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The end of the year is approaching, and as we prepare for the celebrations for the new year, what could be better than sitting down with a warm drink and recapping 2017 in the world of rejuvenation biotechnology?

Winter kick-off

This year has been pretty intense, with a lot going on both at LEAF and in the rest of the community. January saw the launch of the LEAF website, shortly followed by both the Lifeboat Foundation and Trust me – I’m a biologist partnering with us. Given that it’s been only a year, we’re amazed at how enthusiastic and supportive the community has been—and how fast it has grown, with nearly 30,000 Facebook followers late in December! We’re also very grateful to our friends at Fight Aging! for their encouragement, support, and appreciation for our work, including honoring us by featuring it on their website!

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Usually, when we’ve referred to Crispr, we’ve really meant Crispr/Cas9—a riboprotein complex composed of a short strand of RNA and an efficient DNA-cutting enzyme. It did for biology and medicine what the Model T did for manufacturing and transportation; democratizing access to a revolutionary technology and disrupting the status quo in the process. Crispr has already been used to treat cancer in humans, and it could be in clinical trials to cure genetic diseases like sickle cell anemia and beta thalassemia as soon as next year.

But like the Model T, Crispr Classic is somewhat clunky, unreliable, and a bit dangerous. It can’t bind to just any place in the genome. It sometimes cuts in the wrong places. And it has no off-switch. If the Model T was prone to overheating, Crispr Classic is prone to overeating.

Even with these limitations, Crispr Classic will continue to be a workhorse for science in 2018 and beyond. But this year, newer, flashier gene editing tools began rolling off the production line, promising to outshine their first-generation cousin. So if you were just getting your head around Crispr, buckle up. Because gene-editing 2.0 is here.

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Virgin Hyperloop One set a test speed record of nearly 240 miles per hour during its third phase of testing at its site in Nevada.

The company also tested a new airlock which helped transition test pods between atmospheric and vacuum conditions during a test campaign which was completed on December 15, 2017.

The tests were conducted in a tube depressurized down to the equivalent air pressure experienced at 200,000 feet above sea level.

A Virgin Hyperloop One pod quickly lifts above the track using magnetic levitation and glides at airline speeds for long distances due to ultra-low aerodynamic drag.

Automation of the Transportation Industry, expect the big roll out around 2022’ish.


Once thought of as a distant fantasy, autonomous trucks are moving toward commercial reality on Canadian highways as companies look to boost productivity amid a driver shortage and governments seek to reduce deadly crashes.

They are not yet driving themselves out of warehouses and down the highways, but companies of all sizes —including General Motors, Google and Uber — are testing out the technology.

Already a banner year in self-driving advancements — including the first on-street test of an autonomous vehicle in Canada — interest in the sector picked up in the closing months of 2017 after Tesla Inc. showcased a fully electric semi-trailer truck equipped with semi-autonomous technology including enhanced autopilot, automated braking and lane departure warnings.

Germany has spent $200 billion over the past two decades to promote cleaner sources of electricity. That enormous investment is now having an unexpected impact — consumers are now actually paid to use power on occasion, as was the case over the weekend.

Power prices plunged below zero for much of Sunday and the early hours of Christmas Day on the EPEX Spot, a large European power trading exchange, the result of low demand, unseasonably warm weather and strong breezes that provided an abundance of wind power on the grid.

Such “negative prices” are not the norm in Germany, but they are far from rare, thanks to the country’s effort to encourage investment in greener forms of power generation. Prices for electricity in Germany have dipped below zero — meaning customers are being paid to consume power — more than 100 times this year alone, according to EPEX Spot.

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But the dream of the nanofabricator is not yet dead. What is perhaps even more astonishing than the idea of having such a device—something that could create anything you want—is the potential consequences it could have for society. Suddenly, all you need is light and raw materials. Starvation ceases to be a problem. After all, what is food? Carbon, hydrogen, nitrogen, phosphorous, sulphur. Nothing that you won’t find with some dirt, some air, and maybe a little biomass thrown in for efficiency’s sake.

Equally, there’s no need to worry about not having medicine as long as you have the recipe and a nanofabricator. After all, the same elements I listed above could just as easily make insulin, paracetamol, and presumably the superior drugs of the future, too.

What the internet did for information—allowing it to be shared, transmitted, and replicated with ease, instantaneously—the nanofabricator would do for physical objects. Energy will be in plentiful supply from the sun; your Santa Clause machine will be able to create new solar panels and batteries to harness and store this energy whenever it needs to.

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It’s that time of year again. Sleigh bells overhead and our jolly, bearded benefactor wafting gifts down the chimney to eagerly awaiting hands. We’ve heard every version of this tale. Except, perhaps, the variant that is currently playing out in East Africa. In the funny way that magic tales and science fiction sometimes become reality, if you swap out sleigh bells for drones and gifts for emergency medical supplies, you’ve got the real world tale of Zipline, a company delivering 20% of national blood supply via drone in Rwanda. The Sequoia and A16Z-backed company recently announced it woul…

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After less than eight months of development, the algorithms are helping intel analysts exploit drone video over the battlefield.

Earlier this month at an undisclosed location in the Middle East, computers using special algorithms helped intelligence analysts identify objects in a video feed from a small ScanEagle drone over the battlefield.

A few days into the trials, the computer identified objects — people, cars, types of building — correctly about 60 percent of the time. Just over a week on the job — and a handful of on-the-fly software updates later — the machine’s accuracy improved to around 80 percent. Next month, when its creators send the technology back to war with more software and hardware updates, they believe it will become even more accurate.

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