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Chemists make cellular forces visible at the molecular scale

Scientists have developed a new technique using tools made of luminescent DNA, lit up like fireflies, to visualize the mechanical forces of cells at the molecular level. Nature Methods published the work, led by chemists at Emory University, who demonstrated their technique on human blood platelets in laboratory experiments.

“Normally, an optical microscope cannot produce images that resolve objects smaller than the length of a light wave, which is about 500 nanometers,” says Khalid Salaita, Emory professor of chemistry and senior author of the study. “We found a way to leverage recent advances in optical imaging along with our molecular DNA sensors to capture forces at 25 nanometers. That resolution is akin to being on the moon and seeing the ripples caused by raindrops hitting the surface of a lake on the Earth.”

Almost every biological process involves a mechanical component, from cell division to blood clotting to mounting an immune response. “Understanding how cells apply forces and sense forces may help in the development of new therapies for many different disorders,” says Salaita, whose lab is a leader in devising ways to image and map bio-mechanical forces.

The first authors of the paper, Joshua Brockman and Hanquan Su, did the work as Emory graduate students in the Salaita lab. Both recently received their PhDs.

The researchers turned strands of synthetic DNA into molecular tension probes that contain hidden pockets. The probes are attached to receptors on a cell’s surface. Free-floating pieces of DNA tagged with fluorescence serve as imagers. As the unanchored pieces of DNA whizz about they create streaks of light in microscopy videos.

When the cell applies force at a particular receptor site, the attached probes stretch out causing their hidden pockets to open and release tendrils of DNA that are stored inside. The free-floating pieces of DNA are engineered to dock onto these DNA tendrils. When the florescent DNA pieces dock, they are briefly demobilized, showing up as still points of light in the microscopy videos.

Hours of microscopy video are taken of the process, then speeded up to show how the points of light change over time, providing the molecular-level view of the mechanical forces of the cell.

The researchers use a firefly analogy to describe the process.

“Imagine you’re in a field on a moonless night and there is a tree that you can’t see because it’s pitch black out,” says Brockman, who graduated from the Wallace H. Coulter Department of Biomedical Engineering, a joint program of Georgia Tech and Emory, and is now a post-doctoral fellow at Harvard. “For some reason, fireflies really like that tree. As they land on all the branches and along the trunk of the tree, you could slowly build up an image of the outline of the tree. And if you were really patient, you could even detect the branches of the tree waving in the wind by recording how the fireflies change their landing spots over time.”

“It’s extremely challenging to image the forces of a living cell at a high resolution,” says Su, who graduated from Emory’s Department of Chemistry and is now a post-doctoral fellow in the Salaita lab. “A big advantage of our technique is that it doesn’t interfere with the normal behavior or health of a cell.”

Another advantage, he adds, is that DNA bases of A, G, T and C, which naturally bind to one another in particular ways, can be engineered within the probe-and-imaging system to control specificity and map multiple forces at one time within a cell.

“Ultimately, we may be able to link various mechanical activities of a cell to specific proteins or to other parts of cellular machinery,” Brockman says. “That may allow us to determine how to alter the cell to change and control its forces.”

By using the technique to image and map the mechanical forces of platelets, the cells that control blood clotting at the site of a wound, the researchers discovered that platelets have a concentrated core of mechanical tension and a thin rim that continuously contracts. “We couldn’t see this pattern before but now we have a crisp image of it,” Salaita says. “How do these mechanical forces control thrombosis and coagulation? We’d like to study them more to see if they could serve as a way to predict a clotting disorder.”

Just as increasingly high-powered telescopes allow us to discover planets, stars and the forces of the universe, higher-powered microscopy allows us to make discoveries about our own biology.

“I hope this new technique leads to better ways to visualize not just the activity of single cells in a laboratory dish, but to learn about cell-to-cell interactions in actual physiological conditions,” Su says. “It’s like opening a new door onto a largely unexplored realm — the forces inside of us.”

Co-authors of the study include researchers from Children’s Healthcare of Atlanta, Ludwig Maximilian University in Munich, the Max Planck Institute and the University of Alabama at Birmingham. The work was funded by grants from the National Institutes of Health, the National Science Foundation, the Naito Foundation and the Uehara Memorial Foundation.

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Sturdy fabric-based piezoelectric energy harvester takes us one step closer to wearable electronics

KAIST researchers presented a highly flexible but sturdy wearable piezoelectric harvester using the simple and easy fabrication process of hot pressing and tape casting. This energy harvester, which has record high interfacial adhesion strength, will take us one step closer to being able to manufacture embedded wearable electronics. A research team led by Professor Seungbum Hong said that the novelty of this result lies in its simplicity, applicability, durability, and its new characterization of wearable electronic devices.

Wearable devices are increasingly being used in a wide array of applications from small electronics to embedded devices such as sensors, actuators, displays, and energy harvesters.

Despite their many advantages, high costs and complex fabrication processes remained challenges for reaching commercialization. In addition, their durability was frequently questioned. To address these issues, Professor Hong’s team developed a new fabrication process and analysis technology for testing the mechanical properties of affordable wearable devices.

For this process, the research team used a hot pressing and tape casting procedure to connect the fabric structures of polyester and a polymer film. Hot pressing has usually been used when making batteries and fuel cells due to its high adhesiveness. Above all, the process takes only two to three minutes.

The newly developed fabrication process will enable the direct application of a device into general garments using hot pressing just as graphic patches can be attached to garments using a heat press.

In particular, when the polymer film is hot pressed onto a fabric below its crystallization temperature, it transforms into an amorphous state. In this state, it compactly attaches to the concave surface of the fabric and infiltrates the gaps between the transverse wefts and longitudinal warps. These features result in high interfacial adhesion strength. For this reason, hot pressing has the potential to reduce the cost of fabrication through the direct application of fabric-based wearable devices to common garments.

In addition to the conventional durability test of bending cycles, the newly introduced surface and interfacial cutting analysis system proved the high mechanical durability of the fabric-based wearable device by measuring the high interfacial adhesion strength between the fabric and the polymer film. Professor Hong said the study lays a new foundation for the manufacturing process and analysis of wearable devices using fabrics and polymers.

He added that his team first used the surface and interfacial cutting analysis system (SAICAS) in the field of wearable electronics to test the mechanical properties of polymer-based wearable devices. Their surface and interfacial cutting analysis system is more precise than conventional methods (peel test, tape test, and microstretch test) because it qualitatively and quantitatively measures the adhesion strength.

Professor Hong explained, “This study could enable the commercialization of highly durable wearable devices based on the analysis of their interfacial adhesion strength. Our study lays a new foundation for the manufacturing process and analysis of other devices using fabrics and polymers. We look forward to fabric-based wearable electronics hitting the market very soon.”

The results of this study were registered as a domestic patent in Korea last year, and published in Nano Energy this month. This study has been conducted through collaboration with Professor Yong Min Lee in the Department of Energy Science and Engineering at DGIST, Professor Kwangsoo No in the Department of Materials Science and Engineering at KAIST, and Professor Seunghwa Ryu in the Department of Mechanical Engineering at KAIST.

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Elephant Edge Webinar 1: The Software

The ElephantEdge challenge is calling on the community to build ML models using the Edge Impulse Studio and tracking dashboards using Avnet’s IoTConnect, which will be deployed onto 10 production-grade collars manufactured by our engineering partner, Institute IRNAS, and deployed by Smart Parks.

In this first of two ElephantEdge webinars you’ll learn about the problems park rangers are facing and how to get started with IoTConnect and Edge Impulse Studio.

Contest Link: https://www.hackster.io/contests/ElephantEdge

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Tool transforms world landmark photos into 4D experiences

Using publicly available tourist photos of world landmarks such as the Trevi Fountain in Rome or Top of the Rock in New York City, Cornell University researchers have developed a method to create maneuverable 3D images that show changes in appearance over time.

The method, which employs deep learning to ingest and synthesize tens of thousands of mostly untagged and undated photos, solves a problem that has eluded experts in computer vision for six decades.

“It’s a new way of modeling scenes that not only allows you to move your head and see, say, the fountain from different viewpoints, but also gives you controls for changing the time,” said Noah Snavely, associate professor of computer science at Cornell Tech and senior author of “Crowdsampling the Plenoptic Function,” presented at the European Conference on Computer Vision, held virtually Aug. 23-28.

“If you really went to the Trevi Fountain on your vacation, the way it would look would depend on what time you went — at night, it would be lit up by floodlights from the bottom. In the afternoon, it would be sunlit, unless you went on a cloudy day,” Snavely said. “We learned the whole range of appearances, based on time of day and weather, from these unorganized photo collections, such that you can explore the whole range and simultaneously move around the scene.”

Representing a place in a photorealistic way is challenging for traditional computer vision, partly because of the sheer number of textures to be reproduced. “The real world is so diverse in its appearance and has different kinds of materials — shiny things, water, thin structures,” Snavely said.

Another problem is the inconsistency of the available data. Describing how something looks from every possible viewpoint in space and time — known as the plenoptic function — would be a manageable task with hundreds of webcams affixed around a scene, recording data day and night. But since this isn’t practical, the researchers had to develop a way to compensate.

“There may not be a photo taken at 4 p.m. from this exact viewpoint in the data set. So we have to learn from a photo taken at 9 p.m. at one location, and a photo taken at 4:03 from another location,” Snavely said. “And we don’t know the granularity of when these photos were taken. But using deep learning allows us to infer what the scene would have looked like at any given time and place.”

The researchers introduced a new scene representation called Deep Multiplane Images to interpolate appearance in four dimensions — 3D, plus changes over time. Their method is inspired in part on a classic animation technique developed by the Walt Disney Company in the 1930s, which uses layers of transparencies to create a 3D effect without redrawing every aspect of a scene.

“We use the same idea invented for creating 3D effects in 2D animation to create 3D effects in real-world scenes, to create this deep multilayer image by fitting it to all these disparate measurements from the tourists’ photos,” Snavely said. “It’s interesting that it kind of stems from this very old, classic technique used in animation.”

In the study, they showed that this model could be trained to create a scene using around 50,000 publicly available images found on sites such as Flickr and Instagram. The method has implications for computer vision research, as well as virtual tourism — particularly useful at a time when few can travel in person.

“You can get the sense of really being there,” Snavely said. “It works surprisingly well for a range of scenes.”

First author of the paper is Cornell Tech doctoral student Zhengqi Li. Abe Davis, assistant professor of computer science in the Faculty of Computing and Information Science, and Cornell Tech doctoral student Wenqi Xian also contributed.

The research was partly supported by philanthropist Eric Schmidt, former CEO of Google, and Wendy Schmidt, by recommendation of the Schmidt Futures Program.

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Small quake clusters can’t hide from AI

Researchers at Rice University’s Brown School of Engineering are using data gathered before a deadly 2017 landslide in Greenland to show how deep learning may someday help predict seismic events like earthquakes and volcanic eruptions.

Seismic data collected before the massive landslide at a Greenland fjord shows the subtle signals of the impending event were there, but no human analyst could possibly have put the clues together in time to make a prediction. The resulting tsunami that devastated the village of Nuugaatsiaq killed four people and injured nine and washed 11 buildings into the sea.

A study lead by former Rice visiting scholar Léonard Seydoux, now an assistant professor at the University of Grenoble-Alpes, employs techniques developed by Rice engineers and co-authors Maarten de Hoop and Richard Baraniuk. Their open-access report in Nature Communications shows how deep learning methods can process the overwhelming amount of data provided by seismic tools fast enough to predict events.

De Hoop, who specializes in mathematical analysis of inverse problems and deep learning in connection with Rice’s Department of Earth, Environmental and Planetary Sciences, said advances in artificial intelligence (AI) are well-suited to independently monitor large and growing amounts of seismic data. AI has the ability to identify clusters of events and detect background noise to make connections that human experts might not recognize due to biases in their models, not to mention sheer volume, he said.

Hours before the Nuugaatsiaq event, those small signals began to appear in data collected by a nearby seismic station. The researchers analyzed data from midnight on June 17, 2017, until one minute before the slide at 11:39 p.m. that released up to 51 million cubic meters of material.

The Rice algorithm revealed weak but repetitive rumblings — undetectable in raw seismic records — that began about nine hours before the event and accelerated over time, leading to the landslide.

“There was a precursor paper to this one by our co-author, Piero Poli at Grenoble, that studied the event without AI,” de Hoop said. “They discovered something in the data they thought we should look at, and because the area is isolated from a lot of other noise and tectonic activity, it was the purest data we could work with to try our ideas.”

De Hoop is continuing to test the algorithm to analyze volcanic activity in Costa Rica and is also involved with NASA’s InSight lander, which delivered a seismic detector to the surface of Mars nearly two years ago.

Constant monitoring that delivers such warnings in real time will save lives, de Hoop said.

“People ask me if this study is significant — and yes, it is a major step forward — and then if we can predict earthquakes. We’re not quite ready to do that, but this direction is, I think, one of the most promising at the moment.”

When de Hoop joined Rice five years ago, he brought expertise in solving inverse problems that involve working backwards from data to find a cause. Baraniuk is a leading expert in machine learning and compressive sensing, which help extract useful data from sparse samples. Together, they’re a formidable team.

“The most exciting thing about this work is not the current result, but the fact that the approach represents a new research direction for machine learning as applied to geophysics,” Baraniuk said.

“I come from the mathematics of deep learning and Rich comes from signal processing, which are at opposite ends of the discipline,” de Hoop said. “But here we meet in the middle. And now we have a tremendous opportunity for Rice to build upon its expertise as a hub for seismologists to gather and put these pieces together. There’s just so much data now that it’s becoming impossible to handle any other way.”

De Hoop is helping to grow Rice’s reputation for seismic expertise with the Simons Foundation Math+X Symposia, which have already featured events on space exploration and mitigating natural hazards like volcanoes and earthquakes. A third event, dates to be announced, will study deep learning applications for solar giants and exoplanets.

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Electron movements in liquid measured in super-slow motion

To understand how chemical reactions begin, chemists have been using super-slow motion experiments for years to study the very first moments of a reaction. These days, measurements with a resolution of a few dozen attoseconds are possible. An attosecond is 1×10^-18 of a second, i.e. a millionth of a millionth of a millionth of a second.

“In these first few dozen attoseconds of a reaction, you can already observe how electrons shift within molecules,” explains Hans Jakob Wörner, Professor at the Laboratory of Physical Chemistry at ETH Zurich. “Later, in the course of about 10,000 attoseconds or 10 femtoseconds, chemical reactions result in movements of atoms up to and including the breaking of chemical bonds.”

Five years ago, the ETH professor was one of the first scientists to be able to detect electron movements in molecules on the attosecond scale. However, up to now such measurements could be carried out only on molecules in gaseous form because they take place in a high-vacuum chamber.

Delayed transport of electrons from the liquid

After building novel measuring equipment, Wörner and his colleagues have now succeeded in detecting such movements in liquids. To this end, the researchers made use of photoemission in water: they irradiated water molecules with light, causing them to emit electrons that the scientists could then measure. “We chose to use this process for our investigation because it is possible to start it with high temporal precision using laser pulses,” Wörner says.

The new measurements also took place in high vacuum. Wörner and his team injected a 25-micrometre-thin water microjet into the measuring chamber. This allowed them to discover that electrons are emitted from water molecules in liquid form 50-70 attoseconds later than from water molecules in vapour form. The time difference is due to the fact that the molecules in liquid form are surrounded by other water molecules, which has a measurable delay effect on individual molecules.

Important step

“Electron movements are the key events in chemical reactions. That’s why it’s so important to measure them on a high-resolution time scale,” Wörner says. “The step from measurements in gases to measurements in liquids is of particular importance, because most chemical reactions — especially the ones that are biochemically interesting — take place in liquids.”

Among those, there are numerous processes that, like photoemission in water, are also triggered by light radiation. These include photosynthesis in plants, the biochemical processes on our retina that enable us to see, and damage to DNA caused by X-rays or other ionising radiation. With the help of attosecond measurements, scientists should gain new insights into these processes in the coming years.

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Cool new worlds found in our cosmic backyard

How complete is our census of the Sun’s closest neighbors? Astronomers using NSF’s NOIRLab facilities and a team of data-sleuthing volunteers participating in Backyard Worlds: Planet 9, a citizen science project, have discovered roughly 100 cool worlds near the Sun — objects more massive than planets but lighter than stars, known as brown dwarfs. Several of these newly discovered worlds are among the very coolest known, with a few approaching the temperature of Earth — cool enough to harbor water clouds.

Discovering and characterizing astronomical objects near the Sun is fundamental to our understanding of our place in, and the history of, the Universe. Yet astronomers are still unearthing new residents of the Solar neighborhood. A remarkable breakthrough was announced today, with the discovery of roughly 100 cool brown dwarfs near the Sun [1].The new Backyard Worlds discoveries bridge a previously empty gap in the range of low-temperature brown dwarfs, identifying a long-sought missing link within the brown dwarf population.

These cool worlds offer the opportunity for new insights into the formation and atmospheres of planets beyond the Solar System,” said Aaron Meisner from the National Science Foundation’s NOIRLab and the lead author of the research paper. “This collection of cool brown dwarfs also allows us to accurately estimate the number of free-floating worlds roaming interstellar space near the Sun.”

This major advancement was made possible with archival data from the Nicholas U. Mayall 4-meter Telescope at Kitt Peak National Observatory (KPNO) and the Víctor M. Blanco 4-meter Telescope at Cerro Tololo Inter-American Observatory (CTIO), which were made available through the Community Science and Data Center (CSDC), all programs of NSF’s NOIRLab. Large survey data sets were then made available to the Backyard Worlds volunteers using NOIRLab’s Astro Data Lab science platform. The results, to be published in TheAstrophysical Journal, demonstrate the rapidly growing role of survey and archival data research in astronomy today.

Brown dwarfs lie somewhere between the most massive planets and the smallest stars. Lacking the mass needed to sustain nuclear reactions in their core, brown dwarfs resemble cooling embers. Their low mass, low temperature and lack of internal nuclear reactions make them extremely faint — and therefore extremely difficult to detect. Because of this, when searching for the very coolest brown dwarfs, astronomers can only hope to detect such objects relatively close to the Sun.

To help find our Sun’s coldest and nearest neighbors, the astronomers of the Backyard Worlds project turned to a worldwide network of more than 100,000 citizen scientists [2]. These volunteers diligently inspect trillions of pixels of telescope images to identify the subtle movements of brown dwarfs and planets. Despite the abilities of machine learning and supercomputers, there’s no substitute for the human eye when it comes to scouring telescope images for moving objects.

The keen eyes of the Backyard Worlds volunteers have already discovered more than 1,500 cold worlds near to the Sun, and today’s paper presents roughly 100 of the coldest in that sample. According to Meisner, this is a record for any citizen science program by a factor of about 20, and 20 citizen scientists are listed as co-authors of the study. A handful of these cool worlds — which are among the very coldest brown dwarfs known — approach the temperature of Earth. NASA’s Spitzer Space Telescope provided the brown dwarf temperature estimates [3].

Brown dwarfs are expected to cool as they age, passing from near-stellar temperatures down to planetary temperatures and below, fading all the while and eventually winking out. The new discoveries attest to this picture by uncovering elusive examples of brown dwarfs approaching Earth-temperature.

“This paper is evidence that the solar neighborhood is still uncharted territory and citizen scientists are excellent astronomical cartographers,” said co-author Jackie Faherty of the American Museum of Natural History. “Mapping the coldest brown dwarfs down to the lowest masses gives us key insights into the low-mass star formation process while providing a target list for detailed studies of the atmospheres of Jupiter analogs.”

Citizen scientist, Astro Data Lab user, and paper co-author Jim Walla added, “It’s awesome to know that our discoveries are now counted among the Sun’s neighbors and will be targets of further research.”

Alongside the dedicated efforts of the Backyard Worlds volunteers, NOIRLab’s Astro Data Lab was instrumental in this research. The technical burden of downloading billion-object astronomical catalogs is typically insurmountable for individual investigators — including most professional astronomers. “AstroData Lab’s open and accessible web portal allowed Backyard Worlds citizen scientists to easily query massive catalogs for brown dwarf candidates,” explained NOIRLab astronomer Stephanie Juneau, who helped introduce the citizen scientists to Astro Data Lab. Astro Data Lab also enables convenient matching between data sets from NOIRLab telescopes and external facilities, such as NASA’s WISE satellite, that jointly contributed to these brown dwarf discoveries.

In addition to Astro Data Lab’s making data accessible to the Backyard Worlds collaboration, archival observations by telescopes at two other NOIRLab Programs — CTIO and KPNO — were also key to this discovery. “Wide-area imaging from NOIRLab’s Mayall and Blanco telescopes was also critical,” explained Aaron Meisner. “To select only the very coldest brown dwarfs, we inspected deep images from a variety of sensitive astronomical surveys.”

“It’s great to see such thrilling results from NOIRLab’s efforts to broaden participation in astronomy research,” said Chris Davis of the National Science Foundation, the US agency that supports operations at the Kitt Peak and Cerro Tololo observatories and at CSDC. “By making archival data from NSF’s Mayall and Blanco telescopes publicly available and easily accessible through CSDC, folks with a fascination for astronomy can make a real contribution to science and to our understanding of the Universe.”

The approach of the Backyard Worlds project — searching for rare objects in large data sets — is also one of the goals for the upcoming Vera C. Rubin Observatory [4]. Currently under construction on Cerro Pachón in the Chilean Andes, Rubin Observatory will image the visible sky from the southern hemisphere every three nights over ten years, providing a vast amount of data that will enable new ways of doing astrophysical research.

“Vast modern data sets can unlock landmark discoveries, and it’s exciting that these could be spotted first by a citizen scientist,” concludes Aaron Meisner. “These Backyard Worlds discoveries show that members of the public can play an important role in reshaping our scientific understanding of our solar neighborhood.”

Notes

[1] The closest of these new discoveries is roughly 23 light-years away from the Sun. Many more of these brown dwarfs are in the 30-60 light-year distance range.

[2] Backyard Worlds: Planet 9 is hosted by Zooniverse.

[3] Complementary follow-up observations were also supplied by Keck Observatory, Mont Mégantic Observatory, and Carnegie Institution for Science’s Las Campanas Observatory.

[4] Rubin Observatory and Department of Energy (DOE) Legacy Survey of Space and Time Camera are operated by NSF’s NOIRLab and SLAC National Accelerator Laboratory (SLAC).

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Long-term risks of joint implants

Using highly complex analytical techniques, a group of researchers from Charité — Universitätsmedizin Berlin were able to observe in detail how different metals are released from joint implants and accumulate in the surrounding bone tissue. Findings showed a steady release of metals from various implant components. In contrast to previous assumptions, this was not related to the degree of mechanical stress involved. The researchers’ findings, which have been published in Advanced Science, will help to optimize the materials used in implants and enhance their safety.

Modern joint implants restore pain-free mobility of patients with chronic degenerative joint disease, thereby drastically enhancing their quality of life. To ensure long-term mechanical stability, artificial joints are made from materials containing a range of different metal alloys. A crucial factor in determining an implant’s long-term effectiveness, however, is its integration into the surrounding bone tissue. Previous studies on implant stability show that friction between the articulating surfaces (bearing surfaces) can result in the formation of metal debris. This wear debris can lead to osteolysis — the destruction of bone around the implant — which can result in premature loosening of the implant. The possibility of a steady release of metal from other parts of the prosthesis had not previously received much attention.

A group of researchers led by Dr. Sven Geißler of Charité’s Julius Wolff Institute for Biomechanics and Musculoskeletal Regeneration and BIH Center for Regenerative Therapies has now studied the spatial distribution and local toxicokinetics of metallic wear and corrosion products within the surrounding bone tissue. For their detailed analysis, the researchers used a unique synchrotron-based X-ray fluorescence imaging setup. “Our work has enabled us to show, for the first time, that both particulate and dissolved metals released from arthroplasty implants are present in the surrounding bone and bone marrow at supraphysiological levels,” says Dr. Geißler. “Therefore, the collagen-rich layer which encapsulates the implant after surgery does not separate these metals from human tissue to the extent previously assumed.”

The researchers collected minute bone and bone marrow samples from 14 patients undergoing either a hip or knee arthroplasty procedure. The researchers then determined the qualitative and quantitative composition of the samples using a technique known a X-ray fluorescence. This technique provides unique insights into the concentration, distribution, location and accumulation of metallic degradation products like cobalt, chromium or titanium in adjacent bone and bone marrow. The extremely bright and intensively focused X-ray beam required was achieved by the synchrotron radiation source at the European Synchrotron Radiation Facility (ESRF). The ESRF, which is located in Grenoble, France, is the only particle accelerator in the world to offer a spatial resolution of up to 30 nanometers. Summing up the researchers’ achievements, the study’s first author, Dr. Janosch Schoon, says: “Our work therefore addresses an issue of enormous clinical relevance with a highly complex experimental setup.”

“Our study has made a major contribution to the improvement of the risk-benefit evaluation of medical devices. It has shown that these evaluations should not only comprise biocompatibility testing of raw materials; rather, biocompatibility testing should also extend to wear and corrosion products. The data from this study will therefore prove instrumental in keeping implant safety at the highest possible level,” explains Dr. Geißler. Based on their findings, the researchers plan to conduct additional studies which will investigate the biological consequences of metal release on bones and bone marrow. At the same time, the researchers will develop new approaches which will facilitate the reliable preclinical testing of implant materials using both human cells and engineered tissues.

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Scientists use CRISPR to knock down gene messages early in development

Since its discovery, scientists have been using the much-lauded gene editing tool CRISPR to alter the DNA of model organisms and uncover the functions of thousands of genes. Now, researchers at the Stowers Institute for Medical Research in Kansas City, Missouri, and the Andalusian Center of Developmental Biology at Pablo de Olavide University in Seville, Spain, have harnessed the technology to target gene messages (messenger RNA) involved in early vertebrate development.

By disrupting gene messages (RNA) instead of the underlying genes (DNA), researchers can study genes that might previously have been difficult or impossible to manipulate because they were essential to life or involved in a critical stage of biological development. This approach also allows targeting of maternally-contributed gene RNAs, which are deposited in the egg to kick off the earliest genetic programs.

The study, which appears online August 7, 2020, in the journal Developmental Cell, establishes the use of CRISPR-Cas technology to target RNA in embryonic animal models in a specific and systematic manner. The findings demonstrate the technique can be applied to a broad range of aquatic and terrestrial models including zebrafish, medaka, killifish, and mice.

“The exciting thing about this study is not just what we found, but what we can do,” says Ariel Bazzini, PhD, an assistant investigator at the Stowers Institute and co-leader of the study. “We still don’t understand how genes jumpstart the earliest stages of development. Now we can find out by targeting their RNA messages, one by one.”

“We are also very excited about the the low cost of the technique,” Bazzini says. “Any lab working with zebrafish or other animal embryos could use this method. Indeed, we have already distributed the reagents and protocol to several labs around the world.”

Before development even begins, egg must first meet sperm. The resulting embryo carries half the genes from the mother and half from the father. In addition to its genome, the embryo has components such as RNA and proteins provided by the mother.

“That maternal contribution is a mystery that many of us want to solve,” says Bazzini. However, attempts to systematically target RNA in zebrafish, the model organism of choice for many developmental biologists, have been unsuccessful. The aptly-named RNA interference method, which has been a mainstay in studies of gene function, does not work in zebrafish, or other fish or frogs. Other methods using synthetics strips of genetic code known as morpholinos or antisense oligonucleotides have sometimes been associated with toxicity and off-target effects.

So when Bazzini and his collaborator and friend Miguel A. Moreno-Mateos, PhD, a professor at Pablo de Olavide University, noticed reports that CRISPR technology had been employed to degrade RNA in yeast, plants, and mammalian cells, they were eager to give it a try. Moreno-Mateos was a postdoc in Antonio Giraldez’s lab at Yale University at the same time as Bazzini, and is considered an expert on the optimization of CRISPR-Cas technology in vivo.

The CRISPR-Cas13 system depends on two ingredients — a short RNA sequence known as a “guide” RNA, and an enzyme called Cas13 (part of the Cas, or CRISPR-associated, family of proteins) that cuts any RNA messages in the cell that could line up and bind to that guide sequence. The researchers tested four different Cas13 proteins that had been successfully used in previous studies. They found that the Cas13 proteins were either inefficient or toxic to the developing zebrafish, except for one protein, called RfxCas13d.

They then examined whether targeting RNA with CRISPR-RfxCas13d in zebrafish embryos could recreate the same defects as altering the organism’s underlying DNA. For example, when they targeted the RNA of the tbxta gene, which is necessary for growing a tail, the zebrafish embryos were tailless.

The researchers went on to show that the CRISPR system could efficiently target a variety of RNAs, both those provided by the mother as well as those produced by the embryo, decreasing RNA levels by an average of 76%. Collaborators within and outside of Stowers helped derive that statistic, and showed that the technique also works in killifish, medaka, and mouse embryos.

“The CRISPR-RfxCas13d system is an efficient, specific and inexpensive method that can be used in animal embryos in a comprehensive manner,” says Moreno-Mateos, who is also co-leader of the study. “With this tool we will help to understand fundamental questions in biology and biomedicine.”

One of the fundamental questions the researchers hope to pursue is the role that RNA plays in the earliest hours of development. The RNAs left behind by the mother have to be removed at precisely the same time that the genome of the embryo comes online; otherwise, the embryo never develops.

“We think this tool could have a profound effect on our understanding of infertility and developmental problems in general,” says Bazzini.

“The Stowers facilities and collaborative environment have allowed us to test CRISPR technology in other animal model systems,” Bazzini says. “When I joined Stowers about four years ago, I would have never predicted that my lab would be doing experiments in mouse or killifish models. It’s been a fun adventure!”

Other coauthors from the Stowers Institute include Gopal Kushawah, PhD, Michelle DeVore, Huzaifa Hassan, Wei Wang, PhD, Timothy J. Corbin, Andrea M. Moran, and Alejandro Sánchez Alvarado, PhD.

This research was funded by the Stowers Institute for Medical Research, Pablo de Olavide University, Consejo Superior de Investigaciones Cientificas, and Junta de Andalucia. Additional support included the Ramon y Cajal program (RyC-2017-23041) and grants (BFU2017-86339-P, PGC2018-097260-B-I00, and MDM-2016-0687) from the Spanish Ministerio de Ciencia, Innovación y Universidades; the Springboard program from Centro Andaluz de Biología del Desarrollo; Genome Engineer Innovation 2019 Grant from Synthego; the Pew Innovation Fund; Innovate Peru (grant 168-PNICP-PIAP-2015); and FONDECYT (travel grant 043-2019).

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Stellar egg hunt with ALMA

Astronomers using the Atacama Large Millimeter/submillimeter Array (ALMA) took a census of stellar eggs in the constellation Taurus and revealed their evolution state. This census helps researchers understand how and when a stellar embryo transforms to a baby star deep inside a gaseous egg. In addition, the team found a bipolar outflow, a pair of gas streams, that could be telltale evidence of a truly newborn star.

Stars are formed by gravitational contraction of gaseous clouds. The densest parts of the clouds, called molecular cloud cores, are the very sites of star formation and mainly located along the Milky Way. The Taurus Molecular Cloud is one of the active star-forming regions and many telescopes have been pointed at the cloud. Previous observations show that some cores are actually stellar eggs before the birth of stars, but others already have infant stars inside.

A research team led by Kazuki Tokuda, an astronomer at Osaka Prefecture University and the National Astronomical Observatory of Japan (NAOJ), utilized the power of ALMA to investigate the inner structure of the stellar eggs. They observed 32 starless cores and nine cores with baby protostars. They detected radio waves from all of the nine cores with stars, but only 12 out of 32 starless cores showed a signal. The team concluded that these 12 eggs have developed internal structures, which shows they are more evolved than the 20 quite cores.

“Generally speaking, radio interferometers using many antennas, like ALMA, are not good at observing featureless objects like stellar eggs,” says Tokuda. “But in our observations, we purposely used only the 7-m antennas of ALMA. This compact array enables us to see objects with smooth structure, and we got information about the internal structure of the stellar eggs, just as we intended.”

Increasing the spacing between the antennas improves the resolution of a radio interferometer, but makes it difficult to detect extended objects. On the other hand, a compact array has lower resolution but allows us to see extended objects. This is why the team used ALMA’s compact array of 7-m antennas, as known as the Morita Array, not the extended array of 12-m antennas.

They found that there is a difference between the two groups in the gas density at the center of the dense cores. Once the density of the center of a dense core exceeds a certain threshold, about one million hydrogen molecules per cubic centimeter, self-gravity leads the egg to transform into a star.

A census is also useful for finding a rare object. The team noticed that there is a weak but clear bipolar gas stream in one stellar egg. The size of the stream is rather small, and no infrared source has been identified in the dense core. These characteristics match well with the theoretical predictions of a “first hydrostatic core,” a short-lived object formed just before the birth of a baby star. “Several candidates for the first hydrostatic cores have been identified in other regions,” explains Kakeru Fujishiro, a member of the research team. “This is the first identification in the Taurus region. It is a good target for future extensive observation.”

Kengo Tachihara, an associate professor at Nagoya University mentions the role of Japanese researchers in this study. “Japanese astronomers have studied the baby stars and stellar eggs in Taurus using the Nagoya 4-m radio telescope and Nobeyama 45-m radio telescope since the 1990s. And, ALMA’s 7-m array was also developed by Japan. The present result is part of the culmination of these efforts.”

“We have succeeded in illustrating the growth history of stellar eggs up to their birth, and now we have established the method for the research,” summarizes Tokuda. “This is an important step to obtain a comprehensive understanding of star formation.”

 

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Materials provided by National Institutes of Natural Sciences. Note: Content may be edited for style and length.

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