Amazing Science

The LHCb experiment finds intriguing anomalies in the way some particles decay. If confirmed, these would be a sign of new physics phenomena not predicted by the Standard Model of particle physics. 

In a recent seminar at CERN, the LHCb collaboration presented new long-awaited results on a particular decay of B0 mesons produced in collisions at the Large Hadron Collider. The Standard Model of particle physics predicts the probability of the many possible decay modes of B0 mesons, and possible discrepancies with the data would signal new physics.

In this study, the LHCb collaboration looked at the decays of B0 mesons to an excited kaon and a pair of electrons or muons. The muon is 200 times heavier than the electron, but in the Standard Model its interactions are otherwise identical to those of the electron, a property known as lepton universality. Lepton universality predicts that, up to a small and calculable effect due to the mass difference, electron and muons should be produced with the same probability in this specific B0 decay. LHCb finds instead that the decays involving muons occur less often.

While potentially exciting, the discrepancy with the Standard Model occurs at the level of 2.2 to 2.5 sigma, which is not yet sufficient to draw a firm conclusion. However, the result is intriguing because a recent measurement by LHCb involving a related decay exhibited similar behavior.

While of great interest, these hints are not enough to come to a conclusive statement. Although of a different nature, there have been many previous measurements supporting the symmetry between electrons and muons. More data and more observations of similar decays are needed in order to clarify whether these hints are just a statistical fluctuation or the first signs for new particles that would extend and complete the Standard Model of particles physics. The measurements discussed were obtained using the entire data sample of the first period of exploitation of the Large Hadron Collider (Run 1). If the new measurements indeed point to physics beyond the Standard Model, the larger data sample collected in Run 2 will be sufficient to confirm these effects.

A new study published in the journal Astrobiology seeks to integrate new exoplanet data as part of the Drake Equation while demonstrating the role of “pessimism” and “optimism” in estimating the odds of finding E.T. (you don’t find what you don’t look for).

“The question of whether advanced civilizations exist elsewhere in the universe has always been vexed with three large uncertainties in the Drake equation,” said University of Rochester astronomer and study coauthor Adam Frank in a statement. “We’ve known for a long time approximately how many stars exist. We didn’t know how many of those stars had planets that could potentially harbor life, how often life might evolve and lead to intelligent beings, and how long any civilizations might last before becoming extinct.”

Estimates derived by projects running under NASA’s Kepler satellite and a few other instruments suggest that out of the estimated 2 x 10^22 stars in the known universe, 20 percent have planets that reside in habitable zones that have temperatures, atmospheres, and other traits that could support life. So that takes care of one uncertainty.

That leaves two other questions:

1. How often would life evolve?
2. How long could those civilizations survive for?

That last one is a particularly tough question to answer, since we can only really work off the history of human civilization — and we haven’t died off yet. That’s where the notion of pessimism and optimism arise. Frank and Sullivan write that their method requires only establishing how low the probability that humans are the only intelligent species to have ever evolved is. They call this the pessimism line. “If the actual probability is greater than the pessimism line,” said Frank, “then a technological species and civilization has likely happened before.”

Using current SETI and exoplanet data, Frank and Sullivan ended up calculating this number at one in 10 billion trillion. That’s incredibly small — which means the odds that another intelligent species has evolved are very, very good. “Think of it this way,” said Frank. “Before our result you’d be considered a pessimist if you imagined the probability of evolving a civilization on a habitable planet were, say, one in a trillion. But even that guess, one chance in a trillion, implies that what has happened here on Earth with humanity has in fact happened about a 10 billion other times over cosmic history!”

The researchers emphasize that this revised interpretation of the Drake equation accounts for the entire 13.78 billion year history of the universe — while the original localizes the odds of finding E.T. to the present day. That being said, optimism for finding alien life has never been higher. After all, three famous names just started a multi-million dollar project to look for aliens in Alpha Centauri — the closest star system to the Earth — and some prominent scientists think there’s a good chance we’ll find something special. There’s certainly never been a time to be an E.T. optimist.

Delivering life-saving drugs directly to the brain in a safe and effective way is a challenge for medical providers. One key reason: the blood-brain barrier, which protects the brain from tissue-specific drug delivery. Methods such as an injection or a pill aren’t as precise or immediate as doctors might prefer, and ensuring delivery right to the brain often requires invasive, risky techniques.

A team of engineers from Washington University in St. Louis has developed a new nanoparticle generation-delivery method that could someday vastly improve drug delivery to the brain, making it as simple as a sniff.

“This would be a nanoparticle nasal spray, and the delivery system could allow a therapeutic dose of medicine to reach the brain within 30 minutes to one hour,” said Ramesh Raliya, research scientist at the School of Engineering & Applied Science.

“The blood-brain barrier protects the brain from foreign substances in the blood that may injure the brain,” Raliya said. “But when we need to deliver something there, getting through that barrier is difficult and invasive. Our non-invasive technique can deliver drugs via nanoparticles, so there’s less risk and better response times.”

The novel approach is based on aerosol science and engineering principles that allow the generation of monodisperse nanoparticles, which can deposit on upper regions of the nasal cavity via diffusion. Working with Assistant Vice Chancellor Pratim Biswas, chair of the Department of Energy, Environmental & Chemical Engineering and the Lucy & Stanley Lopata Professor, Raliya developed an aerosol consisting of gold nanoparticles of controlled size, shape and surface charge. The nanoparticles were tagged with fluorescent markers, allowing the researchers to track their movement.

Next, Raliya and biomedical engineering postdoctoral fellow Debajit Saha exposed locusts’ antennae to the aerosol, and observed the nanoparticles travel from the antennas up through the olfactory nerves. Due to their tiny size, the nanoparticles passed through the brain-blood barrier, reaching the brain and suffusing it in a matter of minutes.

When Boston Dynamics introduced its massively upgraded Atlas last year, we said the robot could “do things we’ve never seen other robots doing before, making it one of the most advanced humanoids in existence.” But now, after seeing the video that Boston Dynamics just released to officially unveil its newest creation, Handle, a sort of Atlas on wheels, we’ll just say it again: Handle can do things we’ve never seen other robots doing before, making it one of the most advanced humanoids in existence.

Boston Dynamics’ wheeled Handle robot received much fanfare earlier this month when DFJ partner Steve Jurvetson slipped us an early video from a company Keynote. Handle can manage some pretty sick hurdles and spins, but the new video shows how the robot can operate in tough environments — on hills, in the snow and over uneven terrain. It’s able to do this with a height of 6.5 feet that surpasses that of most humans. On wheels, it can move at a chipper nine mph and manage four-foot vertical jumps. If you’re wondering, the highest human jump ever recorded is 5.3 feet.

Researchers have discovered a fish venom that contains opioid properties, which could help in the development of new pain-killing drugs. The fierce-looking fang blenny, also known as the poison-fang blenny or the saber-tooth blenny, fends off predators and competitors by injecting them with a heroin-like substance that impairs them rather than kills them.

"The venom causes the bitten fish to become slower in movement and dizzy by acting on their opioid receptors," said Bryan Fry, who led the study published Tuesday in the science journal Current Biology. Although used for defense, the venom "inhibits pain rather than causing it."

It's not the first time animal poison has been found to have analgesic properties: Ziconotide which was derived from cone snails, is used to treat chronic pain. But it's the first time scientists have identified opioid peptides in fish venom, Fry said. This venom is "chemically unique," which drives home the importance of biodiversity, said Fry of the University of
Queensland.

"This discovery is an excellent example as to why we must urgently protect all of nature," Fry told CBC News. "It is impossible to predict where the next wonder drug will come from."

Advances in high-throughput sequencing are reshaping how we perceive microbial communities inhabiting the human body, with implications for therapeutic interventions. Several large-scale datasets derived from hundreds of human microbiome samples sourced from multiple studies are now publicly available.

However, idiosyncratic data processing methods between studies introduce systematic differences that confound comparative analyses. To overcome these challenges, scientists developed GUTCYC, a compendium of environmental pathway genome databases (ePGDBs) constructed from 418 assembled human microbiome datasets using METAPATHWAYS, enabling reproducible functional metagenomic annotation. They also generated metabolic network reconstructions for each metagenome using the PATHWAYTOOLS software, empowering researchers and clinicians interested in visualizing and interpreting metabolic pathways encoded by the human gut microbiome. For the first time, GUTCYC provides consistent annotations and metabolic pathway predictions, making possible comparative community analyses between health and disease states in inflammatory bowel disease, Crohn’s disease, and type 2 diabetes. GUTCYC data products are searchable online, or may be downloaded and explored locally using METAPATHWAYS and PATHWAY TOOLS.

Brain-computer interfacing is a hot topic in the tech world, with Elon Musk's announcement of his new Neuralink startup. Here, researchers separate what's science from what's currently still fiction.

Just as ancient Greeks fantasized about soaring flight, today’s imaginations dream of melding minds and machines as a remedy to the pesky problem of human mortality. Can the mind connect directly with artificial intelligence, robots and other minds through brain-computer interface (BCI) technologies to transcend our human limitations?

Over the last 50 years, researchers at university labs and companies around the world have made impressive progress toward achieving such a vision. Recently, successful entrepreneurs such as Elon Musk (Neuralink) and Bryan Johnson (Kernel) have announced new startups that seek to enhance human capabilities through brain-computer interfacing.

How close are we really to successfully connecting our brains to our technologies? And what might the implications be when our minds are plugged in?

Eb Fetz, a researcher here at the Center for Sensorimotor Neural Engineering (CSNE), is one of the earliest pioneers to connect machines to minds. In 1969, before there were even personal computers, he showed that monkeys can amplify their brain signals to control a needle that moved on a dial. Much of the recent work on BCIs aims to improve the quality of life of people who are paralyzed or have severe motor disabilities.

You may have seen some recent accomplishments in the news: University of Pittsburgh researchers use signals recorded inside the brain to control a robotic arm. Stanford researchers can extract the movement intentions of paralyzed patients from their brain signals, allowing them to use a tablet wirelessly.

Similarly, some limited virtual sensations can be sent back to the brain, by delivering electrical current inside the brain or to the brain surface.

What about our main senses of sight and sound? Very early versions of bionic eyes for people with severe vision impairment have been deployed commercially, and improved versions are undergoing human trials right now. Cochlear implants, on the other hand, have become one of the most successful and most prevalent bionic implants – over 300,000 users around the world use the implants to hear.

Face2Gene takes advantage of the fact that so many genetic conditions have a tell-tale “face”—a unique constellation of features that can provide clues to a potential diagnosis. It is just one of several new technologies taking advantage of how quickly modern computers can analyze, sort, and find patterns across huge reams of data. They are built in fields of artificial intelligence known as deep learning and neural nets—among the most promising to deliver AI’s 50-year old promise to revolutionize medicine by recognizing and diagnosing disease.

Genetic syndromes aren’t the only diagnoses that could get help from machine learning. The RightEye GeoPref Autism Test can identify the early stages of autism in infants as young as 12 months—the crucial stages where early intervention can make a big difference. Unveiled January 2, 2017 at CES in Las Vegas, the technology uses infrared sensors test the child’s eye movement as they watch a split-screen video: one side fills with people and faces, the other with moving geometric shapes. Children at that age should be much more attracted to faces than abstract objects, so the amount of time they look at each screen can indicate where on the autism spectrum a child might fall.

In validation studies done by the test’s inventor, UC San Diego researcher Karen Pierce,1 the test correctly predicted autism spectrum disorder 86 percent of the time in more than 400 toddlers. That said, it’s still pretty new, and hasn’t yet been approved by the FDA as a diagnostic tool. “In terms of machine learning, it’s the simplest test we have,” says RightEye’s Chief Science Officer Melissa Hunfalvay. “But before this, it was just physician or parent observations that might lead to a diagnosis. And the problem with that is it hasn’t been quantifiable.”

A similar tool could help with early detection of America’s sixth leading cause of death: Alzheimer’s disease. Often, doctors don’t recognize physical symptoms in time to try any of the disease’s few existing interventions. But machine learning hears what doctor’s can’t: Signs of cognitive impairment in speech. This is how Toronto-based Winterlight Labs is developing a tool to pick out hints of dementia in its very early stages. Co-founder Frank Rudzicz calls these clues “jitters,” and “shimmers:” high frequency wavelets only computers, not humans, can hear.

Although the giant shipworm was first categorized as a species more than 200 years ago, no living specimen had been examined by scientists and almost nothing had been known about it. That changed when Daniel Distel, a researcher at Northeastern University, and colleagues got their hands on a handful of the creatures during a research trip to the Philippines. Their analysis, in a study published April 17 in the journal Proceedings of the National Academy of Sciences, shows that these creatures are quite bizarre.

The giant shipworm, or Kuphus polythalamia, live inside large shells on the seafloor and grow to a length of more than five feet. That is much larger than other shipworms, which are generally diminutive. That, of course, led biologists to wonder why these creatures grow so big.

Other shipworms contain bacteria in their guts that break down cellulose, the stiff material of which plant cell walls are made. An investigation by the researchers, including Margo Haygoodof the University of Utah College of Pharmacy, shows that Kuphus polythalamia don’t contain large amounts of these bacteria, nor do they have other shipworms’ hefty quantities of woody pulp in their guts. Rather, these giant weirdos contain a trove of unique bacteria that actually feast upon hydrogen sulfide.

This gas, which to humans reeks of rotten eggs, is produced by festering wood and other rotting organic material in the seafloor. The unique adaption allows these huge animals to live in areas of the seafloor that would otherwise be uninhabitable, and it may also help explain their large size, allowing them to feed on a resource that moves to them, rather than having to move about nibbling wood. 

The targeted supermassive black hole is hidden in plain sight, lurking in the centre of the Milky Way in a region called the Sagittarius constellation, some 26,000 light years from Earth. Dubbed Sagittarius A* (Sgr A* for short), the gravity- and light-sucking monster weighs as much as four million Suns. Theoretical astronomy tells us when a black hole absorbs matter—planets, debris, anything that comes too close—a brief flash of light is visible.

NASA has new evidence that the most likely places to find life beyond Earth are Jupiter's moon Europa or Saturn's moon Enceladus. In terms of potential habitability, Enceladus particularly has almost all of the key ingredients for life as we know it, researchers said. New observations of these active ocean worlds in our solar system have been captured by two NASA missions and were presented in two separate studies in an announcement at NASA HQ in Washington today.

Using a mass spectrometer, the Cassini spacecraft detected an abundance of hydrogen molecules in water plumes rising from the "tiger stripe" fractures in Enceladus' icy surface. Saturn's sixth-largest moon is an ice-encased world with an ocean beneath. The researchers believe that the hydrogen originated from a hydrothermal reaction between the moon's ocean and its rocky core. If that is the case, the crucial chemical methane could be forming in the ocean as well.

"Now, Enceladus is high on the list in the solar system for showing habitable conditions," said Hunter Waite, leader of the Cassini Ion and Neutral Mass Spectrometer team at the Southwest Research Institute in San Antonio and lead author of the Enceladus study. "The presence of hydrogen established another reference point saying there is hydrothermal activity inside this body, and that's interesting because we know in our own oceans, those are very important places that are teeming with life, and they are probably one of the earliest places where life happened on Earth."

Additionally, the Hubble Space Telescope showed a water plume erupting on the warmest part of the surface of Europa, one of Jupiter's moons with an icy crust over a salty liquid water ocean containing twice as much water as Earth's seas. This is the second time a plume has been observed in this exact spot, which has researchers excited that it could prove to be a feature on the surface.

"This is significant, because the rest of the planet isn't easy to predict or understand, and it's happening for the second time in the warmest spot," said Britney Schmidt, second author on the Europa study.

Amazon's Echo, a Bluetooth speaker powered by voice assistant Alexa, burst on to the scene a couple years ago and instantly captured the hearts and minds of consumers. You could hear the collective cry: voice control is finally here! Of course, there was lots of voice control on the market already (including Apple's O.G. Siri), but Alexa was the first out of the gate that promised—and delivered—on making voice commands useful in the home. With "Skills" being developed for a wealth of tasks (and Alexa being built into a lot of smart products like cars, refrigerators and lamps), it's as easy to ask her to tell you the weather or read you news headlines as it is to have her water your lawn, lock your door or order you a pizza.

But Alexa has a new competitor—Google Home. It's a speaker just like Alexa, but its brains are powered by the all-knowing Google Assistant. It's empowered with all that Google knows about search, plus data from other Google apps (like traffic from Google Maps). It can also get personal, alerting you to meetings on your Google Calendar or changes in your flight information by reading your Gmail Inbox.

The options are seemingly endless for these two equally charming and brainy gadgets, but how do their strengths and weaknesses stack up if they were engaged in a little battle? Which of the two would be the most useful?

Many extensions of the Standard Model of particle physics explain the dominance of matter over antimatter in our Universe by neutrinos being their own antiparticles. This would imply the existence of neutrinoless double-β decay, which is an extremely rare lepton-number-violating radioactive decay process whose detection requires the utmost background suppression. Among the programmes that aim to detect this decay, the GERDA Collaboration is searching for neutrinoless double-β decay of 76Ge by operating bare detectors, made of germanium with an enriched 76Ge fraction, in liquid argon.

After having completed Phase I of data taking, scientists have recently launched Phase II and report now that in GERDA Phase II that they have achieved a background level of approximately 10−3 counts keV−1kg−1 yr−1. This implies that the experiment is background-free, even when increasing the exposure up to design level. This is achieved by use of an active veto system, superior germanium detector energy resolution and improved background recognition of our new detectors.

No signal of neutrinoless double-β decay was found when Phase I and Phase II data were combined, and scientists deduce a lower-limit half-life of 5.3 × 1025 years at the 90 per cent confidence level. The half-life sensitivity of 4.0 × 1025 years is competitive with the best experiments that use a substantially larger isotope mass. The potential of an essentially background-free search for neutrinoless double-β decay will facilitate a larger germanium experiment with sensitivity levels that will bring us closer to clarifying whether neutrinos are their own antiparticles.