Tag Archives: neurons

Stretchy optical materials for implants that could pulse light

An Oct. 17, 2016 Massachusetts Institute of Technology (MIT) news release (also on EurekAlert) by Emily Chu describes research that could lead to long-lasting implants offering preventive health strategies,

Researchers from MIT and Harvard Medical School have developed a biocompatible and highly stretchable optical fiber made from hydrogel — an elastic, rubbery material composed mostly of water. The fiber, which is as bendable as a rope of licorice, may one day be implanted in the body to deliver therapeutic pulses of light or light up at the first sign of disease. [emphasis mine]

The researchers say the fiber may serve as a long-lasting implant that would bend and twist with the body without breaking down. The team has published its results online in the journal Advanced Materials.

Using light to activate cells, and particularly neurons in the brain, is a highly active field known as optogenetics, in which researchers deliver short pulses of light to targeted tissues using needle-like fibers, through which they shine light from an LED source.

“But the brain is like a bowl of Jell-O, whereas these fibers are like glass — very rigid, which can possibly damage brain tissues,” says Xuanhe Zhao, the Robert N. Noyce Career Development Associate Professor in MIT’s Department of Mechanical Engineering. “If these fibers could match the flexibility and softness of the brain, they could provide long-term more effective stimulation and therapy.”

Getting to the core of it

Zhao’s group at MIT, including graduate students Xinyue Liu and Hyunwoo Yuk, specializes in tuning the mechanical properties of hydrogels. The researchers have devised multiple recipes for making tough yet pliable hydrogels out of various biopolymers. The team has also come up with ways to bond hydrogels with various surfaces such as metallic sensors and LEDs, to create stretchable electronics.

The researchers only thought to explore hydrogel’s use in optical fibers after conversations with the bio-optics group at Harvard Medical School, led by Associate Professor Seok-Hyun (Andy) Yun. Yun’s group had previously fabricated an optical fiber from hydrogel material that successfully transmitted light through the fiber. However, the material broke apart when bent or slightly stretched. Zhao’s hydrogels, in contrast, could stretch and bend like taffy. The two groups joined efforts and looked for ways to incorporate Zhao’s hydrogel into Yun’s optical fiber design.

Yun’s design consists of a core material encased in an outer cladding. To transmit the maximum amount of light through the core of the fiber, the core and the cladding should be made of materials with very different refractive indices, or degrees to which they can bend light.

“If these two things are too similar, whatever light source flows through the fiber will just fade away,” Yuk explains. “In optical fibers, people want to have a much higher refractive index in the core, versus cladding, so that when light goes through the core, it bounces off the interface of the cladding and stays within the core.”

Happily, they found that Zhao’s hydrogel material was highly transparent and possessed a refractive index that was ideal as a core material. But when they tried to coat the hydrogel with a cladding polymer solution, the two materials tended to peel apart when the fiber was stretched or bent.

To bond the two materials together, the researchers added conjugation chemicals to the cladding solution, which, when coated over the hydrogel core, generated chemical links between the outer surfaces of both materials.

“It clicks together the carboxyl groups in the cladding, and the amine groups in the core material, like molecular-level glue,” Yuk says.

Sensing strain

The researchers tested the optical fibers’ ability to propagate light by shining a laser through fibers of various lengths. Each fiber transmitted light without significant attenuation, or fading. They also found that fibers could be stretched over seven times their original length without breaking.

Now that they had developed a highly flexible and robust optical fiber, made from a hydrogel material that was also biocompatible, the researchers began to play with the fiber’s optical properties, to see if they could design a fiber that could sense when and where it was being stretched.

They first loaded a fiber with red, green, and blue organic dyes, placed at specific spots along the fiber’s length. Next, they shone a laser through the fiber and stretched, for instance, the red region. They measured the spectrum of light that made it all the way through the fiber, and noted the intensity of the red light. They reasoned that this intensity relates directly to the amount of light absorbed by the red dye, as a result of that region being stretched.

In other words, by measuring the amount of light at the far end of the fiber, the researchers can quantitatively determine where and by how much a fiber was stretched.

“When you stretch a certain portion of the fiber, the dimensions of that part of the fiber changes, along with the amount of light that region absorbs and scatters, so in this way, the fiber can serve as a sensor of strain,” Liu explains.

“This is like a multistrain sensor through a single fiber,” Yuk adds. “So it can be an implantable or wearable strain gauge.”

The researchers imagine that such stretchable, strain-sensing optical fibers could be implanted or fitted along the length of a patient’s arm or leg, to monitor for signs of improving mobility.

Zhao envisions the fibers may also serve as sensors, lighting up in response to signs of disease.

“We may be able to use optical fibers for long-term diagnostics, to optically monitor tumors or inflammation,” he says. “The applications can be impactful.”

Here’s a link to and a citation for the paper,

Highly Stretchable, Strain Sensing Hydrogel Optical Fibers by Jingjing Guo, Xinyue Liu, Nan Jiang, Ali K. Yetisen, Hyunwoo Yuk, Changxi Yang, Ali Khademhosseini, Xuanhe Zhao, and Seok-Hyun Yun. Advanced Materials DOI: 10.1002/adma.201603160 Version of Record online: 7 OCT 2016

© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

This paper is behind a paywall.

A bionic hybrid neurochip from the University of Calgary (Canada)

The University of Calgary is publishing some very exciting work these days as can be seen in my Sept. 21, 2016 posting about quantum teleportation. Today, the university announced this via an Oct. 26, 2016 news item on Nanowerk (Note: A link has been removed),

Brain functions are controlled by millions of brain cells. However, in order to understand how the brain controls functions, such as simple reflexes or learning and memory, we must be able to record the activity of large networks and groups of neurons. Conventional methods have allowed scientists to record the activity of neurons for minutes, but a new technology, developed by University of Calgary researchers, known as a bionic hybrid neuro chip, is able to record activity in animal brain cells for weeks at a much higher resolution. The technological advancement was published in the journal Scientific Reports(“A novel bio-mimicking, planar nano-edge microelectrode enables enhanced long-term neural recording”).

There’s more from an Oct. 26, 2016 University of Calgary news release on EurekAlert, which originated the news item,

“These chips are 15 times more sensitive than conventional neuro chips,” says Naweed Syed, PhD, scientific director of the University of Calgary, Cumming School of Medicine’s Alberta Children’s Hospital Research Institute, member of the Hotchkiss Brain Institute and senior author on the study. “This allows brain cell signals to be amplified more easily and to see real time recordings of brain cell activity at a resolution that has never been achieved before.”

The development of this technology will allow researchers to investigate and understand in greater depth, in animal models, the origins of neurological diseases and conditions such as epilepsy, as well as other cognitive functions such as learning and memory.

“Recording this activity over a long period of time allows you to see changes that occur over time, in the activity itself,” says Pierre Wijdenes, a PhD student in the Biomedical Engineering Graduate Program and the study’s first author. “This helps to understand why certain neurons form connections with each other and why others won’t.”

The cross-faculty team created the chip to mimic the natural biological contact between brain cells, essentially tricking the brain cells into believing that they are connecting with other brain cells. As a result, the cells immediately connect with the chip, thereby allowing researchers to view and record the two-way communication that would go on between two normal functioning brain cells.

“We simulated what mother-nature does in nature and provided brain cells with an environment where they feel as if they are at home,” says Syed. “This has allowed us to increase the sensitivity of our readings and help neurons build a long-term relationship with our electronic chip.”

While the chip is currently used to analyze animal brain cells, this increased resolution and the ability to make long-term recordings is bringing the technology one step closer to being effective in the recording of human brain cell activity.

“Human brain cell signals are smaller and therefore require more sensitive electronic tools to be designed to pick up the signals,” says Colin Dalton, Adjunct Professor in the Department of Electrical and Computer Engineering at the Schulich School of Engineering and a co-author on this study. Dalton is also the Facility Manager of the University of Calgary’s Advanced Micro/nanosystems Integration Facility (AMIF), where the chips were designed and fabricated.

Researchers hope the technology will one day be used as a tool to bring personalized therapeutic options to patients facing neurological disease.

Here’s a link to and a citation for the paper,

A novel bio-mimicking, planar nano-edge microelectrode enables enhanced long-term neural recording by Pierre Wijdenes, Hasan Ali, Ryden Armstrong, Wali Zaidi, Colin Dalton & Naweed I. Syed. Scientific Reports 6, Article number: 34553 (2016) doi:10.1038/srep34553
Published online: 12 October 2016

This paper is  open access.

Nanotubes tunnel between neurons in Parkinson’s disease

An Aug. 22, 2016 news item on ScienceDaily describes how scientists from the Institut Pasteur (France) have developed insight into one of the processes in Parkinson’s disease,

Scientists have demonstrated the role of lysosomal vesicles in transporting alpha-synuclein aggregates, responsible for Parkinson’s and other neurodegenerative diseases, between neurons. These proteins move from one neuron to the next in lysosomal vesicles which travel along the ‘tunneling nanotubes’ between cells.

An Aug. 22, 2016 Institut Pasteur press release (also on EurekAlert), expands on the theme,

Synucleinopathies, a group of neurodegenerative diseases including Parkinson’s disease, are characterized by the pathological deposition of aggregates of the misfolded α-synuclein protein into inclusions throughout the central and peripheral nervous system. Intercellular propagation (from one neuron to the next) of α-synuclein aggregates contributes to the progression of the neuropathology, but little was known about the mechanism by which spread occurs.

In this study, scientists from the Membrane Traffic and Pathogenesis Unit, directed by Chiara Zurzolo at the Institut Pasteur, used fluorescence microscopy to demonstrate that pathogenic α-synuclein fibrils travel between neurons in culture, inside lysosomal vesicles through tunneling nanotubes (TNTs), a new mechanism of intercellular communication.

After being transferred via TNTs, α-synuclein fibrils are able to recruit and induce aggregation of the soluble α-synuclein protein in the cytosol of cells receiving the fibrils, thus explaining the propagation of the disease. The scientists propose that cells overloaded with α-synuclein aggregates in lysosomes dispose of this material by hijacking TNT-mediated intercellular trafficking. However, this results in the disease being spread to naive neurons.

This study demonstrates that TNTs play a significant part in the intercellular transfer of α-synuclein fibrils and reveals the specific role of lysosomes in this process. This represents a major breakthrough in understanding the mechanisms underlying the progression of synucleinopathies.

These compelling findings, together with previous reports from the same team, point to the general role of TNTs in the propagation of prion-like proteins in neurodegenerative diseases and identify TNTs as a new therapeutic target to combat the progression of these incurable diseases.

Here’s a link to and a citation for the paper,

Tunneling nanotubes spread fibrillar α‐synuclein by intercellular trafficking of lysosomes by Saïda Abounit, Luc Bousset, Frida Loria, Seng Zhu, Fabrice de Chaumont, Laura Pieri, Jean-Christophe Olivo-Marin, Ronald Melki, Chiara Zurzolo. The EMBO Journal (2016) e201593411 DOI 10.15252/embj.201593411 Published online 22.08.2016

This paper is behind a paywall.

US white paper on neuromorphic computing (or the nanotechnology-inspired Grand Challenge for future computing)

The US has embarked on a number of what is called “Grand Challenges.” I first came across the concept when reading about the Bill and Melinda Gates (of Microsoft fame) Foundation. I gather these challenges are intended to provide funding for research that advances bold visions.

There is the US National Strategic Computing Initiative established on July 29, 2015 and its first anniversary results were announced one year to the day later. Within that initiative a nanotechnology-inspired Grand Challenge for Future Computing was issued and, according to a July 29, 2016 news item on Nanowerk, a white paper on the topic has been issued (Note: A link has been removed),

Today [July 29, 2016), Federal agencies participating in the National Nanotechnology Initiative (NNI) released a white paper (pdf) describing the collective Federal vision for the emerging and innovative solutions needed to realize the Nanotechnology-Inspired Grand Challenge for Future Computing.

The grand challenge, announced on October 20, 2015, is to “create a new type of computer that can proactively interpret and learn from data, solve unfamiliar problems using what it has learned, and operate with the energy efficiency of the human brain.” The white paper describes the technical priorities shared by the agencies, highlights the challenges and opportunities associated with these priorities, and presents a guiding vision for the research and development (R&D) needed to achieve key technical goals. By coordinating and collaborating across multiple levels of government, industry, academia, and nonprofit organizations, the nanotechnology and computer science communities can look beyond the decades-old approach to computing based on the von Neumann architecture and chart a new path that will continue the rapid pace of innovation beyond the next decade.

A July 29, 2016 US National Nanotechnology Coordination Office news release, which originated the news item, further and succinctly describes the contents of the paper,

“Materials and devices for computing have been and will continue to be a key application domain in the field of nanotechnology. As evident by the R&D topics highlighted in the white paper, this challenge will require the convergence of nanotechnology, neuroscience, and computer science to create a whole new paradigm for low-power computing with revolutionary, brain-like capabilities,” said Dr. Michael Meador, Director of the National Nanotechnology Coordination Office. …

The white paper was produced as a collaboration by technical staff at the Department of Energy, the National Science Foundation, the Department of Defense, the National Institute of Standards and Technology, and the Intelligence Community. …

The white paper titled “A Federal Vision for Future Computing: A Nanotechnology-Inspired Grand Challenge” is 15 pp. and it offers tidbits such as this (Note: Footnotes not included),

A new materials base may be needed for future electronic hardware. While most of today’s electronics use silicon, this approach is unsustainable if billions of disposable and short-lived sensor nodes are needed for the coming Internet-of-Things (IoT). To what extent can the materials base for the implementation of future information technology (IT) components and systems support sustainability through recycling and bio-degradability? More sustainable materials, such as compostable or biodegradable systems (polymers, paper, etc.) that can be recycled or reused,  may play an important role. The potential role for such alternative materials in the fabrication of integrated systems needs to be explored as well. [p. 5]

The basic architecture of computers today is essentially the same as those built in the 1940s—the von Neumann architecture—with separate compute, high-speed memory, and high-density storage components that are electronically interconnected. However, it is well known that continued performance increases using this architecture are not feasible in the long term, with power density constraints being one of the fundamental roadblocks.7 Further advances in the current approach using multiple cores, chip multiprocessors, and associated architectures are plagued by challenges in software and programming models. Thus,  research and development is required in radically new and different computing architectures involving processors, memory, input-output devices, and how they behave and are interconnected. [p. 7]

Neuroscience research suggests that the brain is a complex, high-performance computing system with low energy consumption and incredible parallelism. A highly plastic and flexible organ, the human brain is able to grow new neurons, synapses, and connections to cope with an ever-changing environment. Energy efficiency, growth, and flexibility occur at all scales, from molecular to cellular, and allow the brain, from early to late stage, to never stop learning and to act with proactive intelligence in both familiar and novel situations. Understanding how these mechanisms work and cooperate within and across scales has the potential to offer tremendous technical insights and novel engineering frameworks for materials, devices, and systems seeking to perform efficient and autonomous computing. This research focus area is the most synergistic with the national BRAIN Initiative. However, unlike the BRAIN Initiative, where the goal is to map the network connectivity of the brain, the objective here is to understand the nature, methods, and mechanisms for computation,  and how the brain performs some of its tasks. Even within this broad paradigm,  one can loosely distinguish between neuromorphic computing and artificial neural network (ANN) approaches. The goal of neuromorphic computing is oriented towards a hardware approach to reverse engineering the computational architecture of the brain. On the other hand, ANNs include algorithmic approaches arising from machinelearning,  which in turn could leverage advancements and understanding in neuroscience as well as novel cognitive, mathematical, and statistical techniques. Indeed, the ultimate intelligent systems may as well be the result of merging existing ANN (e.g., deep learning) and bio-inspired techniques. [p. 8]

As government documents go, this is quite readable.

For anyone interested in learning more about the future federal plans for computing in the US, there is a July 29, 2016 posting on the White House blog celebrating the first year of the US National Strategic Computing Initiative Strategic Plan (29 pp. PDF; awkward but that is the title).

Memory material with functions resembling synapses and neurons in the brain

This work comes from the University of Twente’s MESA+ Institute for Nanotechnology according to a July 8, 2016 news item on ScienceDaily,

Our brain does not work like a typical computer memory storing just ones and zeroes: thanks to a much larger variation in memory states, it can calculate faster consuming less energy. Scientists of the MESA+ Institute for Nanotechnology of the University of Twente (The Netherlands) now developed a ferro-electric material with a memory function resembling synapses and neurons in the brain, resulting in a multistate memory. …

A July 8, 2016 University of Twente press release, which originated the news item, provides more technical detail,

The material that could be the basic building block for ‘brain-inspired computing’ is lead-zirconium-titanate (PZT): a sandwich of materials with several attractive properties. One of them is that it is ferro-electric: you can switch it to a desired state, this state remains stable after the electric field is gone. This is called polarization: it leads to a fast memory function that is non-volatile. Combined with processor chips, a computer could be designed that starts much faster, for example. The UT scientists now added a thin layer of zinc oxide to the PZT, 25 nanometer thickness. They discovered that switching from one state to another not only happens from ‘zero’ to ‘one’ vice versa. It is possible to control smaller areas within the crystal: will they be polarized (‘flip’) or not?

In a PZT layer without zinc oxide (ZnO) there are basically two memorystates. Adding a nano layer of ZnO, every state in between is possible as well.

Multistate

By using variable writing times in those smaller areas, the result is that many states can be stored anywhere between zero and one. This resembles the way synapses and neurons ‘weigh’ signals in our brain. Multistate memories, coupled to transistors, could drastically improve the speed of pattern recognition, for example: our brain performs this kind of tasks consuming only a fraction of the energy a computer system needs. Looking at the graphs, the writing times seem quite long compared to nowaday’s processor speeds, but it is possible to create many memories in parallel. The function of the brain has already been mimicked in software like neurale networks, but in that case conventional digital hardware is still a limitation. The new material is a first step towards electronic hardware with a brain-like memory. Finding solutions for combining PZT with semiconductors, or even developing new kinds of semiconductors for this, is one of the next steps.

Here’s a link to and a citation for the paper,

Multistability in Bistable Ferroelectric Materials toward Adaptive Applications by Anirban Ghosh, Gertjan Koster, and Guus Rijnders. Advanced Functional Materials DOI: 10.1002/adfm.201601353 Version of Record online: 4 JUL 2016

© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

This paper is behind a paywall.

3D brain-on-a-chip from the University of Twente

Dutch researchers have developed a 3D brain-on-a-chip according to a June 23, 2016 news item on Nanowerk,

To study brain cell’s operation and test the effect of medication on individual cells, the conventional Petri dish with flat electrodes is not sufficient. For truly realistic studies, cells have to flourish within three-dimensional surroundings.

Bart Schurink, researcher at University of Twente’s MESA+ Institute for Nanotechnology, has developed a sieve with 900 openings, each of which has the shape of an inverted pyramid. On top of this array of pyramids, a micro-reactor takes care of cell growth. Schurink defends his PhD thesis June 23 [2016].

A June 23, 2016 University of Twente press release, which originated the news item, provides more detail,

A brain-on-a-chip demands more than a series of electrodes in 2D, on which brain cells can be cultured. To mimic the brain in a realistic way, you need facilities for fluid flow, and the cells need some freedom for themselves even when they are kept at predefined spaces. Schurink therefore developed a micro sieve structure with hundreds of openings on a 2 by 2 mm surface. Each of these holes has the shape of  an inverted pyramid. Each pyramid, in turn, is equipped with an electrode, for measuring electrical signals or sending stimuli to the network. At the same time, liquids can flow through tiny holes, needed to capture the cells and for sending nutrients or medication to a single cell.

NEURONAL NETWORK

After neurons have been placed inside all the pyramids, they will start to form a network. This is not just a 2D network between the holes: by placing a micro reactor on top of the sieve, a neuron network can develop in the vertical direction as well. Growth and electrical activity can be monitored subsequently: each individual cell can be identified by the pyramid it is in. Manufacturing this system, demands a lot of both the production facilities at UT’s NanoLab and of creative solutions the designers come up with. For example, finding the proper way of guaranteeing  the same dimensions for every hole, is quite challenging.

Schurink’s new µSEA (micro sieve electrode array) has been tested with living cells, from the brains of laboratory rats. Both the positioning of the cells and neuronal network growth have been tested. The result of this PhD research is a fully new research platform for performing research on the brain, diseases and effects of medication.

Schurink (1982) has conducted his research within the group Meso Scale Chemical Systems, of Prof Han Gardeniers. The group is part of the MESA+ Institute for Nanotechnology of the University of Twente. Schurink’s thesis is titled ‘Microfabrication and microfluidics for 3D brain-on-chip’ …

I have written about one other piece about a ‘3D’ organ-on-a-chip project in China (my Jan. 29, 2016 posting).

Small, soft, and electrically functional: an injectable biomaterial

This development could be looked at as a form of synthetic biology without the genetic engineering. From a July 1, 2016 news item on ScienceDaily,

Ideally, injectable or implantable medical devices should not only be small and electrically functional, they should be soft, like the body tissues with which they interact. Scientists from two UChicago labs set out to see if they could design a material with all three of those properties.

The material they came up with, published online June 27, 2016, in Nature Materials, forms the basis of an ingenious light-activated injectable device that could eventually be used to stimulate nerve cells and manipulate the behavior of muscles and organs.

“Most traditional materials for implants are very rigid and bulky, especially if you want to do electrical stimulation,” said Bozhi Tian, an assistant professor in chemistry whose lab collaborated with that of neuroscientist Francisco Bezanilla on the research.

The new material, in contrast, is soft and tiny — particles just a few micrometers in diameter (far less than the width of a human hair) that disperse easily in a saline solution so they can be injected. The particles also degrade naturally inside the body after a few months, so no surgery would be needed to remove them.

A July 1, 2016 University of Chicago news release (also on EurekAlert) by , which originated the news item, provides more detail,

Each particle is built of two types of silicon that together form a structure full of nano-scale pores, like a tiny sponge. And like a sponge, it is squishy — a hundred to a thousand times less rigid than the familiar crystalline silicon used in transistors and solar cells. “It is comparable to the rigidity of the collagen fibers in our bodies,” said Yuanwen Jiang, Tian’s graduate student. “So we’re creating a material that matches the rigidity of real tissue.”

The material constitutes half of an electrical device that creates itself spontaneously when one of the silicon particles is injected into a cell culture, or, eventually, a human body. The particle attaches to a cell, making an interface with the cell’s plasma membrane. Those two elements together — cell membrane plus particle — form a unit that generates current when light is shined on the silicon particle.

“You don’t need to inject the entire device; you just need to inject one component,” João L. Carvalho-de-Souza , Bezanilla’s postdoc said. “This single particle connection with the cell membrane allows sufficient generation of current that could be used to stimulate the cell and change its activity. After you achieve your therapeutic goal, the material degrades naturally. And if you want to do therapy again, you do another injection.”

The scientists built the particles using a process they call nano-casting. They fabricate a silicon dioxide mold composed of tiny channels — “nano-wires” — about seven nanometers in diameter (less than 10,000 times smaller than the width of a human hair) connected by much smaller “micro-bridges.” Into the mold they inject silane gas, which fills the pores and channels and decomposes into silicon.

And this is where things get particularly cunning. The scientists exploit the fact the smaller an object is, the more the atoms on its surface dominate its reactions to what is around it. The micro-bridges are minute, so most of their atoms are on the surface. These interact with oxygen that is present in the silicon dioxide mold, creating micro-bridges made of oxidized silicon gleaned from materials at hand. The much larger nano-wires have proportionately fewer surface atoms, are much less interactive, and remain mostly pure silicon. [I have a note regarding ‘micro’ and ‘nano’ later in this posting.]

“This is the beauty of nanoscience,” Jiang said. “It allows you to engineer chemical compositions just by manipulating the size of things.”

Web-like nanostructure

Finally, the mold is dissolved. What remains is a web-like structure of silicon nano-wires connected by micro-bridges of oxidized silicon that can absorb water and help increase the structure’s softness. The pure silicon retains its ability to absorb light.

Transmission electron microscopy image shows an ordered nanowire array. The 100-nanometer scale bar is 1,000 times narrower than a hair. Courtesy of Tian Lab

Transmission electron microscopy image shows an ordered nanowire array. The 100-nanometer scale bar is 1,000 times narrower than a hair. Courtesy of
Tian Lab

The scientists have added the particles onto neurons in culture in the lab, shone light on the particles, and seen current flow into the neurons which activates the cells. The next step is to see what happens in living animals. They are particularly interested in stimulating nerves in the peripheral nervous system that connect to organs. These nerves are relatively close to the surface of the body, so near-infra-red wavelength light can reach them through the skin.

Tian imagines using the light-activated devices to engineer human tissue and create artificial organs to replace damaged ones. Currently, scientists can make engineered organs with the correct form but not the ideal function.

To get a lab-built organ to function properly, they will need to be able to manipulate individual cells in the engineered tissue. The injectable device would allow a scientist to do that, tweaking an individual cell using a tightly focused beam of light like a mechanic reaching into an engine and turning a single bolt. The possibility of doing this kind of synthetic biology without genetic engineering [emphasis mine] is enticing.

“No one wants their genetics to be altered,” Tian said. “It can be risky. There’s a need for a non-genetic system that can still manipulate cell behavior. This could be that kind of system.”

Tian’s graduate student Yuanwen Jiang did the material development and characterization on the project. The biological part of the collaboration was done in the lab of Francisco Bezanilla, the Lillian Eichelberger Cannon Professor of Biochemistry and Molecular Biology, by postdoc João L. Carvalho-de-Souza. They were, said Tian, the “heroes” of the work.

I was a little puzzled about the use of the word ‘micro’ in a context suggesting it was smaller than something measured at the nanoscale. Dr. Tian very kindly cleared up my confusion with this response in a July 4, 2016 email,

In fact, the definition of ‘micro’ and ’nano’ have been quite ambiguous in literature. For example, microporous materials (e.g., zeolite) usually refer to materials with pore sizes of less than 2 nm — this is defined based on IUPAC [International Union of Pure and Applied Chemistry] definition (http://goldbook.iupac.org/M03853.html). We used ‘micro-bridges’ because they come from the ‘micropores’ in the original template.

Thank you Dr. Tian for that very clear reply and Steve Koppes for forwarding my request to Dr. Tian!

Here’s a link to and a citation for the paper,

Heterogeneous silicon mesostructures for lipid-supported bioelectric interfaces by Yuanwen Jiang, João L. Carvalho-de-Souza, Raymond C. S. Wong, Zhiqiang Luo, Dieter Isheim, Xiaobing Zuo, Alan W. Nicholls, Il Woong Jung, Jiping Yue, Di-Jia Liu, Yucai Wang, Vincent De Andrade, Xianghui Xiao, Luizetta Navrazhnykh, Dara E. Weiss, Xiaoyang Wu, David N. Seidman, Francisco Bezanilla, & Bozhi Tian. Nature Materials (2016)  doi:10.1038/nmat4673 Published online 27 June 2016

This paper is behind a paywall.

I gather animal testing will be the next step as they continue to develop this exciting technology. Good luck!

Replicating brain’s neural networks with 3D nanoprinting

An announcement about European Union funding for a project to reproduce neural networks by 3D nanoprinting can be found in a June 10, 2016 news item on Nanowerk,

The MESO-BRAIN consortium has received a prestigious award of €3.3million in funding from the European Commission as part of its Future and Emerging Technology (FET) scheme. The project aims to develop three-dimensional (3D) human neural networks with specific biological architecture, and the inherent ability to interrogate the network’s brain-like activity both electrophysiologically and optically. It is expected that the MESO-BRAIN will facilitate a better understanding of human disease progression, neuronal growth and enable the development of large-scale human cell-based assays to test the modulatory effects of pharmacological and toxicological compounds on neural network activity. The use of more physiologically relevant human models will increase drug screening efficiency and reduce the need for animal testing.

A June 9, 2016 Institute of Photonic Sciences (ICFO) press release (also on EurekAlert), which originated the news item, provides more detail,

About the MESO-BRAIN project

The MESO-BRAIN project’s cornerstone will use human induced pluripotent stem cells (iPSCs) that have been differentiated into neurons upon a defined and reproducible 3D scaffold to support the development of human neural networks that emulate brain activity. The structure will be based on a brain cortical module and will be unique in that it will be designed and produced using nanoscale 3D-laser-printed structures incorporating nano-electrodes to enable downstream electrophysiological analysis of neural network function. Optical analysis will be conducted using cutting-edge light sheet-based, fast volumetric imaging technology to enable cellular resolution throughout the 3D network. The MESO-BRAIN project will allow for a comprehensive and detailed investigation of neural network development in health and disease.

Prof Edik Rafailov, Head of the MESO-BRAIN project (Aston University) said: “What we’re proposing to achieve with this project has, until recently, been the stuff of science fiction. Being able to extract and replicate neural networks from the brain through 3D nanoprinting promises to change this. The MESO-BRAIN project has the potential to revolutionise the way we are able to understand the onset and development of disease and discover treatments for those with dementia or brain injuries. We cannot wait to get started!”

The MESO-BRAIN project will launch in September 2016 and research will be conducted over three years.

About the MESO-BRAIN consortium

Each of the consortium partners have been chosen for the highly specific skills & knowledge that they bring to this project. These include technologies and expertise in stem cells, photonics, physics, 3D nanoprinting, electrophysiology, molecular biology, imaging and commercialisation.

Aston University (UK) Aston Institute of Photonic Technologies (School of Engineering and Applied Science) is one of the largest photonic groups in UK and an internationally recognised research centre in the fields of lasers, fibre-optics, high-speed optical communications, nonlinear and biomedical photonics. The Cell & Tissue Biomedical Research Group (Aston Research Centre for Healthy Ageing) combines collective expertise in genetic manipulation, tissue engineering and neuronal modelling with the electrophysiological and optical analysis of human iPSC-derived neural networks. Axol Bioscience Ltd. (UK) was founded to fulfil the unmet demand for high quality, clinically relevant human iPSC-derived cells for use in biomedical research and drug discovery. The Laser Zentrum Hannover (Germany) is a leading research organisation in the fields of laser development, material processing, laser medicine, and laser-based nanotechnologies. The Neurophysics Group (Physics Department) at University of Barcelona (Spain) are experts in combing experiments with theoretical and computational modelling to infer functional connectivity in neuronal circuits. The Institute of Photonic Sciences (ICFO) (Spain) is a world-leading research centre in photonics with expertise in several microscopy techniques including light sheet imaging. KITE Innovation (UK) helps to bridge the gap between the academic and business sectors in supporting collaboration, enterprise, and knowledge-based business development.

For anyone curious about the FET funding scheme, there’s this from the press release,

Horizon 2020 aims to ensure Europe produces world-class science by removing barriers to innovation through funding programmes such as the FET. The FET (Open) funds forward-looking collaborations between advanced multidisciplinary science and cutting-edge engineering for radically new future technologies. The published success rate is below 1.4%, making it amongst the toughest in the Horizon 2020 suite of funding schemes. The MESO-BRAIN proposal scored a perfect 5/5.

You can find out more about the MESO-BRAIN project on its ICFO webpage.

They don’t say anything about it but I can’t help wondering if the scientists aren’t also considering the possibility of creating an artificial brain.

Memristor-based electronic synapses for neural networks

Caption: Neuron connections in biological neural networks. Credit: MIPT press office

Caption: Neuron connections in biological neural networks. Credit: MIPT press office

Russian scientists have recently published a paper about neural networks and electronic synapses based on ‘thin film’ memristors according to an April 19, 2016 news item on Nanowerk,

A team of scientists from the Moscow Institute of Physics and Technology (MIPT) have created prototypes of “electronic synapses” based on ultra-thin films of hafnium oxide (HfO2). These prototypes could potentially be used in fundamentally new computing systems.

An April 20, 2016 MIPT press release (also on EurekAlert), which originated the news item (the date inconsistency likely due to timezone differences) explains the connection between thin films and memristors,

The group of researchers from MIPT have made HfO2-based memristors measuring just 40×40 nm2. The nanostructures they built exhibit properties similar to biological synapses. Using newly developed technology, the memristors were integrated in matrices: in the future this technology may be used to design computers that function similar to biological neural networks.

Memristors (resistors with memory) are devices that are able to change their state (conductivity) depending on the charge passing through them, and they therefore have a memory of their “history”. In this study, the scientists used devices based on thin-film hafnium oxide, a material that is already used in the production of modern processors. This means that this new lab technology could, if required, easily be used in industrial processes.

“In a simpler version, memristors are promising binary non-volatile memory cells, in which information is written by switching the electric resistance – from high to low and back again. What we are trying to demonstrate are much more complex functions of memristors – that they behave similar to biological synapses,” said Yury Matveyev, the corresponding author of the paper, and senior researcher of MIPT’s Laboratory of Functional Materials and Devices for Nanoelectronics, commenting on the study.

The press release offers a description of biological synapses and their relationship to learning and memory,

A synapse is point of connection between neurons, the main function of which is to transmit a signal (a spike – a particular type of signal, see fig. 2) from one neuron to another. Each neuron may have thousands of synapses, i.e. connect with a large number of other neurons. This means that information can be processed in parallel, rather than sequentially (as in modern computers). This is the reason why “living” neural networks are so immensely effective both in terms of speed and energy consumption in solving large range of tasks, such as image / voice recognition, etc.

Over time, synapses may change their “weight”, i.e. their ability to transmit a signal. This property is believed to be the key to understanding the learning and memory functions of thebrain.

From the physical point of view, synaptic “memory” and “learning” in the brain can be interpreted as follows: the neural connection possesses a certain “conductivity”, which is determined by the previous “history” of signals that have passed through the connection. If a synapse transmits a signal from one neuron to another, we can say that it has high “conductivity”, and if it does not, we say it has low “conductivity”. However, synapses do not simply function in on/off mode; they can have any intermediate “weight” (intermediate conductivity value). Accordingly, if we want to simulate them using certain devices, these devices will also have to have analogous characteristics.

The researchers have provided an illustration of a biological synapse,

Fig.2 The type of electrical signal transmitted by neurons (a “spike”). The red lines are various other biological signals, the black line is the averaged signal. Source: MIPT press office

Fig.2 The type of electrical signal transmitted by neurons (a “spike”). The red lines are various other biological signals, the black line is the averaged signal. Source: MIPT press office

Now, the press release ties the memristor information together with the biological synapse information to describe the new work at the MIPT,

As in a biological synapse, the value of the electrical conductivity of a memristor is the result of its previous “life” – from the moment it was made.

There is a number of physical effects that can be exploited to design memristors. In this study, the authors used devices based on ultrathin-film hafnium oxide, which exhibit the effect of soft (reversible) electrical breakdown under an applied external electric field. Most often, these devices use only two different states encoding logic zero and one. However, in order to simulate biological synapses, a continuous spectrum of conductivities had to be used in the devices.

“The detailed physical mechanism behind the function of the memristors in question is still debated. However, the qualitative model is as follows: in the metal–ultrathin oxide–metal structure, charged point defects, such as vacancies of oxygen atoms, are formed and move around in the oxide layer when exposed to an electric field. It is these defects that are responsible for the reversible change in the conductivity of the oxide layer,” says the co-author of the paper and researcher of MIPT’s Laboratory of Functional Materials and Devices for Nanoelectronics, Sergey Zakharchenko.

The authors used the newly developed “analogue” memristors to model various learning mechanisms (“plasticity”) of biological synapses. In particular, this involved functions such as long-term potentiation (LTP) or long-term depression (LTD) of a connection between two neurons. It is generally accepted that these functions are the underlying mechanisms of  memory in the brain.

The authors also succeeded in demonstrating a more complex mechanism – spike-timing-dependent plasticity, i.e. the dependence of the value of the connection between neurons on the relative time taken for them to be “triggered”. It had previously been shown that this mechanism is responsible for associative learning – the ability of the brain to find connections between different events.

To demonstrate this function in their memristor devices, the authors purposefully used an electric signal which reproduced, as far as possible, the signals in living neurons, and they obtained a dependency very similar to those observed in living synapses (see fig. 3).

Fig.3. The change in conductivity of memristors depending on the temporal separation between "spikes"(rigth) and thr change in potential of the neuron connections in biological neural networks. Source: MIPT press office

Fig.3. The change in conductivity of memristors depending on the temporal separation between “spikes”(rigth) and thr change in potential of the neuron connections in biological neural networks. Source: MIPT press office

These results allowed the authors to confirm that the elements that they had developed could be considered a prototype of the “electronic synapse”, which could be used as a basis for the hardware implementation of artificial neural networks.

“We have created a baseline matrix of nanoscale memristors demonstrating the properties of biological synapses. Thanks to this research, we are now one step closer to building an artificial neural network. It may only be the very simplest of networks, but it is nevertheless a hardware prototype,” said the head of MIPT’s Laboratory of Functional Materials and Devices for Nanoelectronics, Andrey Zenkevich.

Here’s a link to and a citation for the paper,

Crossbar Nanoscale HfO2-Based Electronic Synapses by Yury Matveyev, Roman Kirtaev, Alena Fetisova, Sergey Zakharchenko, Dmitry Negrov and Andrey Zenkevich. Nanoscale Research Letters201611:147 DOI: 10.1186/s11671-016-1360-6

Published: 15 March 2016

This is an open access paper.

Graphene Flagship high points

The European Union’s Graphene Flagship project has provided a series of highlights in place of an overview for the project’s ramp-up phase (in 2013 the Graphene Flagship was announced as one of two winners of a science competition, the other winner was the Human Brain Project, with two prizes of 1B Euros for each project). Here are the highlights from the April 19, 2016 Graphene Flagship press release,

Graphene and Neurons – the Best of Friends

Flagship researchers have shown that it is possible to interface untreated graphene with neuron cells whilst maintaining the integrity of these vital cells [1]. This result is a significant first step towards using graphene to produce better deep brain implants which can both harness and control the brain.

Graphene and Neurons
 

This paper emerged from the Graphene Flagship Work Package Health and Environment. Prof. Prato, the WP leader from the University of Trieste in Italy, commented that “We are currently involved in frontline research in graphene technology towards biomedical applications, exploring the interactions between graphene nano- and micro-sheets with the sophisticated signalling machinery of nerve cells. Our work is a first step in that direction.”

[1] Fabbro A., et al., Graphene-Based Interfaces do not Alter Target Nerve Cells. ACS Nano, 10 (1), 615 (2016).

Pressure Sensing with Graphene: Quite a Squeeze

The Graphene Flagship developed a small, robust, highly efficient squeeze film pressure sensor [2]. Pressure sensors are present in most mobile handsets and by replacing current sensor membranes with a graphene membrane they allow the sensor to decrease in size and significantly increase its responsiveness and lifetime.

Discussing this work which emerged from the Graphene Flagship Work Package Sensors is the paper’s lead author, Robin Dolleman from the Technical University of Delft in The Netherlands “After spending a year modelling various systems the idea of the squeeze-film pressure sensor was formed. Funding from the Graphene Flagship provided the opportunity to perform the experiments and we obtained very good results. We built a squeeze-film pressure sensor from 31 layers of graphene, which showed a 45 times higher response than silicon based devices, while reducing the area of the device by a factor of 25. Currently, our work is focused on obtaining similar results on monolayer graphene.”

 

[2] Dolleman R. J. et al., Graphene Squeeze-Film Pressure Sensors. Nano Lett., 16, 568 (2016)

Frictionless Graphene


Image caption: A graphene nanoribbon was anchored at the tip of a atomic force microscope and dragged over a gold surface. The observed friction force was extremely low.

Image caption: A graphene nanoribbon was anchored at the tip of a atomic force microscope and dragged over a gold surface. The observed friction force was extremely low.

Research done within the Graphene Flagship, has observed the onset of superlubricity in graphene nanoribbons sliding on a surface, unravelling the role played by ribbon size and elasticity [3]. This important finding opens up the development potential of nanographene frictionless coatings. This research lead by the Graphene Flagship Work Package Nanocomposites also involved researchers from Work Package Materials and Work Package Health and the Environment, a shining example of the inter-disciplinary, cross-collaborative approach to research undertaken within the Graphene Flagship. Discussing this further is the Work Package Nanocomposites Leader, Dr Vincenzo Palermo from CNR National Research Council, Italy “Strengthening the collaboration and interactions with other Flagship Work Packages created added value through a strong exchange of materials, samples and information”.

[3] Kawai S., et al., Superlubricity of graphene nanoribbons on gold surfaces. Science. 351, 6276, 957 (2016) 

​Graphene Paddles Forward

Work undertaken within the Graphene Flagship saw Spanish automotive interiors specialist, and Flagship partner, Grupo Antolin SA work in collaboration with Roman Kayaks to develop an innovative kayak that incorporates graphene into its thermoset polymeric matrices. The use of graphene and related materials results in a significant increase in both impact strength and stiffness, improving the resistance to breakage in critical areas of the boat. Pushing the graphene canoe well beyond the prototype demonstration bubble, Roman Kayaks chose to use the K-1 kayak in the Canoe Marathon World Championships held in September in Gyor, Hungary where the Graphene Canoe was really put through its paces.

Talking further about this collaboration from the Graphene Flagship Work Package Production is the WP leader, Dr Ken Teo from Aixtron Ltd., UK “In the Graphene Flagship project, Work Package Production works as a technology enabler for real-world applications. Here we show the worlds first K-1 kayak (5.2 meters long), using graphene related materials developed by Grupo Antolin. We are very happy to see that graphene is creating value beyond traditional industries.” 

​Graphene Production – a Kitchen Sink Approach

Researchers from the Graphene Flagship have devised a way of producing large quantities of graphene by separating graphite flakes in liquids with a rotating tool that works in much the same way as a kitchen blender [4]. This paves the way to mass production of high quality graphene at a low cost.

The method was produced within the Graphene Flagship Work Package Production and is talked about further here by the WP deputy leader, Prof. Jonathan Coleman from Trinity College Dublin, Ireland “This technique produced graphene at higher rates than most other methods, and produced sheets of 2D materials that will be useful in a range of applications, from printed electronics to energy generation.” 

[4] Paton K.R., et al., Scalable production of large quantities of defect-free few-layer graphene by shear exfoliation in liquids. Nat. Mater. 13, 624 (2014).

Flexible Displays – Rolled Up in your Pocket

Working with researchers from the Graphene Flagship the Flagship partner, FlexEnable, demonstrated the world’s first flexible display with graphene incorporated into its pixel backplane. Combined with an electrophoretic imaging film, the result is a low-power, durable display suitable for use in many and varied environments.

Emerging from the Graphene Flagship Work Package Flexible Electronics this illustrates the power of collaboration.  Talking about this is the WP leader Dr Henrik Sandberg from the VTT Technical Research Centre of Finland Ltd., Finland “Here we show the power of collaboration. To deliver these flexible demonstrators and prototypes we have seen materials experts working together with components manufacturers and system integrators. These devices will have a potential impact in several emerging fields such as wearables and the Internet of Things.”

​Fibre-Optics Data Boost from Graphene

A team of researches from the Graphene Flagship have demonstrated high-performance photo detectors for infrared fibre-optic communication systems based on wafer-scale graphene [5]. This can increase the amount of information transferred whilst at the same time make the devises smaller and more cost effective.

Discussing this work which emerged from the Graphene Flagship Work Package Optoelectronics is the paper’s lead author, Daniel Schall from AMO, Germany “Graphene has outstanding properties when it comes to the mobility of its electric charge carriers, and this can increase the speed at which electronic devices operate.”

[5] Schall D., et al., 50 GBit/s Photodetectors Based on Wafer-Scale Graphene for Integrated Silicon Photonic Communication Systems. ACS Photonics. 1 (9), 781 (2014)

​Rechargeable Batteries with Graphene

A number of different research groups within the Graphene Flagship are working on rechargeable batteries. One group has developed a graphene-based rechargeable battery of the lithium-ion type used in portable electronic devices [6]. Graphene is incorporated into the battery anode in the form of a spreadable ink containing a suspension of graphene nanoflakes giving an increased energy efficiency of 20%. A second group of researchers have demonstrated a lithium-oxygen battery with high energy density, efficiency and stability [7]. They produced a device with over 90% efficiency that may be recharged more than 2,000 times. Their lithium-oxygen cell features a porous, ‘fluffy’ electrode made from graphene together with additives that alter the chemical reactions at work in the battery.

Graphene Flagship researchers show how the 2D material graphene can improve the energy capacity, efficiency and stability of lithium-oxygen batteries.

Both devices were developed in different groups within the Graphene Flagship Work Package Energy and speaking of the technology further is Prof. Clare Grey from Cambridge University, UK “What we’ve achieved is a significant advance for this technology, and suggests whole new areas for research – we haven’t solved all the problems inherent to this chemistry, but our results do show routes forward towards a practical device”.

[6] Liu T., et al. Cycling Li-O2 batteries via LiOH formation and decomposition. Science. 350, 6260, 530 (2015)

[7] Hassoun J., et al., An Advanced Lithium-Ion Battery Based on a Graphene Anode and a Lithium Iron Phosphate Cathode. Nano Lett., 14 (8), 4901 (2014)

Graphene – What and Why?

Graphene is a two-dimensional material formed by a single atom-thick layer of carbon, with the carbon atoms arranged in a honeycomb-like lattice. This transparent, flexible material has a number of unique properties. For example, it is 100 times stronger than steel, and conducts electricity and heat with great efficiency.

A number of practical applications for graphene are currently being developed. These include flexible and wearable electronics and antennas, sensors, optoelectronics and data communication systems, medical and bioengineering technologies, filtration, super-strong composites, photovoltaics and energy storage.

Graphene and Beyond

The Graphene Flagship also covers other layered materials, as well as hybrids formed by combining graphene with these complementary materials, or with other materials and structures, ranging from polymers, to metals, cement, and traditional semiconductors such as silicon. Graphene is just the first of thousands of possible single layer materials. The Flagship plans to accelerate their journey from laboratory to factory floor.

Especially exciting is the possibility of stacking monolayers of different elements to create materials not found in nature, with properties tailored for specific applications. Such composite layered materials could be combined with other nanomaterials, such as metal nanoparticles, in order to further enhance their properties and uses.​

Graphene – the Fruit of European Scientific Excellence

Europe, North America and Asia are all active centres of graphene R&D, but Europe has special claim to be at the centre of this activity. The ground-breaking experiments on graphene recognised in the award of the 2010 Nobel Prize in Physics were conducted by European physicists, Andre Geim and Konstantin Novoselov, both at Manchester University. Since then, graphene research in Europe has continued apace, with major public funding for specialist centres, and the stimulation of academic-industrial partnerships devoted to graphene and related materials. It is European scientists and engineers who as part of the Graphene Flagship are closely coordinating research efforts, and accelerating the transfer of layered materials from the laboratory to factory floor.

For anyone who would like links to the published papers, you can check out an April 20, 2016 news item featuring the Graphene Flagship highlights on Nanowerk.