Science Weekly: When plants bite back

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Plants get aggressive in the Royal Institution’s Christmas lectures; and the astronaut’s cookbook

Dear Bloggers, we will be on vacation from December 25, 2009 to January 3, 2010, and will resume on Monday, January 4, 2010.

Have a Wonderful Holiday and a Happy New Year………………this next decade of 2010 will be a very big deal for all of us!


We wanted to share with you some of the photos from our recent THI Annual Holiday Party.























The scientists at GE Global Research have made it a tradition each year to showcase the latest and greatest technology developments during the holiday season. Last year, the team flipped the switch on the first-ever OLED Christmas tree using GE’s bendable, paper-thin lights. This year they figured out a way to top it – and stay on Santa’s good list – by dreaming up a futuristic new sleigh featuring 10 real Global Research technologies that reached key milestones in 2009. “After all, we do have cool technology that could make Santa’s life a lot easier,” writes physical chemist Anil Duggal on GE’s research blog. Just click on the 3-D sleigh to get details on the new features – from lightweight carbon fiber composites for the frame, to icephobic coatings, to a wireless medical sensor for Santa to make sure he’s still his jolly old self at 30,000 feet!


The Best Robots Of 2009!, January 2010 — 2009 has been an amazing year in the world of robots and Singularity Hub is here to tell you all about it! Thats right, its time to unveil our second annual roundup of the best robots of the year. In 2009 robots continued their advance towards world domination with several impressive breakouts in areas such as walking, automation, and agility, while still lacking in adaptability and reasoning ability. It will be several years until robots can gain the artificial intelligence that will truly make them remarkable, but in the meantime they are still pretty awesome. If you haven’t seen it yet you won’t want to miss our best robots of 2008 story from last year, but now lets not delay any further and get on with the best robots of 2009:

Industrial/Manufacturing Robots

Nextage, the latest humanoid robot from Kawada, and the Motoman SDA 10 both put on impressive manufacturing demonstrations this year in the videos below. When watching the videos it is easy to see why factory workers should be terrified for their job security. The robots demonstrate agility with their hands, the ability to work together, and the ability to divide portions of a complex task amongst themselves. As with all robots these days, these humanoid manufacturing robots are superior to humans in strength, endurance, and dependability, but seem ill equipped to adapt to changing situations that have not been anticipated ahead of time. And yet the path is clear – these robots will get even more capable and adaptable with each passing year. Factory workers look out!

Of course for most industrial applications humanoid robots are not needed. In these cases the humans aren’t losing their jobs…they have already lost them. Across the globe humans have been replaced and improved with countless incredible robots that are designed to perform one type of task with repetition and speed that is simply beyond human. One of our favorite examples of robotic manufacturing prowess is in the task of sorting and moving all manner of objects, from pancakes, to sausages, to screws and bolts. The flexpicker is one of our favorites in this category. Check it out:

The flexpicker is not the only player in the sorting game, nor is it even the undisputed champ. Late in 2009 Adept Technology claimed that its Quattro s650 was the world’s fastest sorting/packing robot on the planet. Watch this workhorse in action below:

When it comes to industrial robots, it isn’t always about speed. Sometimes the name of the game is agility, range of motion, and versatility. In such cases, the 2009 debut of ABB’s IRB120 was a powerful entrant to the field, offering the versatility of a human arm, but with the strength and endurance for repetition that we expect from robots. The IRB120 is “ABB’s smallest ever multipurpose industrial robot weighing just 25kg and capable of handling a payload of 3kg (4kg for vertical wrist) with a reach of 580mm.” See this robotic wonder below:

Lest you think industrial robots are destined to remain hidden behind the relatively closed doors of manufacturing facilities, witness perhaps my favorite robot demonstration of the year – robotic chefs in a Japanese raman noodle restaurant! The robots are fully autonomous, taking a customer order and cooking it from start to finish. This includes boiling the noodles, pouring broth, adding spices and toppings, and so on. The orders are complex too, requiring the robots to take customer preference for amount and type of sauce, salt, noodle, and so on. The finished product is handed off to a human server who brings the food to the customer’s table. The irony could not be more real as we witness the lowly human in the role of a mere server while the robot takes on the cooking:

With such awesome capabilities in tow, we shouldn’t be surprised that these robots (or at least their human creators) exhibit an urge to show off from time to time. In October 2009 ABB Robotics stunned us with its “Fanta Challenges” where ABB robots move metal rods in between six packs of Fanta soda cans at a blistering pace with only 1 millimeter of clearance between the metal rod and the cans. The feat would already be impressive if the 6 pack of cans was stationary, but then ABB ups the ante by putting the cans on a tray and programming another robot to rapidly move the tray around. Don’t miss the video below:

Humanoid Robots

In the world of humanoid robots, 2009 was a bumper year with some outstanding demonstrations from multiple efforts around the world. By far our favorite humanoid demonstration of the year comes from robotic phenom Boston Robotics and its latest robot dubbed Petman. In the video below, watch in awe as the humanoid Petman robot conquers the treadmill in classic human style:

Right on the heels of Petman was the Dexter humanoid robot from Anybots, just up the street from Hub Headquarters in Silicon Valley. Dexter can remain stable on its two legs as it jumps, walks, and is even kicked by nearby human. Pretty sweet:

A surprising entrant into the humanoid robot field this year came from Toyota as part of its now multi-year partner robot effort. The Toyota robot to our knowledge is the fastest large scale humanoid robot on the planet right now with an ability to run at an impressive 7 Km/hr (4 mph). Check out this running humanoid in action below:

Willow Garage made waves in the world of humanoid robots, not just for creating a robot, but more importantly for creating an open source platform upon which the entire world can build robots of the future. In 2009 Willow Garage announced that it had achieved its second major milestone: getting a robot to navigate it’s way around their labs, identifying and plugging itself into electrical outlets. The Personal Robot mark 2 (PR2) wandered around the labs, opening doors, and plugging in to 9 different outlets and identifying one that was unreachable. See below:

Although most of the robots we cover seem to come from Japan and the US, Europe held its own this year with progress from their Justin humanoid robot program. Justin is a collaboration between the University of Napoli and the German Space Agency, DLR under a European project called Physical Human-Robot Interaction: Dependability and Safety. The Justin robot features software algorithms that allows the hands and arms to dynamically react to their environment and to each other to avoid collision and complete tasks:

The ASIMO robot has consistently been a perennial player in the humanoid robotics genre, and 2009 was not exception. At Carnegie Mellon, researchers were able to teach ASIMO to dynamically navigate around cut out shapes that represented real-world barriers. Able to dodge spinning blades, Frogger-like moving lines, and dynamic environments, ASIMO showed us again why its one of the top humanoid bots out there:

Random Other Awesome Robots

The Blob Bot from iRobot defnitely stacks up as one of the more interesting robots of the year. Keeping in tune with several scifi visions from past and present, the blob bot is a first generation attempt at creating a robot that can morph itself to slip through cracks or even resemble other objects. The blob bot is built of a shell of many jammable silicone sacs with a central fluid reservoir in the center. By controlling pressure in each sac and the center reservoir, the blob can expand and contract in order to change shape and flop around. This robot is nowhere near to becoming anything more than a novel prototype for now, but still it deserves an honorable mention for breaking some exciting ground. A true solution to this type of robot will likely use some sort of nanotechnology, and would thus appear to be decades away from realization:

Another interesting robot this year was the DASH robot from UC Berkeley. DASH or Dynamic Autonomous Sprawled Hexapod is a six legged robot made from cardboard and polymer. It’s the size of your open hand, weighs just 16 grams, can run up to 1.5 m/s, and survives falls of 28 meters without damage! This cockroach bot is really something to behold:

The stickybot from Stanford has been around for a number of years, but in 2009 the gecko inspired wall climbing robot underwent its third revision and is now more capable than ever. The robot looks almost exactly like a gecko and the adhesive on its padded feet are derived from the tiny hairs the lizards use to cling. The dry adhesive technique uses micro-hairs and intramolecular (van der waals) forces to stick bot to wall.

iRobot impressed us earlier this year with video footage of a pocket sized robotic scout it has been building for the army. The robotic scout is small and able to conquer rugged terrain. By itself the robot doesn’t look like much, but it doesn’t take much imagination to envision the power of a fleet of hundreds or thousands of these things taking video, picking up samples, planting bombs, and generally wreaking havoc in enemy or even civilian territory.

Although the robots themselves are fairly simple, MIT’s creation of robotic gardeners is so cool that they have earned their way into our roundup of the year’s best robots. MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) is pioneering the field of automated farming. During a semester long experiment, CSAIL’s researchers created a laboratory farm: tomato plants in terra cotta pots with artificial turf for grass. The goal of the experiment: to see if these tomatoes could be grown, tended, and harvested by robot caretakers. Enjoy the video below:The HRP-4C showed in 2009 that robots can be useful AND look good while doing it by wowing the world with its female manga style hottie robot. Of course there are no technical barriers to making robots look more human, but nevertheless robot makers rarely try to make their creations look too human, perhaps in respect to human fear of the uncanny valley. Even in the case of the HRP-4C, we hear that the creators intentionally limited how lifelike their robot hottie would look. The positive and overwhelming press that this robot received, however, should serve as a sign to robot creators that the public is indeed ready to see more lifelike robots.

Well, that ends our roundup of the best robots of 2009. There are dozens of other awesome robots that didn’t make the cut and certainly a few have somehow evaded our radar. Feel free to post links to other great robots in the comments. In the meantime, my cyborg implant is telling me that some awesome robots are going to come out of the gate first thing in 2010.



New publications, experiments and breakthroughs in biomedicine -and what they mean

MIT Technology Review, January/February 2010, by Emily Singer  — 

Three-Dimensional Genome
New technology reveals the higher-order structure of DNA.

Source: “Comprehensive mapping of long-range interactions reveals folding principles of the human genome”
Eric S. Lander, Job Dekker, et al.
326: 289-293

Results: Scientists developed a tool that makes it possible to map the three-dimensional structure of the entire human genome, shedding light on how six feet of DNA is packed into a cell nucleus about three micrometers in diameter. According to the resulting analysis, chromosomes are folded so that the active genes–the ones this particular cell is using to make proteins–are close together.

Why it matters: Growing evidence suggests that the way the genome is packed in a particular cell is key to determining which of its genes are active. The new findings could allow scientists to study this crucial aspect of gene regulation more precisely.

Methods: Scientists treated a folded DNA molecule with a preservative in order to create bonds between genes that are close together in the three-dimensional structure even though they may be far apart in the linear sequence. Then they broke the molecule into a million pieces using a DNA-cutting enzyme. The researchers sequenced these pieces to identify which genes had bonded together and then used this information to develop a model of how the chromosome had been folded.

Next steps: Scientists plan to study how the three-dimensional structure of the genome varies between different cell types, between different organisms, and between normal and cancerous cells. They also hope that improving the resolution of the technology might reveal new structural properties of the genome. They can currently analyze DNA in chunks comprising millions of bases, but they would like to zero in on sequences thousands of bases long.
Diabetic Cells
Stem cells derived from patients with diabetes provide a new model for studying the disease

Source: “Generation of pluripotent stem cells from patients with type 1 diabetes”
Douglas A. Melton et al.
Proceedings of the National Academy of Sciences
106: 15768-15773

Results: Scientists collected cells from patients with type 1 diabetes and turned them into induced pluripotent stem cells, adult stem cells with an embryonic cell’s capacity to differentiate into many different cell types. Then they stimulated these cells to differentiate into insulin-producing pancreatic cells.

Why it matters: The stem cells carry the same genetic vulnerabilities that led the patients to develop diabetes. Watching them develop into insulin-producing cells should shed light on the development and progression of diabetes. Researchers may also be able to test new treatments on the developing cells.

Methods: Researchers “reprogrammed” skin cells from two diabetes patients by using a virus to insert three genes involved in normal development. The new genes caused other genes to turn on and off in a pattern more typical of embryonic cells, returning the skin cells to an earlier developmental stage. The scientists then exposed the cells to a series of chemicals, encouraging them to differentiate into insulin-producing cells.

Next steps: The researchers will examine the interaction between the different cell types affected by diabetes: the pancreatic beta cells and the immune cells that attack them. Initially they will study these interactions in a test tube, but ultimately they hope to incorporate the lab-generated human stem cells into mice. This will help scientists understand which cells are affected first. Armed with that knowledge, they could begin developing treatments that involve replacing some of those cells.


Lab on a chip: Fluidigm’s microfluidic chip (the gray square in the center) uses tiny channels and valves to manipulate liquids. It allows fast and sensitive bioassays     Credit: Joshua Scott

Why does it take so long to commercialize new technologies?


MIT Technology Review, January/February 2010, by David Rotman  —  The new microfluidic chip fabricated by Fluidigm, a startup based in South San Francisco, represents a decade of successive inventions. This small square of spongy polymer–the same type used in contact lenses and window caulking–holds a complex network of microscopic channels, pumps, and valves. Minute volumes of liquid from, say, a blood sample can flow through the maze of channels to be segregated by the valves and pumps into nearly 10,000 tiny chambers. In each chamber, nanoliters (billionths of a liter) of the liquid can be analyzed.

The ability to move fluids around a chip on a microscopic scale is one of the most impressive achievements of biochemistry over the last 10 years. Microfluidic chips, which are now produced by a handful of startup companies and a similar number of university-­based foundries, allow biologists and chemists to manipulate tiny amounts of fluid in a precise and highly automated way. The potential applications are numerous, including handheld devices to detect various diseases and machines that can rapidly analyze the content of a large number of individual cells (each holding about one picoliter of liquid) to identify, for example, rare and deadly cancerous mutations. But microfluidics also represents a fundamental breakthrough in how researchers can interact with the biological world. “Life is water flowing through pipes,” says George Whitesides, a chemist at Harvard University who has invented much of the technology used in microfluidics. “If we’re interested in life, we must be interested in fluids on small scales.”

By way of explaining the importance of the technology and the complexity of its microscopic apparatus, those involved in microfluidics often make comparisons to microprocessors and integrated circuits. Indeed, a microfluidic chip and an electronic microprocessor have similar architectures, with valves replacing transistors and channels replacing wires. But manipulating liquids through channels is far more difficult than routing electrons around an integrated circuit. Fluids are, well, messy. They can be hard to move around, they often consist of a complex stew of ingredients, and they can stick and leak.

Over the last decade, researchers have overcome many such challenges. But if microfluidics is ever to become truly comparable to microelectronics, it will need to overcome a far more daunting challenge: the transition from promising laboratory tool to widely used commercial technology. Can it be turned into products that scientists, medical technicians, and physicians will want to use? Biologists are increasingly interested in using microfluidic systems, Whitesides says. But, he adds, “do you go into the lab and find these devices everywhere? The answer is no. What’s interesting is that it hasn’t really taken off. The question is, why not?”

A similar question could just as well be asked about at least two other important technologies that have emerged over the last decade: genomic-based medicine and nanotechnology. Each began this century with significant breakthroughs and much fanfare. The sequencing of the human genome was first announced in early 2001; the National Nanotechnology Initiative, which helped launch much of today’s nanotech research, got its first federal funding in 2000. While all three technologies have produced a smattering of new products, none has had the transformative effects many experts expected. Why does it take so long for a technology as obviously important and valuable as these to make an impact? How do you create popular products out of radically new technologies? And how do you attract potential users?
Patience, Patience
Despite the economic, social, and scientific importance of technology, the process of creating it is poorly understood. In particular, researchers have largely overlooked the question of how technologies develop over time. That’s the starting point of W. Brian Arthur’s The Nature of Technology, an attempt to develop a comprehensive theory of “what technology is and how it evolves.” Arthur set to work in the library stacks at Stanford University. “As I began to read, I was astonished that some of the key questions had not been very deeply thought about,” he recalled in a recent interview. While much has been written on the sociology of technology and engineering, and there’s plenty on the histories of various technologies, he said, “there were big gaps in the literature. How does technology actually evolve? How do you define technology?”


A patent map created by IPVision, based in Cambridge, MA, shows many of the key inventions by Stephen Quake and Fluidigm over the last decade that make possible the company’s microfluidic chips. The timeline shows several key initial advances and how today’s microfluidics use both advances in microfabrication and biochemistry. Such a complex network of inventions is not uncommon in the development of new bodies of technology.
Credit: IPVision

Arthur hopes to do for technology what Thomas Kuhn famously did for science in his 1962 The Structure of Scientific Revolutions, which described how scientific breakthroughs come about and how they are adopted. A key part of Arthur’s argument is that technology has its own characteristics and “nature,” and that it has too long been treated as subservient to science or simply as “applied science.” Science and technology are “completely interwoven” but different, he says: “Science is about understanding phenomena, whereas technology is really about harnessing and using phenomena. They build out of each other.”

Arthur, a former professor of economics and population studies at Stanford who is now an external professor at the Santa Fe Institute and a visiting researcher at the Palo Alto Research Center, is perhaps best known for his work on complexity theory and for his analysis of increasing returns, which helped explain how one company comes to dominate the market for a new technology. Whether he fulfills his goal of formulating a rigorous theory of technology is debatable. The book does, however, offer a detailed description of the characteristics of technologies, peppered with interesting historical tidbits. And it provides a context in which to begin understanding the often laborious and lengthy processes by which technologies are commercially exploited.

Particularly valuable are Arthur’s insights into how different “domains” of technology evolve differently compared to individual technologies. Domains, as Arthur defines them, are groups of technologies that fit together because they harness a common phenomenon. Electronics is a domain; its devices–capacitors, inductors, transistors–all work with electrons and thus naturally fit together. Likewise, in photonics, lasers, fiber-optic cables, and optical switches all manipulate light. Whereas an individual technology–say, the jet engine–is designed for a particular purpose, a domain is “a toolbox of useful components”–“a constellation of technologies”–that can be applied across many industries. A technology is invented, Arthur writes. A domain “emerges piece by piece from its individual parts.”

The distinction is critical, he argues, because users may quickly adopt an individual technology to replace existing devices, whereas new domains are “encountered” by potential users who must try to understand them, figure out how to use them, determine whether they are worthwhile, and create applications for them. Meanwhile, those developing the new domains must improve the tools in the toolbox and invent the “missing pieces” necessary for new applications. All this “normally takes decades,” Arthur says. “It is a very, very slow process.”

What Arthur touches on just briefly is that this evolution of a new body of technology is often matched by an even more familiar progression: enthusiasm about a new technology, investor and user disillusionment as the technology fails to live up to the hyperbole, and a slow reëmergence as the technology matures and begins to meet the market’s needs.
A Solution Looking for Problems
In the late 1990s, microfluidics (or, as it is sometimes called, “lab on a chip” technology) became another overhyped advance in an era notorious for them. Advocates talked up the potential of the chips. But the devices couldn’t perform the complex fluid manipulations required for many applications. “They were touted as a replacement for everything. That clearly didn’t pan out too well,” says Michael Hunkapiller, a venture capitalist at Alloy Ventures in Palo Alto, CA, who is now investing in several microfluidics startups, including Fluidigm. The technology’s capabilities in the 1990s, he says, “were far less universal than the hype.”

The problem, as Arthur might put it, was that the toolbox was missing key pieces. Prominent among the needed components were valves, which would allow the flow of liquids to be turned on and off at specific spots on the chip. Without valves, you merely have a hose; with valves you can build pumps and begin to think of ways to construct plumbing. The problem was solved in the lab of Stephen Quake, then a professor of applied physics at Caltech and now in the bioengineering department at Stanford. Quake and his Caltech coworkers found a simple way to make valves in microfluidic channels on a polymer slab. Within two years of publishing a paper on the valves, the group had learned how to create a microfluidic chip with thousands of valves and hundreds of reaction chambers. It was the first such chip worthy of being compared to an integrated circuit. The technology was licensed to Fluidigm, which Quake cofounded in 1999.

Meanwhile, other academic labs invented other increasingly complex ways to manipulate liquids in microfluidic devices. The result is a new generation of companies equipped with far more capable technologies. Still, many potential users remain skeptical. Once again, microfluidics finds itself in a familiar phase of technology development. As David Weitz, a physics professor at Harvard and cofounder of several microfluidics companies, explains: “It is a wonderful solution still looking for the best problems.”

There are plenty of possibilities. Biomedical researchers have begun to use microfluidics to look at how individual cells express genes. In one experiment, cancer researchers are using one of Fluidigm’s chips to analyze prostate tumor cells, seeking patterns that would help them select the drugs that will most effectively combat the tumor. Also, Fluidigm has recently introduced a chip designed to grow stem cells in a precisely controlled microenvironment. Currently, when stem cells are grown in the lab, it can be difficult to mimic the chemical conditions in a living animal. But tiny groups of stem cells could be partitioned in sections of a microfluidic chip and bathed in combinations of biochemicals, allowing scientists to optimize their growing conditions.

And microfluidics could make possible cheap and portable diagnostic devices for use in doctor’s offices or even remote clinics. In theory, a sample of, say, blood could be dropped on a microfluidic chip, which would perform the necessary bioassay–identifying a virus, detecting telltale cancer proteins, or finding biochemical signs of a heart attack. But in medical diagnostics as in biomedical research, microfluidics has yet to be widely adopted.

Again, Arthur’s analysis offers an explanation. Users who encounter the new tools must determine whether they are worthwhile. In the case of many diagnostic applications, biologists must better understand which biochemicals to detect in order to develop tests. Meanwhile, those developing microfluidic devices must make the devices easier to use. As Arthur reminds us, the science and technology must build on each other, and technologists must invent the missing pieces that users want; it is a slow, painstaking evolution.

It’s often hard to predict what those missing pieces will be. Hunkapiller recalls the commercialization history of the automated DNA sequencer, a machine that he and his colleagues invented at Caltech and that was commercialized in 1986 at Applied Biosystems. (The machine helped make possible the Human Genome Project.) “Sometimes, it is a strange thing that makes a technology take off,” he says. Automated sequencing didn’t become popular until around 1991 or 1992, he says, when the company introduced a sample preparation kit. Though it wasn’t a particularly impressive technical advance–certainly not on the level of the automated sequencer itself–the kit had an enormous impact because it made it easier to use the machines and led to more reliable results. Suddenly, he recalls, sales boomed: “It wasn’t a big deal to pay $100,000 for a machine anymore.”

In a recent interview, Whitesides demonstrated a microfluidic chip made out of paper in which liquids are wicked through channels to tiny chambers where test reactions are carried out. Then he pulled a new smart phone, still in its plastic wrapping, out of its box. What if, he mused, you could somehow use the phone’s camera to capture the microchip’s data and use its computational power to process the results, instead of relying on bulky dedicated readers? A simple readout on the phone could give the user the information he or she needs. But before that happens, he acknowledged, various other advances will be needed. Indeed, as if reminded of the difficult job ahead, ­Whitesides quickly slipped the smart phone back into the box.


Advances in antiaging drugs, acoustic brain surgery, flu vaccines
-and the secret to IQ


MIT Technology Review, December 24, 2009, by Emily Singer  —  We may look back on 2009 as the year human genome sequencing finally became routine enough to generate useful medical information (“A Turning Point for Personal Genomes“). The number of sequenced and published genomes shot up from two or three to approximately nine, with another 40 or so genomes sequenced but not yet published. In a few cases, scientists have already found the genetic cause of a disorder by sequencing an affected person’s genome.

Scientists have also sequenced the genomes of a number of cancers, comparing that sequence to patients’ normal genome to find the genetic mistakes that might have caused the cells to become cancerous and to metastasize (“Sequencing Tumors to Target Treatment“). The results suggest that even low-grade and medium-grade tumors can be genetically heterogeneous, which could be problematic for molecularly targeted drugs. That points to a need to develop new strategies for drug development and treatment in cancer.

The year brought more good news for aging mice, and maybe humans, too, as scientists identified the first drug that can extend lifespan in mammals (“First Drug Shown to Extend Lifespan in Mammals“). Rapamycin, an antifungal drug currently used to prevent rejection of organ transplants, was found to boost longevity 9 to 13 percent even when it was given to mice that were the mouse equivalent of 60 years old. Previously, genetic engineering and caloric restriction–a nutritionally complete but very low-calorie diet–were the only proven methods of extending lifespan in mammals (“A Clue to Living Longer“).

Because of its potent immunosuppressant effect, the drug isn’t suitable for this application in humans. But researchers have already found that disrupting part of the same signaling pathway has similar life-extending benefits (“Genetic Fountain of Youth“). Mice with the relevant protein disabled showed superior motor skills, stronger bones, and better insulin sensitivity when they reached mouse middle age. Female mice lived about 20 percent longer than their unaltered counterparts. But male mice, while healthy, didn’t have longer lifespans. (In comparison, caloric restriction boosts longevity by about 50 percent.) Scientists now aim to develop drugs that target this pathway, which is thought to act as a kind of gauge for the amount of food available in the environment.

The emergence in April of a new pandemic flu strain, H1N1, rapidly renewed interest in new approaches to making vaccines (“New Vaccines for Swine Flu“). For the first time during an active pandemic, pharmaceutical companies were able to use faster cell-based production methods to create vaccines against the virus, in addition to the traditional egg-based method. (None of these methods has yet been approved for use in the United States–the vaccine currently available was made in eggs.) In November, an advisory panel for the U.S. Food and Drug Administration declared that a novel method of producing flu vaccines in insect cells, while effective, needs more safety testing before it can be approved (“Caterpillar Flu Vaccine Delayed“). The vaccine, developed by Protein Sciences, based in Meriden, CT, uses a single protein from the virus to induce immunity, rather than a dead or weakened version of the virus. Two other companies began clinical trials of flu vaccines made from virus-like particles–protein shells that look just like viruses but do not contain viral DNA (“Delivering a Virus Imposter Quicker“).

A new approach to brain surgery, tested by a Swiss team earlier this year, allows surgeons to burn out small chunks of brain tissue without major surgery using specialized sound waves (“Brain Surgery Using Sound Waves“). Neurosurgeons used a technology developed by InSightec, an ultrasound technology company headquartered in Israel. The method employs high-intensity focused ultrasound (HIFU) to target the brain. (HIFU is different than the ultrasound used for diagnostic purposes, such as prenatal screening, and has previously been used to remove uterine fibroids.) Beams from an array of more than 1,000 ultrasound transducers are focused through the skull onto a small piece of diseased tissue, heating it up and destroying it. In the study, nine patients with chronic debilitating pain reported immediate pain relief after the procedure.

Scientists also hope to co-opt the technologies developed for HIFU to modulate brain activity, using low intensity focused ultrasound to activate nerve cells (“Targeting the Brain with Sound Waves“). This approach might one day provide a less invasive alternative to deep-brain stimulation. This procedure, in which surgically implanted electrodes stimulate parts of the brain, is an increasingly common treatment for Parkinson’s disease and other neurological problems.

In another first for the brain, scientists discovered this year that our IQ, or general intelligence, depends in large part on our white matter–the fatty layer of insulation that coats the neural wiring of the brain (“Brain Images Reveal the Secret to Higher IQ“). Using a type of brain imaging called diffusion tensor imaging, researchers analyzed the neural wiring in 92 pairs of fraternal and identical twins and found a strong correlation between the integrity of the white matter and performance on a standard IQ test. In addition, the researchers found that the quality of one’s white matter is largely genetically determined. They are now searching for genetic variants tied to white matter and IQ.

A feature in the November issue of the magazine further explored the secret of intelligence, revealing that our smarts may be determined by the function and efficiency of the networks within the brain, rather than the number of neurons or the size of any particular region (“Intelligence Explained“).


Credit: Technology Review

Scientists are finally starting to find medical information of value


MIT Technology Review —  Last year, when more than 100 of the world’s top geneticists, technologists, and clinicians converged on Cold Spring Harbor Laboratory in New York for the first annual Personal-Genomes conference, the main focus was James Watson‘s genome. The codiscoverer of the structure of DNA was the first to have his genome sequenced and published (aside from Craig Venter, who used his own DNA for the private arm of the human genome project.) Watson sat in the front row of the lecture hall as scientists presented their analysis of his genome. They paid special attention to the number of single-letter variations or small insertions and deletions in his DNA–clues as to whether he had a genetic variation that slightly boosted his risk for heart disease or cancer. But there was very little usable information in the genome.

That has all changed. In the last year, the number of sequenced, published genomes has shot up from two or three to approximately nine, with another 40 or so genomes sequenced but not yet published. “While the numbers are still small numbers, we are starting to put this research into the real disease context and get something out of it,” says Jay Shendure, a geneticist at the University of Washington in Seattle, and a TR35 winner in 2006.

Last year, sequencing a genome was still a feat in itself, and much of the conference focused on the technical details–assessing accuracy and error rates and comparing one method to another. While these issues are still of central importance, sequencing a human genome has become routine enough to generate medically useful information. “Now we are able to do things automatically, so the biology starts to come out,” says Paul Flicek, a bioinformaticist with the European Bioinformatics Institute and one of the conference organizers.

In a few cases, scientists have already been able to find the genetic cause of a disorder by sequencing an affected person’s genome. Shendure has sequenced the coding region–the 1 percent of the genome that directs production of proteins–of the genomes of a handful of families with children afflicted with a rare inherited disorder called Miller Syndrome, which is linked to facial and limb abnormalities. Researchers compiled a list of genetic variations in each person and filtered out those that have been commonly found in people without the disease variations. They then looked for variants present only in affected people, and came up with one candidate gene. Shendure declined to identify the gene prior to publishing the findings, but noted that it was one they would not have anticipated. He hopes the technique can be applied to more common diseases as well, perhaps by studying people with early onset or extreme cases.

Genome sequencing has also engendered a new approach to cancer research. Last year, Elaine Mardis and her team at Washington University School of Medicine in St. Louis sequenced the complete genomes of cancerous and normal tissue in a patient with acute myeloid leukemia, identifying 10 mutated genes that appear to play a role in this cancer. This year, her team has sequenced the genome of four different types of tissue from a breast-cancer patient–the normal genome, DNA from the primary tumor, DNA from a metastatic brain tumor (a secondary tumor formed from cancer cells originally from the breast tumor), and DNA from the patient’s cancerous tissue implanted into a mouse. (Because the cancerous tissue removed during surgery is often inadequate for genetic research, scientists sometimes grow tumor tissue from the patient’s cancer cells in mice.)

While the vast majority of the sequence will be identical in all four samples, identifying differences could pinpoint the genetic changes that lead to the initial formation of the tumor, as well as those that trigger metastasis. If scientists can find drugs that block the primary tumor from spreading, cancer could be converted into a manageable chronic disease.

Mardis’s team has already identified a number of variants that are unique to either the primary tumor or the metastatic tumor. They have also found some variants that appear in both but are more common in the metastatic tissue, suggesting that this type of mutation might enable cells to spread through the body. “We are now looking at breast-cancer-derived brain, lung, and liver tumors to see if there are commonalities in metastatic disease,” says Mardis. Her center aims to sequence 150 cancer genomes this year. Next year, that number will likely seem small.

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