Friday, September 03, 2021

Astronomers create the first 3D-printed stellar nurseries

Researchers can now hold stellar nurseries in their hands thanks to 3D printing, revealing features often obscured in traditional renderings and animations

Peer-Reviewed Publication

UNIVERSITY OF CALIFORNIA - SANTA CRUZ

Stellar nursery models 

IMAGE: THE FIRST 3D-PRINTED STELLAR NURSERIES ARE HIGHLY POLISHED SPHERES ABOUT THE SIZE OF A BASEBALL, IN WHICH SWIRLING CLUMPS AND FILAMENTS REPRESENT STAR-FORMING CLOUDS OF GAS AND DUST. RESEARCHERS CREATED THE MODELS USING DATA FROM SIMULATIONS OF STAR-FORMING CLOUDS AND A SOPHISTICATED 3D PRINTING PROCESS IN WHICH THE FINE-SCALE DENSITIES AND GRADIENTS OF THE TURBULENT CLOUDS ARE EMBEDDED IN A TRANSPARENT RESIN. view more 

CREDIT: PHOTO BY SAURABH MHATRE

Astronomers can’t touch the stars they study, but astrophysicist Nia Imara is using 3-dimensional models that fit in the palm of her hand to unravel the structural complexities of stellar nurseries, the vast clouds of gas and dust where star formation occurs.

Imara and her collaborators created the models using data from simulations of star-forming clouds and a sophisticated 3D printing process in which the fine-scale densities and gradients of the turbulent clouds are embedded in a transparent resin. The resulting models—the first 3D-printed stellar nurseries—are highly polished spheres about the size of a baseball (8 centimeters in diameter), in which the star-forming material appears as swirling clumps and filaments.

“We wanted an interactive object to help us visualize those structures where stars form so we can better understand the physical processes,” said Imara, an assistant professor of astronomy and astrophysics at UC Santa Cruz and first author of a paper describing this novel approach published August 25 in Astrophysical Journal Letters.

An artist as well as an astrophysicist, Imara said the idea is an example of science imitating art. “Years ago, I sketched a portrait of myself touching a star. Later, the idea just clicked. Star formation within molecular clouds is my area of expertise, so why not try to build one?” she said.

She worked with coauthor John Forbes at the Flatiron Institute’s Center for Computational Astrophysics to develop a suite of nine simulations representing different physical conditions within molecular clouds. The collaboration also included coauthor James Weaver at Harvard University’s School of Engineering and Applied Sciences, who helped to turn the data from the astronomical simulations into physical objects using high-resolution and photo-realistic multi-material 3D printing.

The results are both visually striking and scientifically illuminating. “Just aesthetically they are really amazing to look at, and then you begin to notice the complex structures that are incredibly difficult to see with the usual techniques for visualizing these simulations,” Forbes said.

For example, sheet-like or pancake-shaped structures are hard to distinguish in two-dimensional slices or projections, because a section through a sheet looks like a filament.

“Within the spheres, you can clearly see a two-dimensional sheet, and inside it are little filaments, and that’s mind boggling from the perspective of someone who is trying to understand what’s going on in these simulations,” Forbes said.


CAPTION

In addition to spheres representing nine different simulations, the researchers also printed half-spheres to reveal the mid-plane data. Lighter material corresponds to regions of higher density, while darker areas represent regions of low density and voids.

CREDIT

Photo by Saurabh Mhatre

The models also reveal structures that are more continuous than they would appear in 2D projections, Imara said. “If you have something winding around through space, you might not realize that two regions are connected by the same structure, so having an interactive object you can rotate in your hand allows us to detect these continuities more easily,” she said.

The nine simulations on which the models are based were designed to investigate the effects of three fundamental physical processes that govern the evolution of molecular clouds: turbulence, gravity, and magnetic fields. By changing different variables, such as the strength of the magnetic fields or how fast the gas is moving, the simulations show how different physical environments affect the morphology of substructures related to star formation.

Stars tend to form in clumps and cores located at the intersection of filaments, where the density of gas and dust becomes high enough for gravity to take over. “We think that the spins of these newborn stars will depend on the structures in which they form—stars in the same filament will ‘know’ about each other’s spins,” Imara said.


CAPTION

Nia Imara is both an astrophysicist and an artist. A portrait of herself touching a star eventually led to the idea of creating physical models of stellar nurseries.

CREDIT

Image courtesy of Nia Imara


With the physical models, it doesn’t take an astrophysicist with expertise in these processes to see the differences between the simulations. “When I looked at 2D projections of the simulation data, it was often challenging to see their subtle differences, whereas with the 3D-printed models, it was obvious,” said Weaver, who has a background in biology and materials science and routinely uses 3D printing to investigate the structural details of a wide range of biological and synthetic materials.

“I’m very interested in exploring the interface between science, art, and education, and I’m passionate about using 3D printing as a tool for the presentation of complex structures and processes in an easily understandable fashion,” Weaver said. “Traditional extrusion-based 3D printing can only produce solid objects with a continuous outer surface, and that’s problematic when trying to depict, gases, clouds, or other diffuse forms. Our approach uses an inkjet-like 3D printing process to deposit tiny individual droplets of opaque resin at precise locations within a surrounding volume of transparent resin to define the cloud's form in exquisite detail.”

He noted that in the future the models could also incorporate additional information through the use of different colors to increase their scientific value. The researchers are also interested in exploring the use of 3D printing to represent observational data from nearby molecular clouds, such as those in the constellation Orion.

The models can also serve as valuable tools for education and public outreach, said Imara, who plans to use them in an astrophysics course she will be teaching this fall.

 

 

TRACS set the stage in flatworm regeneration

Transient regeneration-activated cell states can exist in tissues near to and distant from a wound site during planarian whole-body regeneration

Peer-Reviewed Publication

STOWERS INSTITUTE FOR MEDICAL RESEARCH

Reconstruction 

IMAGE: AN “ATLAS” REPRESENTATION CAPTURES THE CELLULAR COMPLEXITY OF FLATWORM REGENERATION. INDIVIDUAL FLATWORM CELLS ARE REPRESENTED BY DOTS, WITH COLORS CORRESPONDING TO COLLECTION TIME POINTS AND DISTANCES REPRESENTING SIMILARITY IN GENE EXPRESSION PROFILES. view more 

CREDIT: SÁNCHEZ ALVARADO LAB

KANSAS CITY, MO—People who fish and regularly use earthworms as bait may be familiar with the animal’s ability to regenerate a head or tail when cut in two. Yet while impressive, an earthworm’s regenerative capacity is child’s play compared with that of the planarian Schmidtea mediterranea. This species, a type of flatworm, can regrow an entire animal from tiny tissue fragments as minuscule as 1/279th of the animal.

How does this happen? What cell types contribute to this astounding regenerative capacity? Besides stem cells, which are obviously important, how many other cell types are important for regulating this process, and what do they do?

Recent research published September 2, 2021, in Nature Cell Biology by members of the Sánchez Alvarado Lab at the Stowers Institute for Medical Research provides some early answers to these complex questions.

“It was already known that the wound-induced epidermis and the wound-induced muscle played different roles in regeneration, but we wanted to understand the big picture,” explains lead author Blair Benham-Pyle, PhD, a postdoctoral scientist in the lab of Stowers Institute Executive Director and Chief Scientific Officer and Howard Hughes Medical Institute Investigator Alejandro Sánchez Alvarado, PhD.

“This is the first study that definitively found that all three germ layers (muscle, epidermis, and intestine) of Schmidtea mediterranea transcriptionally respond to amputation, and that both tissues near the wound site and far away from the wound site are contributing to regenerative capacity,” says Benham-Pyle.

“Regeneration was a little bit of a black box before—we knew some genes that were important, and we could look at how some genes were altered globally in response to amputation and during regeneration, but we didn’t know how individual cell types across the animal were changing their behavior or function. That’s what this experiment allowed us to characterize.”

“The dream experiment,” described Benham-Pyle, and what they ultimately accomplished, was to “characterize gene expression on the single-cell level, across all of the different cell types of a regenerating animal, over time.”

At first, the researchers considered doing the experiment using large-scale RNA sequencing because droplet-based single-cell sequencing—where every single cell is encapsulated in a lipid droplet with a barcode, and then lysed to label all mRNAs with that barcode— was not feasible at the scale needed for this experiment. But in early 2017, Sánchez Alvarado came across a preprint that had just been posted to bioRxiv reporting a new single-cell sequencing method named SplitSeq. Once Benham-Pyle had reviewed and discussed with Sánchez Alvarado the merits of the work in the preprint, they decided to give it a go. After several tries, a number of optimizations, and troubleshooting with the molecular biology and cytometry technology center teams, Benham-Pyle succeeded in bringing a new single-cell sequencing technology to the Stowers Institute.

After getting it to work, Benham-Pyle and colleagues captured almost 300,000 single cell transcriptomes across eight different tissues and the stem cell compartment in animals that had lost the ability to regenerate, compared with those that were capable of regenerating.

“This allowed us to look at all of the different cell types across the entire animal to see which responded to amputation and what genes were marking these cells as they changed and responded to regeneration,” explains Benham-Pyle.

The researchers found and characterized five different cell types, from all three germ layers, that transiently altered their transcriptional output after amputation. When genes enriched in these cell types were knocked down, says Benham-Pyle, “we found that all of them contribute to regeneration in different ways, being activated at different times and in different parts of the body.”

Some of their findings were more unexpected than others. For example, that muscle is important for patterning, and that the epidermis is important for early stem cell proliferation bursts during regeneration, was not as unexpected. The researchers were surprised, however, to discover rare cells, states induced during whole-body regeneration, called transient regeneration-activating cell states (TRACS), and to find that the intestine seems to be important for both stem cell maintenance and regulating tissue remodeling after amputation.

“I didn’t expect the intestine to globally change its output and remodel its function after injury,” says Benham-Pyle. “But if you think about it, it does make sense. The planarian normally grows its body plan based on its nutrient environment. The worm eats, and that fuels a burst of stem cell proliferation and the addition of new biomass. When you cut the animal, especially in extreme injury, it often loses its ability to eat. All of the growth and remodeling now needs to be fueled by nutrients already existing within the body plan. So, after amputation, the intestine alters its function to scavenge material from dying cells within the animal, and to convert those materials into new healthy cells in a regenerated worm.”

Acquiring and making sense of the data was a team effort.

“We had to do all of our manuscript revisions during the COVID-19 pandemic, when we were at 50% research capacity,” recounts Benham-Pyle. “Sean McKinney and the Microscopy Center found ways to automate imaging, and we worked out a system where I could give them forty to eighty slides at a time, of all different samples and RNAi conditions, to be imaged on overnight runs. They were able to generate terabytes of imaging data for us on the scanning confocal microscope, which helped give us the big lift we needed to get the paper accepted. They set a very high bar for microscopy facilities.”

Other coauthors of the study include: Carolyn E. Brewster, a bioinformatics specialist who helped analyze the data generated from the experiment, and was instrumental in creating the website associated with the paper; Aubrey M. Kent, who helped describe some of the first RNAi phenotypes that came out of the dataset (she is now following up on some of the epidermal genes that were found to affect the stem cell compartment); Frederick G. Mann, PhD, who helped clone many of the genes that Benham-Pyle screened and characterized in the paper; Shiyuan Chen; Allison R. Scott; and Andrew C. Box; and Alejandro Sánchez Alvarado, PhD.

Taking a step back, “what this paper does is take a global look at what sorts of cells need to be in a signaling environment to stimulate stem cells to create new tissue and replace missing tissue,” Benham-Pyle reflects.

“It turns out that a number of genes that we characterized, for instance in the intestine, have also been implicated in immune evasion in the context of cancer, or in wound healing. A lot of the same mechanisms that stem cells use to avoid the immune system and to fuel proliferation and growth during regeneration may be the same mechanisms that are co-opted by tumors. By understanding what non-stem cell states and tissue types are helping to create that signaling environment, we might eventually find new targets for either stimulating healthy and normal wound healing in contexts where regenerative capacity is limited, or, limiting growth capacities of things that we don’t want to grow, like tumors.”

“Now that we have a map, we can go and figure out how the cells are talking to each other, what they’re doing, and how they’re doing it.”

The work was supported in part by the Stowers Institute for Medical Research, the Howard Hughes Medical Institute, the National Institute of General Medical Sciences of the National Institutes of Health (award R37GM057260 to A.S.A), the Jane Coffin Childs Memorial Fund Postdoctoral Fellowship (B.W.B.P), and a Howard Hughes Medical Institute Postdoctoral Fellowship (F.G.M). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Lay Summary of Findings

The free-living planarian Schmidtea mediterranea (a type of flatworm) is capable of regenerating an entire body from a tiny portion of tissue. How it accomplishes this has largely been a mystery. In a report published September 2, 2021, in Nature Cell Biology, members from the lab of Alejandro Sánchez Alvarado, PhD, of the Stowers Institute for Medical Research, describe an atlas of cell identity and cellular behavior over time in worms that are healthy, beginning the process of regeneration, and completing regeneration.

The study, led by Blair Benham-Pyle, PhD, is the first to definitively show that whole-body regeneration involves transcriptional changes in cells from all three germ layers (muscle, epidermis, and intestine) of the body, and that tissue from areas distant from, as well as nearby to the site of injury, contribute to the process of regeneration.

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About the Stowers Institute for Medical Research 

Founded in 1994 through the generosity of Jim Stowers, founder of American Century Investments, and his wife, Virginia, the Stowers Institute for Medical Research is a non-profit, biomedical research organization with a focus on foundational research. Its mission is to expand our understanding of the secrets of life and improve life’s quality through innovative approaches to the causes, treatment, and prevention of diseases.

The Institute consists of sixteen independent research programs. Of the approximately 500 members, over 370 are scientific staff that includes principal investigators, technology center directors, postdoctoral scientists, graduate students, and technical support staff. Learn more about the Institute at www.stowers.org and about its graduate program at www.stowers.org/gradschool.

 

Many of the fastest-evolving human genes linked to evolutionary changes in brain development


Peer-Reviewed Publication

CELL PRESS

Astrocytes and cell nuclei in ferret cerebellum 

IMAGE: THIS IMAGE SHOWS A THIN SECTION TAKEN FROM THE CEREBELLUM OF AN ADULT FERRET BRAIN, WITH ASTROCYTES LABELED IN YELLOW, AND CELL NUCLEI LABELED IN BLUE. ASTROCYTES ARE A VISUALLY STRIKING TYPE OF NON-NEURAL CELL IN THE BRAIN THAT WERE FOUND TO CONTINUE TO EXPRESS PPP1R17 ONLY IN ADULT NON-HUMAN PRIMATES IN THIS STUDY, BUT NOT IN THE CEREBRAL CORTEX OR THE CEREBELLUM OF NON-PRIMATE SPECIES SUCH AS THE FERRET, SHOWN HERE. view more 

CREDIT: ELLEN DEGENNARO

More than 3,000 regions in the human genome are very different in people from in any other mammals, including our closest primate relatives. Now, a study reported in the journal Neuron on September 2 has evidence to confirm that nearly half of these so-called human accelerated regions (HARs) have played an important role in rewriting the course of human brain development, offering important insight into the genetic basis of human evolution.

“Probably one of the most interesting questions in neuroscience is, ‘What makes us human?’” says Christopher Walsh (@chrisawalsh1) of Harvard University and the Allen Discovery Center for Human Brain Evolution. “Specifically, what is it about the human brain that differentiates it from those of other closely related species? Looking at human accelerated regions provided us with a very targeted way to investigate that question from a genetic perspective.”

To systematically identify which of the 3,171 previously identified HARs are most likely to be contributing to recent evolution of the human cerebral cortex, the researchers examined the role of these regions in regulating genes in studies of multiple human and mouse cell types and tissues.

“We knew going into this study that many HARs were likely to function as regulators of gene expression in the brain, but we knew very little about which cell types in the brain they worked in, where, or at what time in the human lifespan,” explains Ellen DeGennaro (@ViolinPlots), one of the study’s first authors in the Walsh lab. “Our goal was to fill in these gaps of knowledge about which HARs had important roles in the brain, and how, so that we and other researchers could take the most important ‘brain HARs’ and perform deeper tests of their evolutionary function.”

To overcome the limitations of earlier methods, Walsh and his colleagues developed an applied approach called CaptureMPRA. The new method leverages barcoded molecular inversion probes to capture target sequences that capture entire HAR elements and their surrounding DNA, overcoming some limitations of prior techniques. Using this approach, they looked for important differences in HAR enhancer function between humans and chimpanzees.

They also integrated this data with epigenetic data at HARs in human fetal neural cells to identify HARs that looked likely to have an important role in guiding human-specific brain development. Some of the activity they uncovered was specific to the brain, as compared to other organs in the body. They also found activity that was even more specific to certain cell types in the fetal brain, as opposed to brains of adults.


CAPTION

This image shows a thin section of ferret cerebellum, with astrocytes (yellow) and cells expressing PPP1R17 (blue).

CREDIT

Ellen DeGennaro

Overall, the new findings show that many HARs do indeed appear to act as neurodevelopmental enhancers, the researchers report. The new data suggests that, as those human sequences diverged from other mammals, they have largely increased their role as neuronal enhancers.

The researchers also show that one HAR-regulated gene in particular, called PPP1R17, has undergone rapid change in both cell-type and developmental expression patterns between non-primates and primates and between non-human primates and humans. They went on to show that PPP1R17 slows the progression of neural progenitor cells through the cell cycle. This is notable given that lengthening of the cell cycle in non-human primates and humans is known to force a slowing of neurological development, an important feature of the human brain.

The new findings define many HARs that play key roles in neuronal gene regulatory programs; nearly half of all HARs show reproducible chromatin accessibility and enhancer activity in neural cells and tissue, according to the researchers. They’ve also developed an easily searchable online resource (the HARHub) consisting of the new data and previously published datasets of common and rare human HAR sequence variation. This databank now serves as a resource for scientists to make even more discoveries. Already, it has offered intriguing insights.

“Our work provides an important advance in studying many genomic regions at once to help us piece together the very complicated but compelling picture of human brain evolution,” Walsh says. “Our data suggest that evolution of the human brain involved changes in dozens or perhaps even hundreds of sites in the genome, rather than just a single key gene.”


CAPTION

This image shows a thin section of mouse cerebellum, with PP1R17-expressing cells labeled in green.

CREDIT

Ellen DeGennaro


This work was supported by the National Institutes of Health; the Allen Discovery Center program, a Paul G. Allen Frontiers Group advised program of the Paul G. Allen Family Foundation; a Career Award for Medical Scientists from the Burroughs Wellcome Fund; the Surpina and Panos Eurnekian BioFund fellowship; the Simons Foundation Autism Research Initiative Bridge to Independence award; and the Simons Center for the Social Brain postdoctoral fellowship. C.A.W. is an Investigator of the Howard Hughes Medical Institute.

Neuron, Girskis et al.: “Rewiring of human neurodevelopmental gene regulatory programs by Human Accelerated Regions (HARs)” https://www.cell.com/neuron/fulltext/S0896-6273(21)00580-8

Neuron (@NeuroCellPress), published by Cell Press, is a bimonthly journal that has established itself as one of the most influential and relied upon journals in the field of neuroscience and one of the premier intellectual forums of the neuroscience community. It publishes interdisciplinary articles that integrate biophysical, cellular, developmental, and molecular approaches with a systems approach to sensory, motor, and higher-order cognitive functions. Visit: http://www.cell.com/neuron. To receive Cell Press media alerts, contact press@cell.com.

 

Scientists create a labor-saving automated method for studying electronic health records

Mount Sinai study suggests new method is as effective as manually-based “gold-standard” at classifying a diagnosis

Peer-Reviewed Publication

THE MOUNT SINAI HOSPITAL / MOUNT SINAI SCHOOL OF MEDICINE

Reading Dementia 

IMAGE: MOUNT SINAI SCIENTISTS CREATED AN AI-BASED, AUTOMATED SYSTEM THAT LEARNS TO READ PATIENT DATA FROM ELECTRONIC HEALTH RECORDS. HERE THE SYSTEM IDENTIFIED DEMENTIA CASES (PURPLE DOTS) FROM A DATABASE OF NEARLY 2 MILLION PATIENTS (BLUE DOTS). view more 

CREDIT: COURTESY OF THE GLICKSBERG LAB, MOUNT SINAI, N.Y., N.Y.

In an article published in the journal Patterns, scientists at the Icahn School of Medicine at Mount Sinai described the creation of a new, automated, artificial intelligence-based algorithm that can learn to read patient data from electronic health records. In a side-by-side comparison, they showed that their method, called Phe2vec (FEE-to-vek), accurately identified patients with certain diseases as well as the traditional, “gold-standard” method, which requires much more manual labor to develop and perform.

“There continues to be an explosion in the amount and types of data electronically stored in a patient’s medical record. Disentangling this complex web of data can be highly burdensome, thus slowing advancements in clinical research,” said Benjamin S. Glicksberg, PhD, Assistant Professor of Genetics and Genomic Sciences, a member of the Hasso Plattner Institute for Digital Health at Mount Sinai (HPIMS), and a senior author of the study. “In this study, we created a new method for mining data from electronic health records with machine learning that is faster and less labor intensive than the industry standard. We hope that this will be a valuable tool that will facilitate further, and less biased, research in clinical informatics.”

The study was led by Jessica K. De Freitas, a graduate student in Dr. Glicksberg lab.

Currently, scientists rely on a set of established computer programs, or algorithms, to mine medical records for new information. The development and storage of these algorithms is managed by a system called the Phenotype Knowledgebase (PheKB). Although the system is highly effective at correctly identifying a patient diagnosis, the process of developing an algorithm can be very time-consuming and inflexible. To study a disease, researchers first have to comb through reams of medical records looking for pieces of data, such as certain lab tests or prescriptions, which are uniquely associated with the disease. They then program the algorithm that guides the computer to search for patients who have those disease-specific pieces of data, which constitute a “phenotype”. In turn, the list of patients identified by the computer needs to be manually double-checked by researchers. Each time researchers want to study a new disease, they have to restart the process from scratch.

In this study, the researchers tried a different approach—one in which the computer learns, on its own, how to spot disease phenotypes and thus save researchers time and effort. This new, Phe2vec method was based on studies the team had already conducted.

“Previously, we showed that unsupervised machine learning could be a highly efficient and effective strategy for mining electronic health records,” said Riccardo Miotto, PhD, a former Assistant Professor at the HPIMS and a senior author of the study. “The potential advantage of our approach is that it learns representations of diseases from the data itself. Therefore, the machine does much of the work experts would normally do to define the combination of data elements from health records that best describes a particular disease.”

Essentially, a computer was programmed to scour through millions of electronic health records and learn how to find connections between data and diseases. This programming relied on “embedding” algorithms that had been previously developed by other researchers, such as linguists, to study word networks in various languages. One of the algorithms, called word2vec, was particularly effective. Then, the computer was programmed to use what it learned to identify the diagnoses of nearly 2 million patients whose data was stored in the Mount Sinai Health System.

Finally, the researchers compared the effectiveness between the new and the old systems. For nine out of ten diseases tested, they found that the new Phe2vec system was as effective as, or performed slightly better than, the gold standard phenotyping process at correctly identifying a diagnoses from electronic health records. A few examples of the diseases included dementia, multiple sclerosis, and sickle cell anemia.

“Overall our results are encouraging and suggest that Phe2vec is a promising technique for large-scale phenotyping of diseases in electronic health record data,” Dr. Glicksberg said. “With further testing and refinement, we hope that it could be used to automate many of the initial steps of clinical informatics research, thus allowing scientists to focus their efforts on downstream analyses like predictive modeling.”

This study was supported by the Hasso Plattner Foundation, the Alzheimer’s Drug

Discovery Foundation, and a courtesy graphics processing unit donation from the NVIDIA Corporation.

Article

De Freitas, J.K., et al., Phe2vec: Automated Disease Phenotyping based on Unsupervised Embeddings from Electronic Health Records, Patterns, September 2, 2021, DOI: 10.1016/j.patter.2021.100337.

About the Mount Sinai Health System

The Mount Sinai Health System is New York City's largest academic medical system, encompassing eight hospitals, a leading medical school, and a vast network of ambulatory practices throughout the greater New York region. Mount Sinai advances medicine and health through unrivaled education and translational research and discovery to deliver care that is the safest, highest-quality, most accessible and equitable, and the best value of any health system in the nation. The Health System includes approximately 7,300 primary and specialty care physicians; 13 joint-venture ambulatory surgery centers; more than 415 ambulatory practices throughout the five boroughs of New York City, Westchester, Long Island, and Florida; and more than 30 affiliated community health centers. The Mount Sinai Hospital is ranked on U.S. News & World Report's "Honor Roll" of the top 20 U.S. hospitals and is top in the nation by specialty: No. 1 in Geriatrics and top 20 in Cardiology/Heart Surgery, Diabetes/Endocrinology, Gastroenterology/GI Surgery, Neurology/Neurosurgery, Orthopedics, Pulmonology/Lung Surgery, Rehabilitation, and Urology. New York Eye and Ear Infirmary of Mount Sinai is ranked No. 12 in Ophthalmology. Mount Sinai Kravis Children's Hospital is ranked in U.S. News & World Report’s “Best Children’s Hospitals” among the country’s best in four out of 10 pediatric specialties. The Icahn School of Medicine is one of three medical schools that have earned distinction by multiple indicators: ranked in the top 20 by U.S. News & World Report's "Best Medical Schools," aligned with a U.S. News & World Report "Honor Roll" Hospital, and No. 14 in the nation for National Institutes of Health funding. Newsweek’s “The World’s Best Smart Hospitals” ranks The Mount Sinai Hospital as No. 1 in New York and in the top five globally, and Mount Sinai Morningside in the top 20 globally.

For more information, visit https://www.mountsinai.org or find Mount Sinai on FacebookTwitter and YouTube.

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Nano ‘camera’ made using molecular glue allows real-time monitoring of chemical reactions

Peer-Reviewed Publication

UNIVERSITY OF CAMBRIDGE

Nano ‘camera’ made using molecular glue allows real-time monitoring of chemical reactions 

IMAGE: THE DEVICE, MADE BY A TEAM FROM THE UNIVERSITY OF CAMBRIDGE, COMBINES TINY SEMICONDUCTOR NANOCRYSTALS CALLED QUANTUM DOTS AND GOLD NANOPARTICLES USING MOLECULAR GLUE CALLED CUCURBITURIL (CB). WHEN ADDED TO WATER WITH THE MOLECULE TO BE STUDIED, THE COMPONENTS SELF-ASSEMBLE IN SECONDS INTO A STABLE, POWERFUL TOOL THAT ALLOWS THE REAL-TIME MONITORING OF CHEMICAL REACTIONS. view more 

CREDIT: UNIVERSITY OF CAMBRIDGE

Researchers have made a tiny camera, held together with ‘molecular glue’ that allows them to observe chemical reactions in real time.

The device, made by a team from the University of Cambridge, combines tiny semiconductor nanocrystals called quantum dots and gold nanoparticles using molecular glue called cucurbituril (CB). When added to water with the molecule to be studied, the components self-assemble in seconds into a stable, powerful tool that allows the real-time monitoring of chemical reactions.

The camera harvests light within the semiconductors, inducing electron transfer processes like those that occur in photosynthesis, which can be monitored using incorporated gold nanoparticle sensors and spectroscopic techniques. They were able to use the camera to observe chemical species which had been previously theorised but not directly observed.

The platform could be used to study a wide range of molecules for a variety of potential applications, such as the improvement of photocatalysis and photovoltaics for renewable energy. The results are reported in the journal Nature Nanotechnology.

Nature controls the assemblies of complex structures at the molecular scale through self-limiting processes. However, mimicking these processes in the lab is usually time-consuming, expensive and reliant on complex procedures.

“In order to develop new materials with superior properties, we often combine different chemical species together to come up with a hybrid material that has the properties we want,” said Professor Oren Scherman from Cambridge’s Yusuf Hamied Department of Chemistry, who led the research. “But making these hybrid nanostructures is difficult, and you often end up with uncontrolled growth or materials that are unstable.”

The new method that Scherman and his colleagues from Cambridge’s Cavendish Laboratory and University College London developed uses cucurbituril – a molecular glue which interacts strongly with both semiconductor quantum dots and gold nanoparticles. The researchers used small semiconductor nanocrystals to control the assembly of larger nanoparticles through a process they coined interfacial self-limiting aggregation. The process leads to permeable and stable hybrid materials that interact with light. The camera was used to observe photocatalysis and track light-induced electron transfer.

“We were surprised how powerful this new tool is, considering how straightforward it is to assemble,” said first author Dr Kamil Sokołowski, also from the Department of Chemistry.

To make their nano camera, the team added the individual components, along with the molecule they wanted to observe, to water at room temperature. Previously, when gold nanoparticles were mixed with the molecular glue in the absence of quantum dots, the components underwent unlimited aggregation and fell out of solution. However, with the strategy developed by the researchers, quantum dots mediate the assembly of these nanostructures so that the semiconductor-metal hybrids control and limit their own size and shape. In addition, these structures stay stable for weeks.

“This self-limiting property was surprising, it wasn’t anything we expected to see,” said co-author Dr Jade McCune, also from the Department of Chemistry. “We found that the aggregation of one nanoparticulate component could be controlled through the addition of another nanoparticle component.”

When the researchers mixed the components together, the team used spectroscopy to observe chemical reactions in real time. Using the camera, they were able to observe the formation of radical species – a molecule with an unpaired electron – and products of their assembly such as sigma dimeric viologen species, where two radicals form a reversible carbon-carbon bond. The latter species had been theorised but never observed.

“People have spent their whole careers getting pieces of matter to come together in a controlled way,” said Scherman, who is also Director of the Melville Laboratory. “This platform will unlock a wide range of processes, including many materials and chemistries that are important for sustainable technologies. The full potential of semiconductor and plasmonic nanocrystals can now be explored, providing an opportunity to simultaneously induce and observe photochemical reactions.”

“This platform is a really big toolbox considering the number of metal and semiconductor building blocks that can be now coupled together using this chemistry– it opens up lots of new possibilities for imaging chemical reactions and sensing through taking snapshots of monitored chemical systems,” said Sokołowski. “The simplicity of the setup means that researchers no longer need complex, expensive methods to get the same results.”

Researchers from the Scherman lab are currently working to further develop these hybrids towards artificial photosynthetic systems and (photo)catalysis where electron-transfer processes can be observed directly in real time. The team is also looking at mechanisms of carbon-carbon bond formation as well as electrode interfaces for battery applications.

The research was carried out in collaboration with Professor Jeremy Baumberg at Cambridge’s Cavendish Laboratory and Dr Edina Rosta at University College London. It was funded in part by the Engineering and Physical Sciences Research Council (EPSRC).