical and surgical complications. We characterized for each patient a unique profile and mapped similar patients into a classification. We also found that the laboratory parameters were sufficient for the automated risk prediction.
We here propose a simple, workable algorithm that provides assistance for interpreting any set of data from the screen of a blood analysis with high accuracy, reliability, and inter-operability with an electronic medical record. This has been made possible at least recently as a result of advances in mathematics, low computational costs, and rapid transmission of the necessary data for computation.  In this example, acute myocardial infarction (AMI) is classified using isoenzyme CKMB activity, total LD, and isoenzyme LD-1, and repeated studies have shown the high power of laboratory features for diagnosis of AMI, especially with NSTEMI.  A later study includes the scale values for chest pain and for ECG changes to create the model.

LH Bernstein, A Qamar, C McPherson, S Zarich.  Evaluating a new graphical ordinal logit method (GOLDminer) in the diagnosis of myocardial infarction utilizing clinical features and laboratory data. Yale J Biol Med 1999; 72(4):259-268. ICID: 825617

The quantitative measure of information, Shannon entropy treats data as a message transmission.  We are interested in classifying data with near errorless discrimination.  The method assigns upper limits of normal to tests computed from Rudolph’s maximum entropy definitions of group-based normal reference.  Using the Bernoulli trial to determine maximum entropy reference, we determine from the entropy in the data a probability of a positive result that is the same for each test and conditionally independent of other results by setting the binary decision level for each test.  The entropy of the discrete distribution is calculated from the probabilities of the distribution. The probability distribution of the binary patterns is not flat and the entropy decreases when there is information in the data.  The decrease in entropy is the Kullback-Liebler distance.

The basic principle of separatory clustering is extracting features from endogenous data that amplify or maximize structural information into disjointed or separable classes.  This differs from other methods because it finds in a database a theoretic – or more – number of variables with required VARIETY that map closest to an ideal, theoretic, or structural information standard. Scaling allows using variables with different numbers of message choices (number bases) in the same matrix, binary, ternary, etc (representing yes-no; small-modest, large, largest).   The ideal number of class is defined by x^n.   In viewing a variable value we think of it as low, normal, high, high high, etc.  A system works with related parts in harmony.  This frame of reference improves the applicability of S-clustering.  By definition, a unit of information is log.r r = 1.

The method of creating a syndromic classification to control variety in the system also performs a semantic function by attributing a term to a Port Royal Class.  If any of the attributes are removed, the meaning of the class is made meaningless.  Any significant overlap between the groups would be improved by adding requisite variety.  S-clustering is an objective and most desirable way to find the shortest route to diagnosis, and is an objective way of determining practice parameters.

Multiple Test Binary Decision Patterns where CK-MB = 18 u/l, LD-1 = 36 u/l, %LD1 = 32 u/l.

No.               Pattern       Freq                   P1                       Self information                Weighted information

0                    000             26                   0.1831                    2.4493                                     0.4485
1                    001                3                    0.0211                   5.5648                                     0.1176
2                    010               4                    0.0282                   5.1497                                     0.1451
3                    011                2                    0.0282                   6.1497                                     0.0866
4                    100               6                    0.0423                   4.5648                                     0.1929
6                    110                8                    0.0563                  4.1497                                     0.2338
7                    111               93                   0.6549                  0.6106                                     0.3999

Entropy: sum of weighted information (average)           1.6243 bits

The effective information values are the least-error points. Non AMI patients exhibit patterns 0, 1, 2, 3, and 4: AMI patients are 6 and 7.  There is 1 fp 4, and 1 fn 6.  The error rate is 1.4%.

Summary:

A major problem in using quantitative data is lack of a justifiable definition of reference (normal).  Our information model consists of a population group, a set of attributes derived from observations, and basic definitions using Shannon’s information measure entropy. In this model, the population set and its values for its variables are considered to be the only information available.  The finding of a flat distribution with the Bernoulli test defines the reference population that has no information.  The complementary syndromic group, treated in the same way, produces a distribution that is not flat and has a less than maximum information uncertainty.

The vector of probabilities – (1/2), (1/2), …(1/2), can be related to the path calculated from the Rypka-Fletcher equation, which

Ct = 1 – 2^-k/1 -2^-n

determines the theoretical maximum comprehension from the test of n attributes.  We constructed a ROC curve from theoriginal IRIS  data of R Fisher from four measurements of leaf and petal with a result obtained using information-based induction principles to determine discriminant points without the classification that had to be used for the discriminant analysis.   The principle of maximum entropy, as formu;ated by Jaynes and Tribus proposes that for problems of statistical inference – which as defined, are problems of induction – the probabilities should be assigned so that the entropy function is maximized.  Good proposed that maximum entropy be used to define the null hypothesis and Rudolph proposed that medical reference be defined as at maximum entropy.

Rudolph RA. A general purpose information processing automation: generating Port Royal Classes with probabilistic information. Intl Proc Soc Gen systems Res 1985;2:624-30.

Jaynes ET. Information theory and statistical mechanics. Phys Rev 1956;106:620-30.

Tribus M. Where do we stand after 30 years of maximum entropy? In: Levine RD, Tribus M, eds. The maximum entropy formalism. Cambridge, Ma: MIT Press, 1978.

Good IJ. Maximum entropy for hypothesis formulation, especially for multidimensional contingency tables. Ann Math Stat 1963;34:911-34.

The most important reason for using as many tests as is practicable is derived from the prominent role of redundancy in transmitting information (Noisy Channel Theorem).  The proof of this theorem does not tell how to accomplish nearly errorless discrimination, but redundancy is essential.

In conclusion, we have been using the effective information (derived from Kullback-Liebler distance) provided by more than one test to determine normal reference and locate decision values.  Syndromes and patterns that are extracted are empirically verifiable.

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