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Category: computing

Nice — another step forward for all things connected.

Scientists can now talk to and even command living cells–to a limited degree at the moment, but with massive implications for the future. MIT biological engineers have created a computer code that allows them to basically hijack living cells and control them. It works similarly to a translation service, using a programming language to create a function for a cell in the form of a DNA sequence. Once it’s scalable, the invention has major ramifications. Future applications could include designing cells that produce a cancer drug when a tumor is detected or creating yeast cells that halt their own fermentation if too many toxic byproducts build up.

That’s not to imply it isn’t a big deal already. The code allows anyone, even someone without a biology background, to modify a pre-existing cell. All that’s required is knowledge of the programming language, which is based on one commonly used for computer chips called Verilog. “You could be completely naive as to how any of it works,” MIT biological engineering professor Christopher Voigt said in a press release. “That’s what’s really different about this. You could be a student in high school and go onto the Web-based server and type out the program you want, and it spits back the DNA sequence.” To learn more, read the full story here. For more on the confluence of biology and technology, watch this TED Talk below.

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A prototype chip with large arrays of phase-change devices that store the state of artificial neuronal populations in their atomic configuration. The devices are accessed via an array of probes in this prototype to allow for characterization and testing. The tiny squares are contact pads used to access the nanometer-scale phase-change cells (inset). Each set of probes can access a population of 100 cells. There are thousands to millions of these cells on one chip and IBM accesses them (in this particular photograph) by means of the sharp needles (probe card). (credit: IBM Research)

Scientists at IBM Research in Zurich have developed artificial neurons that emulate how neurons spike (fire). The goal is to create energy-efficient, high-speed, ultra-dense integrated neuromorphic (brain-like) technologies for applications in cognitive computing, such as unsupervised learning for detecting and analyzing patterns.

Applications could include internet of things sensors that collect and analyze volumes of weather data for faster forecasts and detecting patterns in financial transactions, for example.

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Prototype wireless battery-less “neural dust” mote (3 x 1 x 1 millimeters) with electrodes attached to a nerve fiber in a rat. The mote contains a piezoelectric crystal (silver cube) that converts ultrasonic signals to electrical current, powering a simple electronic circuit containing a transistor (black square) that responds to the voltage generated by a nerve firing and triggers the piezoelectric crystal to create ultrasonic backscatter, which indicates detection of a neural signal. (photo credit: Ryan Neely/UC Berkeley)

University of California, Berkeley engineers have designed and built millimeter-scale device wireless, batteryless “neural dust” sensors and implanted them in muscles and peripheral nerves of rats to make in vivo electrophysiological recordings.

The new technology opens the door to “electroceuticals” — bioelectronic methods to monitor and record wireless electromyogram (EMG) signals from muscle membranes and electroneurogram (ENG) signals from local neuron electrical activity, and to stimulate the immune system, reduce inflammation, and treat disorders such as epilepsy.

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IBM scientists have developed a new lab-on-a-chip technology that can, for the first time, separate biological particles at the nanoscale and could help enable physicians to detect diseases such as cancer before symptoms appear.

As reported today in the journal Nature Nanotechnology*, the IBM team’s results show size-based separation of bioparticles down to 20 nanometers (nm) in diameter, a scale that gives access to important particles such as DNA, viruses and exosomes. Once separated, these particles can be analyzed by physicians to potentially reveal signs of disease even before patients experience any physical symptoms and when the outcome from treatment is most positive. Until now, the smallest bioparticle that could be separated by size with on-chip technologies was about 50 times or larger, for example, separation of circulating tumor cells from other biological components.

IBM is collaborating with a team from the Icahn School of Medicine at Mount Sinai to continue development of this lab-on-a-chip technology and plans to test it on prostate cancer, the most common cancer in men in the U.S.

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Quantum computing remains mysterious and elusive to many, but USC Viterbi School of Engineering researchers might have taken us one step closer to bring such super-powered devices to practical reality. The USC Viterbi School of Engineering and Information Sciences Institute is home to the USC-Lockheed Martin Quantum Computing Center (QCC), a super-cooled, magnetically shielded facility specially built to house the first commercially available quantum optimization processors — devices so advanced that there are currently only two in use outside the Canadian company D-Wave Systems Inc., where they were built: The first one went to USC and Lockheed Martin, and the second to NASA and Google.

Quantum computers encode data in quantum bits, or “qubits,” which have the capability of representing the two digits of one and zero at the same time — as opposed to traditional bits, which can encode distinctly either a one or a zero. This property, called superposition, along with the ability of quantum states to “interfere” (cancel or reinforce each other like waves in a pond) and “tunnel” through energy barriers, is what may one day allow quantum processors to ultimately perform optimization calculations much faster than is possible using traditional processors. Optimization problems can take many forms, and quantum processors have been theorized to be useful for a variety of machine learning and big data problems like stock portfolio optimization, image recognition and classification, and detecting anomalies. Yet, exactly because of the exotic way in which quantum computers process information, they are highly sensitive to errors of different kinds.

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Consider the paradox of the modern business office: It’s a place of productivity where busy people meet deadlines, yet it’s teeming with distractions.

Companies are loading up on game rooms and snack bars, while 70 percent of American offices have adopted an open-office floor plan. The hope for open offices was to encourage random hallway banter, which can lead to innovation, but it’s not working out so great. Turns out privacy is a necessary condition for supporting productive people.

To end the oppression of open offices, several startups are building workstations of the future: software that pulls everything we normally do on a computer inside of virtual reality (VR). After all, what’s more private than a VR display around your head?

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The benefits of the technology for humans, while still largely hypothetical, are promising. The sensors could allow physicians to monitor the health of organs, create new therapies for neurological disorders, and help the physically impaired to control prosthetics.

While chips have been implanted in humans and other animals before, these sensors mark a significant improvement because they are small, wireless, batteryless, and could last in the body for years without degrading, said Michel Maharbiz, the associate professor who devised and studied the sensors alongside neuroscientist Jose Carmena.

“Hopefully the [tiny sensors] demonstrate a new direction for the field, and then you could build the consensus that’s needed to drive these forward,” Maharbiz said.

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Magine a future in which hyper-efficient solar panels provide renewable sources of energy, improved water filters quickly remove toxins from drinking water, and the air is scrubbed clean of pollution and greenhouse gases. That could become a reality with the right molecules and materials.

Scientists from Harvard and Google have taken a major step toward making the search for those molecules easier, demonstrating for the first time that a quantum computer could be used to model the electron interactions in a complex molecule. The work is described in a new paper published in the journal Physical Review X by Professor Alán Aspuru-Guzik from the Department of Chemistry and Chemical Biology and several co-authors.

“There are a number of applications that a quantum computer would be useful for: cryptography, machine learning, and certain number-theory problems,” Aspuru-Guzik said. “But one that has always been mentioned, even from the first conceptions of a quantum computer, was to use it to simulate matter. In this case, we use it to simulate chemistry.”

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