Researchers in Budapest have been studying worms to slow down or stop ageing in humans by researching transposable elements in our DNA.
Researchers discovered that bismuth atoms embedded in calcium oxide can function as qubits for quantum computers, providing a low-noise, durable, and inexpensive alternative to current materials. This groundbreaking study highlights its potential to transform quantum computing and telecommunications.
Calcium oxide is an inexpensive, chalky chemical compound frequently used in the manufacturing of cement, plaster, paper, and steel. However, the common material may soon have a more high-tech application.
Scientists used theoretical and computational approaches to discover how tiny, lone atoms of bismuth embedded within solid calcium oxide can act as qubits — the building blocks of quantum computers and quantum communication devices. These qubits were described by University of Chicago Pritzker School of Molecular Engineering researchers and their collaborator in Sweden on June 6 in the scientific journal Nature Communications.
One of the main scientific objectives of next-generation observatories (like the James Webb Space Telescope) has been to observe the first galaxies in the Universe – those that existed at Cosmic Dawn. This period is when the first stars, galaxies, and black holes in our Universe formed, roughly 50 million to 1 billion years after the Big Bang. By examining how these galaxies formed and evolved during the earliest cosmological periods, astronomers will have a complete picture of how the Universe has changed with time.
As addressed in previous articles, the results of Webb’s most distant observations have turned up a few surprises. In addition to revealing that galaxies formed rapidly in the early Universe, astronomers also noticed these galaxies had particularly massive supermassive black holes (SMBH) at their centers. This was particularly confounding since, according to conventional models, these galaxies and black holes didn’t have enough time to form. In a recent study, a team led by Penn State astronomers has developed a model that could explain how SMBHs grew so quickly in the early Universe.
The research team was led by W. Niel Brandt, the Eberly Family Chair Professor of Astronomy and Astrophysics at Penn State’s Eberly College of Science. Their research is described in two papers presented at the 244th meeting of the American Astronomical Society (AAS224), which took place from June 9th to June 13th in Madison, Wisconsin. Their first paper, “Mapping the Growth of Supermassive Black Holes as a Function of Galaxy Stellar Mass and Redshift,” appeared on March 29th in The Astrophysical Journal, while the second is pending publication. Fan Zou, an Eberly College graduate student, was the lead author of both papers.
Today I’m thrilled to announce BrainBridge, the world’s first concept for a head transplant system, which integrates advanced robotics and artificial intelligence to execute complete head and face transplantation procedures. This state-of-the-art system offers new hope to patients suffering from untreatable conditions such as stage-4 cancer, paralysis, and neurodegenerative diseases like Alzheimer’s and Parkinson’s.
Official website: https://brainbridge.tech/
Follow me everywhere: https://muse.io/hashemalghaili.
Using observations by NASA’s TESS (Transiting Exoplanet Survey Satellite) and many other facilities, two international teams of astronomers have discovered a planet between the sizes of Earth and Venus only 40 light-years away. Multiple factors make it a candidate well-suited for further study using NASA’s James Webb Space Telescope.
TESS stares at a large swath of the sky for about a month at a time, tracking the brightness changes of tens of thousands of stars at intervals ranging from 20 seconds to 30 minutes. Capturing transits — brief, regular dimmings of stars caused by the passage of orbiting worlds — is one of the mission’s primary goals.
“We’ve found the nearest, transiting, temperate, Earth-size world located to date,” said Masayuki Kuzuhara, a project assistant professor at the Astrobiology Center in Tokyo, who co-led one research team with Akihiko Fukui, a project assistant professor at the University of Tokyo. “Although we don’t yet know whether it possesses an atmosphere, we’ve been thinking of it as an exo-Venus, with similar size and energy received from its star as our planetary neighbor in the solar system.”
As ESA’s satellite INTEGRAL scanned the skies, it detected a surge of gamma-rays emanating from the nearby galaxy M82. Shortly after this observation, ESA’s XMM-Newton X-ray space telescope sought any residual glow from the event but detected nothing. An international research group, with contributors from the University of Geneva (UNIGE), concluded that the burst was an extragalactic flare from a magnetar, a young neutron star known for its intense magnetic field. This finding was documented in the journal Nature.
On 15 November 2023, ESA’s satellite INTEGRAL spotted a sudden explosion from a rare object. For only a tenth of a second, a short burst of energetic gamma-rays appeared in the sky. “The satellite data were received in the INTEGRAL Science Data Centre (ISDC), based on the Ecogia site of the UNIGE Astronomy Department, from where a gamma-ray burst alert was sent out to astronomers worldwide, only 13 seconds after its detection,” explains Carlo Ferrigno, senior research associate in the Astronomy Department at UNIGE Faculty of Science, PI of the ISDC and co-author of the publication. The IBAS (Integral Burst Alert System) software gave an automatic localization coinciding with the galaxy M82, 12 million light-years away. This alert system was developed and is operated by scientists and engineers from the UNIGE in collaboration with international colleagues.
A Stanford Medicine study reveals six subtypes of depression, identified through brain imaging and machine learning. These subtypes exhibit unique brain activity patterns, helping predict which patients will benefit from specific antidepressants or behavioral therapies. This approach aims to personalize and improve depression treatment efficacy.
In the not-too-distant future, a quick brain scan during a screening assessment for depression could identify the best treatment.
According to a new study led by researchers at Stanford Medicine, brain imaging combined with a type of AI called machine learning can reveal subtypes of depression and anxiety. The study, to be published today (June 17) in the journal Nature Medicine, sorts depression into six biological subtypes, or “biotypes,” and identifies treatments that are more likely or less likely to work for three of these subtypes.
MIT neuroscientists propose a new framework that describes how thought arises from the coordination of neural activity driven by oscillating electric fields — a.k.a. brain “waves” or “rhythms.”
It could be very informative to observe the pixels on your phone under a microscope, but not if your goal is to understand what a whole video on the screen shows. Cognition is much the same kind of emergent property in the brain. It can only be understood by observing how millions of cells act in coordination, argues a trio of MIT neuroscientists. In a new article, they lay out a framework for understanding how thought arises from the coordination of neural activity driven by oscillating electric fields — also known as brain “waves” or “rhythms.”
The Significance of Brain Rhythms.
The capacity to adjust beliefs about one’s actions and their consequences in a constantly changing environment is a defining characteristic of advanced cognition. Disruptions to this ability, however, can negatively affect cognition and behavior, leading to such states of mind as paranoia, or the belief that others intend to harm us.
In a new study, Yale scientists uncover how one specific region of the brain might causally provoke these feelings of paranoia.
Their novel approach — which involved aligning data collected from monkeys with human data — also offers a new cross-species framework through which scientists might better understand human cognition through the study of other species.
A team from Nagoya University invented a heat-switch device for lunar rovers to withstand the Moon’s extreme temperatures. The technology optimizes thermal control, alternating between cooling and insulating, facilitating longer missions with less energy.
Astronauts navigating the moon’s terrain in a vehicle contend with not only the perils of zero gravity and potential crater falls, but also drastic temperature swings. The moon’s climate ranges from searing highs of 127°C (260°F) to bone-chilling lows of −173°C (−280°F).
Team from Nagoya University in Japan developed a heat-switch device designed to enhance the durability of lunar rovers. Their collaborative research with the Japan Aerospace Exploration Agency was featured in the journal Applied Thermal Engineering.
