SAN JOSE, CA- MDBlackBox announces the new, easier to use, on-demand, no-risk Practice Management EMR suite with wellness tools for use by patients.
Users can sign up and have MDBlackBox up and running in less than 2 minutes with no licensing or hosting fees and without purchasing special equipment.

MDBlackBox available free to physicians, clinics and patients was founded by a hospitalist doctor who was not satisfied with available EMR systems sufficiently eased challenges while simultaneously providing safe, secure and user-friendly access for patients.

The user friendly MDBlackBox is not only for patient record keeping, but also appointment scheduling, billing, laboratory and radiology order entry, electronic prescription transmission, staff management, and arrangement of referrals yet is designed to be user-friendly, secure and easily used from any web-accessible computer, phone, or tablet.

MDBlackBox securely and reliably uses the same security standards used by online banking systems. Keeping all of a patient’s records in a  reliable data vault prevents information gaps that can develop when a patient sees multiple practitioners.

MDBlackBox is a SaaS (Software as a Service) product designed for practices ranging from solo practitioners to large multi-facility clinics. Its wide spectrum of features is robust but designed to be user-friendly, bring the gap together of communicating with patients, manage their care and follow their progress as well as substantially increase practice management efficiency and aid in human resource management and practice marketing.

The wellness tools help patients monitor and relay their daily condition and activities improving compliance with ongoing treatment programs such as weight management or mobile device text reminders to help patients maintain their medication schedules.

As the nationwide goal of universal EMR adoption by 2015 approaches, MDBlackBox is an excellent across-the-board solution that is ready right now.  Interested physicians and clinics can start the process of evaluating and adopting MDBlackBox with a visit to www.mdblackbox.com.

About MDBlackBox

MDBlackBox addresses the complexities and critical needs of today’s healthcare environments by providing a revolutionary web-based, on-demand platform for record keeping and patient support that reduces the costs and challenges associated with licensing, implementation, integration and support usually experienced with leading enterprise software solutions. With MDBlackBox providers can deliver the highest level of care and service to their patients simply, easily and inexpensively. Learn more at www.mdblackbox.com.

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A team of scientists at the Institute of Human Genetics of the Christian-Albrechts-University and the University Medical Center Schleswig-Holstein in Kiel, Germany, is currently using sophisticated data analysis software on a number of national and international projects in order to study the epigenetic alterations related to several cancers, including malignant lymphoma, colorectal cancer, and hepatocellular carcinoma, as well as developmental disorders and other diseases.

The team, led by Dr. Ole Ammerpohl, is currently studying the raw data obtained from array-based DNA methylation analysis, including Illumina’s HumanMethylation27k Bead Chip, which provides semi-quantitative data from more than 27,000 CpG loci.

Although studies like these are proving invaluable to the study of human biology, the amount of data that is produced by this kind of research is enormous. As a result, it is impossible to derive any real biological meaning from these findings unless sophisticated analysis methods are used to help interpret the data effectively.

“Because of the amount of data being analysed, conducting microarray analysis has always been a hassle,” says Dr. Ammerpohl. “Larger studies, especially those which include multiple samples that need to be analysed on comprehensive array platforms, have traditionally been very time-consuming, and have also required a considerable amount of computer power. Plus, in most cases, it is mandatory to define the exact conditions before beginning the intended analysis, and just this process alone can take hours. Worse still, any recalculations – even if they are just minor adjustments to these initial conditions – would mean that the whole process would have to be restarted from the beginning.”

Fortunately, new technological advances in this area are making it much easier for scientists to compare the vast quantity of data generated by epigenetic studies, to test different hypotheses, and to explore alternative scenarios within seconds. As a result, the latest generation of data analysis software is helping scientists to regain control of this analysis, and to realise the true potential of research in this area.

Epigenetics:  unlocking the mysteries of human disease

Epigenetics, the name given to the study of changes in phenotype (appearance) or gene expression caused by mechanisms other than changes in the underlying DNA sequence, is helping to provide a link between the (static) genome and the unsettled environment, and therefore to establish a gene expression profile that will enable the survival of the cell in certain environmental conditions.

“The methylation of the cytosine residue in a CpG dinucleotide is probably the best characterised epigenetic modification in the human epigenome,” explains Dr. Ammerpohl. “DNA methylation is essential for normal development; it is not only a key player in gene expression control and parental imprinting, but it also assures genomic integrity by preventing repetitive sequences from recombination. At the same time, it also silences parasitic sequences, such as retroviral sequences which have been integrated into the genome.”

Epigenetic variations are involved in many processes, starting with transgeneration heritable effects, but also in areas like stress tolerance, behavior, psychological problems, drug addiction, and severe developmental disorders and diseases. Since epigenetic modifications are more responsive to drug treatment than genetic alterations, understanding epigenetic alterations might provide new therapeutic options in the future.

As such, Dr. Ammerpohl, along with his team of four scientists and three technicians, is working to understand how alterations in the DNA methylation pattern contribute to a specific phenotype or disease like cancer, as well as the way in which tumour induction introduces epigenetic alterations which support tumour growth and progression.

Coping with information overload

Until now, most of the software that has been designed to study areas like array-based DNA methylation has mainly focused on the ability to handle increasingly vast amounts of data, which means that the role of the scientist/researcher has been largely set aside. As a result, a lot of data analysis has been passed on to bioinformaticians and biostatisticians.

A new generation of data analysis software is helping to redress the balance, however, and is already playing a key role in unveiling important new discoveries, since it allows the actual researchers involved to study the data and to look for patterns and structures, without having to be a statistics or computer expert.

At the same time, the overall performance of data analysis software has been optimised significantly over the past three years. With key actions and plots now displayed within a fraction of a second, researchers can increasingly perform the research they want and find the results they need instantly.

“For us, a big advantage of the latest data analysis software is its speed,” says Dr. Ammerpohl. “We are using an application called Qlucore Omics Explorer, and this software makes it very easy to assign samples to defined groups, to change the applied statistical methods, to create new groups, and to modify the thresholds for items such as variance and p-value in real time, with results returned immediately.”

Data analysis software rises to the challenge

Products like Qlucore Omics Explorer are now making it possible for scientists to analyse proteomic, genomic and microarray data with a combination of statistical methods and visualisation techniques such as Heat maps and Principal Component Analysis (PCA).

As a result, scientists studying DNA methylation analysis and other genomic data can now analyse all of this important information in real-time, by themselves, directly on their computer screen, since the software can provide instant user feedback on all actions, as well as an intuitive user interface that can present all data in 3D.

By using Qlucore Omics Explorer in this way, Dr. Ammerpohl is able to apply different statistical approaches, and to keep track of the effects in a PCA or cluster analysis. As such, subgroups in the sample collection – comprised of specific groups of genes – can be identified intuitively. All relevant statistics (together with the corresponding variable and sample list) can be exported, as well, so that they can be easily integrated into publications or presentations.

Making sense of important data

The latest data analysis software can generate PCA-plots between various sample data interactively and in real time, directly on the computer screen, and work with all annotations and other links in a fully integrated way, all at the same time. This approach has helped to open up new ways of working with data analysis and, as a consequence, has helped the biologists to be more actively involved in the analysis process.

Qlucore Omics Explorer, for example, graphically represents the high dimensional data in form of 3-dimensions plots on the computer screen. This instant visualisation technique is then combined with powerful statistical methods and filters, all of which are handled with just a single mouse-click. 

“As humans, we are all used to interpreting 3D pictures in our environment, and so our brain is able to find structures in complex 3D figures very quickly. Therefore, it’s no wonder that a 3D presentation of complex mathematical/statistical coherences makes its interpretation much easier for us,” Dr. Ammerpohl adds.

A step-by-step approach to data analysis

For their research into array-based DNA methylation, Dr. Ammerpohl and his colleagues have compared the DNA methylation pattern in normal liver tissue, in cirrhosis of the liver, which is thought being a precursor of hepatocellular carcinoma (HCC), and in HCC. In addition to the DNA methylation values obtained from the array analysis, the researchers have also included information on the tissue, clinical features or exogenous exposures like viral infection of the patient.

Afterwards, the analysis of the data could easily be performed. By selecting the appropriate test and adapting the applied statistical thresholds for p-value, false discovery rate, or the minimal variance by using sliders in the Qlucore software, groups of samples with similar characteristics could be identified easily by PCA.

Furthermore, a PCA of the variables (in this case, the DNA methylation values of the CpG loci) or a hierarchical cluster analysis is available. In the particular study, the team of researchers identified genes which acquire epigenetic alterations already in cirrhosis, which are maintained in HCC, or genes acquiring epigenetic alterations in HCC exclusively.

The future

Dr. Ammerpohl has been using Qlucore Omics Explorer to analyse numerous epigenomes of tumour entities including colorectal cancer, HCC, lymphomas as well as of developmental sex disorders or imprinting diseases. These studies have already resulted in valuable data that is helping Dr. Ammerpohl and his team in their efforts to understand the epigenetic background of these diseases or disorders.

“The exceptional speed that Qlucore’s software provides is very important for us. The fast analysis of the data highly contributes to the identification of subpopulations in a sample collection or a list of variables,” says Dr. Ammerpohl. “Without a doubt, these rapid results – and the way in which they are presented – prompted us to perform analyses that we would have never performed otherwise.”

“We don’t want to give away too much at the moment, as many of our major findings have yet to be published, but I can report that we are feeling very positive about our research in this area, and about the future of the entire project,” he adds. “It is fair to say that we have already obtained some very interesting results.”

In scientific publishing, how much reuse of text is too much? Researchers at the Virginia Bioinformatics Institute at Virginia Tech and collaborators have shown that a computer-based text-searching tool is capable of unearthing questionable publication practices from thousands of full-text papers in the biomedical literature.

The first step in the process is to find out what is restated before zeroing in on who may have crossed an ethically unacceptable threshold. The findings, published in PLoS ONE, offer hope for curbing unethical scientific publication practice, a growing problem throughout the world.

“Building upon our earlier work reported in Science and Nature, which uncovered ethically questionable journal articles by comparing their abstracts, we have now re-tuned our computer program, eTBLAST, to scan thousands of full-text articles in PubMed Central, a freely available repository of full-text biomedical literature,” said Harold “Skip” Garner, author on the paper and executive director of the Virginia Bioinformatics Institute. “Our goal was to measure how much and where in papers – for example, the introduction, methods or results sections – text is duplicated to establish the ‘norm’ in publishing. This will allow ethicists, which we are not, to begin to develop guidelines as to what is and what is not acceptable publication practice.”

Although abstract search is an effective approach to detect potential plagiarism, full text analysis is needed to uncover all potential duplicate citations in the scientific literature. The researchers examined 72 011 full-text articles using the eTBLAST computer program, which is only the tip of the iceberg for the number of published biomedical articles in the archives.

“We found that most papers are novel, as expected in scientific reporting, but even in papers reporting novel results, certain sections, such as the introduction or methods section, frequently have large amounts of content that appear elsewhere,” said Garner. The researchers went on to explain that the re-use of text in certain sections, such as the methods section of papers, where authors provide details on how the work was done, is not a bad thing because it is important to use the accepted and most consistent techniques. “We also expect that other sections like the results section to be very unique just like the abstract. And this is the case in the overwhelming majority of papers,” said Garner.

The current study revealed that the introduction section tended to be copied the most in similar citations. Also review articles were confirmed as being particularly prone to repetition.

“We believe this type of research will help us write better, more informative scientific papers, and prepare reviewers and journal editors for interpreting the similarity results that are emerging from the computational analysis of scientific papers. This approach is becoming increasingly commonplace as part of the scientific review process,” added Garner. “Before crossing the line between acceptable and unacceptable writing, it is important to know the location of the line,” concluded Garner.

The work was supported by the Hudson Foundation and the National Institutes of Health/National Library of Medicine. The paper is the 100^th article funded by the US Department of Health & Human Services Office of Research Integrity.

Related links

Plagiarism sleuths

http://www.sciencemag.org/cgi/content/full/324/5930/1004

A tale of two citations

http://www.nature.com/nature/journal/v451/n7177/full/451397a.html

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