Neutrinos yield first experimental evidence of catalyzed fusion dominant in many stars

An international team of about 100 scientists of the Borexino Collaboration, including particle physicist Andrea Pocar at the University of Massachusetts Amherst, report in Nature this week detection of neutrinos from the sun, directly revealing for the first time that the carbon-nitrogen-oxygen (CNO) fusion-cycle is at work in our sun.

The CNO cycle is the dominant energy source powering stars heavier than the sun, but it had so far never been directly detected in any star, Pocar explains.

For much of their life, stars get energy by fusing hydrogen into helium, he adds. In stars like our sun or lighter, this mostly happens through the ‘proton-proton’ chains. However, many stars are heavier and hotter than our sun, and include elements heavier than helium in their composition, a quality known as metallicity. The prediction since the 1930’s is that the CNO-cycle will be dominant in heavy stars.

Neutrinos emitted as part of these processes provide a spectral signature allowing scientists to distinguish those from the ‘proton-proton chain’ from those from the ‘CNO-cycle.’ Pocar points out, “Confirmation of CNO burning in our sun, where it operates at only one percent, reinforces our confidence that we understand how stars work.”

Beyond this, CNO neutrinos can help resolve an important open question in stellar physics, he adds. That is, how the sun’s central metallicity, as can only be determined by the CNO neutrino rate from the core, is related to metallicity elsewhere in a star. Traditional models have run into a difficulty — surface metallicity measures by spectroscopy do not agree with the sub-surface metallicity measurements inferred from a different method, helioseismology observations.

Pocar says neutrinos are really the only direct probe science has for the core of stars, including the sun, but they are exceedingly difficult to measure. As many as 420 billion of them hit every square inch of the earth’s surface per second, yet virtually all pass through without interacting. Scientists can only detect them using very large detectors with exceptionally low background radiation levels.

The Borexino detector lies deep under the Apennine Mountains in central Italy at the INFN’s Laboratori Nazionali del Gran Sasso. It detects neutrinos as flashes of light produced when neutrinos collide with electrons in 300-tons of ultra-pure organic scintillator. Its great depth, size and purity make Borexino a unique detector for this type of science, alone in its class for low-background radiation, Pocar says. The project was initiated in the early 1990s by a group of physicists led by Gianpaolo Bellini at the University of Milan, Frank Calaprice at Princeton and the late Raju Raghavan at Bell Labs.

Until its latest detections, the Borexino collaboration had successfully measured components of the ‘proton-proton’ solar neutrino fluxes, helped refine neutrino flavor-oscillation parameters, and most impressively, even measured the first step in the cycle: the very low-energy ‘pp’ neutrinos, Pocar recalls.

Its researchers dreamed of expanding the science scope to also look for the CNO neutrinos — in a narrow spectral region with particularly low background — but that prize seemed out of reach. However, research groups at Princeton, Virginia Tech and UMass Amherst believed CNO neutrinos might yet be revealed using the additional purification steps and methods they had developed to realize the exquisite detector stability required.

Over the years and thanks to a sequence of moves to identify and stabilize the backgrounds, the U.S. scientists and the entire collaboration were successful. “Beyond revealing the CNO neutrinos which is the subject of this week’s Nature article, there is now even a potential to help resolve the metallicity problem as well,” Pocar says.

Before the CNO neutrino discovery, the lab had scheduled Borexino to end operations at the close of 2020. But because the data used in the analysis for the Nature paper was frozen, scientists have continued collecting data, as the central purity has continued to improve, making a new result focused on the metallicity a real possibility, Pocar says. Data collection could extend into 2021 since the logistics and permitting required, while underway, are non-trivial and time-consuming. “Every extra day helps,” he remarks.

Pocar has been with the project since his graduate school days at Princeton in the group led by Frank Calaprice, where he worked on the design, construction of the nylon vessel and the commissioning of the fluid handling system. He later worked with his students at UMass Amherst on data analysis and, most recently, on techniques to characterize the backgrounds for the CNO neutrino measurement.

This work was supported in the U.S. by the National Science Foundation. Borexino is an international collaboration also funded by the Italian National Institute for Nuclear Physics (INFN), and funding agencies in Germany, Russia and Poland.

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Understanding the power of our Sun

Stars produce their energy through nuclear fusion by converting hydrogen into helium — a process known to researchers as “hydrogen burning.” There are two ways of carrying out this fusion reaction: one, the so-called pp cycle (proton-proton reaction) or the other, the Bethe Weizsäcker cycle (also known as the CNO cycle, derived from the elements carbon (C), nitrogen (N) and oxygen (O)).

The pp cycle is the predominant energy source in our Sun, only about 1.6 per mil of its energy comes from the CNO cycle. However, the Standard Solar Model (SSM) predicts that the CNO cycle is probably the predominant reaction in much larger stars. As early as the 1930s, the cycle was theoretically predicted by the physicists Hans Bethe and Carl Friedrich von Weizsäcker and subsequently named after these two gentlemen. While the pp cycle could already be experimentally proven in 1992 at the GALLEX experiment, also in the Gran Sasso massif, the experimental proof of the CNO cycle has so far not been successful.

Both the pp cycle and the CNO cycle produce countless neutrinos — very light and electrically neutral elementary particles. The fact that neutrinos hardly interact with other matter allows them to leave the interior of the sun at almost the speed of light and to transport the information about their origin to earth unhindered. Here the ghost particles have no more than to be captured. This is a rather complex undertaking, which is only possible in a few large-scale experiments worldwide, since neutrinos show up as small flashes of light in a huge tank full of a mixture of water, mineral oil and other substances, also called scintillator. The evaluation of the measured data is complex and resembles looking for a needle in a haystack.

Compared to all previous and ongoing solar neutrino experiments, Borexino is the first and only experiment worldwide that is able to measure these different components individually, in real time and with a high statistical power. This week, the Borexino research collaboration was able to announce a great success: In the scientific journal Nature, they present their results on the first experimental detection of CNO neutrinos — a milestone in neutrino research.

Dresden physicist Professor Kai Zuber is a passionate neutrino hunter.

He is involved in many different experiments worldwide, such as the SNO collaboration in Canada, which was awarded the Nobel Prize for its discovery of a neutrino mass. The fact that with Borexino, he and his colleagues Dr Mikko Meyer and Jan Thurn have now succeeded in experimentally proving the CNO neutrinos for the first time is another major milestone in Zuber’s scientific career: “Actually, I have now achieved everything I had imagined and hoped for. I (almost) no longer believe in great new discoveries in solar neutrino research for the rest of my lifetime. However, I would like to continue working on the optimization of the experiments, in which the Felsenkeller accelerator here in Dresden plays an extremely important role. For sure, we will be able to have even more precise measurements of the Sun in the future.”

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Phytoplankton disturbed by nanoparticles

Products derived from nanotechnology are efficient and highly sought-after, yet their effects on the environment are still poorly understood. A research team from the University of Geneva (UNIGE), working in collaboration with the University of California at Santa Barbara, have investigated the effects of nanosilver, currently used in almost 450 products for its antibacterial properties, on the algae known as Poterioochromonas malhamensis. The results — published in the journal Scientific Reports — show that nanosilver and its derivative, ionic silver, disturb the alga’s entire metabolism. Its membrane becomes more permeable, the cellular reactive oxygen species increases and photosynthesis is less effective. The Swiss-American team was able to demonstrate for the first time the metabolic perturbations induced by nanosilver following its uptake in the food vacuoles of freshwater algae, paving the way for early detection of the metabolic changes before they express themselves physiologically.

The nanosilver is used for its antibacterial properties and is employed in textiles and cosmetics, inter alia. In addition, the agro-food, biomedical and biopharmaceutical industry is interested in it for developing drugs, devices and pesticides. “Since nanosilver is designed to destroy, repel or render harmless noxious organisms such as bacteria, scientists have realised that it might also be harmful to organisms that are crucial to our environment,” begins Vera Slaveykova from the Department F.A. Forel for Environmental and Aquatic Sciences in UNIGE’s Faculty of Sciences. To assess the influence of nanotechnology products on phytoplankton and to evaluate the impacts on aquatic environment, the researcher team conducted a study on the alga Poterioochromonas malhamensis as a model phytoplankton species. “The phytoplankton are everywhere, in lakes and oceans,” continues Professor Slaveykova. “As a whole, phytoplankton generate almost half of the oxygen we breathe. And they have a second essential role, since they are at the base of the food chain. If they accumulate nanoparticles, these will be integrated into the aquatic food chain.”

Multiple disturbances

The study led by Professor Slaveykova shows that treating the algae with nanosilver disrupts the metabolism of the amino acids that are vital for producing cellular proteins, the nucleotide metabolism that is important for genes, and fatty and tricarboxylic acids making up the membranes, as well as the photosynthesis and photorespiration elements.

The study results suggest that the silver ions released by the silver nanoparticles are the main toxicity factor. “The nanosilver is internalised in the algal cells by the phagocytotic mechanism used to supply cells with organic matter,” continues Professor Slaveykova. The study is the first to demonstrate that nanoparticles can follow such internalisation path in a species of phytoplankton. “These measurements were carried out in Geneva by Dr Liu using transmission electron microscopy. This entry mechanism is only known in Poterioochromonas malhamensis; it is still unknown if other phytoplankton species express it,” explains the Geneva researcher.

To finish demonstrating nanosilver’s toxicity, the international research team highlighted the fact that metabolic disturbances induce physiological dysfunctions. Professor Slaveykova observed lipid peroxidation leading to membrane permeabilization, increased oxidative stress and less efficient photosynthesis — and, it follows, reduced oxygen production.

An Approach That Needs to Be Implemented

The study underlines the full potential of metabolomics geared towards the molecular basis of the disruptions observed. “It’s a fundamental contribution to the field: although the metabolomics approaches are properly in place in medical and pharmaceutical sciences, it’s not at all the case for environmental toxicology where phytoplankton metabolomics is still in its infancy. The metabolomics is, therefore, a technique that offers the possibility of early detection of changes induced by a toxin, upstream of more global effects such as the alga growth inhibition and their impact on oxygen production. As it’s never easy to demonstrate the relationships between cause and effect in complex environment, it is now essential to use approaches like these.”

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A microscope for everyone: Researchers develop open-source optical toolbox

Modern microscopes used for biological imaging are expensive, are located in specialized laboratories and require highly qualified staff. To research novel, creative approaches to address urgent scientific issues — for example in the fight against infectious diseases such as Covid-19 — is thus primarily reserved for scientists at well-equipped research institutions in rich countries. A young research team from the Leibniz Institute of Photonic Technology (Leibniz IPHT) in Jena, the Friedrich Schiller University and Jena University Hospital wants to change this: The researchers have developed an optical toolbox to build microscopes for a few hundred euros that deliver high-resolution images comparable to commercial microscopes that cost a hundred to a thousand times more. With open-source blueprints, components from the 3D printer and smartphone camera, the UC2 (You. See. Too.) modular system can be combined specifically in the way the research question requires — from long-term observation of living organisms in the incubator to a toolbox for optics education.

The basic building block of the UC2 system is a simple 3D printable cube with an edge length of 5 centimeters, which can host a variety of components such as lenses, LEDs or cameras. Several such cubes are plugged on a magnetic raster base plate. Cleverly arranged, the modules thus result in a powerful optical instrument. An optical concept according to which focal planes of adjacent lenses coincide is the basis for most of the complex optical setups such as modern microscopes. With the UC2 toolbox, the research team of PhD students at the lab of Prof. Dr. Rainer Heintzmann, Leibniz IPHT and Friedrich Schiller University Jena, shows how this inherently modular process can be understood intuitively in hands-on-experiments. In this way, UC2 also provides users without technical training with an optical tool that they can use, modify and expand — depending on what they are researching.

Monitor pathogens — and then recycle the contaminated microscope

Helge Ewers, Professor of Biochemistry at the Free University of Berlin and the Charité, is investigating pathogens usind the UC2 toolbox. “The UC2 system allows us to produce a high-quality microscope at low cost, with which we can observe living cells in an incubator,” he states. UC2 thus opens up areas of application for biomedical research for which conventional microscopes are not suitable. “Commercial microscopes that can be used to examine pathogens over a longer period of time cost hundreds or thousands of times more than our UC2 setup,” says Benedict Diederich, PhD student at Leibniz-IPHT, who developed the optical toolbox there together with René Lachmann. “You can hardly get them into a contaminated laboratory from which you may not be able to remove them because they cannot be cleaned easily.” The UC2 microscope made of plastic, on the other hand, can be easily burned or recycled after its successful use in the biological safety laboratory. For a study at Jena University Hospital, the UC2 team observed the differentiation of monocytes into macrophages in the incubator over a period of one week in order to gain insights into how the innate immune system fights off pathogens in the body.

Building according to the Lego principle: From the idea to the prototype

Building according to the Lego principle — this not only awakens the users’ inner play instinct, observes the UC2 team, but it also opens up new possibilities for researchers to design an instrument precisely tailored to their research question. “With our method, it is possible to quickly assemble the right tool to map specific cells,” explains Benedict Diederich. “If, for example, a red wavelength is required as excitation, you simply install the appropriate laser and change the filter. If an inverted microscope is needed, you stack the cubes accordingly. With the UC2 system, elements can be combined depending on the required resolution, stability, duration or microscopy method and tested directly in the “rapid prototyping” process.

The Vision: Open Science

The researchers publish construction plans and software on the freely accessible online repository GitHub, so that the open-source community worldwide can access, rebuild, modify and expand the presented systems. “With the feedback from users, we improve the system step by step and add ever new creative solutions,” reports René Lachmann. The first users have already started to expand the system for themselves and their purposes. “We are eager to see when we can present the first user solutions.”

The aim behind this is to enable open science. Thanks to the detailed documentation, researchers can reproduce and further develop experiments anywhere in the world, even beyond well-equipped laboratories. “Change in Paradigm: Science for a Dime” is what Benedict Diederich calls this vision: to herald a paradigm shift in which the scientific process is as open and transparent as possible, freely accessible to all, where researchers share their knowledge with each other and incorporate it into their work.

UC2 experiment box brings science to schools

In order to get especially young people interested in optics, the research team has developed a sophisticated tool set for educational purposes in schools and universities. With “The Box” UC2 introduces a kit that enables users to learn about and try out optical concepts and microscopy methods. “The components can be combined to form a projector or a telescope; you can build a spectrometer or a smartphone microscope,” explains Barbora Maršíková, who developed experiments and a series of ready-to-use documentations that the UC2 team already tested in several workshops in and around Jena as well as in the US, in Great Britain and Norway. In Jena, the young researchers have already used the UC2 toolbox in several schools and e.g. supported pupils to build a fluorescence microscope to detect microplastics. “We have combined UC2 with our smartphone. This enabled us to build our own fluorescence microscope cost-effectively without any major optical knowledge and to develop a comparably simple method for detecting plastic particles in cosmetics,” reports Emilia Walther from the Montessori School in Jena, who together with her group is pursuing an innovative interdisciplinary learning approach.

“We want to make modern microscopy techniques accessible to a broad public,” says Benedict Diederich, “and build up an open and creative microscopy community.” This build-it-yourself approach to teaching has a huge potential, especially at times of the Corona pandemics, when access to teaching material at home is severely limited.

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Patterning method could pave the way for new fiber-based devices, smart textiles

Multimaterial fibers that integrate metal, glass and semiconductors could be useful for applications such as biomedicine, smart textiles and robotics. But because the fibers are composed of the same materials along their lengths, it is difficult to position functional elements, such as electrodes or sensors, at specific locations. Now, researchers reporting in ACS Central Science have developed a method to pattern hundreds-of-meters-long multimaterial fibers with embedded functional elements.

Youngbin Lee, Polina Anikeeva and colleagues developed a thiol-epoxy/thiol-ene polymer that could be combined with other materials, heated and drawn from a macroscale model into fibers that were coated with the polymer. When exposed to ultraviolet light, the polymer, which is photosensitive, crosslinked into a network that was insoluble to common solvents, such as acetone. By placing “masks” at specific locations along the fiber in a process known as photolithography, the researchers could protect the underlying areas from UV light. Then, they removed the masks and treated the fiber with acetone. The polymer in the areas that had been covered dissolved to expose the underlying materials.

As a proof of concept, the researchers made patterns along fibers that exposed an electrically conducting filament underneath the thiol-epoxy/thiol-ene coating. The remaining polymer acted as an insulator along the length of the fiber. In this way, electrodes or other microdevices could be placed in customizable patterns along multimaterial fibers, the researchers say.

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Journal Reference:

  1. Youngbin Lee, Andres Canales, Gabriel Loke, Mehmet Kanik, Yoel Fink, Polina Anikeeva. Selectively Micro-Patternable Fibers via In-Fiber Photolithography. ACS Central Science, 2020; DOI: 10.1021/acscentsci.0c01188

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When consumers trust AI recommendations, or resist them

Researchers from Boston University and University of Virginia published a new paper in the Journal of Marketing that examines how consumers respond to AI recommenders when focused on the functional and practical aspects of a product (its utilitarian value) versus the experiential and sensory aspects of a product (its hedonic value).

The study, forthcoming in the the Journal of Marketing, is titled “Artificial Intelligence in Utilitarian vs. Hedonic Contexts: The ‘Word-of-Machine’ Effect” and is authored by Chiara Longoni and Luca Cian.

More and more companies are leveraging technological advances in AI, machine learning, and natural language processing to provide recommendations to consumers. As these companies evaluate AI-based assistance, one critical question must be asked: When do consumers trust the “word of machine,” and when do they resist it?

A new Journal of Marketing study explores reasons behind the preference of recommendation source (AI vs. human). The key factor in deciding how to incorporate AI recommenders is whether consumers are focused on the functional and practical aspects of a product (its utilitarian value) or on the experiential and sensory aspects of a product (its hedonic value).

Relying on data from over 3,000 study participants, the research team provides evidence supporting a word-of-machine effect, defined as the phenomenon by which the trade-offs between utilitarian and hedonic aspects of a product determine the preference for, or resistance to, AI recommenders. The word-of-machine effect stems from a widespread belief that AI systems are more competent than humans at dispensing advice when functional and practical qualities (utilitarian) are desired and less competent when the desired qualities are experiential and sensory-based (hedonic). Consequently, the importance or salience of utilitarian attributes determine preference for AI recommenders over human ones, while the importance or salience of hedonic attributes determine resistance to AI recommenders over human ones.

The researchers tested the word-of-machine effect using experiments designed to assess people’s tendency to choose products based on consumption experiences and recommendation source. Longoni explains that “We found that when presented with instructions to choose products based solely on utilitarian/functional attributes, more participants chose AI-recommended products. When asked to only consider hedonic/experiential attributes, a higher percentage of participants chose human recommenders.”

When utilitarian features are most important, the word-of-machine effect was more distinct. In one study, participants were asked to imagine buying a winter coat and rate how important utilitarian/functional attributes (e.g., breathability) and hedonic/experiential attributes (e.g., fabric type) were in their decision making. The more utilitarian/functional features were highly rated, the greater the preference for AI over human assistance, and the more hedonic/experiential features were highly rated, the greater the preference for human over AI assistance.

Another study indicated that when consumers wanted recommendations matched to their unique preferences, they resisted AI recommenders and preferred human recommenders regardless of hedonic or utilitarian preferences. These results suggest that companies whose customers are known to be satisfied with “one size fits all” recommendations (i.e., not in need of a high level of customization) may rely on AI-systems. However, companies whose customers are known to desire personalized recommendations should rely on humans.

Although there is a clear correlation between utilitarian attributes and consumer trust in AI recommenders, companies selling products that promise more sensorial experiences (e.g., fragrances, food, wine) may still use AI to engage customers. In fact, people embrace AI’s recommendations as long as AI works in partnership with humans. When AI plays an assistive role, “augmenting” human intelligence rather than replacing it, the AI-human hybrid recommender performs as well as a human-only assistant.

Overall, the word-of-machine effect has important implications as the development and adoption of AI, machine learning, and natural language processing challenges managers and policy-makers to harness these transformative technologies. As Cian says, “The digital marketplace is crowded and consumer attention span is short. Understanding the conditions under which consumers trust, and do not trust, AI advice will give companies a competitive advantage in this space.”

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Research creates hydrogen-producing living droplets, paving way for alternative future energy source

Scientists have built tiny droplet-based microbial factories that produce hydrogen, instead of oxygen, when exposed to daylight in air.

The findings of the international research team based at the University of Bristol and Harbin Institute of Technology in China, are published today in Nature Communications.

Normally, algal cells fix carbon dioxide and produce oxygen by photosynthesis. The study used sugary droplets packed with living algal cells to generate hydrogen, rather than oxygen, by photosynthesis.

Hydrogen is potentially a climate-neutral fuel, offering many possible uses as a future energy source. A major drawback is that making hydrogen involves using a lot of energy, so green alternatives are being sought and this discovery could provide an important step forward.

The team, comprising Professor Stephen Mann and Dr Mei Li from Bristol’s School of Chemistry together with Professor Xin Huang and colleagues at Harbin Institute of Technology in China, trapped ten thousand or so algal cells in each droplet, which were then crammed together by osmotic compression. By burying the cells deep inside the droplets, oxygen levels fell to a level that switched on special enzymes called hydrogenases that hijacked the normal photosynthetic pathway to produce hydrogen. In this way, around a quarter of a million microbial factories, typically only one-tenth of a millimetre in size, could be prepared in one millilitre of water.

To increase the level of hydrogen evolution, the team coated the living micro-reactors with a thin shell of bacteria, which were able to scavenge for oxygen and therefore increase the number of algal cells geared up for hydrogenase activity.

Although still at an early stage, the work provides a step towards photobiological green energy development under natural aerobic conditions.

Professor Stephen Mann, Co-Director of the Max Planck Bristol Centre for Minimal Biology at Bristol, said: “Using simple droplets as vectors for controlling algal cell organization and photosynthesis in synthetic micro-spaces offers a potentially environmentally benign approach to hydrogen production that we hope to develop in future work.”

Professor Xin Huang at Harbin Institute of Technology added: “Our methodology is facile and should be capable of scale-up without impairing the viability of the living cells. It also seems flexible; for example, we recently captured large numbers of yeast cells in the droplets and used the microbial reactors for ethanol production.”

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Cutting edge technology to bioprint mini-kidneys

Researchers have used cutting edge technology to bioprint miniature human kidneys in the lab, paving the way for new treatments for kidney failure and possibly lab-grown transplants.

The study, led by the Murdoch Children’s Research Institute (MCRI) and biotech company Organovo and published in Nature Materials, saw the research team also validate the use of 3D bioprinted human mini kidneys for screening of drug toxicity from a class of drugs known to cause kidney damage in people.

The research showed how 3D bioprinting of stem cells can produce large enough sheets of kidney tissue needed for transplants.

Like squeezing toothpaste out of a tube, extrusion-based 3D bioprinting uses a ‘bioink’ made from a stem cell paste, squeezed out through a computer-guided pipette to create artificial living tissue in a dish.

MCRI researchers teamed up with San Diego based Organovo Inc to create the mini organs.

MCRI Professor Melissa Little, a world leader in modelling the human kidney, first began growing kidney organoids in 2015. But this new bio-printing method is faster, more reliable and allows the whole process to be scaled up. 3D bioprinting could now create about 200 mini kidneys in 10 minutes without compromising quality, the study found.

From larger than a grain of rice to the size of a fingernail, bioprinted mini-kidneys fully resemble a regular-sized kidney, including the tiny tubes and blood vessels that form the organ’s filtering structures called nephrons.

Professor Little said by using mini-organs her team hope to screen drugs to find new treatments for kidney disease or to test if a new drug was likely to injure the kidney.

“Drug-induced injury to the kidney is a major side effect and difficult to predict using animal studies. Bioprinting human kidneys are a practical approach to testing for toxicity before use,” she said.

In this study, the toxicity of aminoglycosides, a class of antibiotics that commonly damage the kidney, were tested.

“We found increased death of particular types of cells in the kidneys treated with aminoglycosides,” Professor Little said.

“By generating stem cells from a patient with a genetic kidney disease, and then growing mini kidneys from them, also paves the way for tailoring treatment plans specific to each patient, which could be extended to a range of kidney diseases.”

Professor Little said the study showed growing human tissue from stem cells also brought the promise of bioengineered kidney tissue.

“3D bioprinting can generate larger amounts of kidney tissue but with precise manipulation of biophysical properties, including cell number and conformation, improving the outcome,” she said.

Currently, 1.5 million Australians are unaware they are living with early signs of kidney disease such as decreased urine output, fluid retention and shortness of breath.

Professor Little said prior to this study the possibility of using mini kidneys to generate transplantable tissue was too far away to contemplate.

“The pathway to renal replacement therapy using stem cell-derived kidney tissue will need a massive increase in the number of nephron structures present in the tissue to be transplanted,” she said.

“By using extrusion bioprinting, we improved the final nephron count, which will ultimately determine whether we can transplant these tissues into people.”

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Pesticide deadly to bees now easily detected in honey

A common insecticide that is a major hazard for honeybees is now effectively detected in honey thanks to a simple new method.

Researchers at the University of Waterloo developed an environmentally friendly, fully automated technique that extracts pyrethroids from the honey. Pyrethroids are one of two main groups of pesticides that contribute to colony collapse disorder in bees, a phenomenon where worker honeybees disappear, leaving the queen and other members of the hive to die. Agricultural producers worldwide rely on honeybees to pollinate hundreds of billions of dollars worth of crops.

Extracting the pyrethroids with the solid phase microextraction (SPME) method makes it easier to measure whether their levels in the honey are above those considered safe for human consumption. It can also help identify locations where farmers use the pesticide and in what amounts. The substance has traditionally been difficult to extract because of its chemical properties.

“Pyrethroids are poorly soluble in water and are actually suspended in honey,” said Janusz Pawliszyn, a professor of chemistry at Waterloo. “We add a small amount of alcohol to dissolve them prior to extraction by the automated SPME system.”

Farmers spray the pesticides on crops. They are neurotoxins, which affect the way the brain and nerves work, causing paralysis and death in insects.

“It is our hope that this very simple method will help authorities determine where these pesticides are in use at unsafe levels to ultimately help protect the honeybee population,” said Pawliszyn.

The Canadian Food Inspection Agency tests for chemical residues in food in Canada. Maximum residue limits are regulated under the Pest Control Products Act. The research team found that of the honey products they tested that contained the pesticide, all were at allowable levels.

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Machine learning: A breakthrough in the study of stellar nurseries

The gas clouds in which stars are born and evolve are vast regions of the Universe that are extremely rich in matter, and hence in physical processes. All these processes are intertwined on different size and time scales, making it almost impossible to fully understand such stellar nurseries. However, the scientists in the ORION-B* programme have now shown that statistics and artificial intelligence can help to break down the barriers still standing in the way of astrophysicists.

With the aim of providing the most detailed analysis yet of the Orion molecular cloud, one of the star-forming regions nearest the Earth, the ORION-B team included in its ranks scientists specialising in massive data processing. This enabled them to develop novel methods based on statistical learning and machine learning to study observations of the cloud made at 240,000 frequencies of light**.

Based on artificial intelligence algorithms, these tools make it possible to retrieve new information from a large mass of data such as that used in the ORION-B project. This enabled the scientists to uncover a certain number of ‘laws’ governing the Orion molecular cloud.

For instance, they were able to discover the relationships between the light emitted by certain molecules and information that was previously inaccessible, namely, the quantity of hydrogen and of free electrons in the cloud, which they were able to estimate from their calculations without observing them directly. By analysing all the data available to them, the research team was also able to determine ways of further improving their observations by eliminating a certain amount of unwanted information.

The ORION-B teams now wish to put this theoretical work to the test, by applying the estimates and recommendations obtained and verifying them under real conditions. Another major theoretical challenge will be to extract information about the speed of molecules, and hence visualise the motion of matter in order to see how it moves within the cloud.


*- Standing for Outstanding Radio-Imaging of OrioN B. The scientists involved are from the Laboratoire d’Etudes du Rayonnement et de la Matière en Astrophysique et Atmosphères (Observatoire de Paris — PSL/CNRS/Sorbonne Université/Université de Cergy-Pontoise), Institut de Radioastronomie Millimétrique (IRAM), Centre de Recherche en Informatique, Signal et Automatique de Lille (CNRS/Université de Lille/Centrale Lille), Institut de Recherche en Astrophysique et Planétologie (CNRS/Université Toulouse III Paul Sabatier), Institut de Recherche en Informatique de Toulouse (CNRS/Toulouse INP/Université Toulouse III Paul Sabatier), Institut Fresnel (CNRS/Aix-Marseille Université/Centrale Marseille), Laboratoire d’Astrophysique de Bordeaux (CNRS/Université de Bordeaux), du Laboratoire de Physique de l’Ecole Normale Supérieure (CNRS/ENS Paris/Sorbonne Université/Université de Paris), Laboratoire Grenoble Images Parole Signal Automatique (CNRS/Université Grenoble Alpes), Instituto de Física Fundamental (CSIC) (Spain), National Radio Astronomy Observatory (United States), Chalmers University of Technology (Sweden), Cardiff University (United Kingdom), Harvard University (United States), Pontificia Universidad Católica de Chile (Chile).

**- The observations were made using one of IRAM’s radio telescopes, the 30-metre antenna located in Spain’s Sierra Nevada.

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