Schizophrenia Genetics Linked to Disruption in How Brain Processes Sound

Staining performed by Konrad Talbot, PhD, targeting a marker for nerve cells involved in inhibition are shown in cross sections of the hippocampus, which is a part of the brain known to be affected in schizophrenia and involved in memory and cognition. In normal mice (top; A and B) a number of inhibitory cells are found. This staining is reduced in mice with reduced dysbindin (bottom; C and D). The finding is identical to that found in tissue from schizophrenia patients and supports the functional finding of the paper that fast inhibitory processes are disrupted in schizophrenia, leading to symptoms of the disease. (Credit: Konrad Talbot, PhD, Perelman School of Medicine, University of Pennsylvania, Neuron)

Science Daily  — Recent studies have identified many genes that may put people with schizophrenia at risk for the disease. But, what links genetic differences to changes in altered brain activity in schizophrenia is not clear. Now, three labs at the Perelman School of Medicine at the University of Pennsylvania have come together using electrophysiological, anatomical, and immunohistochemical approaches -- along with a unique high-speed imaging technique -- to understand how schizophrenia works at the cellular level, especially in identifying how changes in the interaction between different types of nerve cells leads to symptoms of the disease.

"Our work provides a model linking genetic risk factors for schizophrenia to a functional disruption in how the brain responds to sound, by identifying reduced activity in special nerve cells that are designed to make other cells in the brain work together at a very fast pace" explains lead author Gregory Carlson, PhD, assistant professor of Neuroscience in Psychiatry. "We know that in schizophrenia this ability is reduced, and now, knowing more about why this happens may help explain how loss of a protein called dysbindin leads to some symptoms of schizophrenia."

The findings are reported this week in the Proceedings of the National Academy of Sciences.

Previous genetic studies had found that some forms of the gene for dysbindin were found in people with schizophrenia. Most importantly, a prior finding at Penn showed that the dysbindin protein is reduced in a majority of schizophrenia patients, suggesting it is involved in a common cause of the disease.

For the current PNAS study, Carlson, Steven J. Siegel, MD, PhD, associate professor of Psychiatry, director of the Translational Neuroscience Program; and Steven E. Arnold, MD, director of the Penn Memory Center, used a mouse with a mutated dysbindin gene to understand how reduced dysbindin protein may cause symptoms of schizophrenia.

The team demonstrated a number of sound-processing deficits in the brains of mice with the mutated gene. They discovered how a specific set of nerve cells that control fast brain activity lose their effectiveness when dysbindin protein levels are reduced. These specific nerve cells inhibit activity, but do so in an extremely fast pace, essentially turning large numbers of cells on and off very quickly in a way that is necessary to normally process the large amount of information travelling into and around the brain.

Other previous work at Penn in the lab of Michael Kahana, PhD has shown that in humans the fast brain activity that is disrupted in mice with the dysbindin mutation is also important for short-term memory. This type of brain activity is reduced in people with schizophrenia and resistant to current therapy. Taken as a whole, this work may suggest new avenues of treatment for currently untreatable symptoms of schizophrenia, says Carlson.

Additional co-authors are: Konrad Talbot, Tobias B. Halene, Michael J. Gandal, Hala A. Kazi, Laura Schlosser, Quan H. Phung, and Raquel E. Gur, all from the Department of Psychiatry at Penn.

This work was funded in part by the National Institutes of Mental Health.

Carbon Nanotube Muscles Generate Giant Twist for Novel Motors

This is a scanning electron micrograph image of a 3.8-micron diameter carbon nanotube yarn that functions as a torsional muscle when filled with an ionically conducting liquid and electrochemically charged. The angle ± indicates the deviation between nanotube orientation and yarn direction for this helical yarn. (Credit: Image courtesy of the University of Texas at Dallas)

Science Daily  — New artificial muscles that twist like the trunk of an elephant, but provide a thousand times higher rotation per length, have been developed by a team of researchers from The University of Texas at Dallas, The University of Wollongong in Australia, The University of British Columbia in Canada, and Hanyang University in Korea.

The research appears in the journalScience.

These muscles, based on carbon nanotubes yarns, accelerate a 2000 times heavier paddle up to 590 revolutions per minute in 1.2 seconds, and then reverse this rotation when the applied voltage is changed. The demonstrated rotation of 250 per millimeter of muscle length is over a thousand times that of previous artificial muscles, which are based on ferroelectrics, shape memory alloys, or conducting organic polymers. The output power per yarn weight is comparable to that for large electric motors, and the weight-normalized performance of these conventional electric motors severely degrades when they are downsized to millimeter scale.

These muscles exploit strong, tough, highly flexible yarns of carbon nanotubes, which consist of nanoscale cylinders of carbon that are ten thousand times smaller in diameter than a human hair. Important for success, these nanotubes are spun into helical yarns, which means that they have left and right handed versions (like our hands), depending upon the direction of rotation during twisting the nanotubes to make yarn. Rotation is torsional, meaning that twist occurs in one direction until a limiting rotation results, and then rotation can be reversed by changing the applied voltage. Left and right hand yarns rotate in opposite directions when electrically charged, but in both cases the effect of charging is to partially untwist the yarn.

Unlike conventional motors, whose complexity makes them difficult to miniaturize, the torsional carbon nanotube muscles are simple to inexpensively construct in either very long or millimeter lengths. The nanotube torsional motors consist of a yarn electrode and a counter-electrode, which are immersed in an ionically conducting liquid. A low voltage battery can serve as the power source, which enables electrochemical charge and discharge of the yarn to provide torsional rotation in opposite directions. In the simplest case, the researchers attach a paddle to the nanotube yarn, which enables torsional rotation to do useful work -- like mixing liquids on "micro-fluidic chips" used for chemical analysis and sensing.

The mechanism of torsional rotation is remarkable. Charging the nanotube yarns is like charging a supercapacitor -- ions migrate into the yarns to electrostatically balance the electronic charge electrically injected onto the nanotubes. Although the yarns are porous, this influx of ions causes the yarn to increase volume, shrink in length by up to a percent, and torsionally rotate. This surprising shrinkage in yarn length as its volume increases is explained by the yarn's helical structure, which is similar in structure to finger cuff toys that trap a child's fingers when elongated, but frees them when shortened.

Nature has used torsional rotation based on helically wound muscles for hundreds of millions of years, and exploits this action for such tasks as twisting the trunks of elephants and octopus limbs. In these natural appendages, helically wound muscle fibers cause rotation by contracting against an essentially incompressible, bone-less core. On the other hand, the helically wound carbon nanotubes in the nanotube yarns are undergoing little change in length, but are instead causing the volume of liquid electrolyte within the porous yarn to increase during electrochemical charging, so that torsional rotation occurs.

The combination of mechanical simplicity, giant torsional rotations, high rotation rates, and micron-size yarn diameters are attractive for applications, such as microfluidic pumps, valve drives, and mixers. In a fluidic mixer demonstrated by the researchers, a 15 micron diameter yarn rotated a 200 times larger radius and 80 times heavier paddle in flowing liquids at up to one rotation per second.

"The discovery, characterization, and understanding of these high performance torsional motors shows the power of international collaborations," said Ray H. Baughman, a corresponding author of the author of the Science article and Robert A. Welch Professor of Chemistry and director of The University of Texas at Dallas Alan G. MacDiarmid NanoTech Institute. "Researchers from four universities in three different continents that were born in eight different countries made critically important contributions."

Other co-authors of this article are Javad Foroughi (first author and research fellow), Geoffrey M. Spinks (a corresponding author and professor), and Gordon G. Wallace (professor) of the University of Wollongong in Australia; Jiyoung Oh (postdoctoral fellow), Mikhail E. Kozlov (research professor), and Shaoli Fang (research professor) at The University of Texas at Dallas; Tissaphern Mirfakhrai (postdoctoral fellow) and John D. W. Madden (professor) at The University of British Columbia; and Min Kyoon Shin (postdoctoral fellow) and Seon Jeong Kim (professor) at Hanyang University.

Funding for this research was provided by grants from the Air Force Office of Scientific Research, the Air Force AOARD program, the Office of Naval Research MURI program, and the Robert A. Welch Foundation in the United States; the Creative Research Initiative Center for Bio-Artificial Muscle in Korea; the Natural Sciences and Engineering Research Council of Canada; and the Australian Research Council.

'Robot Biologist' Solves Complex Problem from Scratch

One of the microformulators that the Wikswo lab has developed that will give ABE the ability to perform experiments without human intervention. (Credit: Courtesy of Wikswo Lab)

Science Daily  — First it was chess. Then it was Jeopardy. Now computers are at it again, but this time they are trying to automate the scientific process itself.

The paper that describes this accomplishment is published in the October issue of the journal Physical Biology and is currently available online.An interdisciplinary team of scientists at Vanderbilt University, Cornell University and CFD Research Corporation, Inc., has taken a major step toward this goal by demonstrating that a computer can analyze raw experimental data from a biological system and derive the basic mathematical equations that describe the way the system operates. According to the researchers, it is one of the most complex scientific modeling problems that a computer has solved completely from scratch.

The work was a collaboration between John P. Wikswo, the Gordon A. Cain University Professor at Vanderbilt, Michael Schmidt and Hod Lipson at the Creative Machines Lab at Cornell University and Jerry Jenkins and Ravishankar Vallabhajosyula at CFDRC in Huntsville, Ala.

The "brains" of the system, which Wikswo has christened the Automated Biology Explorer (ABE), is a unique piece of software called Eureqa developed at Cornell and released in 2009. Schmidt and Lipson originally created Eureqa to design robots without going through the normal trial and error stage that is both slow and expensive. After it succeeded, they realized it could also be applied to solving science problems.

One of Eureqa's initial achievements was identifying the basic laws of motion by analyzing the motion of a double pendulum. What took Sir Isaac Newton years to discover, Eureqa did in a few hours when running on a personal computer.

In 2006, Wikswo heard Lipson lecture about his research. "I had a 'eureka moment' of my own when I realized the system Hod had developed could be used to solve biological problems and even control them," Wikswo said. So he started talking to Lipson immediately after the lecture and they began a collaboration to adapt Eureqa to analyze biological problems.

"Biology is the area where the gap between theory and data is growing the most rapidly," said Lipson. "So it is the area in greatest need of automation."

Software passes test

The biological system that the researchers used to test ABE is glycolysis, the primary process that produces energy in a living cell. Specifically, they focused on the manner in which yeast cells control fluctuations in the chemical compounds produced by the process.

The researchers chose this specific system, called glycolytic oscillations, to perform a virtual test of the software because it is one of the most extensively studied biological control systems. Jenkins and Vallabhajosyula used one of the process' detailed mathematical models to generate a data set corresponding to the measurements a scientist would make under various conditions. To increase the realism of the test, the researchers salted the data with a 10 percent random error. When they fed the data into Eureqa, it derived a series of equations that were nearly identical to the known equations.

"What's really amazing is that it produced these equations a priori," said Vallabhajosyula. "The only thing the software knew in advance was addition, subtraction, multiplication and division."

Beyond Adam

The ability to generate mathematical equations from scratch is what sets ABE apart from Adam, the robot scientist developed by Ross King and his colleagues at the University of Wales at Aberystwyth. Adam runs yeast genetics experiments and made international headlines two years ago by making a novel scientific discovery without direct human input. King fed Adam with a model of yeast metabolism and a database of genes and proteins involved in metabolism in other species. He also linked the computer to a remote-controlled genetics laboratory. This allowed the computer to generate hypotheses, then design and conduct actual experiments to test them.

"It's a classic paper," Wikswo said.

In order to give ABE the ability to run experiments like Adam, Wikswo's group is currently developing "laboratory-on-a-chip" technology that can be controlled by Eureqa. This will allow ABE to design and perform a wide variety of basic biology experiments. Their initial effort is focused on developing a microfluidics device that can test cell metabolism.

"Generally, the way that scientists design experiments is to vary one factor at a time while keeping the other factors constant, but, in many cases, the most effective way to test a biological system may be to tweak a large number of different factors at the same time and see what happens. ABE will let us do that," Wikswo said.

The project was funded by grants from the National Science Foundation, National Institute on Drug Abuse, the Defense Threat Reduction Agency and the National Academies Keck Futures Initiative.