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Posts from the ‘science’ Category

How A Startup Tries To Understand The Network Relationship Of Diseases

In the basement office of Jeff Hammerbacher at Mount Sinai’s Icahn School of Medicine, a supercomputer called Minerva named after the Roman goddess of wisdom and medicine was installed in 2013. In just a few months Minerva generated 300 million new calculations to support healthcare decisions. Dr. Joel Dudley, director of biomedical informatics at the Icahn School of Medicine, said that what they are trying to build is a learning healthcare system.

“We first need to collect the data on a large population of people and connect that to outcomes. Let’s throw in everything we think we know about biology and let’s just look at the raw measurements of how these things are moving within a large population. Eventually the data will tell us how biology is wired up.”

From The Guide to the Future of Medicine

When they assembled and analyzed the health data of 30,000 patients who volunteered to share their information, it turned out that there might be new clusters or subtypes of diabetes. By analyzing huge amounts of data it might be possible to pinpoint genes that are unique to diabetes patients in these different clusters, providing potentially new ways to understand how our genomic background and environment are linked to the disease, its symptoms, and treatments.

Analyzing big data is key to the future of healthcare. But it’s not only about computational power, but a new paradigm about how we look at the networks of diseases. I loved the book, Burst, from Albert-László Barabási, the world-known expert of network medicine. It proved there are hidden patterns behind everything from e-mails to science.

I had a chance to meet him in person a few weeks ago and we chatted about his theories of network medicine for an hour. He thinks disease-disease relationships can be predicted and uncovered through the protein network, so-called interactome which is incomplete at this time. He and his team think that there are molecular fingerprints behind diseases and hidden structures which can only be uncovered with smart algorithms and bioinformatic methods.

Map of protein-protein interactions in asthma. The colour of a node signifies the phenotypic effect of removing the corresponding protein (red, lethal; green, non-lethal; orange, slow growth; yellow, unknown).

Map of protein-protein interactions in asthma. The colour of a node signifies the phenotypic effect of removing the corresponding protein (red, lethal; green, non-lethal; orange, slow growth; yellow, unknown).

The system they have been developing is aiming at interpreting gene expressions and genome-wide association study data to drug target identification and re-purposing. The name of Barabasi’s exciting start-up is DZZOM, derived from their map called „Diseasome”. Their approach and tools are certainly offering new opportunities to reclassify disease relationship from a network perspective and molecular level interactions. Obviously, biopharmaceutical companies are the primer targets for their services.

We will see how it transforms the way pharma companies develop new drugs and how it affects everyday medicine. Until then, read the paper published in Science.

Torrent Site For Academics: Brilliant!

Researchers at the University of Massachusetts came up with a very simple but still brilliant idea of creating a torrent site for academics. They have community sites such as ResearchGATE and reference managers such as Mendeley, but this torrent site sharing even huge datasets could find its target audience quickly.

AcademicTorrents provides researchers with a reliable and decentralized platform to share their work with peers, as well as the rest of the world. The site currently indexes over 1.5 petabytes of data, including NASA’s map of Mars. 

AcademicTorrents allows researchers to upload datasets, articles and other research material. The site runs it own tracker and supports web-seeds as well, which guarantee that files are available at all times.

acatorr

Optogenetics: Explained

When I published the 40 trends that shape the future of medicine white paper, this is what I wrote about optogenetics:

Optogenetics is a neuromodulation technique using a combination of methods from optics and genetics to control the activity of individual neurons in living tissue. Optogenetics will provide new solutions in therapies. A recent study published in Science reported that scientists were able to create false memories in the hippocampus of mice. This is the first time fear memory was generated via artificial means. By time, we will understand the placebo effect clearly; and just imagine the outcomes we can reach when false memories of taking drugs can be generated in humans as well. The ultimate goal is to be able to modulate our senses, repair lost senses or even perform specific DNA targeting with femtosecond laser.

Well, here is a great new explanation from MIT News:

The First Medical Paper About Google Glass

Christian Assad-Kottner and his colleagues published the first paper focusing on the medical use of Google Glass: Wearable technology to improve education and patient outcomes in a cardiology fellowship program – a feasibility study.

Graduate medical education (GME) is a balance between providing optimal patient care while ensuring that trainees (residents and fellows) develop independent medical decision making skills as well as the ability to manage serious medical conditions. We used one form of wearable technology (“Google Glass”) to explore different scenarios in cardiovascular practice where fellows can better their education.

GoogleGlass

By the way, a quick tip! I use Grammarly’s plagiarism checker because it makes sure I only post creative content and avoid plagiarism. Check it out!

The Future Belongs to Interdisciplinary Innovations: Real-Time MRI-Guided Gene Therapy in Brain Cancer

Without doubt, the future belongs to interdisciplinary innovations and just to show you a recent and practical example why I’m saying that, see what neurosurgeons at the University of California, San Diego School of Medicine and UC San Diego Moores Cancer Center just did.

They used magnetic resonance imaging (MRI) guidance for delivering gene therapy as a potential treatment for brain tumors.

Using MRI navigational technology, neurosurgeons can inject Toca 511 (vocimagene amiretrorepvec), a novel investigational gene therapy, directly into a brain malignancy. This new approach offers a precise way to deliver a therapeutic virus designed to make the tumor susceptible to cancer-killing drugs.

“With MRI, we can see the tumor light up in real time during drug infusion. The rest of the brain remains unaffected so the risk of the procedure is minimized.”

Medical professionals in any specialties have to start looking at the same medical problem from different angles and as medical education focuses on giving you a very much specialized knowledge, social media and other digital technologies can help us get glimples into other areas looking for new ways of collaboration.

Predicting Response to Therapies with Genomics: Our recent paper is out!

It’s a pleasure to announce that our recent paper (the last piece of my PhD) was just published in Genome Medicine. The title is “Peripheral blood derived gene panels predict response to infliximab in rheumatoid arthritis and Crohn’s disease“.

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Background
Biological therapies have been introduced to the treatment of chronic inflammatory diseases including rheumatoid arthritis (RA) and Crohn’s disease (CD). The efficacy of biologics differs from patient to patient. Moreover these therapies are rather expensive, therefore treatment of primary non-responders should be avoided.

Method
We addressed this issue by combining gene expression profiling and biostatistical approaches. We performed peripheral blood global gene expression profiling in order to filter the genome for target genes in cohorts of 20 CD and 19 RA patients. Then RT-qPCR validation was performed, followed by multivariate analyses of genes in independent cohorts of 20 CD and 15 RA patients, in order to identify sets of interrelated genes that can separate responders from non-responders to the humanized chimeric anti-TNFalpha antibody infliximab at baseline.

Results
Gene panels separating responders from non-responders were identified using leave-one-out cross-validation test, and a pool of genes that should be tested on larger cohorts was created in both conditions.

Conclusions
Our data show that peripheral blood gene expression profiles are suitable for determining gene panels with high discriminatory power to differentiate responders from non-responders in infliximab therapy at baseline in CD and RA, which could be cross-validated successfully. Biostatistical analysis of peripheral blood gene expression data leads to the identification of gene panels that can help predict responsiveness of therapy and support the clinical decision-making process.

As usual, I’m more than happy to receive feedback!

Biomedical literature search and recommendation tool: Pubchase

I’ve recently come across an interesting application, Pubchase, that would like to serve as a search and recommendation tool in the biomedical literature.

As the user saves articles to his or her library, PubChase recommends newly-published articles that are relevant to the individual.  This is a free service, available on the web, iOS, or Android devices.

The heart of PubChase is not simply a pretty mobile interface to the published literature.  With over 100,000 biomedical articles published each month, our hope is to enable scientists to discover new research important to them, no matter where it is published (as opposed to simply scanning tables of contents of high-impact journals, as many of us commonly do now).

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