Amazing Science

The mutual arrangement of atoms in crystal space is known to correspond to the minimum of the potential energy of interaction of all crystal atoms. The principle of potential energy minimum can be implemented in a number of geometric ways for approximate description of the atomic arrangement in crystals. In particular, these ways include the principle of close packing for crystals of inorganic compounds with undirected bonds and the principle of close packing of molecules for molecular crystals. Researchers at the Department of Crystallography and Experimental Physics of the Lobachevsky University believe that when analyzing the possibility of implementing a specific space group as a crystal symmetry group, one should consider as the main factors the volume and shape of the part of crystal space where ions or molecules can be located, as well as the symmetry of molecules (because of the presence of regular systems of points at which the atoms of a given molecule can be located).

"If one considers atoms as geometric objects, which have a finite volume comparable with the volume of a crystal unit cell, it is necessary to consider the geometric limitations on the mutual arrangement of atoms in crystal space. These limitations are due to the fact that the distance between two atoms cannot be smaller than the sum of their crystallo-chemical radii," comments Head of the Department of Crystallography and Experimental Physics, Rector of the Lobachevsky University Professor Evgeny Chuprunov.

Each of the 230 symmetry space groups is characterized by specific limitations on the atomic arrangement in crystal space, which are determined by the set of elements of space group symmetry, as well as the unit-cell sizes. This means that some regular systems of points of these groups cannot exist in nature for purely geometric reasons. The set of these points forms "forbidden regions" in crystal space, and the existence of such regions was demonstrated by the outstanding chemist and crystallographer, laureate of the Chugaev Prize Mikhail Porai-Koshits.

A large saltwater lake seems to lurk under ice near Mars’s south pole. If confirmed, it would be the first body of liquid water ever detected on the red planet and a significant milestone in the quest to determine whether life exists there. The lake would be the first body of liquid water ever detected on the red planet, if observations by a European spacecraft are confirmed.

“It’s a very promising place to look for life on Mars,” says Roberto Orosei, a planetary scientist at the National Institute of Astrophysics in Bologna, Italy. “But we do not know for sure if it is inhabited.” On Earth, similar ‘subglacial’ lakes are home to microbial life.

A team of Italian researchers, led by Orosei, reported the discovery on 25 July in Science1. They spotted evidence of the buried lake in radar data from the European Space Agency’s Mars Express spacecraft. Others say that the work is tantalizing but, like anything else in the controversial hunt for water on Mars, it needs more supporting evidence. “It’s not quite a slam dunk yet,” says Jeffrey Plaut, a planetary scientist at NASA’s Jet Propulsion Laboratory in Pasadena, California, who has searched for water using data from Mars Express2.

If further studies confirm the existence of a lake, it could open new avenues for investigating Mars. Researchers have drilled into subglacial lakes on Earth and sampled the water for signs of microbes, while others are developing technologies to reach a buried ocean on Jupiter’s moon Europa. There are no ice-drilling missions currently slated for Mars — but the latest discovery could change how scientists think about exploring the planet. “It begins a new line of inquiry that’s very exciting,” says Jim Green, NASA’s chief scientist.

Water appears across Mars today in various forms, left over from a time billions of years ago when the planet was warmer and wetter. Orbiting probes have spotted ice, including buried glaciers, in many locations. Spacecraft have photographed steep slopes whose appearance changes seasonally, as if liquid water is running downhill and leaving dark marks. And NASA’s Curiosity rover has measured water vapor in the planet’s atmosphere.

Orosei and his colleagues found the lake using a radar instrument called MARSIS aboard Mars Express, which launched in 2003. It sends radio waves bouncing off the surface and subsurface layers; the way in which the radar signal reflects back reveals the type of material that is present, such as rock, ice or water. The scientists focused their search on the layers of ice and dust that cover the planet’s south pole.

But the observations were frustratingly inconsistent. Mars Express sometimes saw a bright reflection in several locations, which did not reappear the next time the spacecraft flew over those sites. Finally, in 2012, the scientists decided to have MARSIS send back raw data, instead of performing automated processing before beaming the data to Earth.

“This changed everything, and it was much more obvious to spot the bright reflectors,” says Orosei. The data showed bright reflections coming from a 20-kilometer-long zone in a region known as Planum Australe. After ruling out other possible explanations, such as carbon dioxide ice, the scientists concluded that the reflections were coming from subsurface water.

Sometimes near misses arise within the realm of mathematics, almost as if mathematics is playing a trick on itself. In the episode “Treehouse of Horror VI” of The Simpsons, mathematically inclined viewers may have noticed something surprising: the equation 178212 + 184112 = 192212. It seemed for a moment that the screenwriters had disproved Fermat’s Last Theorem, which states that an equation of the form xn + yn = zn has no integer solution when n is larger than 2. If you punch those numbers into a pocket calculator, the equation seems valid. But if you do the calculation with more precision than most hand calculators can manage, you will find that the twelfth root of the left side of the equation is 1921.999999955867 …, not 1922, and Fermat can rest in peace. It is a striking near miss—off by less than a 10-millionth.

But near misses are more than just jokes. “The ones that are the most compelling to me are the ones where they’re potentially a clue that there’s a big story,” says University of California-Riverside mathematician John Baez. That’s the case for a number sometimes called the Ramanujan constant. This number is eπ √163, which equals approximately

262,537,412,640,768,743.99999999999925 —

amazingly close to a whole number. A priori, there’s no reason we should expect that these three irrational numbers—e, π, and √163—should somehow combine to form a rational number, let alone a perfect integer. There’s a reason they get so close. “It’s not some coincidence we have no understanding of,” says Baez. “It’s a clue to a deep piece of mathematics.” The precise explanation is complicated, but hinges on the fact that 163 is what is called a Heegner number. Exponentials related to these numbers are nearly integers.

Or take the mathematical relationship fancifully known as “Monstrous Moonshine.” The story goes that in 1978 mathematician John McKay made an observation both completely trivial and oddly specific: 196,884 = 196,883 + 1. The first number, 196,884, had come up as a coefficient in an important polynomial called the j-invariant, and 196,883 came up in relation to an enormous mathematical object called the Monster group. Many people probably would have shrugged and moved along, but the observations intrigued some mathematicians, who decided to take a closer look. They uncovered connections between two seemingly unrelated subjects: number theory and the symmetries of the Monster group. These linkages may even have broader, as yet ungrasped, significance for other subjects. The physicist Edward Witten has argued that the Monster group may be related to quantum gravity and the deep structure of spacetime.

The limits of human existence might not be as limited as we have long thought.

"Our data tell us that there is no fixed limit to the human life span yet in sight," Wachter said. "Very few of us are going to reach those kinds of ages, but the fact that mortality rates are not getting worse forever and ever tells us there may well be more progress to be made improving survival past the ages of 80 to 90. This is a valuable, encouraging discovery." Specifically, the study showed that people at age 110 had the same continued chances of survival as those between the ages of 105 and 109—a 50/50 chance of dying within the year and an expected further life span of 1.5 years.

This plateau runs counter to the way death risk relentlessly rises as we age from age 40 onward, Wachter said. "If mortality rates kept rising at the rates they rise from age 40 to age 90, then there would be a strong barrier to progress at extreme ages—great diminishing returns to behavioral change or to new medical advances," Wachter said. "The fact these rates ultimately level out gives hope there's more leeway for those advances."

The oldest known human on record is Jeanne Calment of France, who died in 1997 at age 122.

The last 10 years have seen enormous progress in both the understanding of cancer as a disease, as well as the development of targeted therapies, with an unprecedented number of new drugs approved for cancer treatment by the FDA and EMA. The availability of a large set of targeted therapies has created the need for efficient molecular profiling of patients.

A decade ago, the term “liquid biopsy” was coined to describe diagnostic procedures carried out to detect molecular biomarkers found in the blood or in other bodily fluids (e.g., urine or cerebrospinal fluid) of patients.

Blood, and potentially any other bodily fluid, contains cancer-derived elements that allow the molecular characterization of the disease, contributing to early diagnosis, accurate prognosis, personalized therapeutics, and disease monitoring. Materials derived from tumors include circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), as well as RNA, protein markers, and extracellular vesicles, such as exosomes.

When a tumor cell dies, it releases DNA molecules from its fragmented genome into the bloodstream. These nucleic acids in the blood can be purified and analyzed using PCR-based methods, next generation sequencing (NGS), or array technologies. Data generated from analyzing liquid biopsies have shown the enormous potential in this approach that could have a revolutionary impact on clinical practice. During the last few years, several studies have shown that key cancer mutations can be detected in liquid biopsies, mirroring those detected in traditional tumor biopsies.

Liquid biopsies may be even superior to standard tissue biopsies, as all parts of a tumor and all metastases are potentially sampled. Recent data indicate that, in most cases, analysis of circulating tumor DNA is faithfully reflecting mutations found in all known metastases of a cancer, or is even superior to such an approach (e.g., detecting mutations if standard biopsies fail, or showing more mutations than the standard tissue biopsies), suggesting that sequencing circulating tumor DNA can give a much more complete molecular picture of the systemic cancer disease than standard biopsies. Moreover, access to the blood of a patient is unproblematic, since the procedure presents minimal risk and sample collection is low cost.

Chemists and engineers today are very interested in a kind of nanotechnology enabled by tiny islands of nanoparticles called "colloidal nanocrystals." They can be made out of abundant and non-toxic materials, and they can be easily tweaked to have a number of different properties as a function of their size. Depending on how they're built, colloidal nanocrystals could be made into solar panels, electronics or optical devices. But all of these applications require making nanocrystals friendly places for electrons to travel along.

A new study published in Nature Nanotechnology helps fill in the cracks for scientists trying to use nanocrystals to design better electronic and optoelectronic devices. According to research by University of Chicago, Argonne National Laboratory and Max Planck Institute for Iron Research scientists, inorganic links between the nanoparticles themselves are changing and reforming on the surface of the nanoparticles.

The team focused on the links between nanoparticles. At first, scientists used organic molecules to link them, but these tended to block the movement of electrons. Some recent experiments have seen much better results for inorganic molecules instead, but no one was sure why. "We never had an atomistic model for the behavior of these inorganic linkers," said study co-author Giulia Galli, the Liew Family Professor of Molecular Engineering and professor of chemistry at the University of Chicago and a senior scientist at Argonne.

Galli worked with colleague Dmitri Talapin, the Louis Block Distinguished Service Professor of Chemistry and a scientist at Argonne, as well as Stefan Wippermann, group leader at the Max Planck Institute, to explore the structure of nanocrystals made with these inorganic links. Through a combination of theory and experiment, the team puzzled out the blow-by-blow of actions. It turns out that the linker molecules react where they're attached and form a sort of glue, which affects the properties of the nanoparticles. "Instead of each having separate identities, the whole thing should really be considered as a complex nanomaterial," Galli said. "This was totally different from what was thought."

"The complete model of the structural properties of the nanoparticles should help scientists and engineers as they try to design materials for better and less toxic electronics, solar panels and more," said Wippermann, who led the study.

In the 1920s, Edwin Hubble made the groundbreaking discovery that the Universe was in a state of expansion. Originally predicted as a consequence of Einstein’s Theory of General Relativity, measurements of this expansion came to be known as Hubble’s Constant. Today, and with the help of next-generation telescopes – like the aptly-namedHubble Space Telescope (HST) – astronomers have remeasured and revised this law many times.

These measurements confirmed that the rate of expansion has increased over time, though scientists are still unsure why. The latest measurements were conducted by an international team using Hubble,who then compared their results with data obtained by the European Space Agency’s (ESA) Gaia observatory. This has led to the most precise measurements of the Hubble Constant to date, though questions about cosmic acceleration remain.

The study which describes their findings appeared in the July 12th issue of the Astrophysical Journal, titled “Milky Way Cepheid Standards for Measuring Cosmic Distances and Application to Gaia DR2: Implications for the Hubble Constant.” The team behind the study included members from the Space Telescope Science Institute (STScI), the Johns Hopkins University, the National Institute for Astrophysics(INAF), UC Berkeley, Texas A&M University, and the European Southern Observatory (ESO).

Coronary artery disease (CAD) and myocardial infarction (MI) remain among the leading causes of mortality worldwide, urgently demanding a better understanding of disease etiology, and more efficient therapeutic strategies. Genetic predisposition as well as the environment and lifestyle are thought to contribute to disease risk. It is likely that non-linear and complex interactions occur between these multiple factors, involving simultaneous pathological changes in diverse cell types, tissues, and organs, at multiple molecular levels.

Recent technological advances have exponentially expanded the breadth of available -omics data, from genome, epigenome, transcriptome, proteome, metabolome to even the microbiome. Integration of multiple layers of information across several -omics domains, i.e., the so-called multi-omics approach, currently holds the promise as a path toward precision medicine. Indeed, a more meaningful interpretation of genotype-phenotype relationships and the development of successful therapeutics tailored to individual patients are urgently needed.

In this review, the authors summarize recent findings and applications of integrative multi-omics in elucidating the etiology of CAD/MI with a special focus on established disease susceptibility loci sequentially identified in genome-wide association studies (GWAS) obtained over the last 10 years. Moreover, in addition to the autosomal genome, the review also considers the genetic variation of the so-called “second genome”—the mitochondrial genome. Finally, the authors of this review summarize the current challenges in the field and point to future research directions required in order to successfully and effectively apply these approaches for precision medicine.

A scientific consortium led by Dr. Eleanor Scerri, British Academy Postdoctoral Fellow at the University of Oxford and researcher at the Max Planck Institute for the Science of Human History, has found that human ancestors were scattered across Africa, and largely kept apart by a combination of diverse habitats and shifting environmental boundaries, such as forests and deserts. Millennia of separation gave rise to a staggering diversity of human forms, whose mixing ultimately shaped our species.

While it is widely accepted that our species originated in Africa, less attention has been paid to how we evolved within the continent. Many had assumed that early human ancestors originated as a single, relatively large ancestral population, and exchanged genes and technologies like stone tools in a more or less random fashion.

In a recent paper published in Trends in Ecology and Evolution, this view is challenged, not only by the usual study of bones (anthropology), stones (archaeology) and genes (population genomics), but also by new and more detailed reconstructions of Africa's climates and habitats over the last 300,000 years.

One species, many origins

"Stone tools and other artifacts -- usually referred to as material culture -- have remarkably clustered distributions in space and through time," said Dr. Eleanor Scerri, researcher at the Max Planck Institute for the Science of Human History and the University of Oxford, and lead author of the study. "While there is a continental-wide trend towards more sophisticated material culture, this 'modernization' clearly doesn't originate in one region or occur at one time period."

Human fossils tell a similar story. "When we look at the morphology of human bones over the last 300,000 years, we see a complex mix of archaic and modern features in different places and at different times," said Prof. Chris Stringer, researcher at the London Natural History Museum and co-author on the study. "As with the material culture, we do see a continental-wide trend towards the modern human form, but different modern features appear in different places at different times, and some archaic features are present until remarkably recently."

Scientists at Stanford used the wire to capture free-floating tumor cells in the blood, a technique that soon could be used in humans to yield an earlier cancer diagnosis.

A magnetic wire used to snag scarce and hard-to-capture tumor cells could prove to be a swift and effective tactic for early cancer detection, according to a study by researchers at the Stanford University School of Medicine. The wire, which is threaded into a vein, attracts special magnetic nanoparticles engineered to glom onto tumor cells that may be roaming the bloodstream if you have a tumor somewhere in your body. With these tumor cells essentially magnetized, the wire can lure the cells out of the free-flowing bloodstream using the same force that holds family photos to your refrigerator.

The technique, which has only been used in pigs so far, attracts from 10-80 times more tumor cells than current blood-based cancer-detection methods, making it a potent tool to catch the disease earlier. The technique could even help doctors evaluate a patient's response to particular cancer treatments: If the therapy is working, tumor-cell levels in the blood should rise as the cells die and break away from the tumor, and then fall as the tumor shrinks.

Toxicologists have just unveiled a digital chemical safety screening tool that could greatly reduce the need for six common animal tests. Those tests account for nearly 60% of the estimated 3 million to 4 million animals used annually in risk testing worldwide.

The computerized tool—built on a massive database of molecular structures and existing safety data—appears to match, and sometimes improve on, the results of animal tests for properties such as skin sensitization and eye irritation, the researchers report in today’s issue of Toxicological Sciences. But it also has limitations; for instance, the method can’t reliably evaluate a chemical’s risk of causing cancer. And it’s not clear how open regulatory agencies will be to adopting a non-animal approach.

Still, “We’re really excited about the potential of this model,” says toxicologist Nicole Kleinstreuer, deputy director of a center that evaluates alternatives to animal testing at the National Institute of Environmental Health Sciences (NIEHS) in Durham, North Carolina. Kleinstreuer, who was not involved in the work, adds that using “big data … to build predictive models is an extremely promising avenue for reducing and replacing animal testing.”

MIT Media Lab researchers have developed a machine-learning model that takes computers a step closer to interpreting our emotions as naturally as humans do. In the growing field of “affective computing,” robots and computers are being developed to analyze facial expressions, interpret our emotions, and respond accordingly. Applications include, for instance, monitoring an individual’s health and well-being, gauging student interest in classrooms, helping diagnose signs of certain diseases, and developing helpful robot companions.

A challenge, however, is people express emotions quite differently, depending on many factors. General differences can be seen among cultures, genders, and age groups. But other differences are even more fine-grained: The time of day, how much you slept, or even your level of familiarity with a conversation partner leads to subtle variations in the way you express, say, happiness or sadness in a given moment.

Human brains instinctively catch these deviations, but machines struggle. Deep-learning techniques were developed in recent years to help catch the subtleties, but they’re still not as accurate or as adaptable across different populations as they could be.

The Media Lab researchers have developed a machine-learning model that outperforms traditional systems in capturing these small facial expression variations, to better gauge mood while training on thousands of images of faces. Moreover, by using a little extra training data, the model can be adapted to an entirely new group of people, with the same efficacy. The aim is to improve existing affective-computing technologies.

“This is an unobtrusive way to monitor our moods,” says Oggi Rudovic, a Media Lab researcher and co-author on a paper describing the model, which was presented last week at the Conference on Machine Learning and Data Mining. “If you want robots with social intelligence, you have to make them intelligently and naturally respond to our moods and emotions, more like humans.”

Co-authors on the paper are: first author Michael Feffer, an undergraduate student in electrical engineering and computer science; and Rosalind Picard, a professor of media arts and sciences and founding director of the Affective Computing research group.

When drug developers assemble their Most Wanted lists, they may overlook the phosphatases, signaling enzymes that are notoriously hard to pick out of a lineup. Phosphatases, however, may soon find themselves the subject of intense investigation, now that scientists from the Medical Research Council (MRC) have created a platform for target-based discovery of phosphatase inhibitors.

Unlike kinases, which come from a different family of signaling enzymes, phosphatases often lack distinguishing characteristics. Consequently, if a drug candidate attempts to apprehend a phosphatase of interest, it may end up seizing many different phosphatases indiscriminately, with dire results. More than 200 types of phosphatases participate in cellular processes, so drug candidates that inhibit multiple phosphatases may cause serious side effects or even kill cells.

So, should phosphatases keep getting away with being “undruggable”? Not according to the MRC’s Anne Bertolotti, Ph.D., a molecular biologist committed to fighting neurodegenerative diseases that are characterized by the accumulation of misfolded proteins in the brain. Such diseases include Alzheimer’s, Parkinson’s, and Huntington’s.

Dr. Bertolotti led a team of MRC researchers in the development of a drug-screening system that uses surface plasmon resonance to identify selective serine/threonine phosphatase inhibitors. The MRC team used this system to find a phosphatase inhibitor capable of targeting a specific phosphatase, one implicated in the accumulation of Huntington’s disease-associated proteins in mice.

Details of this work appeared July 26 in the journal Cell, in an article titled, “Target-Based Discovery of an Inhibitor of the Regulatory Phosphatase PPP1R15B.”

This article describes how the MRC team screened for molecules that could engage a regulatory subunit of protein phosphatase 1, PPP1R15B (R15B), a negative regulator of proteostasis. Ultimately, the screen yielded Raphin1, a selective inhibitor of R15B.

“In cells, Raphin1 caused a rapid and transient accumulation of its phosphorylated substrate, resulting in a transient attenuation of protein synthesis,” the article’s authors wrote. “In vitro, Raphin1 inhibits the recombinant R15B-PP1c holoenzyme, but not the closely related R15A-PP1c, by interfering with substrate recruitment.”

When Dr. Bertolotti and colleagues tested Raphin1 in a mouse model of Huntington's disease, they found it could cross into the brain where it reduced the accumulation of the disease-associated misfolded proteins in neurons. The scientists emphasize that this is early-stage research and more work is needed to test if the drug will be safe or effective in humans.

This study was performed by members of the Social Science Genetic Association Consortium (SSGAC). The SSGAC is a multi-institutional, international research group that aims to identify statistically robust links between genetic variants and social-science-relevant traits. These include traits such as behavior, preferences, and personality that are traditionally studied by social and behavioral scientists (e.g., economists, psychologists, sociologists) but are often also of interest to health and other researchers.

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The SSGAC was formed in 2011 to overcome a specific set of scientific challenges. Most traits and behaviors are associated with thousands of genetic variants. Although their collective effect can be substantial (see FAQs 1.5 & 2.3), we now know that almost every one of these genetic variants has an extremely weak effect on its own. To identify specific variants with such small effects, scientists must study at least hundreds of thousands of people (to separate weak signals from noise). One promising strategy for doing this is for many investigators to pool their data into one large study. This approach has borne considerable fruit when used by medical geneticists interested in a range of diseases and conditions (Visscher et al. 2017). Most of these advances would not have been possible without large research collaborations between multiple research groups interested in similar questions. The SSGAC was formed in an attempt by social scientists to adopt this research model.

Educational attainment is the amount of formal education a person completes (measured as the number of years of education completed for people in our sample, all of whom are at least age 30 or older). Although educational attainment is most strongly influenced by social and other environmental factors (see FAQ 1.7), it is also influenced by thousands of genes. People vary considerably in how much education they complete. Education is recognized throughout the social and biomedical sciences as an important “predictor” (see FAQ 1.4) of many other life outcomes, such as income, occupation, health, and longevity (Ross & Wu 1995; Cutler & Lleras-Muney 2008). Educational attainment is also among the relatively few social-scientific traits for which it is feasible to conduct a large-scale genome-wide study, because educational attainment is frequently measured by a variety of cohorts, including medical cohorts, due to its robust association with health. A large-scale study is necessary (but not sufficient) to generate scientific findings that are reproducible.

The study found 1,271 genetic variants that were associated with educational attainment (using the standard statistical threshold in GWAS, which adjusts for multiple hypothesis testing). This is a substantial increase from the 74 variants identified in our last GWAS of around 300,000 individuals (Okbay, Beauchamp, et al. 2016), confirming the importance of large sample size for identifying specific genetic variants associated with behavioral traits.

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The current study further confirmed the finding from our earlier work that the effects of individual genetic variants on educational attainment are extremely small. The average effect size across the 1,271 genetic variants was just 1.8 weeks of schooling per allele; even the SNPs with the strongest associations only predicted around 3 weeks of additional schooling per allele. Taken together, these 1,271 SNPs accounted for just 3.9% of the variation across individuals in years of education completed.

Thin mulch films made of polyethylene are used in agriculture in numerous countries, where they cause extensive soil contamination. Researchers at ETH Zurich and Eawag have now identified an alternative: films made of the polymer PBAT biodegrade in soils.

Our world is drowning in a flood of plastic. Eight million tons of plastic end up in the oceans every year. Agricultural soils are also threatened by plastic pollution. Farmers around the world apply enormous amounts of polyethylene (PE) mulch films onto soils to combat weeds, increase soil temperature and keep the soil moist, thereby increasing overall crop yields.

After harvest, it often is impossible for farmers to re-collect the entire films, particularly when films are only a few micrometers thin. Film debris then makes its way into the soil and accumulates in the soil over time, because PE does not biodegrade. Film residues in soils decrease soil fertility, interfere with water transport and diminish crop growth.

Soil microbes mineralize films composed of alternative polymer

Researchers at ETH Zurich and the Swiss Federal Institute of Aquatic Science and Technology (Eawag) have now shown in an interdisciplinary study that there is reason to be hopeful. In their recent study, they demonstrate that soil microbes degrade films composed of the alternative polymer poly(butylene adipate-co-terephthalate) (PBAT). Their work has just been published in the journal Science Advances.

In the research project coordinated by Michael Sander, Kristopher McNeill and Hans-Peter Köhler, former ETH doctoral student Michael Zumstein succeeded in demonstrating that soil microorganisms metabolically utilized the carbon in the PBAT polymer both for energy production and also to build up microbial biomass.

"This research directly demonstrates, for the first time, that soil microorganisms mineralize PBAT films in soils and transfer carbon from the polymer into their biomass," says Michael Sander, Senior Scientist in the Environmental Chemistry Group in the Department of Environmental Systems Science at ETH Zurich.

Regulatory agencies say that recombinant proteins intended for therapeutic use must be produced from a cell line derived from a single progenitor cell. In addition, single-cell cloning has gained increasing importance as genome editing techniques have entered routine laboratory practice.

Pure clonal isolation from a single progenitor cell is a critical step in the genetic and functional characterization of mutations achieved by targeted genome editing methods such as those incorporating ZFNs, TALENs, and CRISPR-Cas9. These nuclease-driven genome editing tools can be used to introduce a change at a specific genomic location, either to cause a mutation or to insert an exogenous sequence.

However, culturing edited cells results in a heterogeneous polyclonal cell population requiring generation of an edited cell line containing a homogeneous genetic background to retain the desired genotype and to facilitate downstream phenotypic characterization.

While traditionally the most laborious and time-consuming step in CRISPR-based genome engineering using cell models, the generation of clonal mutant cell lines, investigators say, is absolutely required to draw any solid conclusions correlating a given mutation and cellular behavior. In the development of biopharmaceutical production cell lines, current workflows have drawbacks that include reduced cell viability, inefficient single-cell isolation, and limited evidence for clonality.

Chinese hamster ovary (CHO) cells remain the major cells of choice for the manufacture of therapeutic recombinant proteins. However, one of the major challenges in CHO cell line generation remains efficient identification of high-producing clones among a large population of low-producing or non-productive clones. It is not unusual for several hundred individual clones to be screened for the identification of a commercial clonal cell line with acceptable productivity and a growth profile appropriate for large-scale production.

Researchers have shown that clusters of boron and lanthanide atoms form interesting 'inverse sandwich' structures that could be useful as molecular magnets.

Brown University researchers and collaborators from Tsinghua University in China have shown that nanoclusters made from boron and lanthanide elements form highly stable and symmetric structures with interesting magnetic properties.

The findings, published in Proceedings of the National Academy of Sciences on Monday, July 9, suggest that these nanoclusters may be useful as molecular magnets or assembled into magnetic nanowires. The research also helps shed light on the structure and chemical bonding of bulk boron lanthanides, which may help in engineering new boride materials.

"Boron lanthanides are an important class of materials used in electronics and other applications, but nanoclusters of boron lanthanides have not been studied," said Lai-Sheng Wang, a professor of chemistry at Brown and senior author of a paper describing the work. "We have just started to investigate these nanoclusters, and here we show that they can have an interesting 'inverse sandwich' structure with the right combination of boron and lanthanide atoms."

Today, diagnosing rare genetic diseases requires a slow process of educated guesswork. Stanford computer scientist and genomicist Gill Bejerano, PhD, is working to speed it up.

In a recent paper published in Genetics in Medicine, Bejerano and colleagues describe an algorithm they’ve developed that automates the most labor-intensive part of genetic diagnosis, that of matching a patient’s genetic sequence and symptoms to a disease described in the scientific literature. Without computer help, this match-up process takes 20 to 40 hours per patient: The expert looks at a list of around 100 of the patient’s suspicious-looking mutations, makes an educated guess about which one might cause disease, checks the scientific literature, then moves on to the next one. The algorithm developed by Bejerano’s team cuts the time needed by 90 percent.

“Clinicians’ time is expensive and computer time is cheap,” said Bejerano, who worked with pediatric geneticist Jon Bernstein, MD, PhD, and other experts in computer science and pediatrics to develop this new technique. “If I’m a busy clinician, before I even open a patient’s case, the computer needs to have done all it can to make my life easier.”

The algorithm’s name, Phrank, a mashup of “phenotype” and “rank,” gives a hint of how it works: Phrank compares a patient’s symptoms and gene data to a medical-literature knowledge base, generating a ranked list of which rare genetic diseases are most likely to be responsible for the symptoms. The clinician has a logical starting point for making a diagnosis, which they can confirm with one to four hours of effort per case instead of 20 to 40.

The mathematical workings of Phrank aren’t tied to a specific database, a first for this type of algorithm. This makes it much more flexible to use. Phrank also dramatically outperforms earlier algorithms that have tried to do the same thing, the scientific paper explained. Bejerano’s team validated Phrank on medical and genetic data from 169 real patients, an important advance over earlier studies in the field. Prior studies had tested algorithms on made-up patients instead because real-patient data for this research is hard to come by.

Diatoms are tiny, unicellular creatures, inhabiting oceans, lakes, rivers, and soils. Through their respiration, they produce close to a quarter of the oxygen on earth, nearly as much as the world's tropical forests. In addition to their ecological success across the planet, they have a number of remarkable properties. Diatoms live in glasslike homes of their own design, visible under magnification in an astonishing and aesthetically beautiful range of forms.

Researchers have found inspiration in these microscopic, jewel-like products of nature since their discovery in the late 18th century. In a new study, Arizona State University (ASU) scientists led by Professor Hao Yan, in collaboration with researchers from the Shanghai Institute of Applied Physics of the Chinese Academy of Sciences and Shanghai Jiaotong University led by Prof. Chunhai Fan, have designed a range of diatom-like nanostructures.

To achieve this, they borrow techniques used by naturally-occurring diatoms to deposit layers of silica -- the primary constituent in glass -- in order to grow their intricate shells. Using a technique known as DNA origami, the group designed nanoscale platforms of various shapes to which particles of silica, drawn by electrical charge, could stick.

The new research demonstrates that silica deposition can be effectively applied to synthetic, DNA-based architectures, improving their elasticity and durability. The work could ultimately have far-reaching applications in new optical systems, semiconductor nanolithography, nano-electronics, nano-robotics and medical applications, including drug delivery.

Yan is the Milton D. Glick Distinguished Professor of Chemistry and Biochemistry and directs the Biodesign Center for Molecular Design and Biomimetics. The group's findings are reported in the advanced online of the journal Nature. Researchers like Yan and Fan create sophisticated nanoarchitectures in 2- and 3-dimensions, using DNA as a building material. The method, known as DNA origami, relies on the base-pairing properties of DNA's four nucleotides, whose names are abbreviated A,T,C and G.

The ladder-like structure of the DNA double-helix is formed when complementary strands of nucleotides bond with each other -- the C nucleotides always pairing with Gs and the As always pairing with Ts. This predictable behavior can be exploited in order to produce a virtually limitless variety of engineered shapes, which can be designed in advance. The nanostructures then self-assemble in a test tube.

In the new study, researchers wanted to see if architectures designed with DNA, each measuring just billionths of a meter in diameter, could be used as structural frameworks on which diatom-like exoskeletons composed of silica could grow in a precise and controllable manner. Their successful results show the power of this hybrid marriage of nature and nanoengineering, which the authors call DNA Origami Silicification (DOS).

Scientists have long suspected that cancer stem cells are at the root of what drives the return and spread of glioblastoma and other cancers. These stem cells give rise to other cancer cells and, if they evade the surgeon’s knife, can lead to an entirely new tumor.

Laterra and Green, who are members of the Johns Hopkins Kimmel Cancer Center, designed a way to efficiently deliver super-tiny packets of microRNAs into established brain tumors. The microRNAs target brain cancer stem cells to halt their capacity to propagate and sustain tumor growth.

The packets are made of biodegradable plastic similar to material used for surgical sutures and that degrades over time. They are 1,000 times smaller than the width of a human hair and typical of the size and shape of natural components that cells use to communicate. When cancer cells engulf the packets, they break apart and release their microRNA “payload” specifically where the microRNAs need to take action within the cancer cells.

Encased in the nanopacket are microRNAs that specifically bind to messenger RNAs linked to two genes: HMGA1 and DNMT, which function together to regulate gene expression programs in cells.

When microRNAs bind to these messenger RNAs, they block their protein-making abilities and turn off programs that drive the cancer cells’ stemlike characteristics. Without their stemlike properties, the cancer cells are more differentiated, they lose their capacity to propagate tumors, and they may be more susceptible to radiation and drugs.

For their experiments, the Johns Hopkins scientists implanted human glioblastoma cells into 18 mice. To mimic the clinical challenge of treating an existing tumor, the scientists waited 45 days before treating the animals to be sure they had well-formed tumors. Half of the animals received infusions of the nanopackets containing active microRNAs directly into their brain tumors, and the other half received nanopackets containing inactive microRNAs. To isolate the effect of the nanoparticles, the scientists used mice that were bred without immune system T-cells that target cancer cells. 

Five of the nine mice receiving inactive microRNAs (controls) died within two months, and the rest of the control mice died within 90 days. Three of the nine mice receiving active microRNAs lasted up to 80 days, and six lived to 133 days. Those six were humanely euthanized, and isolated mouse brains were examined for the presence of tumors.

All of the control mice had large tumors in their brains when they died. Four of the mice that received active microRNAs and lived to 133 days had no tumors, and two had small ones.

NASA’s Human Exploration and Operations and Science Mission Directorates are collaborating to make interplanetary internet a reality.

Sometimes, a genetic tweak can make a really big difference in an animal’s appearance. That’s what likely happened when the predecessors of modern snakes lost their legs, a process that started some 150 million years ago, two separate groups of scientists have discovered. Although the teams took very different approaches to solve the mystery of how those limbs vanished, both came up with similar results: Mutations in DNA located near a gene key to limb formation keep that gene from ever turning on, they reported recently.

The new studies have impressed other scientists in the field. In both cases, "there is a correlation between the molecular findings on the one hand and the evolutionary trend of limb reduction and loss on the other," says Michael Richardson, a developmental biologist at Leiden University in the Netherlands. The findings show “there can be pretty minor changes in the genome that can account for very big specific changes,” adds James Hanken, an evolutionary developmental biologist at Harvard University.  

Though they are reptiles, almost all snakes are completely missing the limbs typical of most land vertebrates. They didn’t start out that way: More than 100 million years ago, snakes had visible legs. And even today pythons and boas have tiny leg bones inside their bodies, suggesting they have vestiges of the molecular pathway for building these appendages.