A crucial component in automobile catalytic converters and in emerging hydrogen fuel cell technology, the demand for this rare silvery white transition metal continues to outstrip supply, driving its price per ounce far above gold and silver.

Palladium and other rare, costly precious metals like platinum, iridium, and ruthenium, are also crucial in chemical transformations, specifically transition metal catalysis, which has become an indispensable tool for putting together complex molecules in the development of pharmaceutical drugs, polymers, and other useful chemicals.

The scarcity and expense of these precious metals has created a need to develop catalysts from transition metals that are more abundant and generally cheaper, like nickel, a cousin of palladium.

As a result, the last decade has seen a dramatic expansion of new catalytic bond-forming transformations involving nickel.

“We know from the literature that nickel complexes are extremely useful in performing some transformations, maybe better than other transition metals out there,” said Liviu Mirica, William H. and Janet G. Lycan Professor of Chemistry at the University of Illinois at Urbana-Champaign. “People have gotten very good at optimizing conditions for specific transformations, so we are slowly getting to where nickel could rival palladium in these transformations.”

More recently, scientists have been focusing on developing nickel catalysts that can be directly photoinitiated by light, which Mirica said has proven to be a very successful area of research producing reactions that have not been previously possible.

However, they still require the use of an additional photocatalyst — typically based on precious metals such as iridium or ruthenium that are even more expensive than palladium.

In a paper recently published in Nature Communications, Mirica and postdoctoral researcher Hanah Na report their work on the development of a completely novel tridentate ligand that coordinates with nickel to create a catalyst that can be directly activated by light to form a carbon-oxygen bond without the use of an additional photocatalyst. C-O bonds are prevalent in many natural products, pharmaceuticals, and agrochemicals.

Mirica and Na believe their new class of tridentate pyridinophane ligands (^RN3) can lead to the development of new nickel catalysts and are a practical platform for detailed mechanical studies of other nickel-catalyzed chemical reactions.

“It is a competent catalyst and on top of it, it can actually do this photocatalysis by itself, it doesn’t require these other photocatalysts,” Mirica said. “It opens up many avenues of research that we think could be used for many additional applications.”

These tridentate pyridinophane ligands (^RN3) build on previous work by Mirica, who had already developed a novel four-pronged molecule known as a tetradentate ligand, whose structure resembles the pocket of a baseball glove. This ligand structure promoted rapid C-C bond forming reactivity while also stabilizing the higher oxidation states of nickel.

“It’s very stable. But all of those intermediates over the past decade have been way too stable. They’re not competent in catalytic applications,” Mirica said.

Then there is the bidentate ligand framework bipyridyl that most chemists are using in nickel photocatalytic processes, which provides enhanced reactivity and the ability to adjust optimization to get the desired reaction.

“It’s great for catalytic chemistry but you can’t isolate or see these special nickel species,” Mirica said.

Typically, Mirica explained, classic organic chemists have a particular chemical transformation in mind and try whatever catalysts they think will be good, and whatever conditions or additives would be useful and optimize it, focusing on a very specific transformation.

“We have a slightly different approach: a metallo-centric approach and in this case nickel is the metal of interest,” he said. “I am interested in being able to design, isolate, characterize nickel complexes with different coordination numbers, different ligand environments, and in different oxidation states, which ultimately will dictate their reactivity.”

This latest ligand structure is somewhere between the other two.

“We open up a coordination site, we open up that nickel center, by removing one of the four nitrogens, to allow other things to bind to it and eventually it allows you to do catalytic activity, but still be able to isolate and characterize intermediates,” he said.

Their novel tridentate ligand enabled them to reveal for the first time the key reaction steps and intermediate species in this catalytic cycle. An in-depth mechanistic understanding of Ni-mediated photocatalysis is essential for rational reaction design and optimization of the nickel-mediated chemical process, the researchers explain in the report.

Their mechanistic study employed techniques including Nuclear Magnetic Resonance (NMR), electron paramagnetic resonance (EPR), in situ infrared (IR) spectroscopy and electrochemical and photophysical measurements, and computational studies.

From a mechanical perspective, the photocatalytic cycle is well-understood, but the Ni-mediated redox cycle has remained a mystery. Paramagnetic Ni(I) and Ni(III) species are assumed to be part of the process, but have not been thoroughly investigated, and the key catalytic steps of oxidative addition, trans-metalation, and reductive elimination at the nickel centers have never been directly observed.

In the past several decades, Na explained, visible light-mediated photoredox catalysis has made vital contributions in the field of synthetic organic chemistry. Traditionally, developing new methodologies and reaction condition optimization are often achieved by trial and error rather than being based on a thorough understanding of the underlying reaction mechanism.

Na said this might be because understanding of the underlying chemistry requires a major contribution from the inorganic and organometallic chemistry fields (beyond the scope of the research interests in synthetic organic chemistry), including the synthesis and characterization of related metal complexes and study of their photochemistry and photophysics.

“As inorganic and organometallic chemists, we want to contribute to this emerging research field, mostly focusing on unraveling clues to understand underlying reaction mechanisms — which is not much done by organic chemists,” Na said. “We believe that our work would provide crucial insight into the reaction design and search for new chemical transformations in the burgeoning field of photoredox catalysis, and thus can impact both the organic and inorganic chemistry community.”

The goal, Mirica explained, is to unleash new reactivity that could ultimately be helpful to organic chemists, who could then employ this system and use it for very particular synthetic targets.

“They may not work now as well as the finely optimized or finely tuned systems that people use on a daily basis in an organic lab, but we hope that our new Ni catalysts will be commonly used several years down the line,” Mirica said.

A new study at the University of Missouri found a “bi-directional” relationship between gastrointestinal issues and internalized symptoms in children and adolescents with autism — meaning the symptoms seem to be impacting each other simultaneously. The findings could influence future precision medicine research aimed at developing personalized treatments to ease pain for individuals with autism experiencing gastrointestinal issues.

“Research has shown gastrointestinal issues are associated with an increased stress response as well as aggression and irritability in some children with autism,” said Brad Ferguson, an assistant research professor in the MU School of Health Professions, Thompson Center for Autism and Neurodevelopmental Disorders and Department of Radiology in the MU School of Medicine. “This likely happens because some kids with autism are unable to verbally communicate their gastrointestinal discomfort as well as how they feel in general, which can be extremely frustrating. The goal of our research is to find out what factors are associated with gastrointestinal problems in individuals with autism so we can design treatments to help these individuals feel better.”

In the study, Ferguson and his team analyzed health data from more than 620 patients with autism at the MU Thompson Center for Autism and Neurodevelopmental Disorders under the age of 18 who experience gastrointestinal issues. Then, the team examined the relationship between the gastrointestinal issues and internalized symptoms, such as stress, anxiety, depression, and social withdrawal. Ferguson explained the findings provide more evidence on the importance of the “gut-brain axis,” or connection between the brain and the digestive tract, in gastrointestinal disorders in individuals with autism.

“Stress signals from the brain can alter the release of neurotransmitters like serotonin and norepinephrine in the gut which control gastrointestinal motility, or the movement of stool through the intestines. Stress also impacts the balance of bacteria living in the gut, called the microbiota, which can alter gastrointestinal functioning,” Ferguson said. “The gut then sends signals back to the brain, and that can, in turn, lead to feelings of anxiety, depression and social withdrawal. The cycle then repeats, so novel treatments addressing signals from both the brain and the gut may provide the most benefit for some kids with gastrointestinal disorders and autism.”

Ferguson said an interdisciplinary team of specialists is needed to help solve this complex problem and develop treatments going forward.

Ferguson collaborates with David Beversdorf, a neurologist at the MU Thompson Center for Autism and Neurodevelopmental Disorders, who also studies gastrointestinal problems in individuals with autism. In a recent study, Beversdorf, who also has appointments in the MU College of Arts and Science and MU School of Medicine, helped identify specific RNA biomarkers linked with gastrointestinal issues in children with autism.

“Interestingly, the study from Beversdorf and colleagues found relationships between microRNA that are related to anxiety behavior following prolonged stress as well as depression and gastrointestinal disturbance, providing some converging evidence with our behavioral findings,” Ferguson said.

Now, Ferguson and Beversdorf are working together to determine the effects of a stress-reducing medication on gastrointestinal issues in a clinical trial.

“I have a great relationship with Beversdorf and the MU Thompson Center Autism Research Core (ARC) that allows our team to quickly go from findings in the laboratory to clinical trials,” Ferguson said.

Ferguson explained that some treatments may work for some individuals with autism but not necessarily for others.

“Our team uses a biomarker-based approach to find what markers in the body are common in those who respond favorably to certain treatments,” Ferguson said. “Our goal is to eventually develop a quick test that tells us which treatment is likely to work for which subgroups of patients based on their unique biomarker signature, including markers of stress, composition of gut bacteria, genetics, co-occurring psychological disorders, or a combination thereof. This way, we can provide the right treatments to the right patients at the right time.”

“Bidirectional relationship between internalizing symptoms and gastrointestinal problems in youth with autism spectrum disorder” was recently published in the Journal of Autism and Developmental Disorders. Ferguson also collaborated with Kristen Dovgan, an assistant professor in the Department of Psychology at Marist College, and Kyra Gynegrowski, an undergraduate student in the Department of Psychology at Marist College. Funding for the study was provided by the Autism Speaks Autism Treatment Network, which is now known as the Autism Care Network.

In a new study published in the journal Nature Microbiology, Efrem Lim and his colleagues explore the galaxy of viruses present in the gut, known as the gut virome. They find that some preterm infants undergo marked alterations in their pattern of gut viruses shortly before developing a serious and often fatal disease known as necrotizing enterocolitis (NEC).

Professor Lim is a researcher in the Biodesign Center for Fundamental and Applied Microbiomics. He is also the principal investigator of the Center for Viral Genomics at ASU and an assistant professor at ASU’s School of Life Sciences.

The study was conducted in collaboration with ASU colleagues and researchers from the Washington University School of Medicine.

Although the bacterial component of the gut microbiome has received considerable research attention, viruses inhabiting the gut remain a largely hidden realm. The viral signature highlighted in the study, along with changes in gut bacterial communities, could provide an early warning signal that an infant is at risk of developing NEC, allowing clinicians to take emergency action.

“For many years now, there’s been some inkling that the microbiome is implicated in this rapidly developing disease,” Lim says. “Studies have shown that changes in the microbiome of the gut in these preterm infants seem to predict the progression to NEC disease.”

Yet teasing out the specific microbial changes leading to the disease has been challenging and the precise mechanism causing the affliction is still unknown. The current study is the first to comprehensively investigate changes in the viral microbiome that appear to set the stage for the development of NEC in preterm infants.

A microbial world is born

Microbes begin colonizing the infant gut during birth, when a baby encounters a variety of microorganisms from its mother’s vaginal tract. As the baby suckles, it picks up additional microbes from its mother’s skin as well as those that have infiltrated her breast milk.

The infant will acquire new microbes from other family and non-family members and even from household pets. These all become incorporated into the developing gut microbiome, composed of some 20-100 billion microbes.

This vast microbial community will go on to shape many aspects of an individual’s health, throughout the person’s life. Unsurprisingly, abnormal alterations in the gut microbiome can spell serious trouble and premature infants are particularly vulnerable to such disruptions.

Before their time

Preterm birth usually refers to infants born after less than 37 weeks of pregnancy. The condition appears to be on the rise, though the causes of this are not fully understood. In many low-income countries, factors including HIV, infections, malaria, and high adolescent pregnancy rates have all been implicated.

In 2020, preterm birth affected 1 of every 10 infants born in the United States. Babies born too early (particularly before 32 weeks), have higher rates of death and disability. Those that survive may experience lasting health issues, including feeding difficulties; breathing, vision and hearing problems; and abnormalities including developmental delays and cerebral palsy.

Babies born prematurely are also at risk of NEC. The disease often strikes suddenly. When babies are born after fewer than 32 weeks of gestation, the incidence of NEC ranged from 2-7% in high-income countries. Mortality among infants with necrotizing enterocolitis ranges from 22-38%.

A stealthy disease

While rarely occurring in full-term infants, this largely mysterious disease affects 1 in 1,000 premature babies. The condition strikes without warning and can cause an infant to go from appearing healthy to a dire state of illness within hours. The disease usually occurs two to six weeks after birth.

The disease produces severe inflammation of intestinal tissue, causing it to die. Such afflictions are known as necro-inflammatory diseases. A perforation may also form in the intestine, allowing bacteria to leak into the abdomen or bloodstream. The sequence of steps leading to NEC remain unclear, though risk factors are believed to include the prolonged use of antibiotics early in life and formula feeding (in addition to preterm birth).

Although studies have strongly implicated changes in the gut microbiome as contributors to the development of NEC, no single bacterial genus has been consistently associated with the disease.

Babies who survive the affliction often face lifelong health issues, which can include neurodevelopmental disabilities and a condition known as short bowel syndrome.

The role of viruses

In the current study, 138 stool samples were collected over the first 11 weeks of life. The samples were from 23 preterm infants in a neonatal intensive care unit in St. Louis, Missouri. Nine of these infants developed NEC, while 14, matched for weight and gestational age, did not.

The study explored the samples using metagenomics, a sequencing method that allows researchers to comprehensively sample genes from all organisms present in a sample. This allows microbiologists like Lim to evaluate bacterial diversity and detect microbial abundance in various environments. The technique also enables the detailed study of microorganisms that are difficult or impossible to culture in the laboratory. (In early 2020, Lim used metagenomic sequencing to rapidly probe the 30,000 letter code of the SARS CoV-2 virus, identifying a unique mutation.)

The study demonstrates that the NEC infants showed a convergence of viral and bacterial signatures in the gut virome. Notably, babies with NEC showed a reduced diversity in viral composition between communities in the gut, a feature known as ?-diversity. The diminishing viral ?-diversity occurred over a 10-day period preceding the onset of NEC, providing a potential biomarker, alerting clinicians to the looming danger. The findings suggest that the developing virome holds vital clues reflecting on the health of preterm infants.

Microbial horizons

The research could lead not only to faster diagnosis and better therapies for NEC but also for a broad range of diseases mediated by the microbiome. Further, existing therapies directed at modifying the gut microbiome, for example, fecal transplant therapy, could be further improved by taking stock of the viral component.

The study demonstrates that the underexplored viral constituents of the microbiome have much to teach us and almost certainly play an important role not only in the transition to NEC in preterm infants but also in other diseases. With new and rapidly evolving sequencing technologies, researchers can begin to mine the virome for valuable diagnostic signposts of disease and develop more effective therapies.

Efrem Lim is the 2022 recipient of the ASU Faculty Research Achievement Award, delivered at the university’s Founder’s Day celebration on March 17.

“Our approach enabled us to read a text that was hidden beneath corrosion, perhaps for hundreds of years,” said Alexandre Locquet, an adjunct professor in ECE and researcher at Georgia Tech-CNRS IRL 2958, a joint international research laboratory at the Georgia Tech-Lorraine campus in Metz, France. “Clearly, approaches that access such information without damaging the object are of great interest to archaeologists.”

The study was reported March 2 in the journal Scientific Reports.

The cross, cut from a sheet of lead, was found in a burial plot at an abbey in Remiremont, France — a couple hours drive from the Georgia Tech-Lorraine campus. Known as a croix d’absolution, it is a type of funerary cross that dates to the Middle Ages and has been found at sites in France, Germany, and England.

“This type of cross typically bears inscriptions of prayers or information about the deceased,” said Aurélien Vacheret, director of the Musée Charles-de-Bruyères in Remiremont and co-author on the study. “It is thought their purpose was to seek a person’s absolution from sin, facilitating their passage to heaven.”

The museum loaned the cross to Citrin’s lab in hopes that the team could use imaging techniques to make the invisible visible. Citrin and his group specialize in non-destructive evaluation and develop techniques that allow for detailed examination of an object’s hidden layers without changing or damaging its original form. Although their work often has industrial applications, such as detecting damage to airplane fuselages, the group embraced the opportunity to inspect the cross — a chance to further explore their technology’s applications for archaeological purposes.

Peeking Beneath the Veil of Corrosion

The team used a commercial terahertz scanner to examine the cross every 500 microns (about every half a millimeter) across the object. First, the scanner sent short pulses of terahertz electromagnetic radiation — a form of light that travels on tiny wavelengths — over each section of the cross. Some waves bounced back from the layer of corrosion, while others penetrated through the corrosion, reflecting from the actual surface of the lead cross. This produced two distinct echoes of the same original pulse.

Next, the team used an algorithm to process the time delay between the two echoes into a signal with two peaks. This data revealed how thick the corrosion was in each scanned point. The measurements of the light beams that reflected from the underlying metal were then collected to form images of the lead surface below the corrosion.

Interdisciplinary Insights

Although crucial data was gathered during the scanning process, the raw images were too noisy and jumbled and the inscription remained illegible at the time. But Junliang Dong, then a Ph.D. student in Citrin’s lab, had the insight to process the images in a special way to eliminate the noise. By subtracting and piecing together parts of the images acquired in different frequencies, Dong was able to restore and enhance the images. What was left was a surprisingly readable image containing the text.

Using the processed images, Vacheret was able to identify multiple Latin words and phrases. He determined they were all part of the Pater Noster, commonly known as the Our Father or the Lord’s Prayer.

The team also worked with a conservationist to chemically reverse the corrosion on the cross, confirming the Pater Noster inscription. Comparing their images to the clean cross, the team found their images had revealed parts of the inscription not observable on the original cross. By uncovering additional aspects of the inscriptions that were previously undocumented, their work was able to offer deeper understanding of the cross and further insight into 16^th-century Christianity in Lorraine, France.

“In this case, we were able to check our work afterwards, but not all lead objects can be treated this way,” Citrin said. “Some objects are large, some must remain in situ, and some are just too delicate. We hope our work opens up the study of other lead objects that might also yield secrets lying underneath corrosion.”

Citrin’s group has also used terahertz imaging to look beneath the surface of 17^th-century paintings, elucidating paint layer structure and providing insights into techniques of master painters. They are currently investigating surface coatings on ancient Roman ceramics.

The cross project illustrates that success requires more than just accurate measurement, but also careful data processing and collaboration between researchers from disparate fields. The team’s approach opens new perspectives for terahertz imaging analysis and could produce great boosts for the fields of digital acquisitions and documentation, as well as character recognition, extraction, and classification.

“Despite three decades of intense development, terahertz imaging is still a rapidly developing field,” said Locquet. “While others focus on developing the hardware, our efforts concentrate on making the most of the data that is measured.”

Reprogramming that robot involves hand-labeling thousands of images that show it how to grasp these new mugs, then training the system all over again.

But a new technique developed by MIT researchers would require only a handful of human demonstrations to reprogram the robot. This machine-learning method enables a robot to pick up and place never-before-seen objects that are in random poses it has never encountered. Within 10 to 15 minutes, the robot would be ready to perform a new pick-and-place task.

The technique uses a neural network specifically designed to reconstruct the shapes of 3D objects. With just a few demonstrations, the system uses what the neural network has learned about 3D geometry to grasp new objects that are similar to those in the demos.

In simulations and using a real robotic arm, the researchers show that their system can effectively manipulate never-before-seen mugs, bowls, and bottles, arranged in random poses, using only 10 demonstrations to teach the robot.

“Our major contribution is the general ability to much more efficiently provide new skills to robots that need to operate in more unstructured environments where there could be a lot of variability. The concept of generalization by construction is a fascinating capability because this problem is typically so much harder,” says Anthony Simeonov, a graduate student in electrical engineering and computer science (EECS) and co-lead author of the paper.

Simeonov wrote the paper with co-lead author Yilun Du, an EECS graduate student; Andrea Tagliasacchi, a staff research scientist at Google Brain; Joshua B. Tenenbaum, the Paul E. Newton Career Development Professor of Cognitive Science and Computation in the Department of Brain and Cognitive Sciences and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL); Alberto Rodriguez, the Class of 1957 Associate Professor in the Department of Mechanical Engineering; and senior authors Pulkit Agrawal, a professor in CSAIL, and Vincent Sitzmann, an incoming assistant professor in EECS. The research will be presented at the International Conference on Robotics and Automation.

Grasping geometry

A robot may be trained to pick up a specific item, but if that object is lying on its side (perhaps it fell over), the robot sees this as a completely new scenario. This is one reason it is so hard for machine-learning systems to generalize to new object orientations.

To overcome this challenge, the researchers created a new type of neural network model, a Neural Descriptor Field (NDF), that learns the 3D geometry of a class of items. The model computes the geometric representation for a specific item using a 3D point cloud, which is a set of data points or coordinates in three dimensions. The data points can be obtained from a depth camera that provides information on the distance between the object and a viewpoint. While the network was trained in simulation on a large dataset of synthetic 3D shapes, it can be directly applied to objects in the real world.

The team designed the NDF with a property known as equivariance. With this property, if the model is shown an image of an upright mug, and then shown an image of the same mug on its side, it understands that the second mug is the same object, just rotated.

“This equivariance is what allows us to much more effectively handle cases where the object you observe is in some arbitrary orientation,” Simeonov says.

As the NDF learns to reconstruct shapes of similar objects, it also learns to associate related parts of those objects. For instance, it learns that the handles of mugs are similar, even if some mugs are taller or wider than others, or have smaller or longer handles.

“If you wanted to do this with another approach, you’d have to hand-label all the parts. Instead, our approach automatically discovers these parts from the shape reconstruction,” Du says.

The researchers use this trained NDF model to teach a robot a new skill with only a few physical examples. They move the hand of the robot onto the part of an object they want it to grip, like the rim of a bowl or the handle of a mug, and record the locations of the fingertips.

Because the NDF has learned so much about 3D geometry and how to reconstruct shapes, it can infer the structure of a new shape, which enables the system to transfer the demonstrations to new objects in arbitrary poses, Du explains.

Picking a winner

They tested their model in simulations and on a real robotic arm using mugs, bowls, and bottles as objects. Their method had a success rate of 85 percent on pick-and-place tasks with new objects in new orientations, while the best baseline was only able to achieve a success rate of 45 percent. Success means grasping a new object and placing it on a target location, like hanging mugs on a rack.

Many baselines use 2D image information rather than 3D geometry, which makes it more difficult for these methods to integrate equivariance. This is one reason the NDF technique performed so much better.

While the researchers were happy with its performance, their method only works for the particular object category on which it is trained. A robot taught to pick up mugs won’t be able to pick up boxes or headphones, since these objects have geometric features that are too different than what the network was trained on.

“In the future, scaling it up to many categories or completely letting go of the notion of category altogether would be ideal,” Simeonov says.

They also plan to adapt the system for nonrigid objects and, in the longer term, enable the system to perform pick-and-place tasks when the target area changes.

This work is supported, in part, by the Defense Advanced Research Projects Agency, the Singapore Defense Science and Technology Agency, and the National Science Foundation.