Computers Math

For the first time, physicists from the University of Basel have produced a graphene compound consisting of carbon atoms and a small number of nitrogen atoms in a regular grid of hexagons and triangles. This honeycomb-structured “kagome lattice” behaves as a semiconductor and may also have unusual electrical properties. In the future, it could potentially be used in electronic sensors or quantum computers.
Researchers around the world are searching for new synthetic materials with special properties such as superconductivity — that is, the conduction of electric current without resistance. These new substances are an important step in the development of highly energy-efficient electronics. The starting material is often a single-layer honeycomb structure of carbon atoms (graphene).
Theoretical calculations predict that the compound known as “kagome graphene” should have completely different properties to graphene. Kagome graphene consists of a regular pattern of hexagons and equilateral triangles that surround one another. The name “kagome” comes from Japanese and refers to the old Japanese art of kagome weaving, in which baskets were woven in the aforementioned pattern.
Kagome lattice with new properties
Researchers from the Department of Physics and the Swiss Nanoscience Institute at the University of Basel, working in collaboration with the University of Bern, have now produced and studied kagome graphene for the first time, as they report in the journal Angewandte Chemie. The researchers’ measurements have delivered promising results that point to unusual electrical or magnetic properties.
To produce the kagome graphene, the team applied a precursor to a silver substrate by vapor deposition and then heated it to form an organometallic intermediate on the metal surface. Further heating produced kagome graphene, which is made up exclusively of carbon and nitrogen atoms and features the same regular pattern of hexagons and triangles.

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Strong interactions between electrons
“We used scanning tunneling and atomic force microscopes to study the structural and electronic properties of the kagome lattice,” reports Dr. Rémy Pawlak, first author of the study. With microscopes of this kind, researchers can probe the structural and electrical properties of materials using a tiny tip — in this case, the tip was terminated with individual carbon monoxide molecules.
In doing so, the researchers observed that electrons of a defined energy, which is selected by applying an electrical voltage, are “trapped” between the triangles that appear in the crystal lattice of kagome graphene. This behavior clearly distinguishes the material from conventional graphene, where electrons are distributed across various energy states in the lattice — in other words, they are delocalized.
“The localization observed in kagome graphene is desirable and precisely what we were looking for,” explains Professor Ernst Meyer, who leads the group in which the projects were carried out. “It causes strong interactions between the electrons — and, in turn, these interactions provide the basis for unusual phenomena, such as conduction without resistance.”
Further investigations planned
The analyses also revealed that kagome graphene features semiconducting properties — in other words, its conducting properties can be switched on or off, as with a transistor. In this way, kagome graphene differs significantly from graphene, whose conductivity cannot be switched on and off as easily.
In subsequent investigations, the team will detach the kagome lattice from its metallic substrate and study its electronic properties further. “The flat band structure identified in the experiments supports the theoretical calculations, which predict that exciting electronic and magnetic phenomena could occur in kagome lattices. In the future, kagome graphene could act as a key building block in sustainable and efficient electronic components,” says Ernst Meyer. More

It does not happen often. But on rare occasions, physicians make mistakes and may make a wrong diagnosis. Patients may have many diseases all at once, where it can be difficult to distinguish the symptoms of one illness from the other, or there may be a lack of symptoms.
Errors in diagnosis may lead to incorrect treatment or a lack of treatment. Therefore, everyone in the healthcare system tries to minimise errors as much as possible.
Now, researchers at the University of Copenhagen have developed an algorithm that can help with just that.
‘Our new algorithm can find the patients who have such an unusual disease trajectory that they may indeed not suffer from the disease they were diagnosed with. It can hopefully end up being a support tool for physicians’, says Isabella Friis Jørgensen, Postdoc at the Novo Nordisk Foundation Center for Protein Research.
The algorithm revealed possible lung cancer
The researchers have developed the algorithm based on disease trajectories for 284,000 patients with chronic obstructive pulmonary disease (COPD), from 1994 to 2015. Based on these data, they came up with approximately 69,000 typical disease trajectories.

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‘In the National Patient Registry, we have been able to map what you could call typical disease trajectory. And if a patient shows up with a very unusual disease trajectory, then it might be that the patient is simply suffering from a different disease. Our tool can help to detect this’, explains Søren Brunak, Professor at the Novo Nordisk Foundation Center for Protein Research.
For example, the researchers found a small group of 2,185 COPD patients who died very shortly after being diagnosed with COPD. According to the researchers, it was a sign that something else might have been wrong, maybe something even more serious.
‘When we studied the laboratory values from these patients more closely, we saw that they deviated from normal values for COPD patients. Instead, the values resembled something that is seen in lung cancer patients. Only 10 per cent of these patients were diagnosed with lung cancer, but we are reasonably convinced that most, if not all of these patients actually had lung cancer’, explains Søren Brunak.
Data that will provide an immediate benefit
Although the algorithm was validated through data from COPD patients, it may be used for many other diseases. The principle is the same: the algorithm uses registry data to map the typical disease trajectories and can detect if some patients’ disease trajectory stand out so much that something may be wrong.
‘Naturally, our most important goal is for the patients to get their money’s worth with respect to their health care. And we believe that in the future, this algorithm may end up becoming a support tool for physicians. Once the algorithm has mapped the typical disease trjaectories, it only takes 10 seconds to match a single patient against everyone else’, says Søren Brunak.
He emphasises that the algorithm must be further validated and tested in clinical trials before it can be implemented in Danish hospitals. But he hopes it is something that can be started soon.
‘In Denmark, we often praise our good health registries because they contain valuable data for researchers. We use them in our research because it may benefit other people in the future in the form of better treatment. But this is actually an example of how your own health data can benefit yourself right away’, says Søren Brunak. More

MIT researchers have invented a new type of amputation surgery that can help amputees to better control their residual muscles and sense where their “phantom limb” is in space. This restored sense of proprioception should translate to better control of prosthetic limbs, as well as a reduction of limb pain, the researchers say.
In most amputations, muscle pairs that control the affected joints, such as elbows or ankles, are severed. However, the MIT team has found that reconnecting these muscle pairs, allowing them to retain their normal push-pull relationship, offers people much better sensory feedback.
“Both our study and previous studies show that the better patients can dynamically move their muscles, the more control they’re going to have. The better a person can actuate muscles that move their phantom ankle, for example, the better they’re actually able to use their prostheses,” says Shriya Srinivasan, an MIT postdoc and lead author of the study.
In a study that will appear this week in the Proceedings of the National Academy of Sciences, 15 patients who received this new type of surgery, known as agonist-antagonist myoneural interface (AMI), could control their muscles more precisely than patients with traditional amputations. The AMI patients also reported feeling more freedom of movement and less pain in their affected limb.
“Through surgical and regenerative techniques that restore natural agonist-antagonist muscle movements, our study shows that persons with an AMI amputation experience a greater phantom joint range of motion, a reduced level of pain, and an increased fidelity of prosthetic limb controllability,” says Hugh Herr, a professor of media arts and sciences, head of the Biomechatronics group in the Media Lab, and the senior author of the paper.
Other authors of the paper include Samantha Gutierrez-Arango and Erica Israel, senior research support associates at the Media Lab; Ashley Chia-En Teng, an MIT undergraduate; Hyungeun Song, a graduate student in the Harvard-MIT Program in Health Sciences and Technology; Zachary Bailey, a former visiting researcher at the Media Lab; Matthew Carty, a visiting scientist at the Media Lab; and Lisa Freed, a Media Lab research scientist.

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Restoring sensation
Most muscles that control limb movement occur in pairs that alternately stretch and contract. One example of these agonist-antagonist pairs is the biceps and triceps. When you bend your elbow, the biceps muscle contracts, causing the triceps to stretch, and that stretch sends sensory information back to the brain.
During a conventional limb amputation, these muscle movements are restricted, cutting off this sensory feedback and making it much harder for amputees to feel where their prosthetic limbs are in space or to sense forces applied to those limbs.
“When one muscle contracts, the other one doesn’t have its antagonist activity, so the brain gets confusing signals,” says Srinivasan, a former member of the Biomechatronics group now working at MIT’s Koch Institute for Integrative Cancer Research. “Even with state-of-the-art prostheses, people are constantly visually following the prosthesis to try to calibrate their brains to where the device is moving.”
A few years ago, the MIT Biomechatronics group invented and scientifically developed in preclinical studies a new amputation technique that maintains the relationships between those muscle pairs. Instead of severing each muscle, they connect the two ends of the muscles so that they still dynamically communicate with each other within the residual limb. In a 2017 study of rats, they showed that when the animals contracted one muscle of the pair, the other muscle would stretch and send sensory information back to the brain.

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Since these preclinical studies, about 25 people have undergone the AMI surgery at Brigham and Women’s Hospital, performed by Carty, who is also a plastic surgeon at the Brigham and Women’s hospital. In the new PNAS study, the researchers measured the precision of muscle movements in the ankle and subtalar joints of 15 patients who had AMI amputations performed below the knee. These patients had two sets of muscles reconnected during their amputation: the muscles that control the ankle, and those that control the subtalar joint, which allows the sole of the foot to tilt inward or outward. The study compared these patients to seven people who had traditional amputations below the knee.
Each patient was evaluated while lying down with their legs propped on a foam pillow, allowing their feet to extend into the air. Patients did not wear prosthetic limbs during the study. The researchers asked them to flex their ankle joints — both the intact one and the “phantom” one — by 25, 50, 75, or 100 percent of their full range of motion. Electrodes attached to each leg allowed the researchers to measure the activity of specific muscles as each movement was performed repeatedly.
The researchers compared the electrical signals coming from the muscles in the amputated limb with those from the intact limb and found that for AMI patients, they were very similar. They also found that patients with the AMI amputation were able to control the muscles of their amputated limb much more precisely than the patients with traditional amputations. Patients with traditional amputations were more likely to perform the same movement over and over in their amputated limb, regardless of how far they were asked to flex their ankle.
“The AMI patients’ ability to control these muscles was a lot more intuitive than those with typical amputations, which largely had to do with the way their brain was processing how the phantom limb was moving,” Srinivasan says.
In a paper that recently appeared in Science Translational Medicine, the researchers reported that brain scans of the AMI amputees showed that they were getting more sensory feedback from their residual muscles than patients with traditional amputations. In work that is now ongoing, the researchers are measuring whether this ability translates to better control of a prosthetic leg while walking.
Freedom of movement
The researchers also discovered an effect they did not anticipate: AMI patients reported much less pain and a greater sensation of freedom of movement in their amputated limbs.
“Our study wasn’t specifically designed to achieve this, but it was a sentiment our subjects expressed over and over again. They had a much greater sensation of what their foot actually felt like and how it was moving in space,” Srinivasan says. “It became increasingly apparent that restoring the muscles to their normal physiology had benefits not only for prosthetic control, but also for their day-to-day mental well-being.”
The research team has also developed a modified version of the surgery that can be performed on people who have already had a traditional amputation. This process, which they call “regenerative AMI,” involves grafting small muscle segments to serve as the agonist and antagonist muscles for an amputated joint. They are also working on developing the AMI procedure for other types of amputations, including above the knee and above and below the elbow.
“We’re learning that this technique of rewiring the limb, and using spare parts to reconstruct that limb, is working, and it’s applicable to various parts of the body,” Herr says.
The research was funded by the MIT Media Lab Consortia, the National Institute of Child Health and Human Development, the National Center for Medical Rehabilitation Research, and the Congressionally Directed Medical Research Programs of the U.S. Department of Defense. More

Researchers have found a way to use light and a single electron to communicate with a cloud of quantum bits and sense their behaviour, making it possible to detect a single quantum bit in a dense cloud.
The researchers, from the University of Cambridge, were able to inject a ‘needle’ of highly fragile quantum information in a ‘haystack’ of 100,000 nuclei. Using lasers to control an electron, the researchers could then use that electron to control the behaviour of the haystack, making it easier to find the needle. They were able to detect the ‘needle’ with a precision of 1.9 parts per million: high enough to detect a single quantum bit in this large ensemble.
The technique makes it possible to send highly fragile quantum information optically to a nuclear system for storage, and to verify its imprint with minimal disturbance, an important step in the development of a quantum internet based on quantum light sources. The results are reported in the journal Nature Physics.
The first quantum computers — which will harness the strange behaviour of subatomic particles to far outperform even the most powerful supercomputers — are on the horizon. However, leveraging their full potential will require a way to network them: a quantum internet. Channels of light that transmit quantum information are promising candidates for a quantum internet, and currently there is no better quantum light source than the semiconductor quantum dot: tiny crystals that are essentially artificial atoms.
However, one thing stands in the way of quantum dots and a quantum internet: the ability to store quantum information temporarily at staging posts along the network.
“The solution to this problem is to store the fragile quantum information by hiding it in the cloud of 100,000 atomic nuclei that each quantum dot contains, like a needle in a haystack,” said Professor Mete Atatüre from Cambridge’s Cavendish Laboratory, who led the research. “But if we try to communicate with these nuclei like we communicate with bits, they tend to ‘flip’ randomly, creating a noisy system.”
The cloud of quantum bits contained in a quantum dot don’t normally act in a collective state, making it a challenge to get information in or out of them. However, Atatüre and his colleagues showed in 2019 that when cooled to ultra-low temperatures also using light, these nuclei can be made to do ‘quantum dances’ in unison, significantly reducing the amount of noise in the system.

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Now, they have shown another fundamental step towards storing and retrieving quantum information in the nuclei. By controlling the collective state of the 100,000 nuclei, they were able to detect the existence of the quantum information as a ‘flipped quantum bit’ at an ultra-high precision of 1.9 parts per million: enough to see a single bit flip in the cloud of nuclei.
“Technically this is extremely demanding,” said Atatüre, who is also a Fellow of St John’s College. “We don’t have a way of ‘talking’ to the cloud and the cloud doesn’t have a way of talking to us. But what we can talk to is an electron: we can communicate with it sort of like a dog that herds sheep.”
Using the light from a laser, the researchers are able to communicate with an electron, which then communicates with the spins, or inherent angular momentum, of the nuclei.
By talking to the electron, the chaotic ensemble of spins starts to cool down and rally around the shepherding electron; out of this more ordered state, the electron can create spin waves in the nuclei.
“If we imagine our cloud of spins as a herd of 100,000 sheep moving randomly, one sheep suddenly changing direction is hard to see,” said Atatüre. “But if the entire herd is moving as a well-defined wave, then a single sheep changing direction becomes highly noticeable.”
In other words, injecting a spin wave made of a single nuclear spin flip into the ensemble makes it easier to detect a single nuclear spin flip among 100,000 nuclear spins.

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Using this technique, the researchers are able to send information to the quantum bit and ‘listen in’ on what the spins are saying with minimal disturbance, down to the fundamental limit set by quantum mechanics.
“Having harnessed this control and sensing capability over this large ensemble of nuclei, our next step will be to demonstrate the storage and retrieval of an arbitrary quantum bit from the nuclear spin register,” said co-first author Daniel Jackson, a PhD student at the Cavendish Laboratory.
“This step will complete a quantum memory connected to light — a major building block on the road to realising the quantum internet,” said co-first author Dorian Gangloff, a Research Fellow at St John’s College.
Besides its potential usage for a future quantum internet, the technique could also be useful in the development of solid-state quantum computing.
The research was supported in part by the European Research Council (ERC), the Engineering and Physical Sciences Research Council (EPSRC) and the Royal Society. More

Engineers at the University of California San Diego have developed a soft, stretchy skin patch that can be worn on the neck to continuously track blood pressure and heart rate while measuring the wearer’s levels of glucose as well as lactate, alcohol or caffeine. It is the first wearable device that monitors cardiovascular signals and multiple biochemical levels in the human body at the same time.
“This type of wearable would be very helpful for people with underlying medical conditions to monitor their own health on a regular basis,” said Lu Yin, a nanoengineering Ph.D. student at UC San Diego and co-first author of the study published Feb. 15 in Nature Biomedical Engineering. “It would also serve as a great tool for remote patient monitoring, especially during the COVID-19 pandemic when people are minimizing in-person visits to the clinic.”
Such a device could benefit individuals managing high blood pressure and diabetes — individuals who are also at high risk of becoming seriously ill with COVID-19. It could also be used to detect the onset of sepsis, which is characterized by a sudden drop in blood pressure accompanied by a rapid rise in lactate level.
One soft skin patch that can do it all would also offer a convenient alternative for patients in intensive care units, including infants in the NICU, who need continuous monitoring of blood pressure and other vital signs. These procedures currently involve inserting catheters deep inside patients’ arteries and tethering patients to multiple hospital monitors.
“The novelty here is that we take completely different sensors and merge them together on a single small platform as small as a stamp,” said Joseph Wang, a professor of nanoengineering at UC San Diego and co-corresponding author of the study. “We can collect so much information with this one wearable and do so in a non-invasive way, without causing discomfort or interruptions to daily activity.”
The new patch is a product of two pioneering efforts in the UC San Diego Center for Wearable Sensors, for which Wang serves as director. Wang’s lab has been developing wearables capable of monitoring multiple signals simultaneously — chemical, physical and electrophysiological — in the body. And in the lab of UC San Diego nanoengineering professor Sheng Xu, researchers have been developing soft, stretchy electronic skin patches that can monitor blood pressure deep inside the body. By joining forces, the researchers created the first flexible, stretchable wearable device that combines chemical sensing (glucose, lactate, alcohol and caffeine) with blood pressure monitoring.

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“Each sensor provides a separate picture of a physical or chemical change. Integrating them all in one wearable patch allows us to stitch those different pictures together to get a more comprehensive overview of what’s going on in our bodies,” said Xu, who is also a co-corresponding author of the study.
Patch of all trades
The patch is a thin sheet of stretchy polymers that can conform to the skin. It is equipped with a blood pressure sensor and two chemical sensors — one that measures levels of lactate (a biomarker of physical exertion), caffeine and alcohol in sweat, and another that measures glucose levels in interstitial fluid.
The patch is capable of measuring three parameters at once, one from each sensor: blood pressure, glucose, and either lactate, alcohol or caffeine. “Theoretically, we can detect all of them at the same time, but that would require a different sensor design,” said Yin, who is also a Ph.D. student in Wang’s lab.
The blood pressure sensor sits near the center of the patch. It consists of a set of small ultrasound transducers that are welded to the patch by a conductive ink. A voltage applied to the transducers causes them to send ultrasound waves into the body. When the ultrasound waves bounce off an artery, the sensor detects the echoes and translates the signals into a blood pressure reading.

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The chemical sensors are two electrodes that are screen printed on the patch from conductive ink. The electrode that senses lactate, caffeine and alcohol is printed on the right side of the patch; it works by releasing a drug called pilocarpine into the skin to induce sweat and detecting the chemical substances in the sweat. The other electrode, which senses glucose, is printed on the left side; it works by passing a mild electrical current through the skin to release interstitial fluid and measuring the glucose in that fluid.
The researchers were interested in measuring these particular biomarkers because they impact blood pressure. “We chose parameters that would give us a more accurate, more reliable blood pressure measurement,” said co-first author Juliane Sempionatto, a nanoengineering Ph.D. student in Wang’s lab.
“Let’s say you are monitoring your blood pressure, and you see spikes during the day and think that something is wrong. But a biomarker reading could tell you if those spikes were due to an intake of alcohol or caffeine. This combination of sensors can give you that type of information,” she said.
In tests, subjects wore the patch on the neck while performing various combinations of the following tasks: exercising on a stationary bicycle; eating a high-sugar meal; drinking an alcoholic beverage; and drinking a caffeinated beverage. Measurements from the patch closely matched those collected by commercial monitoring devices such as a blood pressure cuff, blood lactate meter, glucometer and breathalyzer. Measurements of the wearers’ caffeine levels were verified with measurements of sweat samples in the lab spiked with caffeine.
Engineering challenges
One of the biggest challenges in making the patch was eliminating interference between the sensors’ signals. To do this, the researchers had to figure out the optimal spacing between the blood pressure sensor and the chemical sensors. They found that one centimeter of spacing did the trick while keeping the device as small as possible.
The researchers also had to figure out how to physically shield the chemical sensors from the blood pressure sensor. The latter normally comes equipped with a liquid ultrasound gel in order to produce clear readings. But the chemical sensors are also equipped with their own hydrogels, and the problem is that if any liquid gel from the blood pressure sensor flows out and makes contact with the other gels, it will cause interference between the sensors. So instead, the researchers used a solid ultrasound gel, which they found works as well as the liquid version but without the leakage.
“Finding the right materials, optimizing the overall layout, integrating the different electronics together in a seamless fashion — these challenges took a lot of time to overcome,” said co-first author Muyang Lin, a nanoengineering Ph.D. student in Xu’s lab. “We are fortunate to have this great collaboration between our lab and Professor Wang’s lab. It has been so fun working together with them on this project.”
Next steps
The team is already at work on a new version of the patch, one with even more sensors. “There are opportunities to monitor other biomarkers associated with various diseases. We are looking to add more clinical value to this device,” Sempionatto said.
Ongoing work also includes shrinking the electronics for the blood pressure sensor. Right now, the sensor needs to be connected to a power source and a benchtop machine to display its readings. The ultimate goal is to put these all on the patch and make everything wireless.
“We want to make a complete system that is fully wearable,” Lin said. This research was supported by the UC San Diego Center of Wearable Sensors and the National Institutes of Health (grant no. 1R21EB027303-01A1). More

Materials having excess electrons are typically conductors. However, moiré patterns — interference patterns that typically arise when one object with a repetitive pattern is placed over another with a similar pattern — can suppress electrical conductivity, a study led by physicists at the University of California, Riverside, has found.
In the lab, the researchers overlaid a single monolayer of tungsten disulfide (WS2) on a single monolayer of tungsten diselenide (WSe2) and aligned the two layers against each other to generate large-scale moiré patterns. The atoms in both the WS2 and WSe2 layers are arranged in a two-dimensional honeycomb lattice with a periodicity, or recurring intervals, of much less than 1 nanometer. But when the two lattices are aligned at 0 or 60 degrees, the composite material generates a moiré pattern with a much larger periodicity of about 8 nanometers. The conductivity of this 2D system depends on how many electrons are placed in the moiré pattern.
“We found that when the moiré pattern is partially filled with electrons, the system exhibits several insulating states as opposed to conductive states expected from conventional understanding,” said Yongtao Cui, an assistant professor of physics and astronomy at UC Riverside, who led the research team. “The filling percentages were found to be simple fractions like 1/2, 1/3, 1/4, 1/6, and so on. The mechanism for such insulating states is the strong interaction among electrons that restricts the mobile electrons into local moiré cells. This understanding may help to develop new ways to control conductivity and to discovery new superconductor materials.”
Study results appear today in Nature Physics.
The moiré patterns generated on the composite material of WS2 and WSe2 can be imagined to be with wells and ridges arranged similarly in a honeycomb pattern.
“WS2 and WSe2 have a slight mismatch where lattice size is concerned, making them ideal for producing moiré patterns,” Cui said. “Further, coupling between electrons becomes strong, meaning the electrons ‘talk to each other’ while moving around across the ridges and the wells.”
Typically, when a small number of electrons are placed in a 2D layer such as WS2 or WSe2, they have enough energy to travel freely and randomly, making the system a conductor. Cui’s lab found that when moiré lattices are formed using both WS2 and WSe2, resulting in a periodic pattern, the electrons begin to slow down and repel from each other.

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“The electrons do not want to stay close to each other,” said Xiong Huang, the first author of the paper and a doctoral graduate student in Cui’s Microwave Nano-Electronics Lab. “When the number of electrons is such that one electron occupies every moiré hexagon, the electrons stay locked in place and cannot move freely anymore. The system then behaves like an insulator.”
Cui likened the behavior of such electrons to social distancing during a pandemic.
“If the hexagons can be imagined to be homes, all the electrons are indoors, one per home, and not moving about in the neighborhood,” he said. “If we don’t have one electron per hexagon, but instead have 95% occupancy of hexagons, meaning some nearby hexagons are empty, then the electrons can still move around a little through the empty cells. That’s when the material is not an insulator. It behaves like a poor conductor.”
His lab was able to fine-tune the number of electrons in the WS2- WSe2 lattice composite in order to change the average occupancy of the hexagons. His team found insulating states occurred when average occupancy was less than one. For example, for an occupancy of one-third, the electrons occupied every other hexagon.
“Using the social distancing analogy, instead of a separation of 6 feet, you now have a separation of, say, 10 feet,” Cui said. “Thus, when one electron occupies a hexagon, it forces all neighboring hexagons to be empty in order to comply with the stricter social distancing rule. When all electrons follow this rule, they form a new pattern and occupy one third of the total hexagons in which they again lose the freedom to move about, leading to an insulating state.”
The study shows similar behaviors can also occur for other occupancy fractions such as 1/4, 1/2, and 1/6, with each corresponding to a different occupation pattern.

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Cui explained that these insulating states are caused by strong interactions between the electrons. This, he added, is the Coulomb repulsion, the repulsive force between two positive or two negative charges, as described by the Coulomb’s law.
He added that in 3D materials, strong electron interactions are known to give rise to various exotic electronic phases. For example, they likely contribute to the formation of unconventional high temperature superconductivity.
“The question we still have no answer for is whether 2D structures, the kind we used in our experiments, can produce high temperature superconductivity,” Cui said.
Next, his group will work on characterizing the strength of the electron interactions.
“The interaction strength of the electrons largely determines the insulation state of the system,” Cui said. “We are also interested in being able to manipulate the strength of the electron interaction.”
Cui and Huang were funded by grants from the National Science Foundation, a Hellman Fellowship, and a seed grant from SHINES. More

By capitalizing on a convergence of chemical, biological and artificial intelligence advances, University of Pittsburgh School of Medicine scientists have developed an unusually fast and efficient method for discovering tiny antibody fragments with big potential for development into therapeutics against deadly diseases.
The technique, published today in the journal Cell Systems, is the same process the Pitt team used to extract tiny SARS-CoV-2 antibody fragments from llamas, which could become an inhalable COVID-19 treatment for humans. This approach has the potential to quickly identify multiple potent nanobodies that target different parts of a pathogen — thwarting variants.
“Most of the vaccines and treatments against SARS-CoV-2 target the spike protein, but if that part of the virus mutates, which we know it is, those vaccines and treatments may be less effective,” said senior author Yi Shi, Ph.D., assistant professor of cell biology at Pitt. “Our approach is an efficient way to develop therapeutic cocktails consisting of multiple nanobodies that can launch a multipronged attack to neutralize the pathogen.”
Shi and his team specialize in finding nanobodies — which are small, highly specific fragments of antibodies produced by llamas and other camelids. Nanobodies are particularly attractive for development into therapeutics because they are easy to produce and bioengineer. In addition, they feature high stability and solubility, and can be aerosolized and inhaled, rather than administered through intravenous infusion, like traditional antibodies.
By immunizing a llama with a piece of a pathogen, the animal’s immune system produces a plethora of mature nanobodies in about two months. Then it’s a matter of teasing out which nanobodies are best at neutralizing the pathogen — and most promising for development into therapies for humans.
That’s where Shi’s “high-throughput proteomics strategy” comes into play.

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“Using this new technique, in a matter of days we’re typically able to identify tens of thousands of distinct, highly potent nanobodies from the immunized llama serum and survey them for certain characteristics, such as where they bind to the pathogen,” Shi said. “Prior to this approach, it has been extremely challenging to identify high-affinity nanobodies.”
After drawing a llama blood sample rich in mature nanobodies, the researchers isolate those nanobodies that bind specifically to the target of interest on the pathogen. The nanobodies are then broken down to release small “fingerprint” peptides that are unique to each nanobody. These fingerprint peptides are placed into a mass spectrometer, which is a machine that measures their mass. By knowing their mass, the scientists can figure out their amino acid sequence — the protein building blocks that determine the nanobody’s structure. Then, from the amino acids, the researchers can work backward to DNA — the directions for building more nanobodies.
Simultaneously, the amino acid sequence is uploaded to a computer outfitted with artificial intelligence software. By rapidly sifting through mountains of data, the program “learns” which nanobodies bind the tightest to the pathogen and where on the pathogen they bind. In the case of most of the currently available COVID-19 therapeutics, this is the spike protein, but recently it has become clear that some sites on the spike are prone to mutations that change its shape and allow for antibody “escape.” Shi’s approach can select for binding sites on the spike that are evolutionarily stable, and therefore less likely to allow new variants to slip past.
Finally, the directions for building the most potent and diverse nanobodies can then be fed into vats of bacterial cells, which act as mini factories, churning out orders of magnitude more nanobodies compared to the human cells required to produce traditional antibodies. Bacterial cells double in 10 minutes, effectively doubling the nanobodies with them, whereas human cells take 24 hours to do the same.
“This drastically reduces the cost of producing these therapeutics,” said Shi.
Shi and his team believe their technology could be beneficial for more than just developing therapeutics against COVID-19 — or even the next pandemic.
“The possible uses of highly potent and specific nanobodies that can be identified quickly and inexpensively are tremendous,” said Shi. “We’re exploring their use in treating cancer and neurodegenerative diseases. Our technique could even be used in personalized medicine, developing specific treatments for mutated superbugs for which every other antibiotic has failed.”
Additional researchers on this publication are Yufei Xiang and Jianquan Xu, Ph.D., both of Pitt; Zhe Sang of Pitt and Carnegie Mellon University; and Lirane Bitton and Dina Schneidman-Duhovny, Ph.D., both of the Hebrew University of Jerusalem.
This research was supported by the UPMC Aging Institute, National Institutes of Health grant 1R35GM137905-01, Israel Science Foundation grant 1466/18, the Ministry of Science and Technology of Israel and the Hebrew University of Jerusalem Center for Interdisciplinary Data Science Research. More

When the Covid-19 pandemic struck in early 2020, doctors and researchers rushed to find effective treatments. There was little time to spare. “Making new drugs takes forever,” says Caroline Uhler, a computational biologist in MIT’s Department of Electrical Engineering and Computer Science and the Institute for Data, Systems and Society, and an associate member of the Broad Institute of MIT and Harvard. “Really, the only expedient option is to repurpose existing drugs.”
Uhler’s team has now developed a machine learning-based approach to identify drugs already on the market that could potentially be repurposed to fight Covid-19, particularly in the elderly. The system accounts for changes in gene expression in lung cells caused by both the disease and aging. That combination could allow medical experts to more quickly seek drugs for clinical testing in elderly patients, who tend to experience more severe symptoms. The researchers pinpointed the protein RIPK1 as a promising target for Covid-19 drugs, and they identified three approved drugs that act on the expression of RIPK1.
The research appears today in the journal Nature Communications. Co-authors include MIT PhD students Anastasiya Belyaeva, Adityanarayanan Radhakrishnan, Chandler Squires, and Karren Dai Yang, as well as PhD student Louis Cammarata of Harvard University and long-term collaborator G.V. Shivashankar of ETH Zurich in Switzerland.
Early in the pandemic, it grew clear that Covid-19 harmed older patients more than younger ones, on average. Uhler’s team wondered why. “The prevalent hypothesis is the aging immune system,” she says. But Uhler and Shivashankar suggested an additional factor: “One of the main changes in the lung that happens through aging is that it becomes stiffer.”
The stiffening lung tissue shows different patterns of gene expression than in younger people, even in response to the same signal. “Earlier work by the Shivashankar lab showed that if you stimulate cells on a stiffer substrate with a cytokine, similar to what the virus does, they actually turn on different genes,” says Uhler. “So, that motivated this hypothesis. We need to look at aging together with SARS-CoV-2 — what are the genes at the intersection of these two pathways?” To select approved drugs that might act on these pathways, the team turned to big data and artificial intelligence.
The researchers zeroed in on the most promising drug repurposing candidates in three broad steps. First, they generated a large list of possible drugs using a machine-learning technique called an autoencoder. Next, they mapped the network of genes and proteins involved in both aging and SARS-CoV-2 infection. Finally, they used statistical algorithms to understand causality in that network, allowing them to pinpoint “upstream” genes that caused cascading effects throughout the network. In principle, drugs targeting those upstream genes and proteins should be promising candidates for clinical trials.
To generate an initial list of potential drugs, the team’s autoencoder relied on two key datasets of gene expression patterns. One dataset showed how expression in various cell types responded to a range of drugs already on the market, and the other showed how expression responded to infection with SARS-CoV-2. The autoencoder scoured the datasets to highlight drugs whose impacts on gene expression appeared to counteract the effects of SARS-CoV-2. “This application of autoencoders was challenging and required foundational insights into the working of these neural networks, which we developed in a paper recently published in PNAS,” notes Radhakrishnan.
Next, the researchers narrowed the list of potential drugs by homing in on key genetic pathways. They mapped the interactions of proteins involved in the aging and Sars-CoV-2 infection pathways. Then they identified areas of overlap among the two maps. That effort pinpointed the precise gene expression network that a drug would need to target to combat Covid-19 in elderly patients.
“At this point, we had an undirected network,” says Belyaeva, meaning the researchers had yet to identify which genes and proteins were “upstream” (i.e. they have cascading effects on the expression of other genes) and which were “downstream” (i.e. their expression is altered by prior changes in the network). An ideal drug candidate would target the genes at the upstream end of the network to minimize the impacts of infection.
“We want to identify a drug that has an effect on all of these differentially expressed genes downstream,” says Belyaeva. So the team used algorithms that infer causality in interacting systems to turn their undirected network into a causal network. The final causal network identified RIPK1 as a target gene/protein for potential Covid-19 drugs, since it has numerous downstream effects. The researchers identified a list of the approved drugs that act on RIPK1 and may have potential to treat Covid-19. Previously these drugs have been approved for the use in cancer. Other drugs that were also identified, including ribavirin and quinapril, are already in clinical trials for Covid-19.
Uhler plans to share the team’s findings with pharmaceutical companies. She emphasizes that before any of the drugs they identified can be approved for repurposed use in elderly Covid-19 patients, clinical testing is needed to determine efficacy. While this particular study focused on Covid-19, the researchers say their framework is extendable. “I’m really excited that this platform can be more generally applied to other infections or diseases,” says Belyaeva. Radhakrishnan emphasizes the importance of gathering information on how various diseases impact gene expression. “The more data we have in this space, the better this could work,” he says.
This research was supported, in part, by the Office of Naval Research, the National Science Foundation, the Simons Foundation, IBM, and the MIT Jameel Clinic for Machine Learning and Health. More