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When galaxies switch off: Hubble's COSMOS survey solves "quenched" galaxy mystery

When galaxies switch off: Hubble's COSMOS survey solves "quenched" galaxy mystery | Amazing Science | Scoop.it

Some galaxies hit a point in their lives when their star formation is snuffed out, and they become "quenched". Quenched galaxies in the distant past appear to be much smaller than the quenched galaxies in the Universe today. This has always puzzled astronomers — how can these galaxies grow if they are no longer forming stars? A team of astronomers has now used a huge set of Hubble observations to give a surprisingly simple answer to this long-standing cosmic riddle.

 

Until now, these small, snuffed-out galaxies were thought to grow into the larger quenched galaxies we see nearby. As these galaxies are no longer forming new stars, they were thought to grow by colliding and merging with other smaller quenched galaxies some five to ten times less massive.

 

However, these mergers would require many such small galaxies floating around for the quenched population to snack on — which we do not see.

Until recently it had not been possible to explore a sufficient number of quenched galaxies, but now a team of astronomers has used observations from the Hubble COSMOS survey to identify and count these switched-off galaxies throughout the last eight billion years of cosmic history.

 

"The apparent puffing up of quenched galaxies has been one of the biggest puzzles about galaxy evolution for many years," says Marcella Carollo of ETH Zurich, Switzerland, lead author on a new paper exploring these galaxies. "No single collection of images has been large enough to enable us to study very large numbers of galaxies in exactly the same way — until Hubble's COSMOS," adds co-author Nick Scoville of Caltech, USA.

 

The team used the large set of COSMOS images, alongside additional observations from the Canada–France–Hawaii Telescope and the Subaru Telescope, both in Hawaii, USA, to peer back to when the Universe was less than half its present age. These observations mapped an area in the sky almost nine times that of the full Moon.

 

The quenched galaxies seen at these times are small and compact — and surprisingly, it seems they stay that way. Rather than puffing up and growing via mergers over time, these small galaxies mostly keep the size they had when their star formation switched off. So why do we see these galaxies apparently growing larger over time?

 

"We found that a large number of the bigger galaxies instead switch off at later times, joining their smaller quenched siblings and giving the mistaken impression of individual galaxy growth over time," says co-author Simon Lilly, also of ETH Zurich."It's like saying that the increase in the average apartment size in a city is not due to the addition of new rooms to old buildings, but rather to the construction of new, larger apartments," adds co-author Alvio Renzini of INAF Padua Observatory, Italy.

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What are Fractals and why do we care?

What are Fractals and why do we care? | Amazing Science | Scoop.it

Fractal geometry is a field of maths born in the 1970’s and mainly developed by Benoit Mandelbrot. The geometry that is taught in school is about how to make shapes; fractal geometry is no different. While the shapes in classical geometry are ‘smooth’, such as a circle or a triangle, the shapes that come out of fractal geometry are ‘rough’ and infinitely complex. However fractal geometry is still about making shapes, measuring shapes and defining shapes, just like classical geomety.

 

There are two reasons why people should care about fractal geometry:

 

  1. The process by which shapes are made in fractal geometry is amazingly simple yet completely different to classical geometry. While classical geometry uses formulas to define a shape, fractal geometry uses iteration. It therefore breaks away from giants such as Pythagoras, Plato and Euclid and heads in another direction. Classical geometry has enjoyed over 2,000 years of scrutinization. Fractal geometry has enjoyed only 40.
  2. The shapes that come out of fractal geometry look like nature derived. This is an amazing fact that is hard to ignore. As we all know, there are no perfect circles in nature and no perfect squares. Not only that, but when you look at trees or mountains or river systems, they don’t resemble any shapes one is used to in math. However with simple formulas iterated multiple times, fractal geometry can model these natural phenomena with alarming accuracy. If you can use simple mathematics to make things look like the world around us, you know you’re onto a winner. Fractal geometry does this with ease.

 

This article shall give a quick overview of how to make fractal shapes and show how these shapes can resemble nature. It shall then go on to talk about dimensionality, which is a good way to measure fractals. It ends by discussing how fractal geometry is also beneficial because randomness can be introduced into the structure of a fractal shape.

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GMO Apples That Don’t Brown to Reach U.S. Shelves This Fall

GMO Apples That Don’t Brown to Reach U.S. Shelves This Fall | Amazing Science | Scoop.it
Can genetic modification appeal to consumers? A new apple will test the market.

 

The so-called Arctic apples are genetically altered to suppress browning and may be offered for sale as bagged slices in up to 400 stores in the Midwest and Southern California, according to the company. The launch is the first significant test of a GMO whose modification is meant to appeal to consumers, rather than help farmers increase production, since a slow-ripening tomato called the Flavr Savr flopped in the 1990s.

 

The modified Golden Delicious apples were developed by Okanagan Specialty Fruits, a privately owned company acquired for $41 million in 2015 by the Maryland biotech Intrexon. Other divisions of that company are already marketing genetically modified salmon, cloned cattle, and self-destructing mosquitoes.

The company plans to sell the apples as bags of pre-sliced fruit but say they will not be labeled as “produced with genetic engineering” and will not come with any other packaging identifying them as GMOs. Instead, as allowed under a 2016 labeling law, there will be a QR code that links to a Web page with detailed information on how the apples were made.

“We didn’t want put ‘GMO’ and a skull and crossbones on the package,” Neal Carter, Okanagan’s founder, said this week, during a presentation in San Francisco.

 

A package of golden delicious apple slices. The fruit has been genetically modified so they don't turn brown. The GM apple is notable partly because Carter, an apple grower and farming innovator, independently developed it and won regulatory approval to sell it. Most GMOs have been developed and marketed as seeds by large corporations like Monsanto or DuPont and involve large-acre crops like soybeans and corn. Using a technique called gene silencing, Carter and his research team engineered the apple’s DNA to produce less polyphenol oxidase, or PPO, the enzyme that causes the flesh to turn brown. Carter says slices of the engineered apples can stay free of browning as long as three weeks.To some, genetic slowing of the browning process could seem like a solution in search of a problem. Commercial apple slices are already preserved with a mixture of calcium and vitamin C, which keeps them from browning long enough to be ordered via Amazon. At home, many cooks know a squirt of lemon juice does the trick, at least for a few hours.Groups opposing GMOs have protested the introduction of Okanagan’s apples and pressured food companies including Burger King not to sell them. Friends of the Earth told the Independent that the Arctic apple is “understudied, unlabeled, and unnecessary.” Because of widespread opposition, genetically modified foods are subject to an array of labeling rules and even outright bans around the world.  

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Tech Showcase: Ribocomputing

Tech Showcase: Ribocomputing | Amazing Science | Scoop.it
A novel method of programming cells to operate like computers, called Ribocomputing, will be aided by Twist Bioscience's streamlined DNA manufacturing process.

 

One goal of synthetic biology is to engineer life to recognize desired inputs and in turn respond with desired outputs. Biocomputing is the management of this input/output system, designing genetic parts that allow life to perform logic based decisions in a manner not dissimilar to the computer you're using to read this article. 
 
Researchers at the Wyss Institute for Biologically Inspired Engineering and Arizona State University, in a recent article in Nature, demonstrated a novel method of programming cells to operate like computers. They call their method ribocomputing because their engineered cells carry out complex logic-based computations exclusively using ribonucleic acids, more commonly known as RNA.
 
Unlike the digital computers ubiquitous in the modern world, which use electricity to accomplish all higher-order functions, these ribocomputers perform logical operations on biological materials, such as proteins, toxins, and immune system molecules. Adding programmability to cells opens up exciting new possibilities for ways to control cells and their interactions with organisms and their environment. The ribocumputing researchers propose that using this new technique, cells and microorganisms can be programmed to accomplish tasks ranging from disease diagnostics and therapeutic drug delivery to green energy production and environmental cleanup.
 
In their ribocomputing demonstration, the research team engineered the bacteria E. coli to sense the presence of 12 different molecules, and then use a computational circuit encoded in RNA to calculate the correct level of green fluorescent protein (GFP) to express. GFP is commonly used as a marker in biological experiments, as its green glow makes it simple for researchers to assess the behavior of genes or pathways in question. 
 
In the ribocomputing experiment, the researchers first designed an RNA circuit to map different combinations and levels of input molecules to specific GFP intensities, as controlled by expression levels. Next, the researchers introduced controlled levels of the input molecules into the engineered E. coli’s cellular environments, and then checked whether GFP was lighting up at the specified levels. By confirming that GFP was behaving in a manner that they expected, the researchers demonstrated the viability of their RNA circuits to carry out computations.
 
In general, the principles in this experiment can be applied to other kinds of bio-computation. Using the same methodology, cells can be engineered to respond with specified behavior to any number of the diverse chemical arrangements they encounter in their complicated environments.
 
The demonstration of successful RNA-based computing represents a significant advancement for cellular computing technology. Although such computing had been described in publications almost two decades ago, the conventional methods required resources and included drawbacks that made the techniques unattractive to pursue for commercial, industrial, and clinical applications. In previous experiments, researchers used combinations of DNA, RNA, proteins, and other molecules to design biological circuits. Incorporating these disparate computing elements into a circuit design is more error-prone: successful operation of the circuit would hinge on the precise coordination of these multifarious components. Each component adds a source of noise to the logical circuit, degrading the results. As the computational load increases, it can limit the effectiveness and applicability of the method. By using RNA only, various sources of noise can be muted.
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Quasars release more energy then 100 galaxies combined

Quasars release more energy then 100 galaxies combined | Amazing Science | Scoop.it

In 2013, researchers discovered a quasar known as SDSS J1106+1939 with the most energetic outflow ever, a finding that may answer questions about how the mass of a galaxy is linked to its central black hole mass and why there are so few large galaxies in the universe. The rate that energy is carried away by the huge mass of material ejected is equivalent to two trillion times the power output of the sun. The black hole at the heart of quasar SDSS J1106-1939 is massive, estimated to be a thousand times heavier than the black hole in the Milky Way.

 

"This is about 100 times higher than the total power output of the Milky Way galaxy — it's a real monster outflow," said Nahum Arav, an associate professor of physics in College of Science atVirginia Tech and leader of the research team, which includes Benoit Borguet, now a postdoctoral researcher now at the University of Liege, Belgium; Doug Edmonds and Carter Chamberlain, both graduate research assistants at Virginia Tech, and Chris Benn, a collaborator who works with the Isaac Newton Group of Telescopes in Spain.

 

Researchers studied the quasar in great detail using the European Southern Observatory's Very Large Telescope in Paranal, Chile – the world's most advanced visible-light astronomical observatory, and found the most energetic quasar outflow ever discovered. The findings were released today (Wednesday, Nov. 28, 2012) by the European Southern Observatory.

 

Theorists have predicted energy flows of this magnitude, and simulations have suggested these outflows impact the galaxies around them, but it has all been speculation — until now.

 

"For the last 15 years many theorists have said that if there were such powerful outflows it would help answer many questions on the formation of galaxies, on the behavior of black holes, and on the enrichment of the intergalactic medium with elements other than hydrogen and helium," Arav said. "This discovery means we can better explain the formation of galaxies. There are hundreds of people doing the theoretical side of the work. They hypothesize outflows in their simulations, and now we've found an outflow in the magnitude that has only been theorized in the past. Now they can refine their already impressive models and base them on empirical data."

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The Genomic Revolution Reaches Crime LabS

The Genomic Revolution Reaches Crime LabS | Amazing Science | Scoop.it
How will law enforcement handle the deluge of new information available from DNA?

 

Lisa Ziegert disappeared from the gift shop where she worked on April 15, 1992, and her body was found four days later. From then until this past Monday, her murder remained unsolved.

Then on Monday, the local district attorney’s office in

 

Massachusetts announced the arrest of a 48-year-old man for Ziegert’s death. Among the clues that led police to him was a computer-generated “mug shot” based on DNA found at the crime scene 25 years ago. Back then, the idea of predicting a face based on DNA would have seemed like science fiction. It is still rare today, but law-enforcement officials can quite easily order up such a test from the Virginia-based company Parabon NanoLabs.

 

Ziegert’s case is already being touted as an example of the power of new DNA technologies to solve crimes. In many ways, it’s the perfect example to take to the media: a young female victim, an infamous murder, a 25-year-old case. It’s unclear exactly how pivotal the DNA evidence was—the district attorney said “a number of factors” contributed to narrowing down the suspects—but there will almost certainly be more cases like this involving DNA.

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Designer biosensors can detect antibiotic molecules

Designer biosensors can detect antibiotic molecules | Amazing Science | Scoop.it

Researchers from North Carolina State University have engineered designer biosensors that can detect antibiotic molecules of interest. The biosensors are a first step toward creating antibiotic-producing “factories” within microbes such as E. coli.

Macrolides are a group of naturally occurring small molecules that can have antibiotic, antifungal or anticancer effects. The antibiotic erythromycin is one example – it is a macrolide produced by soil-dwelling bacteria. Researchers are interested in using these natural antibiotics and the microbes that produce them in order to develop new antibiotics; however, microbes that produce antibiotic macrolides only make small amounts of a limited variety of antibiotics.

 

“Our ultimate goal is to engineer microbes to make new versions of these antibiotics for our use, which will drastically reduce the amount of time and money necessary for new drug testing and development,” says Gavin Williams, associate professor of bio-organic chemistry at NC State and corresponding author of a paper describing the research. “In order to do that, we first need to be able to detect the antibiotic molecules of interest produced by the microbes.”

 

Williams and his team used a naturally occurring molecular switch – a protein called MphR – as their biosensor. In E. coli, MphR can detect the presence of macrolide antibiotics being secreted by microbes that are attacking E. coli. When MphR senses the antibiotic, it turns on a resistance mechanism to negate the antibiotic’s effects.

 

The researchers created a large library of MphR protein variants and screened them for the ability to switch on production of a fluorescent green protein when they were in the presence of a desired macrolide. They tested the variants against erythromycin, which MphR already recognizes, and found that some of the MphR variants improved their detection ability tenfold. They also successfully tested the variants against macrolides that were not closely related to erythromycin, such as tylosin.

 

“Essentially we have co-opted and evolved the MphR sensor system, increasing its sensitivity in recognizing the molecules that we’re interested in,” says Williams. “We know that we can tailor this biosensor and that it will detect the molecules we’re interested in, which will enable us to screen millions of different strains quickly. This is the first step toward high-throughput engineering of antibiotics, where we create vast libraries of genetically modified strains and variants of microbes in order to find the few strains and variants that produce the desired molecule in the desired yield.”

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Predatory bacteria: The quest for a new class of antibiotics

Predatory bacteria: The quest for a new class of antibiotics | Amazing Science | Scoop.it
OIST researchers take one step forward toward understanding and genetically manipulating B. bacteriovorus, a type of bacteria with promising potential use as a living antibiotic.

 

In 2016 the World Health Organization named antibiotic resistance as "one of the biggest threats to global health, food security, and development today." The announcement cited a growing list of infections, such as tuberculosis and gonorrhea, that are becoming more difficult to treat each year as resistance to current antibiotic treatments increases. Yet antibiotics are essential--without them, the human race would be plagued by persistent infections. So what is the solution to ensuring continual treatment while also addressing the alarming rise in resistance?

 

One potential solution lies within a unique type of predatory bacteria that feeds on other bacteria, such as those that cause diseases. Dubbed "living antibiotics," this group of carnivorous fauna have caught researchers' attention, including those at the Okinawa Institute of Science and Technology Graduate University (OIST). In a recently published paper in ACS Synthetic Biology, OIST researchers have taken the first steps toward genetic manipulation of one such tiny cannibal, B. bacteriovorus. They have identified tools that may allow for the manipulation of genes that influence this bacteria's predatory behavior.

 

"In the future, we want to control the predation of the bacteria--the timing and extent of predation," explains Dr. Mohammed Dwidar from the Nucleic Acid Chemistry and Engineering Unit and first author on the paper. "[At the moment] we lack the basic engineering tools in order to do this."

 

B. bacteriovorus is harmless to humans yet lethal to its prey--Gram-negative bacteria--which includes baddies such as E. coli, Salmonella, Legionella, and others. As such, being able to control it could potentially treat many different types of infections. However, due to its unusual predatory nature and other unique features, genetic manipulation of B. bacteriovorus has been limited.

The OIST researchers used riboswitches, which are gene expression-controlling tools known to function well in other bacteria, to tackle the challenge of understanding and manipulating B. bacteriovorus's predation. The way in which a gene is expressed follows a specific pathway--DNA is converted into RNA via transcription, RNA is converted into proteins via translation, and then the proteins carry out different functions. The riboswitch comes in at the translation phase. By putting a riboswitch at the beginning of a strand of RNA, and then "activating" it with a chemical, the riboswitch can start or stop the RNA from being translated into a protein.

 

For their study, the OIST researchers inserted a riboswitch into one of the genes believed to be important to B. bacteriovorus's predatory behavior: flagellar sigma factor fliA. They then activated it with the chemical theophylline. After placing the modified bacteria in petri dishes together with some delicious E. coli prey, the modified B. bacteriovorus seemed to multiply more quickly in presence of theophylline than in its absence. This quicker multiplication implies that B. bacteriovorus was consuming its prey faster, and thus multiplying faster. This in turn shows that the predatory lifecycle can be controlled by theophylline.

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Replaying evolution for over 100 years with E.coli bacteria

Replaying evolution for over 100 years with E.coli bacteria | Amazing Science | Scoop.it

Richard Lenski began the (Long Term E.coli Evolution) LTEE in 1988. For more than 66,500 generations, the project has followed the evolution of 12 initially identical populations of E. coli. These populations are grown in gently shaking flasks, incubated at body temperature, and filled with a broth that contains a small amount of glucose for food. Every day a researcher in the lab takes the flasks out of the incubator, transfers 1 percent of each population to fresh flasks of broth, and places them back in the incubator. The remaining 99 percent go into the refrigerator as a backup for two days before they are destroyed. Living samples of each population are frozen every 75 days, or about every 500 generations. Thus, ancestral and evolved clones can be revived for direct comparison and studied with other organisms at different stages of the experiment.

 

The experiment is highly simplified: The environment never changes. There is neither immigration nor emigration. Mutation is the sole source of the new variation that is grist for the mill of natural selection, to be retained if beneficial or purged if detrimental. No matter how beneficial it is, a mutation may also be lost at random because of the chance fluctuations of genetic drift—for instance, if its carrier were not in the lucky 1 percent of the population that is transferred to a new flask. This simplicity makes the experiment powerful, because mutation, natural selection, and genetic drift are the core processes of evolution that operate across all life.

 

The LTEE has essentially been a matter of rerunning evolution 12 times simultaneously. This “parallel replay” design allows the LTEE to examine how repeatable evolution is under identical conditions. But if the populations started the same, and conditions have been stable, how could they evolve differently?

 

The main reason is that mutations are spontaneous, random occurrences. Different mutations have arisen at different times and in different orders across the populations, giving each a unique mutational history. These differences can have consequences, because mutations can interact with one another, a phenomenon called epistasis. Each mutation can potentially change the effects and even the possibility of later mutations.

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Computer approaches human skill for first time in mapping brain

Computer approaches human skill for first time in mapping brain | Amazing Science | Scoop.it

A WSU research team for the first time has developed a computer algorithm that is nearly as accurate as people are at mapping brain neural networks—a breakthrough that could speed up the image analysis that researchers use to understand brain circuitry.

 

For more than a generation, people have been trying to improve understanding of human brain circuitry, but are challenged by its vast complexity. It is similar to having a satellite image of the earth and trying to map out 100 billion homes, all of the connecting streets and everyone's destinations, said Shuiwang Ji, associate professor in the School of Electrical Engineering and Computer Science and lead researcher on the project.

 

Researchers, in fact, took more than a decade to fully map the circuitry of just one animal's brain—a worm that has only 302 neurons. The human brain, meanwhile, has about 100 billion neurons, and the amount of data needed to fully understand its circuitry would require 1000 exabytes of data, or the equivalent of all the data that is currently available in the world.

 

To map neurons, researchers currently use an electron microscope to take pictures—with one image usually containing a small number of neurons. The researchers then study each neuron's shape and size as well as its thousands of connections with other nearby neurons to learn about its role in behavior or biology.

 

"We don't know much about how brains work," said Ji. With such rudimentary understanding of our circuitry, researchers are limited in their ability to understand the causes of devastating brain diseases, such as Alzheimer's, schizophrenia, autism or Parkinson's disease, he said. Instead, they have to rely on trial and error experimentation to come up with treatments. The National Academy of Engineering has listed improving understanding of the human brain as one of its grand challenges for the 21st century.

 

In 2013, MIT organized a competition that called on researchers to develop automated computer algorithms that could speed up image analysis, decode and understand images of brain circuitry.

 

As part of the competition, the algorithms are compared to work that was done by a real team of neuroscientists. If computers can become as accurate as humans, they will be able to do the computations much faster and cheaper than humans, said Ji.

 

WSU's research team developed the first computational model that was able to reach a human level of performance in accuracy.

Just as a human eye takes in information and then analyzes it in multiple stages, the WSU team developed acomputational model that takes the image as its input and then processes it in a many-layered network before coming to a decision. In their algorithm, the researchers developed an artificial neural network that imitates humans' complex biological neural networks.

 

While the WSU research team was able to approach human accuracy in the MIT challenge, they still have a lot of work to do in getting the computers to develop complete and accurate neural maps. The computers still make a large number of mistakes, and there is not yet a gold standard for comparing human and computational results, said Ji. Although it may not be realistic to expect that automated methods would completely replace human soon, improvements in computational methods will certainly lead to reduced manual proof-reading, he added.

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Top 11 maps that ultimately explain climate change and its impact

Top 11 maps that ultimately explain climate change and its impact | Amazing Science | Scoop.it
Scientists and politicians all agree – climate change and global warming are not just myths. They are a fact. This compilation of maps will show you what are the reasons behind it and what are the consequences of that process.

Via Fernando Gil
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Google's new AI can mimic human speech almost perfectly

Google's new AI can mimic human speech almost perfectly | Amazing Science | Scoop.it

Last year, artificial intelligence (AI) research company DeepMind shared details on WaveNet, a deep neural network used to synthesize realistic human speech. Now, an improved version of the technology is being rolled out for use with Google Assistant.

A system for speech synthesis — otherwise known as text-to-speech (TTS) — typically utilizes one of two techniques.

 

Concatenative TTS involves the piecing together of chunks of recordings from a voice actor. The drawback of this method is that audio libraries must be replaced whenever upgrades or changes are made.

 

The other technique, parametric TTS, uses a set of parameters to produce computer-generated speech, but this speech can sometimes sound unnatural and robotic.

 

WaveNet, on the other hand, produces waveforms from scratch based on a system developed using a convolutional neural network.

 

To begin, a large number of speech samples were used to train the platform to synthesize voices, taking into account which waveforms sounded realistic and which did not. This gave the speech synthesizer the ability to produce natural intonation, even including details like lip smacks. Depending on the samples fed into the system, it would develop a unique “accent,” which means it could be used to create any number of distinct voices if fed different data sets.


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Nik Peachey's curator insight, October 6, 1:19 AM

An interesting development.

David W. Deeds's curator insight, October 8, 6:53 AM

Cool stuff! Thanks to Giselle Pempedjian. 

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The revolution will not be crystallized: a new method sweeps through structural biology

The revolution will not be crystallized: a new method sweeps through structural biology | Amazing Science | Scoop.it

In recent years, scientists worked methodically on technical improvements to electron microscopes — in particular, on better ways to sense electrons. Long after digital cameras had taken the world by storm, many electron microscopists still preferred old-fashioned film because it recorded electrons more efficiently than did digital sensors. But, working with microscope manufacturers, the researchers developed a new generation of ‘direct electron detectors’ that vastly outperforms both film and digital-camera detectors.

Available since about 2012, the detectors can capture quick-fire images of an individual molecule at dozens of frames per second. In parallel, researchers had written sophisticated software programs to morph thousands of 2D images into sharp 3D models that, in many cases, match the quality of those deciphered with crystallography.

Cryo-EM is suited to large, stable molecules that can withstand electron bombardment without jiggling around — so molecular machines, often built from dozens of proteins, are good targets. None has proved more suitable than ribosomes, which are braced by rigid twists of RNA. The solution of ribosome structures by X-ray crystallography won three chemists the 2009 Nobel Prize in Chemistry — but those efforts took decades. In the past couple of years, ‘ribosomania’ has gripped cryo-EM researchers, and various teams have quickly determined and published dozens of cryo-EM structures of ribosomes from a multitude of organisms, including the first high-resolution models of human ribosomes. X-ray crystallography has largely fallen by the wayside in the LMB laboratory of Venki Ramakrishnan, who shared the 2009 Nobel. For large molecules, “it’s safe to predict that cryo-EM will largely supersede crystallography”, he says.

The rocketing number of cryo-EM publications suggests this to be true: in 2015 alone, the technique has so far been used to map the structures of more than 100 molecules. And, unlike X-ray crystallography, in which crystals lock proteins in a single, static pose, researchers can use cryo-EM to calculate the structure of a protein that has been flash-frozen in several conformations and so deduce the mechanisms by which it works.

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Astronomers Detect Gravitational Waves From Two Colliding Neutron Stars For The First Time

Astronomers Detect Gravitational Waves From Two Colliding Neutron Stars For The First Time | Amazing Science | Scoop.it
In an astonishing discovery, astronomers used gravitational waves to locate two neutron stars smashing together. The collision created 200 Earth masses of pure gold, along with other elements.

 

For the first time, scientists have caught two neutron stars in the act of colliding, revealing that these strange smashups are the source of heavy elements such as gold and platinum. The discovery, announced Monday at a news conference and in scientific reports written by some 3,500 researchers, solves a long-standing mystery about the origin of these heavy elements — which are found in everything from wedding rings to cellphones to nuclear weapons.

 

It's also a dramatic demonstration of how astrophysics is being transformed by humanity's newfound ability to detect gravitational waves, ripples in the fabric of space-time that are created when massive objects spin around each other and finally collide. "It's so beautiful. It's so beautiful it makes me want to cry. It's the fulfillment of dozens, hundreds, thousands of people's efforts, but it's also the fulfillment of an idea suddenly becoming real," says Peter Saulson of Syracuse University, who has spent more than three decades working on the detection of gravitational waves.

 

Albert Einstein predicted the existence of these ripples more than a century ago, but scientists didn't manage to detect them until 2015. Until now, they'd made only four such detections, and each time the distortions in space-time were caused by the collision of two black holes.

 

That bizarre phenomenon, however, can't normally be seen by telescopes that look for light. Neutron stars, by contrast, spew out visible cosmic fireworks when they come together. These incredibly dense stars are as small as cities like New York and yet have more mass than our sun.

 

In this case, what scientists managed to spot was a pair of neutron stars that likely spent more than 11 billion years circling each other more and more closely before finally slamming together about 130 million years ago.

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CRISPR gene therapy could turn your skin into a glucose sensor

CRISPR gene therapy could turn your skin into a glucose sensor | Amazing Science | Scoop.it

Diabetics might ultimately have glucose sensors built into their bodies.

 

For diabetics, the constant finger pricks to obtain a blood drop and measure its glucose level is an annoyance. But it’s essential, too. Out-of-whack blood sugar can be fatal. That’s why engineers have tried for decades to create a noninvasive glucose sensor,  but developing one has proved difficult. It’s just not feasible to accurately measure sugar levels through the skin.

 

So why not, instead, redesign a person’s body to do the measuring instead? That’s the bright idea that Xiaoyang Wu and colleagues at the University of Chicago’s Ben May Department for Cancer Research had. 

 

In a fascinating mashup of technologies, the Chicago team says it has genetically edited skin cells from a mouse and turned them into a glucose detector that, once grafted onto the animals, works all the time and doesn’t need a battery.

 

It’s the first time living skin has been turned into a sensor, says Wu, adding that “a skin-based technology would have a lot of advantages” over finger pricks or even the continuous monitors some diabetics use.

 

Skin is one of the largest organs in the body, Wu and his colleagues point out in their report, which appeared last week on the publishing website bioRxiv. Skin is easy to get ahold of and—they say—easy to remove later if things go wrong. To make their biological invention, Wu and team first collected from mice some of the stem cells whose job it is to make new skin. Next, they used the gene-editing technique CRISPR to create their built-in glucose detector. That involved adding a gene from E. coli bacteria whose product is a protein that sticks to sugar molecules. 

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Scientists create genetically modified mosquitoes and bacteria in mosquitoes' guts to combat deadly malaria

Scientists create genetically modified mosquitoes and bacteria in mosquitoes' guts to combat deadly malaria | Amazing Science | Scoop.it
Scientists explore genetically modifying mosquitoes and bacteria in mosquitoes' guts to combat deadly malaria.

 

The first study focused on whether mosquitoes that have been genetically modified to be more resistant to the malaria-causing parasite would become weaker and less able to mate and breed.

If modified mosquitoes are going to be used against malaria, the transformed mosquitoes must be as fit as wild ones and able to pass on their genetic modification in large scale to future generations.

 

The study, led by mosquito vector biologist George Dimopoulos, found that one type of genetically modified mosquito not only bred well, but became more attractive to normal mosquitoes.

Dimopoulos took a group of genetically modified mosquitoes and a group of wild normal mosquitoes and locked them up together. To his surprise, the normal male mosquitoes preferred the genetically modified females, while the genetically modified males went wild over the normal females. Those mating preferences meant that within one generation, the mosquito population was becoming 90 percent genetically modified.

 

“We found the modification was changing the microbiome and bacteria of the genetically modified mosquitoes,” Dimopoulos said. “It made them smell different, better to their mates.”

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Haplobank: A biobank of reversible mutant embryonic stem cells

Haplobank: A biobank of reversible mutant embryonic stem cells | Amazing Science | Scoop.it
Scientist have developed a biobank of revertible, mutant embryonic stem cells – called Haplobank - which contains over 100,000 mutated, conditional mouse embryonic stem cell lines, targeting about 70% of the protein-coding genome.

 

Genetic screens have revolutionized our understanding of biological processes and disease mechanisms. Recent technical advances have broadened the available approaches for disrupting gene function in a cell population prior to screening, from chemical and insertional mutagenesis to RNA interference, and, most recently, CRISPR-mediated genome editing. However, RNA interference and CRISPR-mediated gene targeting often suffer from poor efficiency and off-target effects. In addition, most mutagenesis approaches are not reversible -- making it difficult to rigorously control for the frequent genetic and epigenetic differences between ostensibly identical cells. These issues can confound the reproducibility, interpretation and overall success of genetic screens.

 

Major concerns about scientific reproducibility and rigor have emerged in recent years. Amgen and Bayer, as well as The Reproducibility Initiative, have been unable to replicate many high-profile cancer studies. Indeed, it is not uncommon to obtain different results from experiments with the same cell line in two different laboratories. These inconsistencies can arise for various reasons. Regardless, irreproducible results waste money, damage the credibility of science and scientists, and delay or undo progress, including the development of effective therapies.

 

To overcome these problems, the Penninger lab at the IMBA developed a biobank of revertible, mutant embryonic stem cells, published in the current issue of Nature. This cell bank -- called Haplobank -- contains over 100,000 mutated, conditional mouse embryonic stem cell lines, targeting about 70% of the protein-coding genome (almost 17,000 genes). "Haplobank is available to all scientists, and represents the largest ever library of hemizyogous mutant embryonic stem cell lines to date. The resource overcomes issues arising from clonal variability, because mutations can be repaired in single cells and at whole genome scale," explains Ulrich Elling, first and corresponding author of the current publication in Nature.

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Green algae could be key to engineering faster-growing crops

Green algae could be key to engineering faster-growing crops | Amazing Science | Scoop.it
How do green algae grow so quickly? Two new collaborations offer insight into how these organisms siphon carbon dioxide from the air for use in photosynthesis, a key factor in their ability to rapidly take over a swimming pool or pond. Understanding this process may someday help researchers improve the growth rate of agricultural crops such as wheat and rice.

 

In two studies published this week in the journal Cell, a Princeton-led team with collaborators from Carnegie and the Max Planck Institute of Biochemistry reported the first detailed inventory of the cellular compartment called the pyrenoid, which algae use to collect and concentrate carbon dioxide, making the photosynthetic process more efficient than it is in most other algae and plants.

The researchers also found that the pyrenoid, long thought to be a solid structure, actually behaves like a liquid droplet that can dissolve into the surrounding cellular medium when the algal cells divide.

 

"Understanding how algae can concentrate carbon dioxide is a key step toward the goal of improving photosynthesis in other plants," said study leader Martin Jonikas, an assistant professor of molecular biology at Princeton and former Carnegie staff associate. "If we could engineer other crops to concentrate carbon, we could address the growing world demand for food.”

Aquatic algae and a handful of other plants have developed carbon-concentrating mechanisms that boost the rate of photosynthesis, the process by which plants turn carbon dioxide and sunlight into sugars for growth. All plants use an enzyme called Rubisco to "fix" carbon dioxide into sugar that can be used or stored by the plant.

 

Algae have an advantage over many land plants because they cluster the Rubisco enzymes inside the pyrenoid, where the enzymes encounter high concentrations of carbon dioxide pumped in from the air. Having more carbon dioxide around allows the Rubisco enzymes to work faster.

 

In one study, the researchers conducted a sweeping search for proteins involved in the carbon-concentrating mechanism of an algae species known as Chlamydomonas reinhardtii. The researchers developed methods for rapidly labeling and evaluating algal proteins, which they used to identify their locations and functions, detailing the physical interactions between the proteins to create a pyrenoid "interactome."

 

The search revealed 89 new pyrenoid proteins, including ones that the researchers think usher carbon into the pyrenoid and others that are required for formation of the pyrenoid. They also identified three previously unknown layers of the pyrenoid that surround the organelle like the layers of an onion.

 

"The information represents the best assessment yet of how this essential carbon-concentrating machinery is organized and suggests new avenues for exploring how it works," said Luke Mackinder, the study's first author and a former Carnegie McClintock postdoctoral fellow who now leads a team of researchers at the University of York.

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Massively Parallel De Novo Protein Design for Targeted Therapeutics

Massively Parallel De Novo Protein Design for Targeted Therapeutics | Amazing Science | Scoop.it

Researchers say they have developed a technique to generate many small, different proteins that can be designed to bind to therapeutic targets. They add that their methodology, which reportedly produces thousands of new drug candidates, may lead to protection against infectious diseases, such as influenza, and antidotes to nerve toxins.

 

The computer-designed proteins, which did not previously exist in nature, combine the stability and bioavailability of small-molecule drugs with the specificity and potency of larger biologics, according to David Baker, Ph.D., who led the multi-institutional research project and is professor of biochemistry at the University of Washington School of Medicine and director of the UW Institute for Protein Design

 

"These mini-protein binders have the potential of becoming a new class of drugs that bridge the gap between small-molecule drugs and biologics. Like monoclonal antibodies, they can be designed to bind to targets with high selectivity, but they are more stable and easier to produce and to administer," said Dr. Baker who with colleagues published their study in Nature ("Massively Parallel De Novo Protein Design for Targeted Therapeutics").

 

The technique relies on the Rosetta computer platform, developed by Dr. Baker and colleagues at the University of Washington. They designed thousands of short proteins, about 40 amino acids in length, that the Rosetta program predicted would bind tightly to the molecular target.

 

Computer modeling identified the amino acid sequences of thousands of short proteins that would fit into and bind to the influenza and botulinum targets. The team created short pieces of DNA that coded each of these proteins, grew the proteins in yeast cells, and then looked at how tightly they bound to their targets. The targets were Influenza H1 hemagglutinin and botulinum neurotoxin B. 

 

The technique allowed them to design and test 22,660 proteins in just a few months, with more than than 2000 of them bound to their targets with high affinity, according to Dr. Baker. He pointed out that of the best candidates found the anti-influenza proteins neutralized viruses in cell culture and other designed proteins prevented the botulinum toxin from entering brain cells.

 

A nasal spray containing one of the custom-designed proteins completely protected mice from the flu if administered before or as much as 72 hours after exposure. The protection that the treatment provides equaled or surpassed that seen with antibodies, the researchers report.

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San Diego Startup Uses Algae Feedstock to Make Renewable Flip-Flops

San Diego Startup Uses Algae Feedstock to Make Renewable Flip-Flops | Amazing Science | Scoop.it

Every year, petroleum-based feedstocks are used worldwide to make roughly 3 billion flip-flops, the rubbery, flat-sole sandals held on the foot by a Y-shaped strap that fits between the first and second toes.

 

It might seem like a throwaway product—and it is, according to Stephen Mayfield, a UC San Diego professor of biology and director of the California Center for Algae Biotechnology. The petrochemicals used to produce flip-flops make them impervious to the elements—and they end up as non-biodegradable rubbish in rivers and oceans, and in landfills and trash heaps. Yet flip-flops also are the No. 1 shoe in the world. “These are the shoes of a fisherman and a farmer,” Mayfield says. “This is the No. 1 shoe in India, the No. 1 shoe in China, and the No. 1 shoe in Africa.”

 

So Mayfield and colleagues at UC San Diego recently unveiled prototype flip-flopsmade from algae-derived polymeric polyols instead of petroleum-based polyurethanes. The idea is to offer consumers more environmentally friendly flip-flops, made with renewable materials and perhaps even biodegradable after a year or two.

 

Mayfield, who was a scientific co-founder of the unsuccessful algal biofuel company Sapphire Energy, worked with UC San Diego chemists Michael Burkart and Robert “Skip” Pomeroy to make a pliable foam from algae-based polyols that could replace conventional polyurethanes. To advance the commercial prospects for biodegradable flip-flops, Mayfield, Burkart, and Pomeroy founded an industrial biotech, Algenesis Materials, in early 2016.

 

“Our goal is to get to 100 percent renewable, and 100 percent biodegradable,” said Mayfield, who is an environmentally conscious surfer and coastal enthusiast. “Burkart’s convinced that we’re going to throw these [flip-flops] in a compost pile, and in six months they’ll be gone. But we’re not there yet.”

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CRISPR-Cas9 fixes Duchenne muscular dystrophy mutation in mice

CRISPR-Cas9 fixes Duchenne muscular dystrophy mutation in mice | Amazing Science | Scoop.it

Scientists at the University of California, Berkeley, have engineered a new way to deliver CRISPR-Cas9 gene-editing technology inside cells and have demonstrated in mice that the technology can repair the mutation that causes Duchenne muscular dystrophy, a severe muscle-wasting disease.

 

A new study shows that a single injection of CRISPR-Gold, as the new delivery system is called, into mice with Duchenne muscular dystrophy led to an 18-times-higher correction rate and a two-fold increase in a strength and agility test compared to control groups.

 

Since 2012, when study co-author Jennifer Doudna, a professor of molecular and cell biology and of chemistry at UC Berkeley, and colleague Emmanuelle Charpentier, of the Max Planck Institute for Infection Biology, repurposed the Cas9 protein to create a cheap, precise and easy-to-use gene editor, researchers have hoped that therapies based on CRISPR-Cas9 would one day revolutionize the treatment of genetic diseases. Yet developing treatments for genetic diseases remains a big challenge in medicine. This is because most genetic diseases can be cured only if the disease-causing gene mutation is corrected back to the normal sequence, and this is impossible to do with conventional therapeutics.

 

CRISPR/Cas9, however, can correct gene mutations by cutting the mutated DNA and triggering homology-directed DNA repair. However, strategies for safely delivering the necessary components (Cas9, guide RNA that directs Cas9 to a specific gene, and donor DNA) into cells need to be developed before the potential of CRISPR-Cas9-based therapeutics can be realized. A common technique to deliver CRISPR-Cas9 into cells employs viruses, but that technique has a number of complications. CRISPR-Gold does not need viruses.

 

In the new study, research lead by the laboratories of Berkeley bioengineering professors Niren Murthy and Irina Conboy demonstrated that their novel approach, called CRISPR-Gold because gold nanoparticles are a key component, can deliver Cas9 – the protein that binds and cuts DNA – along with guide RNA and donor DNA into the cells of a living organism to fix a gene mutation.

 

“CRISPR-Gold is the first example of a delivery vehicle that can deliver all of the CRISPR components needed to correct gene mutations, without the use of viruses,” Murthy said.

 

The study was published October 2 in the journal Nature Biomedical Engineering.

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Largest virtual universe created involving 10 trillion digital particles

Largest virtual universe created involving 10 trillion digital particles | Amazing Science | Scoop.it

A team of researchers with the Chinese Academy of Sciences in Beijing has announced that it has broken a record set just last month by a team at the University of Zurich in Switzerland.

 

Since the advent of computers, space scientists have attempted to use them to create a virtual, or simulated universe. The idea is that if the universe can be simulated, it can be better studied because it can be observed over manipulated time from its birth to today. The problem with simulating the universe, of course, is that it is made up of so much stuff. Such simulations are known in the field as N-body simulations, because they become more intense as more particles are added. During the early years of such efforts, in the 1970s, computers could only handle on the order of a thousand particles. That number increased to the trillions over the past few years as computers have grown ever more powerful.

 

The researchers with this new effort used the most powerful computer available in the world today, the Sunway TaihuLight supercomputer, built by China and based in Wuxi. Officials with the project told the press that the team had simulated the universe from birth to early expansions (approximately ten million years after the Big Bang) over the course of one hour and that the effort involved 10 trillion digital particles. The result was a virtual universe five times as big as the one created by the team in Switzerland just last month.

 

The supercomputer gets its speed by utilizing millions of CPU cores—each able to carry out instructions independently. During the creation of the virtual universe, the team was able to make use of 10 million cores, which they described "as lots of calculations."

 

The researchers also reported that because of the unique architecture of the Sunway TaihuLight, the team had to write almost all of the software for the project from scratch—a very labor-intensive task. They also noted that the supercomputer encountered no problems and that the simulation was terminated after just an hour because another team had booked time on the computer.

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Researchers invent camouflaged membrane that hides like an octopus

Researchers invent camouflaged membrane that hides like an octopus | Amazing Science | Scoop.it

No other animal has mastered camouflage like the octopus. The mightiest of these morphing creatures, the mimic octopus, contorts its body into a thin ribbon and adopts the colors of a venomous sea serpent to scare predators away. Divers have seen mimic octopuses masquerade as lion fish, sea stars, shrimp and anemones. When peckish, the octopus takes the form of a lusty crab. Crustaceans fooled by the display end up eaten.

 

Octopuses are covered in muscly bundles called papillae, Hanlon and his colleagues documented in the Journal of Morphology in 2014. The papillae go slack when an octopus wants to decrease the drag of water against skin, allowing it to speed away in a hurry. Contractions cause fleshy nubs to appear, and the skin bulges. Octopuses can match the texture of seaweed so closely they become almost invisible.

 

Materials scientists and engineers also have fallen under the octopuses' spell. A team of Cornell University researchers, with the aid of octopus expert Roger Hanlon, successfully mimicked the mimic using sheets of rubber and mesh.

 

As they report in a study published Thursday in the journal Science, the researchers created a thin membrane that contorts into complex 3-D shapes — much like the shape-shifting skin of an octopus. The membranes can inflate in seconds to the shapes of everyday objects, such as potted plants or a cluster of stones.

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Scientists discover more than 600 new periodic orbits of the famous three body problem

Scientists discover more than 600 new periodic orbits of the famous three body problem | Amazing Science | Scoop.it

The famous three-body problem can be traced back to Isaac Newton in 1680s, thereafter Lagrange, Euler, Poincare and so on. Studies on the three-body problem leaded to the discovery of the so-called sensitivity dependence of initial condition (SDIC) of chaotic dynamic system. Nowadays, the chaotic dynamics is widely regarded as the third great scientific revolution in physics in 20th century, comparable to the relativity and the quantum mechanics. Thus, the studies on three-body problem have very important scientific meanings.

 

Poincaré in 1890 revealed that trajectories of three-body systems are commonly non-periodic, i.e. not repeating. This can explain why it is so hard to gain periodic orbits of three-body system. In the 300 years since three-body problem was first recognized, only three families of periodic orbits had been found, until 2013 when Suvakov and Dmitrasinovic [Phys. Rev. Lett. 110, 114301 (2013)] made a breakthrough to numerically find 13 new distinct periodic orbits, which belong to 11 new families of Newtonian planar three-body problem with equal mass and zero angular momentum (see http://www.sciencemag.org/news/2013/03/physicists-discover-whopping-13-new-solutions-three-body-problem).

 

Currently, two scientists, XiaoMing Li and ShiJun Liao at Shanghai Jiaotong University, China, successfully gained 695 families of periodic orbits of the above-mentioned Newtonian planar three-body system by means of national supercomputer TH-2 at Guangzhou, China, which are published online via SCIENCE CHINA-Physics Mechanics Astronomy, 2017, Vol. 60, No. 12: 129511. The movies of these orbits are given on the website http://numericaltank.sjtu.edu.cn/three-body/three-body.htm

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A Breakthrough in Packing Higher Dimensional Spheres

How do you stack hundred-dimensional oranges? Learn about recent breakthroughs in our understanding of hyperspheres in the first episode of Infinite Series, a show that tackles the mysteries and the joy of mathematics. From Logic to Calculus, from Probability to Projective Geometry, Infinite Series both entertains and challenges its viewers to take their math game to the next level.

 

Higher dimensional spheres, or hyperspheres, are counter-intuitive and almost impossible to visualize. Mathematician Kelsey Houston-Edwards explains higher dimensional spheres and how recent revelations in sphere packing have exposed truths about 8 and 24 dimensions that we don't even understand in 4 dimensions.

Sphere Packing in Higher Dimensions - Quanta Magazine
https://www.quantamagazine.org/201603...

Why You Should Care about High-Dimensional Sphere Packing - Scientific American
https://blogs.scientificamerican.com/...

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A trick to visualizing higher dimensions

How do you think about a sphere in four dimensions? What about ten dimensions? Problem driven learning on at https://brilliant.org/3b1b

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