To do this, they rewired kidney cells with light-sensitive molecules from the eye, they reported in the journal Science.
When pulsed with blue light, these cells churned out proteins on demand.
Ultimately, this technique could avoid the need for people with diabetes to inject themselves regularly.
“When I speak to diabetes patients they say that if you could take away always having to inject themselves it would really increase their quality of life,” said lead author Martin Fussenegger, a bioengineer of the Swiss Federal Institute of Technology, Zurich.
Dr Fussenegger thought he saw a solution in his own field of optogenetics. Optogenetics, as the name suggests, uses light to control the behaviour cells.
To get a cell to respond to light you first have to rejigger it so it has a light-sensitive molecule on its surface. Dr Fussenegger coaxed kidney cells to express melanopsin, a molecule usually found in animals’ eyes.
He then placed these cells into diabetic mice. Along with the cells he placed an optic fibre, down which he could pulse blue light to expose the cells at his command.
In the dark, these cells behaved as usual; In the light, however, genes in the cell were switched on and the cell pumped out a protein required for the breakdown of sugars in the blood, helping the mice to control their glucose levels.
He hopes that cells like these could ultimately be implanted into people, and exposed to light – either through the skin or down a optic fibre – to release proteins that would help treat diabetes.
The new technique is a proof of principle. He told BBC News that it was not limited to treating diabetes; this technology could be usedto switch on genes to produce many different proteins in people who do not make them naturally, or are not making enough of them to be healthy.
“I think this is a phenomenal research tool,” said James Collins, a synthetic biologist at Howard Hughes Medical Institute, Maryland, US, who was not involved in the work.
Dr Collins explained that as we move into an age of regenerative medicine, and begin to think of how we use stem cells to produce different tissues in the body, one of the challenges will be to work out which genes are needed to produce certain tissues and cells.
This new technique allows researchers to switch genes on and off to determine which are essential to make a specific tissues.
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Worried about having enough hard drive space to store all of your holiday pictures? Just be glad you don’t have to cope with the 9.57 zettabytes—that’s 9,570,000,000,000,000,000,000 bytes—of information that the world’s 27 million business computer servers process each year. If you divided 9.57 zettabytes among the 3.18 billion workers that make up today’s global labor force, then each person would receive around 3 terabytes of information per year. That’s enough to fill the largest external hard drive three times over. What’s most worrying is that this number will likely double every 2 years, according to researchers who presented their estimates at a conference for data storage professionals in the United States in Santa Clara, California, today. Might be time for a reformat.
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If you ever wanted to know how the inner organs of a mouse embryo form, this is the movie for you. The animation was created by imaging thin sections of an embryo and then stacking these images to make a 3D movie. “If you look closely, you can see the developing lungs, gut, kidney, and bladder,” says the movie’s creator, Ian Smyth, a developmental biologist at Monash University in Australia. His video was selected from among several for being the most “striking and technically excellent” of the animations submitted to this year’s Wellcome Image Awards in London. Smyth uses these animations to compare normal tissues in embryos with those whose development is disrupted because of disease or exposure to a toxin. The animation was selected because of its ability to illustrate how effective this imaging technique can be for looking at the internal structure of the organs in a noninvasive way, explains Catherine Draycott, one of this year’s judges. “You can almost travel through [the mouse] as it develops.”
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LAST MAY, JURE ŽBONTAR, A 25-YEAR-OLD computer scientist at the University of Ljubljana in Slovenia, was among the 125 million people around the world paying close attention to the televised finale of the annual Eurovision Song Contest. Started in 1956 as a modest battle between bands or singers representing European nations, the contest has become an often-bizarre affair in which some acts seem deliberately bad—France’s 2008 entry involved a chorus of women wearing fake beards and a lead singer altering his vocals by sucking helium—and the outcome, determined by a tally of points awarded by each country following telephone voting, has become increasingly politicized.
Žbontar and his friends gather annually and bet on which of the acts will win. But this year he had an edge because he had spent hours analyzing the competition’s past voting patterns. That’s because he was among the 22 entries in, and the eventual winner of, an online competition to predict the song contest’s results.
The competition was run by Kaggle, a small Australian start-up company that seeks to exploit the concept of “crowdsourcing” in a novel way. Kaggle’s core idea is to facilitate the analysis of data, whether it belongs to a scientist, a company, or an organization, by allowing outsiders to model it. To do that, the company organizes competitions in which anyone with a passion for data analysis can battle it out. The contests offered so far have ranged widely, encompassing everything from ranking international chess players to evaluating whether a person will respond to HIV treatments to forecasting if a researcher’s grant application will be approved. Despite often modest prizes—Žbontar won just $1000—the competitions have so far attracted more than 3000 statisticians, computer scientists, econometrists, mathematicians, and physicists from approximately 200 universities in 100 countries, Kaggle founder Anthony Goldbloom boasts.
And the wisdom of the crowds can sometimes outsmart those offering up their data. In the HIV contest, entrants significantly improved on the efforts of the research team that posed the challenge. Citing Žbontar’s success as another example, Goldbloom argues that Kaggle can help bring fresh ideas to data analysis. “This is the beauty of competitions. He won not because he is perhaps the best statistician out there but because his model was the best for that particular problem. … It was a true meritocracy,” he says.
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The scene at the nursing home is grim. An elderly man lies in a pool of blood on the floor of his bedroom. Detectives also find blood from an unknown individual near the door, suggesting the victim put up a fight. Was the assailant one of the octogenarian’s fellow residents, or perhaps a nurse or an orderly? The detectives have little to go on until analysis of the unknown blood reveals it came from someone in their 20s or 30s.
That’s a fictional scenario—for now. But researchers report online today in Current Biologythat they can estimate someone’s age—give or take about a decade—simply by analyzing a drop of blood. If validated, the new forensic technique could revive police investigations that have hit a dead end.
The blood-age test relies on a peculiarity of T cells, immune cells that recognize and fight microbial invaders. As a T cell develops, it cuts up some of its DNA and splices some of it back together in various combinations; that helps it generate unique cell-surface receptors that can recognize a wide variety of bacteria or other pathogens. Any leftover DNA forms a circle that is useless to the T cell.
Researchers can quantify how many circles exist in the blood, says Manfred Kayser, a forensic molecular biologist at Erasmus University Medical Centre in Rotterdam. He and his colleagues have found that the amount declines with age because the body produces fewer and fewer new T cells as people get older. “We take advantage of this waste product,” he says.
The researchers established the promise of the forensic technique by analyzing the blood samples of about 200 people varying in age from a few weeks old to 80 years old. They probed the samples with fluorescent DNA designed to bind to the excess T cell DNA fragments, allowing them to quantify those fragments in a matter of hours. The team found a correlation between the number of T cell DNA fragments and age, one strong enough to pinpoint how old a person was, plus or minus 9 years.
That may seem like a big range, but it’s enough to place suspects into generational categories, which is very helpful to police, says Peter de Knijff, head of the forensic laboratory at Leiden University Medical Center in the Netherlands. Right now, law enforcement officials armed with a blood sample can identify its owner only if they can match it to a known suspect, or if it matches DNA in a database. With this new test, and a test for eye color, also developed in Kayser’s lab, de Knijff says that at least police can narrow down their suspect pool. “This is the best we have right now.”
Kayser says that he hopes to make the T cell test more accurate by combining it with other aging biomarkers that his team is developing. He also notes that the T cell test was still accurate on blood collected a year and a half earlier. That means it could be used to resolve cold cases as well as help police identify disaster victims.
Before the technique becomes widely available to forensic teams in the Netherlands, it will need to be verified by two independent labs, says de Knijff. There are calls for this test already, he adds, in cases where the trail has gone cold and new evidence is desperately needed.
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In the 1960s, a Danish company, seeking to improve on the traditional football made from the bladder and stomach of animals, invented the modern football. The designers realised that to form a perfect ball they needed to combine 20 leather hexagons with 12 pentagons, and in so doing demonstrated one of the basic laws of shape – that you cannot wrap a sheet of six-sided hexagons around a sphere. To induce the sheet to bend, the company had to introduce five-sided pentagons alongside the hexagons.
On the micro scale, the human immunodeficiency virus (HIV), which causes AIDS, faces a similar challenge during the assembly of new viral particles: how to coerce its hexagonshaped building blocks to form the spherical envelope that
surrounds its viral innards. Lifting a page from the football manual, structural biologist John Briggs, group leader at EMBL Heidelberg, wondered if HIV likewise solved this shape conundrum by introducing pentagons between the hexagons.
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