Computers Math

Nearly half of all patients with brain metastasis experience cognitive impairment. Until now, it was thought that this was due to the physical presence of the tumour pressing on neural tissue. But this ‘mass effect’ hypothesis is flawed because there is often no relationship between the size of the tumour and its cognitive impact. Small tumours can cause significant changes, and large tumours can produce mild effects. Why is this?
The explanation may lie in the fact that brain metastasis hacks the brain’s activity, a study featured on Cancer Cell’s cover shows for the first time.
The authors, from the Spanish National Research Council (CSIC) and the Spanish National Cancer Research Centre (CNIO), have discovered that when cancer spreads (metastasises) in the brain, it changes the brain’s chemistry and disrupts neuronal communication — neurons communicate through electrical impulses generated and transmitted by biochemical changes in the cells and their surroundings.
In this study, the laboratories of Manuel Valiente (CNIO) and Liset Menéndez de La Prida (Cajal Institute CSIC) have collaborated within the EU-funded NanoBRIGHT project, aimed at developing new technologies for the study of the brain, and with the participation of other funding agencies such as MICINN, AECC, ERC, NIH and EMBO.
Demonstration with artificial intelligence
The researchers measured the electrical activity of the brains of mice with and without metastases and observed that the electrophysiological recordings of the two groups of animals with cancer were different from each other. To be sure that this difference was attributable to metastases, they turned to artificial intelligence. They trained an automatic algorithm with numerous electrophysiological recordings, and the model was indeed able to identify the presence of metastases. The system was even able to distinguish metastases from different primary tumours — skin, lung and breast cancer.
These results show that metastasis does indeed affect the brain’s electrical activity in a specific way, leaving clear and recognizable signatures. More

University of Oxford researchers have made a significant step towards realising miniature bio-integrated devices, capable of directly stimulating cells. The work has been published today in the journal Nature.
Small bio-integrated devices that can interact with and stimulate cells could have important therapeutic applications, including the delivery of targeted drug therapies and the acceleration of wound healing. However, such devices all need a power source to operate. To date, there has been no efficient means to provide power at the microscale level.
To address this, researchers fromthe University of Oxford’s Department of Chemistry have developed a miniature power source capable of altering the activity of cultured human nerve cells. Inspired by how electric eels generate electricity, the device uses internal ion gradients to generate energy.
The miniaturized soft power source is produced by depositing a chain of five nanolitre-sized droplets of a conductive hydrogel (a 3D network of polymer chains containing a large quantity of absorbed water). Each droplet has a different composition so that a salt concentration gradient is created across the chain. The droplets are separated from their neighbours by lipid bilayers, which provide mechanical support while preventing ions from flowing between the droplets.
The power source is turned on by cooling the structure to 4°C and changing the surrounding medium: this disrupts the lipid bilayers and causes the droplets to form a continuous hydrogel. This allows the ions to move through the conductive hydrogel, from the high-salt droplets at the two ends to the low-salt droplet in the middle. By connecting the end droplets to electrodes, the energy released from the ion gradients is transformed into electricity, enabling the hydrogel structure to act as a power source for external components.
In the study, the activated droplet power source produced a current which persisted for over 30 minutes. The maximum output power of a unit made of 50 nanolitre droplets was around 65 nanowatts (nW). The devices produced a similar amount of current after being stored for 36 hours.
The research team then demonstrated how living cells could be attached to one end of the device so that their activity could be directly regulated by the ionic current. The team attached the device to droplets containing human neural progenitor cells, which had been stained with a fluorescent dye to indicate their activity. When the power source was turned on, time-lapse recording demonstrated waves of intercellular calcium signalling* in the neurons, induced by the local ionic current. More

Quantum physics has allowed for the creation of sensors far surpassing the precision of classical devices. Now, several studies in Nature show that the precision of these quantum sensors can be significantly improved using entanglement produced by finite-range interactions. Innsbruck researchers led by Christian Roos were able to demonstrate this enhancement using entangled ion-chains with up to 51 particles.
Metrological institutions around the world administer our time, using atomic clocks based on the natural oscillations of atoms. These clocks, pivotal for applications like satellite navigation or data transfer, have recently been improved by using ever higher oscillation frequencies in optical atomic clocks. Now, scientists at the University of Innsbruck and the Institute of Quantum Optics and Quantum Information (IQOQI) of the Austrian Academy of Sciences led by Christian Roos show how a particular way of creating entanglement can be used to further improve the accuracy of measurements integral to an optical atomic clock’s function.
Measurement error halved in experiment
Observations of quantum systems are always subject to a certain statistical uncertainty. “This is due to the nature of the quantum world,” explains Johannes Franke from Christian Roos’ team. “Entanglement can help us reduce these errors.” With the support of theorist Ana Maria Rey from JILA in Boulder, USA, the Innsbruck physicists tested the measurement accuracy on an entangled ensemble of particles in the laboratory. The researchers used lasers to tune the interaction of ions lined up in a vacuum chamber and entangled them. “The interaction between neighboring particles decreases with the distance between the particles. Therefore, we used spin-exchange interactions to allow the system to behave more collectively,” explains Raphael Kaubrügger from the Department of Theoretical Physics at the University of Innsbruck. Thus, all particles in the chain were entangled with each other and produced a so-called squeezed quantum state. Using this, the physicists were able to show that measurement errors can be roughly halved by entangling 51 ions in relation to individual particles. Previously, entanglement-enhanced sensing mainly relied on infinite interactions, limiting its applicability to only certain quantum platforms.
Even more accurate clocks
With their experiments, the Innsbruck quantum physicists were able to show that quantum entanglement makes sensors even more sensitive. “We used an optical transition in our experiments that is also employed in atomic clocks,” says Christian Roos. This technology could improve areas where atomic clocks are currently used, such as satellite-based navigation or data transfer. Moreover, these advanced clocks could open new possibilities in pursuits like the search for dark matter or the determination of time-variations of fundamental constants.
Christian Roos and his team now want to test the new method in two-dimensional ion ensembles. The current results were published in the journal Nature. In the same issue, researchers published very similar results using neutral atoms. The research in Innsbruck was financially supported by the Austrian Science Fund FWF and the Federation of Austrian Industries Tyrol, among others. More

A team of researchers from Yale University and other institutions globally has developed an innovative patient triage platform powered by artificial intelligence (AI) that the researchers say is capable of predicting patient disease severity and length of hospitalization during a viral outbreak.
The platform, which leverages machine learning and metabolomics data, is intended to improve patient management and help health care providers allocate resources more efficiently during severe viral outbreaks that can quickly overwhelm local health care systems. Metabolomics is the study of small molecules related to cell metabolism.
“Being able to predict which patients can be sent home and those possibly needing intensive care unit admission is critical for health officials seeking to optimize patient health outcomes and use hospital resources most efficiently during an outbreak,” said senior author Vasilis Vasiliou, a professor of epidemiology at Yale School of Public Health (YSPH).The researchers developed the platform using COVID-19 as a disease model. The findings were published online in the journal Human Genomics.
The platform integrates routine clinical data, patient comorbidity information, and untargeted plasma metabolomics data to drive its predictions.
“Our AI-powered patient triage platform is distinct from typical COVID-19 AI prediction models,” said Georgia Charkoftaki, a lead author of the study and an associate research scientist in the Department of Environmental Health Sciences at YSPH. “It serves as the cornerstone for a proactive and methodical approach to addressing upcoming viral outbreaks.”
Using machine learning, the researchers built a model of COVID-19 severity and prediction of hospitalization based on clinical data and metabolic profiles collected from patients hospitalized with the disease. “The model led us to identify a panel of unique clinical and metabolic biomarkers that were highly indicative of disease progression and allows the prediction of patient management needs very soon after hospitalization,” the researchers wrote in the study.
For the study, the research team collected comprehensive data from 111 COVID-19 patients admitted to Yale New Haven Hospital during a two-month period in 2020 and 342 healthy individuals (health care workers) who served as controls. The patients were categorized into different classes based on their treatment needs, ranging from not requiring external oxygen to requiring positive airway pressure or intubation. More

Recently, a Korean company donated a wearable robot, designed to aid patients with limited mobility during their rehabilitation, to a hospital. These patients wear this robot to receive assistance for muscle and joint exercises while performing actions such as walking or sitting. Wearable devices including smartwatches or eyewear that people wear and attached to their skin have the potential to enhance our quality of life, offering a glimmer of hope to some people much like this robotic innovation.
The strain sensors used in these rehabilitative robots analyze data by translating specific physical changes in specific regions into electric signals. Notably flexible, these sensors are pliable and adept at gauging even the most subtle bodily changes as they are made from lightweight materials for ease of attachment to the skin. However, conventional soft strain sensors often exhibit inadequate durability due to susceptibility to external factors such as temperature and humidity. Furthermore, their complicated fabrication process poses challenges for widespread commercialization.
A research team led by Professor Sung-Min Park from the Department of Convergence IT Engineering and the Department of Mechanical Engineering and PhD candidate Sunguk Hong from the Department of Mechanical Engineering at Pohang University of Science and Technology (POSTECH) has successfully overcome the limitations of these soft strain sensors by integrating computer vision technology into optical sensors. Their research findings were featured in npj Flexible Electronics.
The research team developed a sensor technology known as computer vision-based optical strain (CVOS) during their study. Unlike conventional sensors reliant on electrical signals, CVOS sensors employ computer vision and optical sensors to analyze microscale optical patterns, extracting data regarding changes. This approach inherently enhances durability by eliminating elements that compromise sensor functionalities and streamlining fabrication processes, thereby facilitating sensor commercialization.
In contrast to conventional sensors that solely detect biaxial strain, CVOS sensors exhibit the exceptional ability to detect three-axial rotational movements through real-time multiaxial strain mapping. In essence, these sensors enable the precise recognition of intricate and various bodily motions through a single sensor. The research team substantiated this claim through experiments applying CVOS sensors to assistive devices in rehabilitative treatments.
Through integration of an AI-based response correction algorithm that corrects diverse error factors arising during signal detection, the experiment results showed a high level of confidence. Even after undergoing more than 10,000 iterations, these sensors consistently maintained their exceptional performance.
Professor Sung-Min Park who led the research explained, “The CVOS sensors excel in distinguishing body movements across diverse direction and angles, thereby optimizing effective rehabilitative interventions.” He further added, “By tailoring design indicators and algorithms to align with specific objectives, CVOS sensors have boundless potential for applications spanning industries.” More

The Empa spin-off BTRY wants to revolutionize rechargeable batteries: Their thin-film batteries are not only safer and longer-lasting than conventional lithium-ion batteries, they are also much more environmentally friendly to manufacture and can be charged and discharged in just one minute. For now, the battery is very small, but the founders have big plans for it.
Lithium-ion batteries are everywhere: from smartphones and laptops to cars and even satellites. It is currently our most mature battery technology. Yet it is not ideal for many applications. Lithium-ion batteries lose capacity with every charge and discharge cycle, charge relatively slowly and only work well in a narrow temperature range.
According to Empa researchers Abdessalem Aribia and Moritz Futscher from Empa’s Thin Films and Photovoltaics laboratory, it is time to rethink battery technology. Compared to other existing or developing technologies, their lithium metal-based solid-state battery brings some significant advantages: It can be charged and discharged within one minute, lasts about ten times as long as a lithium-ion battery, and is insensitive to temperature fluctuations.
In addition, unlike lithium-ion batteries, it is not flammable — a major advantage, because today’s rechargeable batteries are considered hazardous materials. Incorrect handling or damage to a conventional lithium-ion cell can lead to a fire that releases toxic gases and is extremely difficult to extinguish. “By contrast, if you cut our battery with scissors,” Aribia says, “you will simply get two batteries that are half as good.”
Aribia and Futscher now want to bring this promising technology to market. Together with lab head Yaroslav Romanyuk, they have founded a spin-off called BTRY (pronounced “battery”). Aribia, who takes on the role of CTO at BTRY, had never previously thought of starting his own company. CEO Moritz Futscher, on the other hand, has been interested in startups since he was a student. The two researchers have been working together on the battery project for years and are a well-established team. “We are convinced that our product can offer real added value,” says Futscher.
High-precision manufacturing
The new battery is a so-called thin-film solid-state battery. The technology itself is not new: Such batteries have been known since the 1980s. However, due to the very low mass of their thin-film components — the entire cell is only a few micrometers thick — they have been able to store very little energy so far. Futscher and Aribia have succeeded in stacking the thin-film cells on top of each other, increasing their capacity. More

Does hot water freeze faster than cold water? Aristotle may have been the first to tackle this question that later became known as the Mpemba effect.
This phenomenon originally referred to the non-monotonic initial temperature dependence of the freezing start time, but it has been observed in various systems — including colloids — and has also become known as a mysterious relaxation phenomenon that depends on initial conditions.
However, very few have previously investigated the effect in quantum systems.
Now, a team of researchers from Kyoto University and the Tokyo University of Agriculture and Technology has shown that the temperature quantum Mpemba effect can be realized over a wide range of initial conditions.
“The quantum Mpemba effect bears the memory of initial conditions that result in anomalous thermal relaxation at later times,” explains project leader and co-author Hisao Hayakawa at KyotoU’s Yukawa Institute for Theoretical Physics.
Hayakawa’s team prepared two systems with quantum dots connected to a heat bath, one with a current flowing and the other in an equilibrium state. Both were quenched to a low-temperature equilibrium state, allowing the team to follow their time evolution toward a steady state regarding the density matrix, energy, entropy, and — most critically — temperature.
“When the two copies crossed each other before reaching the same equilibrium state — so that the hotter part became colder and vice versa in an identity reversal — we knew we had achieved the thermal quantum Mpemba effect,” says co-author Satoshi Takada of TUAT.
“After analyzing the quantum master equation, we also discovered we had obtained the thermal quantum Mpemba effect in a wide range of parameters, including reservoir temperatures and chemical potentials,” adds first and corresponding author Amit Kumar Chatterjee, also of KyotoU.
“Our results encourage us to explore the potential use of the quantum Mpemba effect in future applications beyond thermal analyses,” reflects Hayakawa. More

Countries like Japan are experiencing declining birth rates and an aging population. The increased burden of care for this aging population may lead to a shortage of caregivers in a decade’s time. Thus, the recruitment and allocation of resources must be planned in advance. Technological interventions in the form of robots that provide home care services to the aged appear to be a promising solution to this problem.
Although care robots are being developed and improved at a rapid pace, their social acceptance has been limited. It is suspected that the ethical issues surrounding the use of such robots may be obstructing the implementation of this technology. Many acceptance models have demonstrated that the ethical perceptions of older people, their families, and professional caregivers regarding care robots can impact their willingness to adopt this technology. However, there is no universal model that can elucidate the relationship between ethical perceptions and the willingness to use care robots across countries and cultural contexts.
To fill this knowledge gap, a team of international researchers led by Professor Sayuri Suwa from Chiba University, including Dr. Hiroo Ide from the University of Tokyo, Dr. Yumi Akuta from Tokyo Healthcare University, Dr. Naonori Kodate from University College Dublin, Dr. Jaakko Hallila from Seinäjoki University of Applied Sciences, and Dr. Wenwei Yu from Chiba University, among others, conducted a cross-sectional study across Japan, Ireland, and Finland. The findings of their study were made available online on July 25, 2023, and will be published in January 2024 in Volume 116 of the journal Archives of Gerontology and Geriatrics.
Sharing the motivation behind the study, Prof. Suwa explains, “Today, in Japan’s super-aged society, various care robots, including monitoring cameras, have been developed and marketed to compensate for the shortage of care staff and to alleviate their stress. However, there are no discussions among users — older people, family caregivers, and care staff — and developers regarding the willingness to use care robots, the protection of privacy, and the appropriate use of personal information associated with the use of care robots. The desire to improve this situation and to promote appropriate utilization of care robots beyond Japan was the impetus for this research.”
The team developed a questionnaire that examined the ethical issues that could affect the willingness to use a care robot across the three countries. The survey was conducted between November 2018 and February 2019 among older people, their family caregivers, and professional caregivers. This study was also reviewed by multiple ethical committees in all three countries. The researchers analyzed a total of 1,132 responses, which comprised 664 responses from Japan, 208 from Ireland, and 260 from Finland. They found that the willingness to use care robots was highest in Japan (77.1%), followed by Ireland (70.3%), and was lowest in Finland (52.8%).
Next, the researchers developed a conceptual model and evaluated it using statistical methods. From the questionnaire, the researchers included responses to ten items in the model, categorized into four broad domains — acquisition of personal information, use of personal information for medical and long-term care, secondary use of personal information, and participation in research and development. They then improved the model using Akaike’s information criterion (AIC). The model underwent incremental improvements to attain better (smaller) AIC values. The final model was then applied to each country.
Thus, this study demonstrated the successful use of a single universal model that could explain the correlation between ethical perceptions and social implementation of care robots across three countries with different geographies, demographics, cultures, and systems.
Discussing the importance and long-term impact of their study, Prof. Suwa concludes, “From our results, we can infer that social implementation of care robots can be promoted if developers and researchers encourage potential users to participate in the development process, proposed in the form of a co-design and co-production concept. We hope that the process of developing care robots will be improved to contribute to human well-being in a global aging society.” More