There has been significant progress in the field of quantum computing. Big global players, such as Google and IBM, are already offering cloud-based quantum computing services. However, quantum computers cannot yet help with problems that occur when standard computers reach the limits of their capacities because the availability of qubits or quantum bits, i.e., the basic units of quantum information, is still insufficient. One of the reasons for this is that bare qubits are not of immediate use for running a quantum algorithm.

While the binary bits of customary computers store information in the form of fixed values of either 0 or 1, qubits can represent 0 and 1 at one and the same time, bringing probability as to their value into play. This is known as quantum superposition. This makes them very susceptible to external influences, which means that the information they store can readily be lost. In order to ensure that quantum computers supply reliable results, it is necessary to generate a genuine entanglement to join together several physical qubits to form a logical qubit. Should one of these physical qubits fail, the other qubits will retain the information. However, one of the main difficulties preventing the development of functional quantum computers is the large number of physical qubits required.

Advantages of a photon-based approach

Many different concepts are being employed to make quantum computing viable. Large corporations currently rely on superconducting solid-state systems, for example, but these have the disadvantage that they only function at temperatures close to absolute zero. Photonic concepts, on the other hand, work at room temperature. Single photons usually serve as physical qubits here. These photons, which are, in a sense, tiny particles of light, inherently operate more rapidly than solid-state qubits but, at the same time, are more easily lost. To avoid qubit losses and other errors, it is necessary to couple several single-photon light pulses together to construct a logical qubit — as in the case of the superconductor-based approach.

A qubit with the inherent capacity for error correction

Researchers of the University of Tokyo together with colleagues from Johannes Gutenberg University Mainz (JGU) in Germany and Palacký University Olomouc in the Czech Republic have recently demonstrated a new means of constructing a photonic quantum computer. Rather than using a single photon, the team employed a laser-generated light pulse that can consist of several photons. “Our laser pulse was converted to a quantum optical state that gives us an inherent capacity to correct errors,” stated Professor Peter van Loock of Mainz University. “Although the system consists only of a laser pulse and is thus very small, it can — in principle — eradicate errors immediately.” Thus, there is no need to generate individual photons as qubits via numerous light pulses and then have them interact as logical qubits. “We need just a single light pulse to obtain a robust logical qubit,” added van Loock. To put it in other words, a physical qubit is already equivalent to a logical qubit in this system — a remarkable and unique concept. However, the logical qubit experimentally produced at the University of Tokyo was not yet of a sufficient quality to provide the necessary level of error tolerance. Nonetheless, the researchers have clearly demonstrated that it is possible to transform non-universally correctable qubits into correctable qubits using the most innovative quantum optical methods.

The corresponding research results have recently been published in Science. They are based on a collaboration going back some 20 years between the experimental group of Akira Furusawa in Japan and the theoretical team of Peter van Loock in Germany.

Jonathan Brande, a doctoral candidate in the ExoLab at the University of Kansas, has just published findings in the open-access scientific journal The Astrophysical Journal Letters showing new atmospheric detail in a set of 15 exoplanets similar to Neptune. While none could support humanity, a better understanding of their behavior might help us to understand why we don’t have a small Neptune, while most solar systems seem to feature a planet of this class.

“Over the past several years at KU, my focus has been studying the atmospheres of exoplanets through a technique known as transmission spectroscopy,” Brande said. “When a planet transits, meaning it moves between our line of sight and the star it orbits, light from the star passes through the planet’s atmosphere, getting absorbed by the various gases present. By capturing a spectrum of the star — passing the light through an instrument called a spectrograph, akin to passing it through a prism — we observe a rainbow, measuring the brightness of different constituent colors. Varied areas of brightness or dimness in the spectrum reveal the gases absorbing light in the planet’s atmosphere.”

With this methodology, several years ago Brande published a paper concerning the “warm Neptune” exoplanet TOI-674 b, where he presented observations indicating the presence of water vapor in its atmosphere. These observations were part of a broader program led by Brande’s adviser, Ian Crossfield, associate professor of physics & astronomy at KU, to observe atmospheres of Neptune-sized exoplanets.

“We want to comprehend the behaviors of these planets, given that those slightly larger than Earth and smaller than Neptune are the most common in the galaxy,” Brande said.

This recent ApJL paper summarizes observations from that program, incorporating data from additional observations to address why some planets appear cloudy while others are clear.

“The goal is to explore the physical explanations behind the distinct appearances of these planets,” Brande said.

Brande and his co-authors took special note of regions where exoplanets tend to form clouds or hazes high up in their atmosphere. When such atmospheric aerosols are present, the KU researcher said hazes can block the light filtering through the atmosphere.

“If a planet has a cloud right above the surface with hundreds of kilometers of clear air above it, starlight can easily pass through the clear air and be absorbed only by the specific gases in that part of the atmosphere,” Brande said. “However, if the cloud is positioned very high, clouds are generally opaque across the electromagnetic spectrum. While hazes have spectral features, for our work, where we focus on a relatively narrow range with Hubble, they also produce mostly flat spectra.”

According to Brande, when these aerosols are present high in the atmosphere, there’s no clear path for light to filter through.

“With Hubble, the single gas we’re most sensitive to is water vapor,” he said. “If we observe water vapor in a planet’s atmosphere, that’s a good indication that there are no clouds high enough to block its absorption. Conversely, if water vapor is not observed and only a flat spectrum is seen, despite knowing that the planet should have an extended atmosphere, it suggests the likely presence of clouds or hazes at higher altitudes.”

Brande led the work of an international team of astronomers on the paper, including Crossfield at KU and collaborators from the Max Planck Institute in Heidelberg, Germany, a cohort led by Laura Kreidberg, and investigators at the University of Texas, Austin, led by Caroline Morley.

Brande and his co-authors approached their analysis differently than previous efforts by focusing on determining the physical parameters of the small-Neptune atmospheres. In contrast, previous analyses often involved fitting a single model spectrum to observations.

“Typically, researchers would take an atmospheric model with pre-computed water content, scale and shift it to match observed planets in their sample,” Brande said. “This approach indicates whether the spectrum is clear or cloudy but provides no information about the amount of water vapor or the location of clouds in the atmosphere.”

Instead, Brande employed a technique known as “atmospheric retrieval.”

“This involved modeling the atmosphere across various planet parameters such as water vapor quantity and cloud location, iterating through hundreds and thousands of simulations to find the best fit configuration,” he said. “Our retrievals gave us a best-fit model spectrum for each planet, from which we calculated how cloudy or clear the planet appeared to be. Then, we compared those measured clarities to a separate suite of models by Caroline Morley, which let us see that our results are in line with expectations for similar planets. In examining cloud and haze behavior, our models indicated that clouds were a better fit than hazes. The sedimentation efficiency parameter, reflecting cloud compactness, suggested observed planets had relatively low sedimentation efficiencies, resulting in fluffy clouds. These clouds, made up of particles like water droplets, remained lofted in the atmosphere due to their low settling tendency.”

Brande’s findings provide insights into the behavior of these planetary atmospheres and caused “substantial interest” when he presented them at a recent meeting of the American Astronomical Society.

Other findings

Moreover, Brande is part of an international observation program, led by Crossfield, that just announced findings of water vapor on GJ 9827d — a planet as hot as Venus 97 light-years from Earth in the constellation Pisces.

The observations, made with the Hubble Space Telescope, show the planet may be just one example of water-rich planets in the Milky Way. They were announced by a team led by Pierre-Alexis Roy of the Trottier Institute for Research on Exoplanets at Université de Montréal.

“We were searching for water vapor on the atmospheres of sub-Neptune-type planets,” Brande said. “Pierre-Alexis’ paper is the latest from that main effort because it took approximately 10 or 11 orbits or transits of the planet to make the water-vapor detection. Pierre-Alexis’ spectrum made it into our paper as one of our trend-data points, and we included all the planets from their proposal and others studied in the literature, making our results stronger. We were in close communication with them during the process of both papers to ensure we were using the proper updated results and accurately reflecting their findings.”

The patients from New Zealand, the Netherlands and the UK have hereditary angioedema, a genetic disorder characterised by severe, painful and unpredictable swelling attacks. These interfere with daily life and can affect airways and prove fatal.

Now researchers from the University of Auckland, Amsterdam University Medical Center and Cambridge University Hospitals have successfully treated more than ten patients with the CRISPR/Cas9 therapy, with interim results just published in a leading journal.

“It looks as if the single-dose treatment will provide a permanent cure for my hereditary angioedema patients’ very disabling symptoms,” says principal investigator Dr Hilary Longhurst, who is both a clinical immunologist at Auckland Hospital Te Toku Tumai and an honorary associate professor at the University of Auckland.

“Plus, of course, there is huge potential for development of similar CRISPR/Cas9 treatments for other genetic disorders.”

Globally, it is estimated one in 50,000 people have hereditary angioedema, however, because it is rare, it is often not correctly diagnosed.

In the phase one study, there were no serious or lasting side-effects from the single infusion, which took place over two to four hours under clinical supervision from late 2021 and onwards.

The investigational therapy, called NTLA-2002, utilises in vivo CRISPR/Cas9 technology to target the KLKB1 gene, which is responsible for producing plasma prekallikrein.

By editing this gene, the therapy reduces the levels of total plasma kallikrein, effectively preventing angioedema (swelling) attacks.

The trial, published in the New England Journal of Medicine, demonstrated dose-dependent reduction in total plasma kallikrein protein with reductions of up to 95 percent achieved.

A mean reduction of 95 percent in angioedema attacks was observed across all patients through to the latest follow-up.

The patients from the initial study will be followed up for a further 15 years to continue to assess long-term safety and efficacy.

A larger and more robust, double-blinded, placebo-controlled phase two trial is under way and a Phase 3 trial is planned to start in the second half of 2024.

Dr Danny Cohn, from the Department of Vascular Medicine at the Amsterdam University Medical Center says these promising results are a step forward for this group of patients.

“We’ve never been closer to the ultimate treatment goal of normalising hereditary angioedema patients’ lives and offering total control of the disease,” says Dr Cohn.

Dr Padmalal Gurugama, consultant in clinical immunology and allergy at Cambridge University Hospitals, UK says the gene editing therapy has the potential to significantly improve patients’ lives.

“Hereditary angioedema can cause patients severe swellings and intense pain which can be life-threatening as well as restricting normal activities, such as going to work or school.

“Because it is often misdiagnosed, many patients undergo unnecessary treatments and invasive procedures.”

The therapy affects only the patient and is not passed onto their children, who still have an even chance of inheriting the disorder.

The studies have been funded by US company Intellia Therapeutics, which chose New Zealand to lead the research as, at that time — late 2021, it had relatively fewer Covid-19 cases than other countries.

So far, the only approved CRISPR therapy, CASGEVY, is for sickle cell disease and beta thalassemia. However, CASGEVY is an ex vivo CRISPR therapy, where the cells are taken from the patient and edited outside of the body and then reinfused, whereas NTLA-2002 is an in vivo CRISPR therapy, where the targeted gene editing occurs directly within the body.

CRISPR technologies are being used to develop treatment for a wide range of diseases, such as genetic disease, cardiovascular disease, cancer and autoimmune diseases.

Findings from the study published in Nature Ecology & Evolution show tree seedlings planted next to the decoy smell solution were 20 times less likely to be eaten by animals.

“This is equivalent to the seedlings being surrounded by actual plants that are unpalatable to the herbivore. In most cases it does trick the animals into leaving the plants alone,” said PhD student Patrick Finnerty, the study’s lead author from the School of Life and Environmental Sciences Behavioural Ecology and Conservation Lab.

“Herbivores cause significant damage to valuable plants in ecological and economically sensitive areas worldwide, but killing the animals to protect the plants can be unethical,” he said.

“So, we created artificial odours that mimicked the smell of plant species they naturally avoid, and this gently nudged problematic herbivores away from areas we didn’t want them to be.

“Given that many herbivores use plant odour as their primary sense to forage, this method provides a new approach that could be used to help protect valued plants globally, either in conservation work or protecting agricultural crops.”

The experiment, conducted in Ku-ring-gai Chase National Park in Sydney, used the swamp wallaby as model herbivore. The researchers selected an unpalatable shrub in the citrus family, Boronia pinnata, and a palatable canopy species, Eucalyptus punctata, to test the concept.

The study compared using B. pinnata solution and the real plant and found both were equally successful at protecting eucalyptseedlings from being eaten by wallabies.

As part of his doctoral research, Mr Finnerty has also tested the method successfully with African elephants, but that fieldwork does not form part of this research paper.

Previous attempts to use repellent substances, such as chilli oil or motor oil, to control animal consumption of plants have inherent limitations, Mr Finnerty said.

“Animals tend to habituate to these unnatural cues and so deterrent effects are only temporary,” he said. “By contrast, by mimicking the smell of plants herbivore naturally encounter, and avoid in day-to-day foraging, our approach works with the natural motivators of these animals, with herbivores less likely to habituate to these smells.”

Researchers took this idea and used solutions that produce these undesired aromas.

“As a management tool to protect palatable plants, our technique offers many advantages over real plants as a repellent,” Mr Finnerty said. “Real plants compete for water and resources, which can outweigh protective effects in providing browsing refuge.

“Our approach should be transferable to any mammalian, or potentially invertebrate, herbivore that relies primarily on plant odour information to forage and could protect valued plants globally, such as threatened species.”

Current solutions to herbivore-related problems often involve costly and environmentally impactful measures such as lethal control or fencing.

The new research introduces an alternative low-cost, humane strategy based on understanding herbivores’ foraging cues, motivations and decisions.

“Plant browsing damage caused by mammalian herbivore populations like deer, elephants and wallabies is a growing global concern,” said senior study author Professor Clare McArthur.

“This damage is one of the greatest limiting factors in areas of post-fire recovery and revegetation, destroying more than half the seedlings in these areas. It also threatens endangered plants and causes billions of dollars of damage in forestry and agriculture globally.

“Current methods to protect plants are expensive and increasingly limited by concerns over animal welfare, so alternate approaches are needed.”

It is well known that obesity increases the risk of insulin resistance and type 2 diabetes. It is also well known that some people who gain weight suffer from the disease and others do not. The reasons for these differences are not clear, but they are related to the function of the adipose tissue rather than the amount of body fat.

The current study, published in the journal PNAS, is mainly based on experiments in mice, but the research indicates that the newly discovered mechanism also applies to humans.

Weight gain increases the breakdown of the structural protein collagen to make room for the growing fat cells within adipose tissue. Collagen is a natural building block in the body that provides strength to cartilage, muscles, and skin.

The breakdown of collagen is handled by macrophages, a type of white blood cell that is part of the immune system. Macrophages are involved in the destruction of invading bacteria, but they also engulf and digest damaged cells and debris such as degraded collagen in adipose tissue during weight gain.

The macrophage function is impaired in obesity

The collagen is fragmented by enzymatic degradation outside the fat cells, and the collagen fragments are then engulfed by macrophages for complete degradation. What this study shows and describes is how highly regulated this uptake of collagen fragments is.

And it is fast when it works properly. However, this function of macrophages was found to be deactivated in obesity and insulin resistance, leading to the accumulation of collagen fragments in adipose tissue.

While this has not been considered a problem until now, the study shows that collagen fragments are not just debris, but actively influence various cellular processes such as inflammation and cell division.

The process thus goes from maintaining normal adipose tissue function during weight gain, to becoming pathogenic in some cases. When samples of human macrophages were exposed to diabetes-like conditions, they also lost their ability to “clean up” collagen.

Identification and prevention

The study was carried out by a research team at the Sahlgrenska Academy, University of Gothenburg, led by Ingrid Wernstedt Asterholm, Professor in Physiology.

“When adipose tissue grows, macrophages help the remodel the tissue in a controlled way. Exactly why this mechanism is sometimes deactivated is difficult to say, but perhaps it happens when there is at a certain, genetically determined, degree of adiposity” she says.

“It is our hope that these results ultimately lead to new strategies for preventing or treating type 2 diabetes. It is also conceivable that certain collagen fragments could serve as measurable biological markers, for example to identify individuals at higher risk of developing type 2 diabetes.”

It’s an achievement with important implications for scientists studying the brain and working on treatments for a broad range of neurological and neurodevelopmental disorders, such as Alzheimer’s and Parkinson’s disease.

“This could be a hugely powerful model to help us understand how brain cells and parts of the brain communicate in humans,” says Su-Chun Zhang, professor of neuroscience and neurology at UW-Madison’s Waisman Center. “It could change the way we look at stem cell biology, neuroscience, and the pathogenesis of many neurological and psychiatric disorders.”

Printing methods have limited the success of previous attempts to print brain tissue, according to Zhang and Yuanwei Yan, a scientist in Zhang’s lab. The group behind the new 3D-printing process described their method today in the journal Cell Stem Cell.

Instead of using the traditional 3D-printing approach, stacking layers vertically, the researchers went horizontally. They situated brain cells, neurons grown from induced pluripotent stem cells, in a softer “bio-ink” gel than previous attempts had employed.

“The tissue still has enough structure to hold together but it is soft enough to allow the neurons to grow into each other and start talking to each other,” Zhang says.

The cells are laid next to each other like pencils laid next to each other on a tabletop.

“Our tissue stays relatively thin and this makes it easy for the neurons to get enough oxygen and enough nutrients from the growth media,” Yan says.

The results speak for themselves — which is to say, the cells can speak to each other. The printed cells reach through the medium to form connections inside each printed layer as well as across layers, forming networks comparable to human brains. The neurons communicate, send signals, interact with each other through neurotransmitters, and even form proper networks with support cells that were added to the printed tissue.

“We printed the cerebral cortex and the striatum and what we found was quite striking,” Zhang says. “Even when we printed different cells belonging to different parts of the brain, they were still able to talk to each other in a very special and specific way.”

The printing technique offers precision — control over the types and arrangement of cells — not found in brain organoids, miniature organs used to study brains. The organoids grow with less organization and control.

“Our lab is very special in that we are able to produce pretty much any type of neurons at any time. Then we can piece them together at almost any time and in whatever way we like,” Zhang says. “Because we can print the tissue by design, we can have a defined system to look at how our human brain network operates. We can look very specifically at how the nerve cells talk to each other under certain conditions because we can print exactly what we want.”

That specificity provides flexibility. The printed brain tissue could be used to study signaling between cells in Down syndrome, interactions between healthy tissue and neighboring tissue affected by Alzheimer’s, testing new drug candidates, or even watching the brain grow.

“In the past, we have often looked at one thing at a time, which means we often miss some critical components. Our brain operates in networks. We want to print brain tissue this way because cells do not operate by themselves. They talk to each other. This is how our brain works and it has to be studied all together like this to truly understand it,” Zhang says. “Our brain tissue could be used to study almost every major aspect of what many people at the Waisman Center are working on. It can be used to look at the molecular mechanisms underlying brain development, human development, developmental disabilities, neurodegenerative disorders, and more.”

The new printing technique should also be accessible to many labs. It does not require special bio-printing equipment or culturing methods to keep the tissue healthy, and can be studied in depth with microscopes, standard imaging techniques and electrodes already common in the field.

The researchers would like to explore the potential of specialization, though, further improving their bio-ink and refining their equipment to allow for specific orientations of cells within their printed tissue..

“Right now, our printer is a benchtop commercialized one,” Yan says. “We can make some specialized improvements to help us print specific types of brain tissue on-demand.”

This study was supported in part by NIH-NINDS (NS096282, NS076352, NS086604), NICHD (HD106197, HD090256), the National Medical Research Council of Singapore (MOH-000212, MOH-000207), Ministry of Education of Singapore (MOE2018-T2-2-103), Aligning Science Across Parkinson’s (ASAP-000301), the Bleser Family Foundation, and the Busta Foundation.

Due to this enormous data gap, researchers have been skeptical that recent AI advances can tell us much about human learning and development. An ideal test for demonstrating a connection would involve training an AI model, not on massive data from the web, but on only the input that a single child receives. What would the model be able to learn then?

A team of New York University researchers ran this exact experiment. They trained a multimodal AI system through the eyes and ears of a single child, using headcam video recordings from when the child was six months and through their second birthday. They examined if the AI model could learn words and concepts present in a child’s everyday experience.

Their findings, reported in the latest issue of the journal Science, showed that the model, or neural network, could, in fact, learn a substantial number of words and concepts using limited slices of what the child experienced. That is, the video only captured about 1% of the child’s waking hours, but that was sufficient for genuine language learning.

In this video, the researchers describe their work in greater detail.

“We show, for the first time, that a neural network trained on this developmentally realistic input from a single child can learn to link words to their visual counterparts,” says Wai Keen Vong, a research scientist at NYU’s Center for Data Science and the paper’s first author. “Our results demonstrate how recent algorithmic advances paired with one child’s naturalistic experience has the potential to reshape our understanding of early language and concept acquisition.”

“By using AI models to study the real language-learning problem faced by children, we can address classic debates about what ingredients children need to learn words — whether they need language-specific biases, innate knowledge, or just associative learning to get going,” adds Brenden Lake, an assistant professor in NYU’s Center for Data Science and Department of Psychology and the paper’s senior author. “It seems we can get more with just learning than commonly thought.”

Vong, Lake, and their NYU colleagues, Wentao Wang and Emin Orhan, analyzed a child’s learning process captured on first-person video — via a light, head-mounted camera — on a weekly basis beginning at six months and through 25 months, using more than 60 hours of footage. The footage contained approximately a quarter of a million word instances (i.e., the number of words communicated, many of them repeatedly) that are linked with video frames of what the child saw when those words were spoken and included a wide range of different activities across development, including mealtimes, reading books, and the child playing.

The NYU researchers then trained a multimodal neural network with two separate modules: one that takes in single video frames (the vision encoder) and another that takes in the transcribed child-directed speech (the language encoder). These two encoders were combined and trained using an algorithm called contrastive learning, which aims to learn useful input features and their cross-modal associations. For instance, when a parent says something in view of the child, it is likely that some of the words used are likely referring to something that the child can see, meaning comprehension is instilled by linking visual and linguistic cues.

“This provides the model a clue as to which words should be associated with which objects,” explains Vong. “Combining these cues is what enables contrastive learning to gradually determine which words belong with which visuals and to capture the learning of a child’s first words.”

After training the model, the researchers tested it using the same kinds of evaluations used to measure word learning in infants — presenting the model with the target word and an array of four different image options and asking it to select the image that matches the target word. Their results showed that the model was able to learn a substantial number of the words and concepts present in the child’s everyday experience. Furthermore, for some of the words the model learned, it could generalize them to very different visual instances than those seen at training, reflecting an aspect of generalization also seen in children when they are tested in the lab.

“These findings suggest that this aspect of word learning is feasible from the kind of naturalistic data that children receive while using relatively generic learning mechanisms such as those found in neural networks,” observes Lake.

The work was supported by the U.S. Department of Defense’s Defense Advanced Research Projects Agency (N6600119C4030) and the National Science Foundation (1922658). Participation of the child was approved by the parents and the methodology was approved by NYU’s Institutional Review Board.