Amazing Science

Our Milky Way galaxy will survive in its current form a bit longer than some astronomers had thought, a new study suggests. The monster collision between our Milky Way and fellow spiral galaxy Andromeda will occur about 4.5 billion years from now, according to the new research, which is based on observations made by Europe’s Gaia spacecraft. Some prominent previous estimates had predicted the crash would happen significantly sooner, in about 3.9 billion years.

“This finding is crucial to our understanding of how galaxies evolve and interact,” Gaia project scientist Timo Prusti, who was not involved in the study, said in a statement. Gaia launched in December of 2013 to help researchers create the best 3D map of the Milky Way ever constructed. The spacecraft has been precisely monitoring the positions and movements of huge numbers of stars and other cosmic objects; the mission team aims to track more than 1 billion stars by the time Gaia shuts its sharp eyes for good.

Most of the stars Gaia is eyeing are in the Milky Way, but some are in nearby galaxies. In the new study, the researchers tracked a number of stars in our galaxy, in Andromeda (also known as M31) and in the spiral Triangulum (or M33). These neighbor galaxies are within 2.5 million to 3 million light-years of the Milky Way and may be interacting with each other, study team members said.

China has built and tested the world’s first robotic, partially submersible boat equipped with a robust system for launching sounding rockets — a technology used by weather scientists (called meteorologists) to better understand the atmosphere over our planet’s oceans. These tests were conducted in years 2017 + 2018 — and published in 2019.

China’s experiment shows advanced capabilities: navigating hostile marine environments, robotically. And autonomously deploying rockets on-target to complete science missions — in places too dangerous or impassable for human teams to go.

This combination of un-manned sea travel — plus a complex, remotely-managed rocket launch — is a clear demonstration of what’s to come. China’s successful test heralds a new era of at-a-distance robotics: with applications in defense, search + rescue, exploration, off-shore drilling, ocean fleet management, environmental protection, and a variety of command-and-control systems.

The test is a non-trivial display of the power of automation. The robotic vessel carried extensive electronic instrumentation, requiring high levels of co-ordination + expertise by remote human operators.

Since the crew isn’t physically there on-location: designers of enormous, computerized, mechanical systems of the future can train teams of engineers who won’t be limited by environmental hazard or distance.

he un-manned ship and its rocket system. China’s ship is technically classified as an “un-manned semi-submersible vehicle.” It’s designed to:

• sail directly into rough marine weather
• deploy a sounding rocket
• collect essential data on the atmosphere + ocean

The ship launched a key tool in weather research called sounding rockets. These rockets make brief flights through different layers of Earth’s atmosphere, carrying meteorological equipment as high as 5 miles above the ocean — higher than weather balloons. Scientific instruments carried by the rockets make real-time measurements of the sea surface temperature — plus profiles of pressure, humidity, wind speed + wind direction.

The Mexican tetra is a creature that spend most of its live in dark caves after its ancestors swam from surface waters into their caves around 1.5 million years ago. Like naked mole rats—another species that lives underground, in perennial darkness—they have no eyes. But whereas key genes controlling eye development in naked mole rats have mutations that inactivate them, there are no such inactivating mutations in the genes of the Mexican cave fish.

But mutations aren't the only way to change gene activity, and new research suggests a different explanation for the fish's lack of eyes. Epigenetic regulation is a means of controlling gene activity that does not alter the DNA sequence of the genes themselves.

Genes undergoing epigenetic regulation can still make normal proteins, but the amount of the protein they make is modulated. One method of epigenetic regulation is the addition of methyl groups to the DNA that controls the activity of specific genes. It is efficient, since it can be used to alter a whole bunch of genes at once. And it seems to explain the Mexican cave fish eye degeneration that has occurred over the past million years—a proverbial blink of an eye in evolutionary terms.

These cave fish have elevated levels of an enzyme that adds methyl groups to DNA compared to surface fish. This enzyme, called a DNA methylase, is expressed in the developing eye, where it decorates genes important in eye development with methyl groups. This reduces their expression to about half of the levels seen in surface fish.

A number of the methylated genes are known to be lost or defective in human eye disorders like colorblindness, night blindness, and even complete blindness. One of these genes (Pax6) controls the expression of a whole host of other eye genes, amplifying the effect.

There's evidence that altered methylation is central to the changes in these fish. A drug called 5-azacytidine (5-AzaC) is a potent inhibitor of DNA methylation (it's used by people with myelodysplastic syndrome, a rare disorder in which blood cells do not mature properly). Injections of the drug into cave fish embryo eyes could partially rescue their development, confirming that their loss is due to changes in methylation rather than mutations or gene loss.

While this sounds like an evolutionary change that isn't reliant on mutations, that may not be the case. The genetic mechanism responsible for the upregulation of the methylating enzyme in cave fish is not yet known. It's likely that some changes in DNA sequences were involved there.

Nature Ecology and Evolution, 2018. DOI: 10.1038/s41559-018-0569-4 (About DOIs).

CRISPR/Cas9 is a form of genetic editing that holds a lot of promise, such as the killing of cancer cells, but also comes with some hefty warnings, such as that it may cause DNA damage. So far, scientists have been using CRISPR/Cas9 in a variety of plants and animals to edit genetic information, including attempts to practice what is called 'active genetics'.

This last approach is an attempt to edit the genome that controls which of the two copies of a gene is passed to the next generation. But the technique is complicated and rife with obstacles so thus far been used only on insects. Not anymore!

A world first achievement

A team of biologists has now achieved the world's first CRISPR/Cas9-based approach to control genetic inheritance in a mammal. "Our motivation was to develop this as a tool for laboratory researchers to control the inheritance of multiple genes in mice," said project lead Assistant Professor at University of California San Diego Kimberly Cooper. "With further development we think it will be possible to make animal models of complex human genetic diseases, like arthritis and cancer, that are not currently possible."

To achieve their lofty goals, the researchers engineered an active genetic "CopyCat" DNA element into the gene responsible for fur color in mice and successfully succeeded in controlling mice fur color, making it white instead of black. Then, over a two-year period, they expanded their work to successfully determine that the CopyCat element could be copied from one chromosome to the other in order to repair a break in the DNA targeted by CRISPR/Cas9.

As a result, they found that as much as 86 percent of the mice offspring inherited the CopyCat element from the female parent. This was a great improvement on the usual 50 percent naturally achieved.

Using a common type of brain scan, researchers programmed a machine-learning algorithm to diagnose early-stage Alzheimer’s disease about six years before a clinical diagnosis is made – potentially giving doctors a chance to intervene with treatment.

No cure exists for Alzheimer’s disease, but promising drugs have emerged in recent years that can help stem the condition’s progression. However, these treatments must be administered early in the course of the disease in order to do any good. This race against the clock has inspired scientists to search for ways to diagnose the condition earlier.

“One of the difficulties with Alzheimer’s disease is that by the time all the clinical symptoms manifest and we can make a definitive diagnosis, too many neurons have died, making it essentially irreversible,” says Jae Ho Sohn, MD, MS, a resident in the Department of Radiology and Biomedical Imaging at UC San Francisco. One of the difficulties with Alzheimer’s disease is that by the time all the clinical symptoms manifest and we can make a definitive diagnosis, too many neurons have died, making it essentially irreversible.

In a recent study, published in Radiology, Sohn combined neuroimaging with machine learning to try to predict whether or not a patient would develop Alzheimer’s disease when they first presented with a memory impairment – the best time to intervene.

Positron emission tomography (PET) scans, which measure the levels of specific molecules, like glucose, in the brain, have been investigated as one tool to help diagnose Alzheimer’s disease before the symptoms become severe. Glucose is the primary source of fuel for brain cells, and the more active a cell is, the more glucose it uses. As brain cells become diseased and die, they use less and, eventually, no glucose. Other types of PET scans look for proteins specifically related to Alzheimer’s disease, but glucose PET scans are much more common and cheaper, especially in smaller health care facilities and developing countries, because they’re also used for cancer staging.

Radiologists have used these scans to try to detect Alzheimer’s by looking for reduced glucose levels across the brain, especially in the frontal and parietal lobes of the brain. However, because the disease is a slow progressive disorder, the changes in glucose are very subtle and so difficult to spot with the naked eye.

To solve this problem, Sohn applied a machine learning algorithm to PET scans to help diagnose early-stage Alzheimer’s disease more reliably. “This is an ideal application of deep learning because it is particularly strong at finding very subtle but diffuse processes. Human radiologists are really strong at identifying tiny focal finding like a brain tumor, but we struggle at detecting more slow, global changes,” says Sohn. “Given the strength of deep learning in this type of application, especially compared to humans, it seemed like a natural application.”

To train the algorithm, Sohn fed it images from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), a massive public dataset of PET scans from patients who were eventually diagnosed with either Alzheimer’s disease, mild cognitive impairment or no disorder. Eventually, the algorithm began to learn on its own which features are important for predicting the diagnosis of Alzheimer’s disease and which are not.

Once the algorithm was trained on 1,921 scans, the scientists tested it on two novel datasets to evaluate its performance. The first were 188 images that came from the same ADNI database but had not been presented to the algorithm yet. The second was an entirely novel set of scans from 40 patients who had presented to the UCSF Memory and Aging Center with possible cognitive impairment.

The algorithm performed with flying colors. It correctly identified 92 percent of patients who developed Alzheimer’s disease in the first test set and 98 percent in the second test set. What’s more, it made these correct predictions on average 75.8 months – a little more than six years – before the patient received their final diagnosis.

An innovative combination therapy can force malignant breast cancer cells to turn into fat cells. This can be used to prevent the formation of metastases in mice, as researchers at the University of Basel’s Department of Biomedicine recently reported in the journal Cancer Cell.

Most of Earth's essential elements for life—including most of the carbon and nitrogen in you—probably came from another planet.

Earth’s status as the only life-sustaining planet is a result of the timing and delivery mechanism of carbon (C), nitrogen (N), sulfur (S), and hydrogen (H). On the basis of their isotopic signatures, terrestrial volatiles are thought to have derived from carbonaceous chondrites, while the isotopic compositions of nonvolatile major and trace elements suggest that enstatite chondrite–like materials are the primary building blocks of Earth. However, the C/N ratio of the bulk silicate Earth (BSE) is superchondritic, which rules out volatile delivery by a chondritic late veneer. In addition, if delivered during the main phase of Earth’s accretion, then, owing to the greater siderophile (metal loving) nature of C relative to N, core formation should have left behind a subchondritic C/N ratio in the BSE.

Scientists now present high pressure-temperature experiments to constrain the fate of mixed C-N-S volatiles during core-mantle segregation in the planetary embryo magma oceans and show that C becomes much less siderophile in N-bearing and S-rich alloys, while the siderophile character of N remains largely unaffected in the presence of S. Using the new data and inverse Monte Carlo simulations, they were able to show that the impact of a Mars-sized planet, having minimal contributions from carbonaceous chondrite-like material and coinciding with the Moon-forming event, can be the source of major volatiles in the BSE.

Cave-inhabiting animals are often categorized as troglobites (cave-limited species), troglophiles (species that can live their entire lives in caves, but also occur in other environments), trogloxenes (species that use caves, but cannot complete their life cycle fully in caves) and accidentals (animals not in one of the previous categories). Some scientists use a separate terminology for aquatic forms (e.g., stygobites, stygophiles, and stygoxenes).

It’s not just new species cavers and scientists are discovering, but also higher groups of animals including a new class, orders, families and genera, previously unknown from any other habitat on the planet. Some of our newfound animals have close relatives living in similar caves on opposite margins of the Atlantic Ocean or even the far side of the Earth (such as the Bahamas versus Western Australia).

While most of these caves are formed in limestone, they can also include seawater-flooded lava tubes created by volcanic eruptions. Amazingly, similar types of animals inhabit both.

In the deserts of West Texas, cavers have discovered and explored the deepest underwater cave in the U.S., reaching a depth of 462 feet. They have uncovered the nature of chemosynthetic processes in caves – how microorganisms use energy from chemical bonds, rather than light energy as in photosynthesis, to produce organic matter – and their significance to the cave food web.

Other scientists are examining records of Ice Age sea level history held in cave sediments, as well as the presence of tree roots penetrating into underwater caves and their importance to the overlying tropical forest. What they are finding is evidence that sister species of cave animals on opposite shores of the Atlantic separated from one another about 110 million years ago as tectonic plate movements initiated the opening of the Atlantic, as well as determining how environmental and ecological factors affect the abundance and diversity of animals in saltwater caves.

This research is important and has significant implications, especially concerning endangered species and environmental protection. Since many cave animals occur only in a single cave and nowhere else on Earth, pollution or destruction of caves can result in species extinctions. Unfortunately, the creation of many protected areas and nature reserves failed to take cave species into account.

Researchers have found bees can do basic mathematics, in a discovery that expands our understanding of the relationship between brain size and brain power. Building on their finding that honeybees can understand the concept of zero, Australian and French researchers set out to test whether bees could perform arithmetic operations like addition and subtraction.

Solving maths problems requires a sophisticated level of cognition, involving the complex mental management of numbers, long-term rules and short term working memory. The revelation that even the miniature brain of a honeybee can grasp basic mathematical operations has implications for the future development of Artificial Intelligence, particularly in improving rapid learning.

Led by researchers from RMIT University in Melbourne, Australia, the new study showed bees can be taught to recognize colors as symbolic representations for addition and subtraction, and that they can use this information to solve arithmetic problems.

RMIT's Associate Professor Adrian Dyer said numerical operations like addition and subtraction are complex because they require two levels of processing. "You need to be able to hold the rules around adding and subtracting in your long-term memory, while mentally manipulating a set of given numbers in your short-term memory," Dyer said.

"On top of this, our bees also used their short-term memories to solve arithmetic problems, as they learned to recognize plus or minus as abstract concepts rather than being given visual aids.

"Our findings suggest that advanced numerical cognition may be found much more widely in nature among non-human animals than previously suspected.

Plants could soon provide our electricity. In a small way they already are doing that in research labs and greenhouses at project Plant-e — a university and commercially sponsored research group at Wageningen University in the Netherlands.

The Plant Microbial Fuel Cell from Plant-e can generate electricity from the natural interaction between plant roots and soil bacteria. It works by taking advantage of the up to 70 percent of organic material produced by a plant’s photo-synthesis process that cannot be used by the plant — and is excreted through the roots.

As natural occurring bacteria around the roots break down this organic residue, electrons are released as a waste product. By placing an electrode close to the bacteria to absorb these electrons, the research team — led by Marjolein Helder PhD — is able to generate electricity.

Helder said: “Solar panels are making more energy per square meter — but we expect to reduce the costs of our system technology in the future. And our system can be used for a variety of applications.”

Plant Microbial Fuel Cells can be used on many scales. An experimental 15 square meter model can produce enough energy to power a computer notebook. Plant-e is working on a system for large scale electricity production in existing green areas like wetlands and rice paddy fields.

Helder said: “Our technology is making electricity — but also could be used as roof insulation or as a water collector. On a bigger scale it’s possible to produce rice and electricity at the same time, and in that way combine food and energy production.”

If everyone on the planet were to step on one side of a giant balance scale, and all the bacteria on Earth were to be placed on the other side, we’d shoot violently upward. That’s because all the bacteria on Earth combined are about 1,166 times more massive than all the humans.

Comparisons to other categories of life similarly demonstrate how very, very small we are. As a sweeping recent study in the Proceedings of the National Academy of Sciences finds, in a census sorting all the life on Earth by weight (measured in gigatons of carbon, the signature element of life on Earth), we make up less than 1 percent of life.

There are an estimated 550 gigatons of carbon of life in the world. A gigaton is equal to a billion metric tons. A metric ton is 1,000 kilograms, or about 2,200 pounds.

We’re talking in huge, huge, mind-boggling terms here. So, using the data in PNAS, we tried to visualize the weight of all life on Earth to get a sense of the scale of it all.

Scientists have come out with an estimate of how much water might be available in near-Earth asteroids. A new study in the Journal of Geophysical Research: Planets, a publication of the American Geophysical Union, suggests there are between 26 and 80 hydrated near-Earth asteroids larger than a kilometer in diameter. Of those, 8 to 26 of the asteroids are easier to get to than the surface of the Moon. The new study also estimates there are between 350 and 1,050 smaller hydrated objects easier to reach than the Moon.

The study’s authors estimate there are between 400 and 1200 billion kilograms (440 to 1.3 billion U.S. tons) of water that could be extracted from the minerals in these asteroids. In liquid terms, that’s between 400 billion and 1,200 billion liters (100 billion and 400 billion U.S. gallons) of water. That’s enough to fill between 160,000 and 480,000 Olympic-sized swimming pools.

Asteroids are rocks in orbit the Sun, generally between Mars and Jupiter, while comets are made up of rock and ice and originate in the outer solar system. Both asteroids and comets are made up of material from the early formation of the solar system.

Approximately 19,000 near-Earth asteroids of various sizes have been discovered. Water in asteroids can provide hints about the nature of the early solar system, including clues about where Earth’s water and the Moon’s polar ice came from. It could also supply water and fuel to future interplanetary space missions, according to the authors of the new study.

“We know that there are minerals with water in them on asteroids. We know that from meteorites that have fallen to the ground.” said Andrew Rivkin of Johns Hopkins University Applied Physics Research Laboratory in Laurel, Maryland. Rivkin is the lead author on the new paper with F. E. DeMeo, of MIT. “It’s also possible that Earth’s water came largely from impacts.”

UC San Francisco researchers have for the first time transformed human stem cells into mature insulin-producing cells, a major breakthrough in the effort to develop a cure for type 1 (T1) diabetes. 

Replacing these cells, which are lost in patients with T1 diabetes, has long been a dream of regenerative medicine, but until now scientists had not been able to figure out how to produce cells in a lab dish that work as they do in healthy adults.

“We can now generate insulin-producing cells that look and act a lot like the pancreatic beta cells you and I have in our bodies. This is a critical step towards our goal of creating cells that could be transplanted into patients with diabetes,” said Matthias Hebrok, PhD, the Hurlbut-Johnson Distinguished Professor in Diabetes Research at UCSF and director of the UCSF Diabetes Center.

The new study is published Feb. 1, 2019, in Nature Cell Biology.

A new study using data from NASA's Chandra X-ray Observatory and ESA's XMM-Newton suggests that dark energy may have varied over cosmic time, as reported in our latest press release. This artist's illustration helps explain how astronomers tracked the effects of dark energy to about one billion years after the Big Bang by determining the distances to quasars, rapidly growing black holes that shine extremely brightly.

First discovered about 20 years ago by measuring the distances to exploded stars called supernovas, dark energy is a proposed type of force, or energy, that permeates all space and causes the expansion of the Universe to accelerate. Using this method, scientists tracked the effects of dark energy out to about 9 billion years ago.

The latest result stems from the development of a new method to determine distances to about 1,598 quasars, which allows the researchers to measure dark energy's effects from the early Universe through to the present day. Two of the most distant quasars studied are shown in Chandra images in the insets.

The new technique uses ultraviolet (UV) and X-ray data to estimate the quasar distances. In quasars, a disk of matter around the supermassive black hole in the center of a galaxy produces UV light (shown in the illustration in blue).

Some of the UV photons collide with electrons in a cloud of hot gas (shown in yellow) above and below the disk, and these collisions can boost the energy of the UV light up to X-ray energies. This interaction causes a correlation between the amounts of observed UV and X-ray radiation. This correlation depends on the luminosity of the quasar, which is the amount of radiation it produces.

Using this technique the quasars become standard candles, as implied by the artist's illustration. Once the luminosity is known, the distance to the quasars can be calculated from the observed amount of radiation.

The researchers compiled UV data for 1,598 quasars to derive a relationship between UV and X-ray fluxes, and the distances to the quasars. They then used this information to study the expansion rate of the universe back to very early times, and found evidence that the amount of dark energy is growing with time.

Newborn babies are born with the innate skills needed to pick out words from language, a new study published in Developmental Science reveals.

Before infants can learn words, they must identify those words in continuous speech. Yet, the speech signal lacks obvious boundary markers, which poses a potential problem for language acquisition. Studies have found that by the middle of the first year, infants seem to have solved this problem, but it is unknown if segmentation abilities are present from birth, or if they only emerge after sufficient language exposure and/or brain maturation.

An international team of researchers from the University of Liverpool, SISSA in Italy, the Neurospin Centre in France and The University of Manchester conducted experiments to find the cues crucial for the segmentation of human speech. The researchers played the infants a three-and-a-half minute audio clip in which four meaningless words, were buried in a stream of syllables.

Using a painless technique called Near-Infrared Spectroscopy, which shines red light into the brain, they were able to measure how much was absorbed, telling them which parts of the brain were active.

The researchers discovered two mechanisms in three-day-old infants, which give them the skills to pick out words in a stream of sounds. The first mechanism is known as prosody, the melody of language, allow us to recognize when a word starts and stops. The second is called the statistics of language, which describes how we compute the frequency of when sounds in a word come together.

The discovery provides a key insight into a first step to learning language.

We recognize two major classes of black holes based on their mass. There are stellar mass black holes that have masses from few to at most several tens of the mass of Sun. Then there are supermassive black holes with masses greater than million solar masses.

Stellar black holes

The stellar black holes arise as a final evolution stage of massive stars. The star has to have mass at least ten times larger than is the mass of Sun. This guarantees that after all the nuclear fuel has been consumed and the star explodes and casts off outer shells, there is still enough mass in its core with enough gravity to collapse into a black hole. The most massive stars have masses only up to about 500 solar masses otherwise they are not stable. It means that the most massive black hole of stellar origin can have a mass of about few hundred solar masses too.

Most of the stars live in pairs as binaries or in some more complicated systems. Our Sun makes quite an exception here because only every fifth star in our Galaxy lives on its own without a companion. Imagine a binary system containing two heavy stars of quite similar but still different masses. The heavier star will evolve slightly more rapidly and will run out of fuel sooner. When that happens, it will explode as a supernova and likely create a black hole from what was left from its core. The other star, assuming it has been able to survive the cataclysmic explosion of its sister, will soon be getting to the end of its live too. For a brief period of time (it is brief from the point of view of the age of the star, but it may last millions of years), before it explodes as a supernova too, it will grow up in size and lower its surface temperature. At this stage it may become large enough for its outer shells to be gravitationally attracted by the black hole short distance away. Material from the star's surface will star to flow onto the black hole. Because the two objects orbit each other, the flow of the material is not straight, but is dragged by non-inertial Corriolis force and forms an accretion disk around the black hole. The gas is viscously heated and emits electromagnetic radiation of wavelengths corresponding to its temperature on the range from infrared to X-rays. This is the stage, when we can discover there is a black hole there and when we can observe it through its accretion disk. When the second star finishes and explodes, we may end up with a binary black-hole system or (depending on the original mass of the stars) with a black hole and neutron star system or with a binary neutron star.

Supermassive black holes

The supermassive black holes are substantially more massive and they are also much older. However, their origin is the same as the origin of stellar mass black holes. When the first stars were created from abundant dense clouds of hydrogen and helium in the early universe, they were heavy with masses of hundreds of solar mass. They also lived briefly because they burned the fuel fast and soon they turned into first black holes. The black holes were bigger and more numerous where the original gas cloud was heavier and smaller and less plentiful where the birth cloud was sparser. They acted on one another by their gravity, larger ones merging with smaller and growing in mass. Billions of years passed, universe had expanded, and the slightly larger black holes grew by continuously merging with smaller ones to enormous masses. They become local centers of gravity and formed whole galaxies around them. Today, we think based on good evidence that every galaxy holds one supermassive black holes in its very center with mass at least a million up to tens of billion of solar masses.

More info from Wikipedia