3-D Printer Can Build Synthetic Tissues

3-D Printer Can Build Synthetic Tissues

  4:26:00 PM    Science Lover

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A custom-built programmable 3D printer can create materials with several of the properties of living tissues, Oxford University scientists have demonstrated.

A custom-built programmable 3D printer can create materials with several of the properties of living tissues, Oxford University scientists have demonstrated: Droplet network c.500 microns across with electrically conductive pathway between electrodes mimicking nerve. (Credit: Oxford University/G Villar)

The new type of material consists of thousands of connected water droplets, encapsulated within lipid films, which can perform some of the functions of the cells inside our bodies.

These printed 'droplet networks' could be the building blocks of a new kind of technology for delivering drugs to places where they are needed and potentially one day replacing or interfacing with damaged human tissues. Because droplet networks are entirely synthetic, have no genome and do not replicate, they avoid some of the problems associated with other approaches to creating artificial tissues -- such as those that use stem cells.

The team report their findings in this week's Science.

'We aren't trying to make materials that faithfully resemble tissues but rather structures that can carry out the functions of tissues,' said Professor Hagan Bayley of Oxford University's Department of Chemistry, who led the research. 'We've shown that it is possible to create networks of tens of thousands connected droplets. The droplets can be printed with protein pores to form pathways through the network that mimic nerves and are able to transmit electrical signals from one side of a network to the other.'

Each droplet is an aqueous compartment about 50 microns in diameter. Although this is around five times larger than living cells the researchers believe there is no reason why they could not be made smaller. The networks remain stable for weeks.

'Conventional 3D printers aren't up to the job of creating these droplet networks, so we custom built one in our Oxford lab to do it,' said Professor Bayley. 'At the moment we've created networks of up to 35,000 droplets but the size of network we can make is really only limited by time and money. For our experiments we used two different types of droplet, but there's no reason why you couldn't use 50 or more different kinds.'

The unique 3D printer was built by Gabriel Villar, a DPhil student in Professor Bayley's group and the lead author of the paper.

The droplet networks can be designed to fold themselves into different shapes after printing -- so, for example, a flat shape that resembles the petals of a flower is 'programmed' to fold itself into a hollow ball, which cannot be obtained by direct printing. The folding, which resembles muscle movement, is powered by osmolarity differences that generate water transfer between droplets.

Gabriel Villar of Oxford University's Department of Chemistry said: 'We have created a scalable way of producing a new type of soft material. The printed structures could in principle employ much of the biological machinery that enables the sophisticated behaviour of living cells and tissues.'

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Visual Searches: Human Brain Beats Computers

Visual Searches: Human Brain Beats Computers

  8:48:00 PM    Science Lover

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You're headed out the door and you realize you don't have your car keys. After a few minutes of rifling through pockets, checking the seat cushions and scanning the coffee table, you find the familiar key ring and off you go. Easy enough, right? What you might not know is that the task that took you a couple seconds to complete is a task that computers -- despite decades of advancement and intricate calculations -- still can't perform as efficiently as humans: the visual search.

Part of the research team in front of the Magnetic Resonance Imaging (MRI) device at the UCSB Brain Imaging Center From left to right : Researcher Tim Preston; Associate Professor of Psychological & Brain Sciences Barry Giesbrecht; and Professor of Psychological & Brain Sciences Miguel P. Eckstein. Not pictured: Koel Das, now a faculty member at the Indian Institute of Science in Bangalore, Karnatka, India; and lead author Fei Guo, now in the software industry. (Credit: Image courtesy of University of California - Santa Barbara)

"Our daily lives are composed of little searches that are constantly changing, depending on what we need to do," said Miguel Eckstein, UC Santa Barbara professor of psychological and brain sciences and co-author of the recently released paper "Feature-Independent Neural Coding of Target Detection during Search of Natural Scenes," published in the Journal of Neuroscience. "So the idea is, where does that take place in the brain?"

A large part of the human brain is dedicated to vision, with different parts involved in processing the many visual properties of the world. Some parts are stimulated by color, others by motion, yet others by shape.

However, those parts of the brain tell only a part of the story. What Eckstein and co-authors wanted to determine was how we decide whether the target object we are looking for is actually in the scene, how difficult the search is, and how we know we've found what we wanted.

They found their answers in the dorsal frontoparietal network, a region of the brain that roughly corresponds to the top of one's head, and is also associated with properties such as attention and eye movements. In the parts of the human brain used earlier in the processing stream, regions stimulated by specific features like color, motion, and direction are a major part of the search. However, in the dorsal frontoparietal network, activity is not confined to any specific features of the object.

"It's flexible," said Eckstein. Using 18 observers, an MRI machine, and hundreds of photos of scenes flashed before the observers with instructions to look for certain items, the scientists monitored their subjects' brain activity. By watching the intraparietal sulcus (IPS), located within the dorsal frontoparietal network, the researchers were able to note not only whether their subjects found the objects, but also how confident they were in their finds.

The IPS region would be stimulated even if the object was not there, said Eckstein, but the pattern of activity would not be the same as it would had the object actually existed in the scene. The pattern of activity was consistent, even though the 368 different objects the subjects searched for were defined by very different visual features. This, Eckstein said, indicates that IPS did not rely on the presence of any fixed feature to determine the presence or absence of various objects. Other visual regions did not show this consistent pattern of activity across objects.

"As you go further up in processing, the neurons are less interested in a specific feature, but they're more interested in whatever is behaviorally relevant to you at the moment," said Eckstein. Thus, a search for an apple, for instance, would make red, green, and rounded shapes relevant. If the search was for your car keys, the interparietal sulcus would now be interested in gold, silver, and key-type shapes and not interested in green, red, and rounded shapes.

"For visual search to be efficient, we want those visual features related to what we are looking for to elicit strong responses in our brain and not others that are not related to our search, and are distracting," Eckstein added. "Our results suggest that this is what is achieved in the intraparietal sulcus, and allows for efficient visual search."

For Eckstein and colleagues, these findings are just the tip of the iceberg. Future research will dig more deeply into the seemingly simple yet essential ability of humans to do a visual search and how they can use the layout of a scene to guide their search.

"What we're trying to really understand is what other mechanisms or strategies the brain has to make searches efficient and easy," said Eckstein. "What part of the brain is doing that?"

Research on this study was also conducted by Tim Preston, Koel Das, Barry Giesbrecht, and first author Fei Guo, all from UC Santa Barbara.

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Electronic 'Nose' Can Predict Pleasantness of Novel Odors

Electronic 'Nose' Can Predict Pleasantness of Novel Odors

  8:35:00 PM    Science Lover

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Weizmann Institute scientists have 'trained' an electronic system to be able to predict the pleasantness of novel odors, just like a human would perceive them -- turning the popular notion that smell is completely personal and culture-specific on its head. In research published in PLoS Computational Biology, the scientists argue that the perception of an odor's pleasantness is innately hard-wired to its molecular structure, and it is only within specific contexts that personal or cultural differences are made apparent.

Scientists have 'trained' an electronic system to
be able to predict the pleasantness of novel odors, 
just like a human would perceive them. 
(Credit: iStockphoto/Sharon Dominick)

These findings have important implications for automated environmental toxicity and malodor monitoring, fast odor screening in the perfume industry, and provide a critical building block for the Holy Grail of sense technology -- transmitting scent digitally.

Over the last decade, electronic devices, commonly known as electronic noses or 'eNoses,' have been developed to be able to detect and recognize odors. The main component of an eNose is an array of chemical sensors. As an odor passes through the eNose, its molecular features stimulate the sensors in such a way as to produce a unique electrical pattern -- an 'odor fingerprint' -- that characterizes that specific odor. Like a sniffer dog, an eNose first needs to be trained with odor samples so as to build a database of reference. Then the instrument can recognize new samples of those odors by comparing the odor's fingerprint to those contained in its database.

But unlike humans, if eNoses are presented with a novel odor whose fingerprint has not already been recorded in their database, they are unable to classify or recognize it.

So a team of Weizmann scientists, led by Dr. Rafi Haddad, then a graduate student of Prof. Noam Sobel of the Neurobiology Department and co-supervisor Prof. David Harel of the Computer Science and Applied Mathematics Department, together with their colleague Abebe Medhanie of the Neurobiology Department, and Dr. Yehudah Roth of the Edith Wolfson Medical Center, Holon, decided to approach this issue from a different perspective. Rather than train an eNose to recognize a particular odor, they trained it to estimate the odor along a particular perceptual axis. The axis they chose was odorant pleasantness. In other words, they trained their eNose to predict whether an odor would be perceived as pleasant or unpleasant, or anywhere in between.

To achieve this, the scientists first asked a group of native Israelis to rate the pleasantness of a selection of odors according to a 30-point scale ranging from 'very pleasant' to 'very unpleasant.' From this dataset, they developed an 'odor pleasantness' algorithm, which they then programmed into the eNose. The scientists then got the eNose to predict the pleasantness of a completely new set of odors not contained in their database against the ratings provided by a completely different group of native Israelis. The scientists found that the eNose was able to generalize and rate the pleasantness of novel odors it never smelled before, and these ratings were about 80% similar to those of naive human raters who had not participated in the eNose training phase. Moreover, if the odors were simply categorized as either 'pleasant' or 'unpleasant,' as opposed to being rated on a scale, it achieved an accuracy of 99%.

But these findings still don't determine whether olfactory perception is culture-specific or not. With this in mind, the scientists decided to test eNose predictions against a group of recent immigrants to Israel from Ethiopia. The results showed that the eNose's ability to predict the pleasantness of novel odors against the native Ethipoians' ratings was just as good, even though it was 'tuned' to the pleasantness of odors as perceived by native Israelis. In other words, even though different odors have different meanings across cultures, the eNose performed equally well across these populations. This suggests a fundamental cross-cultural similarity in odorant pleasantness.

Sobel comments: "Being able to predict whether a person who we never tested before would like a specific odorant, no matter their cultural background, provides evidence that odor pleasantness is a fundamental biological property, and that certain aspects of molecular structure are what determine whether an odor is pleasant or not.' So how are cultural differences accounted for? 'We believe that culture influences the perception of olfactory pleasantness mostly in particular contexts. To stress this point, many may wonder how the French can like the smell of their cheese, when most find the smell quite repulsive. We believe that it is not that the French think the smell is pleasant per se, they merely think it is a sign of good cheese. However, if the smell was presented out of context in a jar, then the French would probably rate the odor just as unpleasant as anyone else would."

The scientists' findings that odor perception is hard-wired to molecular structure and their design of an eNose that is able to classify new odors could provide new methods for odor screening and environmental monitoring, and may, in the future, allow for the digital transmission of smell to scent-enable movies, games and music to provide a more immersive and captivating experience.

Prof. Noam Sobel's research is supported by the Nella and Leon Benoziyo Center for Neurosciences; the J&R Foundation; and Regina Wachter, New York. This research was funded by an FP7 grant from the European Research Council awarded to Noam Sobel.

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Computer Algorithm Able to 'Read' Memories

Computer Algorithm Able to 'Read' Memories

  9:58:00 PM    Science Lover

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Computer programs have been able to predict which of three short films a person is thinking about, just by looking at their brain activity. The research, conducted by scientists at the Wellcome Trust Centre for Neuroimaging at UCL (University College London), provides further insight into how our memories are recorded.

To explore how memories are recorded, researchers showed volunteers three short films and asked them to memorize what they saw. The films were very simple, sharing a number of similar features -- all included a woman carrying out an everyday task in a typical urban street, and each film was the same length, seven seconds long. For example, one film showed a woman posting a letter. (Credit: Wellcome Trust Centre for Neuroimaging at UCL)

Professor Eleanor Maguire led this Wellcome Trust-funded study, an extension of work published last year which showed how spatial memories -- in that case, where a volunteer was standing in a virtual reality room -- are recorded in regular patterns of activity in the hippocampus, the area of the brain responsible for learning and memory.

"In our previous experiment, we were looking at basic memories, at someone's location in an environment," says Professor Maguire. "What is more interesting is to look at 'episodic' memories -- the complex, everyday memories that include much more information on where we are, what we are doing and how we feel."

To explore how such memories are recorded, the researchers showed ten volunteers three short films and asked them to memorise what they saw. The films were very simple, sharing a number of similar features -- all included a woman carrying out an everyday task in a typical urban street, and each film was the same length, seven seconds long. For example, one film showed a woman drinking coffee from a paper cup in the street before discarding the cup in a litter bin; another film showed a (different) woman posting a letter.

The volunteers were then asked to recall each of the films in turn whilst inside an fMRI scanner, which records brain activity by measuring changes in blood flow within the brain.

A computer algorithm then studied the patterns and had to identify which film the volunteer was recalling purely by looking at the pattern of their brain activity. The results are published in the journal Current Biology.

"The algorithm was able to predict correctly which of the three films the volunteer was recalling significantly above what would be expected by chance," explains Martin Chadwick, lead author of the study. "This suggests that our memories are recorded in a regular pattern."

Although a whole network of brain areas support memory, the researchers focused their study on the medial temporal lobe, an area deep within the brain believed to be most heavily involved in episodic memory. It includes the hippocampus -- an area which Professor Maguire and colleagues have studied extensively in the past.

They found that the key areas involved in recording the memories were the hippocampus and its immediate neighbours. However, the computer algorithm performed best when analysing activity in the hippocampus itself, suggesting that this is the most important region for recording episodic memories. In particular, three areas of the hippocampus -- the rear right and the front left and front right areas -- seemed to be involved consistently across all participants. The rear right area had been implicated in the earlier study, further enforcing the idea that this is where spatial information is recorded. However, it is still not clear what role the front two regions play.

"Now that we are developing a clearer picture of how our memories are stored, we hope to examine how they are affected by time, the ageing process and by brain injury," says Professor Maguire.

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Nanoscale Origami From DNA

Nanoscale Origami From DNA

  7:52:00 PM    Science Lover

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Scientists at the Technische Universitaet Muenchen (TUM) and Harvard University have thrown the lid off a new toolbox for building nanoscale structures out of DNA, with complex twisting and curving shapes. In the August 7 issue of the journal Science, they report a series of experiments in which they folded DNA, origami-like, into three dimensional objects including a beachball-shaped wireframe capsule just 50 nanometers in diameter.

Scientists at the Technische Universitaet Muenchen and Harvard University have thrown the lid off a new toolbox for building nanoscale structures out of DNA, with complex twisting and curving shapes. They report a series of experiments in which they folded DNA, origami-like, into 3-D objects including a beach ball-shaped wireframe capsule just 50 nanometers in diameter. (Credit: Used by permission of H. Dietz, TUM Dept. of Physics, all rights reserved.)

"Our goal was to find out whether we could program DNA to assemble into shapes that exhibit custom curvature or twist, with features just a few nanometers wide," says biophysicist Hendrik Dietz, a professor at the Technische Universitaet Muenchen. Dietz's collaborators in these experiments were Professor William Shih and Dr. Shawn Douglas of Harvard University. "It worked," he says, "and we can now build a diversity of three-dimensional nanoscale machine parts, such as round gears or curved tubes or capsules. Assembling those parts into bigger, more complex and functional devices should be possible."

As a medium for nanoscale engineering, DNA has the dual advantages of being a smart material – not only tough and flexible but also programmable – and being very well characterized by decades of study. Basic tools that Dietz, Douglas, and Shih employ are programmable self-assembly – directing DNA strands to form custom-shaped bundles of cross-linked double helices – and targeted insertions or deletions of base pairs that can give such bundles a desired twist or curve. Right-handed or left-handed twisting can be specified. They report achieving precise, quantitative control of these shapes, with a radius of curvature as tight as 6 nanometers.

The toolbox they have developed includes a graphical software program that helps to translate specific design concepts into the DNA programming required to realize them. Three-dimensional shapes are produced by "tuning" the number, arrangement, and lengths of helices.

In their current paper, the researchers present a wide variety of nanoscale structures and describe in detail how they designed, formed, and verified them. "Many advanced macroscopic machines require curiously shaped parts in order to function," Dietz says, "and we have the tools to make them. But we currently cannot build something intricate such as an ant's leg or, much smaller, a ten-nanometer-small chemical plant such as a protein enzyme. We expect many benefits if only we could build super-miniaturized devices on the nanoscale using materials that work robustly in the cells of our bodies – biomolecules such as DNA."

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