Nanotube Yarn Used for Neurological Applications
Tapping into the autonomous nervous system – the control center for things like heartbeat and breathing – is a relatively new part of neurostimulation technologies to both record and direct organ function. Implants designed for stimulating peripheral nerves often fail because the protective tissue surrounding nerve bundles (the perineurium) is difficult to penetrate, and the body’s immune response often builds a scar around the implanted device.
Now, a team of scientists from Case Western Reserve University (CWRUL) has used carbon nanotubes to overcome these obstacles, reporting their findings in Scientific Reports. The authors, led by Dominique M. Durand, Ph.D., Director of the Neural Engineering Center and El Lindseth Professor of Biomedical Engineering, Neurosciences, Physiology and Biophysics at CWRU, fabricated yarn made of carbon nanotubes that was 10 to 20 µm in diameter. The yarn was then used to create electrodes, which were implanted into rats to monitor activity of the glossopharyngeal and vagus nerves.
The authors found that they could use the implants to monitor nerve activity under conditions of hypoxia and stomach distention. They report that the success of their experiments likely derives from the similarity of the nanotube yarn to the actual neural tissue surrounding the implant. The implants are a long way from being tried in humans, but the large number of functions controlled by just these two nerves indicates that such implants could find use in an enormous number of diseases.
Better Screening of Nanoparticle Delivery
As we discussed last week, the development of gene-based therapies is hindered by the sheer size of the human genome. The immense volume of information involved can quickly become difficult to manage, so one way in which scientists “keep track” of genetic information during the process of introducing new genetic material into an organism is DNA barcoding. This process attaches a small piece of DNA to the gene being studied; if and when the gene causes cells to replicate, these cells will bear the barcode, thus allowing the observer to be certain of the gene identities the whole time.
Seeking to determine whether DNA barcoding of lipid nanoparticles for injection into living models would outperform in vitro testing, a team of investigators at Georgia Tech and Emory University conducted a comparison of the two techniques, reporting their findings in Nano Letters. The authors, led by James Dahlman, Ph.D., Assistant Professor of Biomedical Engineering at GT/Emory, found that in vitro testing did not predict in vivo delivery. Further, they were able to track several dozen barcodes delivered by nanoparticles to eight different cell lines.
The authors believe that their technique, which they call JOint Rapid DNA Analysis of Nanoparticles (JORDAN), is superior to in vitro screening of nanoparticles to predict successful transplantation. They are offering JORDAN online as open source software so other scientists can use the technology to more accurately screen nanomaterials.
Synthetic Biologists Create Gene Circuits
Among the many types of molecules that regulate genetic expression in the body are microRNAs, non-coding strands of RNA that are responsible for gene silencing and other forms of gene expression regulation. The ability to harness and control the functions of microRNAs could have important implications for disease prevention and treatment.
In a recent article in Systems Biology and Applications, researchers at the University of Texas, Dallas, report on their engineering of a microRNA-based genetic circuit and its deployment in living cells. They created the circuit using strands of RNA from a variety of organisms, including viruses and jellyfish. The authors, led by Leonidas Bleris, Ph.D., Associate Professor of Bioengineering at UT Dallas, used the circuits to better understand how microRNAs change gene expression under different conditions.
More importantly, the authors found that their circuit had the ability to outproduce types of gene expression, which decreased as the number of gene replications increased. The authors believe that their discoveries could have applications in a number of genetic disorders.
Discouraging Smoking at the Level of the Brain
Cigarette smoking is the single greatest contributor to negative health outcomes in the population. Nicotine addiction often appears during the teenage years, and aggressive advertising has been used for the last couple of decades to encourage people to quit smoking and younger people not to start. Despite the widespread use of advertising to change human behavior, remarkably little is known on how the brain responds to advertising messages.
Danielle S. Bassett, Ph.D., Eduardo D. Glandt Faculty Fellow and Associate Professor of Bioengineering at Penn, recently collaborated with faculty from Penn’s Annenberg School of Communication to determine the neuroscience underlying this outcome. The collaborators showed graphic warning labels to a cohort of smokers while they were subjected to functional magnetic resonance imaging, which images brain activity during specific tasks. They found that smokers whose brains showed greater coherence between regions in the valuation network were more likely to quit smoking. Determining why these brain regions acted as they did could yield even more effective smoking-cessation messaging.
Purdue Startup Working to Expand MRI
Engineers at Purdue, including Zhongming Liu, Ph.D., Assistant Professor of Biomedical Engineering and Electrical and Computer Engineering, have cofounded at startup company, called MR-Link, to develop and produce a coin-sized device that can be inserted into MRI machines, allowing them to perform multiple scans simultaneously.
The device could be useful in reducing the amount of electromagnetic force to which patients are exposed during an MRI scan. In addition, Dr. Liu and his colleagues believe the device will cost perhaps less than a tenth of what similar devices currently cost. Given the widespread use of MRI, the device could ultimately impact how a number of diseases and disorders are diagnosed and tracked.