In Greek, apnea (ἄπνοια) denotes the “absence of breathing.” Hence, obstructive sleep apnea is a disease defined by interruptions in breathing, which recurs while the person suffering from it is asleep. A feeling of breathlessness, fatigue and drowsiness are symptoms that patients suffer. This disease is also related to the incidence of cardiovascular disorders, so to deal with these related problems, adequate diagnosis of the severity of the disease is necessary.

Alterations in the metabolism of people with sleep apnea are key to determining the severity of the disease. These changes are usually analyzed in blood or urine. However, in search of a less invasive and more accessible alternative, a team from the Department of Analytical Chemistry at the University of Córdoba and the Maimonides Institute for Biomedical Research in Córdoba (IMIBIC), formed by researchers Laura Castillo, Mónica Calderón, Feliciano Priego and Bernabé Jurado, has verified, for the first time, the potential of sweat samples to ascertain the severity of sleep apnea.

“By analyzing sweat metabolome and its alterations, mainly at night, we were able to see what stage of the disease the patients were in,” explains Laura Castillo, the study’s lead author. For her, the advantages of using sweat over other samples are clear: “it is a non-invasive and clean sample since, unlike the case with blood, we don’t have to remove proteins, and it’s much easier to analyze and detect metabolites.”

In this study, sweat samples from before and after sleep were analyzed from a series of individuals with sleep apnea at different stages, as well as from a control group without the disease.

In these samples, using the gas chromatography technique, coupled with high-resolution mass spectrometry, 78 metabolites were identified and their changes were studied, mostly related to energy production and oxidative stress. “We could see how the sweat metabolism itself indicates those alterations during sleep as a result of which the person’s energy production worsens and their oxidative stress increases,” says Castillo. Thus, with a personalized follow-up using the sweat excreted during the sleep of a person with the disease, its development can be tracked, and its possible effects, such as cardiovascular problems, can be monitored. This metabolomic profile also made it possible, in the trial, to distinguish between those who suffered from the disease and those who did not have it and belonged to the control group.

An index to learn more about the disease

In addition to establishing sweat as a good sentinel when it comes to determining the stage of the disease, this work also reveals the importance of taking into account the oxygen desaturation index when diagnosing it.

The diagnosis of sleep apnea is currently based on the Apnea-Hypopnea Index (AHI), which measures sleep apnea based on the episodes of shortness of breath one suffers per hour (for example, the disease is severe when one has 30 or more episodes per hour). According to the team, this index “does not provide all the information about the disease or the patient’s situation at a given time” since it counts how many events there are, but not their severity.

Therefore, in their study they also verify the importance of using the oxygen desaturation index, which shows how serious the episodes are by measuring the number of events in which oxygen saturation has decreased by more than 3%. After verifying the linear relationship between this index and the AHI, its validity has been confirmed, since, in addition to the data provided by the AHI, it also measures severity, taking into account oxygen saturation loss.

Details of their breakthrough were published in the journal Acta Materialia on November 17, 2024.

Hydrogen is carbon dioxide free, and it has long been touted as a source of clean energy. Yet, shifting society towards a hydrogen energy-based one requires overcoming some significant technical issues. Structural and functional materials that produce, store, transport and preserve hydrogen are needed.

To develop advanced materials for hydrogen-related applications, a fundamental understanding of how hydrogen behaves in alloys is crucial. However, current technology falls short in this area. Detecting atomic state hydrogen — the smallest atom in the universe — with X-rays or lasers is challenging due to its unique characteristics. Researchers are currently focusing on better analytical and visualization techniques that can incorporate high spatial and time resolutions simultaneously.

Hiroshi Kakinuma, an assistant professor at Tohoku University, and his co-authors developed a new visualization technique harnessing an optical microscope and polyaniline layer. “When the color of the polyaniline layer reacts with the atomic state hydrogen in metals, it changes colors, allowing us to analyze the flow of hydrogen atoms based on the color distribution of the polyaniline layer,” points out Kakinuma. “Additionally, optical microscopes can observe the sub-millimeter-scale view with microscale spatial resolution in real time, thereby capturing hydrogen behavior with unprecedented high spatial and time resolutions.”

Thanks to this method, the researchers successfully filmed the flow of hydrogen atoms in pure nickel (Ni). The color of polyaniline changed from purple to white when reacting with hydrogen atoms in a metal. In situ visualization revealed that hydrogen atoms in pure Ni preferentially diffused through grain boundaries in disordered Ni atoms.

Furthermore, the group found that hydrogen diffusion was dependent on the geometrical structure of the grain boundaries: the hydrogen flux grew at grain boundaries with large geometric spaces. These results experimentally clarified the relationship between the atomic-scale structure of pure Ni and the hydrogen diffusion behavior.

The approach has broader applications as well. It can be applied to other metals and alloys, such as steels and aluminum alloys, and drastically facilitates elucidating the microscopic hydrogen-material interactions, which could be further investigated through simulations.

“Understanding hydrogen behaviors related to the atomic-scale structure of alloys will enable efficient alloy design, which will dramatically accelerate the development of highly functional materials and usher us one step closer to a hydrogen energy-based society,” adds Kakinuma.

Our ability to process verbal language is not based solely on semantics, i.e. the meaning and combination of linguistic units. Other parameters come into play, such as prosody, which includes pauses, accentuation and intonation. Affective bursts — ”Aaaah!” or ”Oh!” for example — are also part of this, and we share these with our primate cousins. They contribute to the meaning and understanding of our vocal communications.

When such a vocal message is emitted, these sounds are processed by the frontal and orbitofrontal regions of our brain. The function of these two areas is, among other things, to integrate sensory and contextual information leading to a decision. Are they activated in the same way when we are exposed to the emotional vocalisations of our close cousins the chimpanzees, macaques and bonobos? Are we able to differentiate between them?

MRI scans with headphones on

A UNIGE team sought to find out by exposing a group of 25 volunteers to various human and simian vocalisations. ”The participants were placed in an MRI scanner and were given headphones. After a short period of familiarisation with the different types of vocalisations, each participant had to categorise them, i.e. identify to which species they belonged,” explains Leonardo Ceravolo, senior lecturer at the UNIGE’s Faculty of Psychology and Educational Sciences, and first author of the study.

These vocalisations were of the affiliative type, i.e. linked to a positive interaction, or of the agonistic type, i.e. linked to a threat or distress. The human vocalisations came from databases recorded by actors. The simian ones came from field recordings made as part of previous research. This study is the first of its kind to include bonobo vocalisations.

Bonobos, not so close cousins

The results show that for macaque and chimpanzee vocalisations, the frontal and orbitofrontal regions of the participants were activated in a similar way to human vocalisations. The participants were able to differentiate between them easily. On the other hand, when confronted with the ”sounds” of bonobos, also close cousins of humans, the involved cerebral areas were much less activated, and categorisation was at chance level.

”It was thought that kinship between species — the ‘phylogenetic distance’ — was the main parameter for having the ability, or not, to recognise these different vocalisations. We thought that the closer we were genetically, the more important this ability was,” explains Didier Grandjean, full professor at the Swiss Center for Affective Sciences and at the UNIGE’s Faculty of Psychology and Educational Sciences, who led the study. ”Our results show that a second parameter comes into play: acoustic distance. The further the dynamics of the acoustic parameters, such as the frequencies used, are from those of humans, the less certain frontal regions are activated. We then lose the ability to recognise these sounds, even if they are emitted by a close cousin, in this case the bonobo.”

Bonobo calls are very high-pitched and can sound like those of certain birds. This acoustic distance in terms of frequencies, compared with human vocalisations, explains our inability to decode them, despite our close phylogenetic proximity. ”Are we capable of identifying the different emotional aspects of affiliative or agonistic vocalisations emitted by a chimpanzee, a macaque or a bonobo? And if so, how? Thiese questions will be at the heart of our next research, which will involve analysing not our ability to categorise vocalisations by species but to identify their emotional content,” concludes Didier Grandjean.

Now, researchers say they’ve solved the mystery. Using CT scanning technology, Steven Manchester, curator of paleobotany at the Florida Museum of Natural History, created 3D reconstructions of the original fossil specimens and others collected since. He showed these to a colleague, who noticed something odd about the five triangular seeds inside.

“When I showed him the 3D images, he said “those aren’t seeds. Those are pyrenes,” Manchester recalled of his conversation with courtesy curator of botany at the Florida Museum, Walter Judd.

Pyrenes are woody dispersal pods that give seeds an extra layer of protection. Examples include the hard stones at the cores of cherries, peaches, dates and pistachios, which prevent the seeds from being digested along with the rest of the fruit.

Distinguishing a seed from a pyrene, especially when they’re the size of snowflakes, requires close scrutiny. Traditional methods of paleobotany, which involve incrementally dissolving fossils in acid and observing each new layer under a microscope, had proven insufficient.

“If we had specimens that fractured at just the right plane, I would have been able to recognize them, but with the material we had on hand, I couldn’t tell,” Manchester said.

There are only a few plant groups that produce pyrenes, fewer still with fruits that contain five seeds arranged in a pentagram. Through a process of elimination, Manchester and Judd determined the fossils belonged to an extinct species in Burseraceae, the Frankincense family.

Fossilized wood, leaves, fruits and flowers from this family have been found elsewhere in India, often sandwiched between thick slabs of basalt created by one of the largest volcanic eruptions in Earth’s history.

At the time, India was an island off the southeast coast of Africa. India’s continental plate was slowly inching toward Europe and Asia, and as it rafted past Madagascar, it broke the seal on a thin layer of Earth’s crust. Rivers of liquid rock poured onto a landscape the size of California and Texas combined. The eruptions occurred intermittently for nearly a million years, and they repeatedly killed any vegetation that grew during the interludes.

“The fossils were preserved at times of quiet between the eruptions,” Manchester said. “Ponds and lakes formed on the relatively fresh lava flows, and vegetation, including wood and seeds, were washed into them and covered by sediment.”

The shield volcano responsible for the destruction was active just before and after the asteroid impact that drew the curtains on the Cretaceous, and both are thought to have contributed to the extinctions that followed.

Most fossils from the Frankincense family have, up until now, been recovered from rocks that postdate the asteroid impact. The original fruits discovered in the 1970s were fossilized before that event. This makes them the oldest Burseraceae fossils discovered to date, which has important implications for the family’s origin. Scientists have a good idea of when plants in the group initially evolved, but it’s still unclear where they came from.

Ancient species of Burseraceae are a common component of fossil beds in southern England, the Czech Republic and parts of North America. Beginning roughly 50 million years ago, however, Earth’s climate began a long cooling process that ultimately resulted in the most recent Ice Ages. As temperatures fell, species in the Frankincense family seemed to reverse their preference for hemispheres. Today, there are more than 700 Burseraceae species, and most of them grow south of the equator.

The ancestors of modern Burseraceae species are thought to have first appeared somewhere in the north. Alternatively, a few early species may have had a global distribution but became isolated as continents drifted apart.

The fossils from India suggest the southern hemisphere may have been the real birthplace of the family.

“It could be that we just don’t have rocks of the right age in Europe to indicate that they were there, but this shows that we can’t dismiss the southern hemisphere as a point of origin,” Manchester said.

In the race towards developing Artificial General Intelligence (AGI), with influential entities like OpenAI and Google DeepMind leading the way, understanding and replicating human-like intelligence has become an important research interest. Central to these technological advancements is the Transformer model, whose fundamental principles are now being explored in new depth.

The key to powerful AI systems is grasping how they learn and remember information. The team applied principles of human brain learning, specifically concentrating on memory consolidation through the NMDA receptor in the hippocampus, to AI models.

The NMDA receptor is like a smart door in your brain that facilitates learning and memory formation. When a brain chemical called glutamate is present, the nerve cell undergoes excitation. On the other hand, a magnesium ion acts as a small gatekeeper blocking the door. Only when this ionic gatekeeper steps aside, substances are allowed to flow into the cell. This is the process that allows the brain to create and keep memories, and the gatekeeper’s (the magnesium ion) role in the whole process is quite specific.

The team made a fascinating discovery: the Transformer model seems to use a gatekeeping process similar to the brain’s NMDA receptor. This revelation led the researchers to investigate if the Transformer’s memory consolidation can be controlled by a mechanism similar to the NMDA receptor’s gating process.

In the animal brain, a low magnesium level is known to weaken memory function. The researchers found that long-term memory in Transformer can be improved by mimicking the NMDA receptor. Just like in the brain, where changing magnesium levels affect memory strength, tweaking the Transformer’s parameters to reflect the gating action of the NMDA receptor led to enhanced memory in the AI model. This breakthrough finding suggests that how AI models learn can be explained with established knowledge in neuroscience.

C. Justin LEE, who is a neuroscientist director at the institute, said, “This research makes a crucial step in advancing AI and neuroscience. It allows us to delve deeper into the brain’s operating principles and develop more advanced AI systems based on these insights.”

CHA Meeyoung, who is a data scientist in the team and at KAIST, notes, “The human brain is remarkable in how it operates with minimal energy, unlike the large AI models that need immense resources. Our work opens up new possibilities for low-cost, high-performance AI systems that learn and remember information like humans.”

What sets this study apart is its initiative to incorporate brain-inspired nonlinearity into an AI construct, signifying a significant advancement in simulating human-like memory consolidation. The convergence of human cognitive mechanisms and AI design not only holds promise for creating low-cost, high-performance AI systems but also provides valuable insights into the workings of the brain through AI models.

The idea of a runaway of the greenhouse effect is not new. In this scenario, a planet can evolve from a temperate state like on Earth to a true hell, with surface temperatures above 1000°C. The cause? Water vapor, a natural greenhouse gas. Water vapor prevents the solar irradiation absorbed by Earth to be reemitted towards the void of space, as thermal radiation. It traps heat a bit like a rescue blanket. A dash of greenhouse effect is useful — without it, Earth would have an average temperature below the freezing point of water, looking like a ball covered with ice and hostile to life.

On the opposite, too much greenhouse effect increases the evaporation of oceans, and thus the amount of water vapor in the atmosphere. “There is a critical threshold for this amount of water vapor, beyond which the planet cannot cool down anymore. From there, everything gets carried away until the oceans end up getting fully evaporated and the temperature reaches several hundred degrees,” explains Guillaume Chaverot, former postdoctoral scholar in the Department of Astronomy at the UNIGE Faculty of Science and main author of the study.

World premiere

“Until now, other key studies in climatology have focused solely on either the temperate state before the runaway, or either the inhabitable state post-runaway,” reveals Martin Turbet, researcher at CNRS laboratories of Paris and Bordeaux, and co-author of the study. “It is the first time a team has studied the transition itself with a 3D global climate model, and has checked how the climate and the atmosphere evolve during that process.”

One of the key points of the study describes the appearance of a very peculiar cloud pattern, increasing the runaway effect, and making the process irreversible. “From the start of the transition, we can observe some very dense clouds developing in the high atmosphere. Actually, the latter does not display anymore the temperature inversion characteristic of the Earth atmosphere and separating its two main layers: the troposphere and the stratosphere. The structure of the atmosphere is deeply altered,” points out Guillaume Chaverot.

Serious consequences for the search of life elsewhere

This discovery is a key feature for the study of climate on other planets, and in particular on exoplanets — planets orbiting other stars than the Sun. “By studying the climate on other planets, one of our strongest motivations is to determine their potential to host life,” indicates Émeline Bolmont, assistant professor and director of the UNIGE Life in the Universe Center (LUC), and co-author of the study.

The LUC leads state-of-the-art interdisciplinary research projects regarding the origins of life on Earth, and the quest for life elsewhere in our solar system and beyond, in exoplanetary systems. “After the previous studies, we suspected already the existence of a water vapor threshold, but the appearance of this cloud pattern is a real surprise!” discloses Émeline Bolmont. “We have also studied in parallel how this cloud pattern could create a specific signature, or ”fingerprint”, detectable when observing exoplanet atmospheres. The upcoming generation of instruments should be able to detect it,” unveils Martin Turbet. The team is also not aiming to stop there, Guillaume Chaverot having received a research grant to continue this study at the “Institut de Planétologie et d’Astrophysique de Grenoble” (IPAG). This new step of the research project will focus on the specific case of the Earth.

A planet Earth in a fragile equilibrium

With their new climate models, the scientists have calculated that a very small increase of the solar irradiation — leading to an increase of the global Earth temperature, of only a few tens of degrees — would be enough to trigger this irreversible runaway process on Earth and make our planet as inhospitable as Venus. One of the current climate goals is to limit global warming on Earth, induced by greenhouse gases, to only 1.5 degrees by 2050. One of the questions of Guillaume Chaverot’s research grant is to determine if greenhouse gases can trigger the runaway process as a slight increase of the Sun luminosity might do. If so, the next question will be to determine if the treshold temperatures are the same for both processes.

The Earth is thus not so far from this apocalyptical scenario. “Assuming this runaway process would be started on Earth, an evaporation of only 10 meters of the oceans’ surface would lead to a 1 bar increase of the atmospheric pressure at ground level. In just a few hundred years, we would reach a ground temperature of over 500°C. Later, we would even reach 273 bars of surface pressure and over 1 500°C, when all of the oceans would end up totally evaporated,” concludes Guillaume Chaverot.