In the past 20 years, an increasing number of bacterial infections caught by children have been resistant to antibiotics, a new study finds.

The research, published in July in the journal JAMA Pediatrics, looked back at the past two decades, as well as looked forward, to predict how resistance rates might change in the decade to come. By 2035, some critical antibiotics will be met with "steep increases" in resistance among common bacteria, such as Acinetobacter baumannii and Klebsiella, the analysis found.

Antibiotic resistance contributed to 840,000 deaths among children under 5 in 2021, global estimates suggest, so if resistance continues to increase, that number could grow.

"These forecasts are warning scenarios, not inevitable outcomes," said study co-author Dr. Yanhong Jessika Hu, a clinical epidemiologist and public health researcher at Murdoch Children's Research Institute (MCRI) in Australia. "The projections broadly assume that historical patterns continue without a major change in direction," Hu told Live Science in an email.

If significant action is taken, that trajectory could be altered, she said.

"Resistance increased across all regions"
Antibiotic resistance is sometimes called "a silent pandemic," as it poses a formidable threat without stirring as much concern as other health crises, such as viral outbreaks. Resistance has gained attention in recent years, but the data on how it has affected children is patchy, said study co-author Dr. Penelope Bryant, a clinician-researcher at MCRI, Royal Children's Hospital Melbourne, and the University of Melbourne.

"It's perceived as being a lesser problem in children," Bryant told Live Science. "It's not a theoretical problem; it's real, and it's happening. But I think the visibility is just substantially less than in adults."

In a global first, researchers at the Institute of High Energy Physics (IHEP) in China have found experimental evidence to confirm the presence of a glueball, a new form of matter. The research findings were made at the Beijing Spectrometer III (BESIII) experiment, as part of an international collaboration headed by the Chinese Academy of Sciences (CAS). 

The Standard Model of physics states that the building blocks of our universe, atoms, are made up of matter particles and force carriers. Matter particles, or fermions, named quarks, build up protons and neutrons, the positively and neutrally charged particles inside the atomic nucleus. A force carrier holds the quarks together; this carrier is called a gluon. 

Physicists have long held that gluons can also attract each other and bind together to form a glueball, an entirely new form of matter that is composed only of a force carrier. For the past five decades, multiple experiments have been carried out to prove the existence of a glueball. However, it was only in 2011 that scientists in China spotted a potential glueball candidate in the experiments conducted at the Beijing Spectrometer III (BES III). 
...
Why is it important? 
More recently, the researchers also found many new decay modes of X(2370) while also determining its ‘flavor-singlet’ nature, where they lack quark flavor signatures. This is the most important and defining characteristic of a glueball and establishes a complete chain of experimental evidence for a pseudoscalar glueball. 

This confirms the theoretical prediction that gluons can bind to each other and form an entirely new kind of matter. The discovery is also a direct test of the non-Abelian gauge structure in quantum chromodynamics (QCD), which also states that gluons are capable of attracting and binding each other, without the involvement of quarks. 

This is important, since it also helps establish that QCD is a correct theory and it has been validated at low energies. As the clearest experiment in over 50 years to have found the evidence for glueballs, the finding also demonstrates the importance of the BEPC II in studies of strong interactions. 

Roughly 660 million years after the Big Bang, a strange bright red spot has been hiding in plain sight in one of the deepest fields ever imaged by the NASA/ESA/CSA James Webb Space Telescope. Astronomers at MIT now believe it may be the first confirmed example of an entirely new class of object: a black hole star.

MIT astronomer Rohan Naidu and colleagues spotted the object while hunting for some of the earliest galaxies in the Universe, as part of Webb’s Mirage or Miracle survey.

Labeled MoM-BH*-1, the source was essentially invisible in Webb’s bluer filters but blazed in the redder ones, giving it one of the most extreme colors ever recorded in a distant object.

Follow-up spectroscopy revealed why: the object shows the strongest ‘Balmer break’ ever measured at any redshift, a sharp drop in brightness at a wavelength normally associated with dense gas in the outer layers of stars.

Ordinary starlight simply can’t produce a break this severe; even the reddest known stellar populations top out at less than a third of the strength seen here.

The spectrum of MoM-BH*-1 also showed unusually broad emission from hydrogen gas, along with deep absorption features cutting through that emission — a combination that points to gas far denser than anything found in a typical star.

“The break we observed in this object is the deepest break we have ever observed in any object, ruling out ‘ordinary’ stars as the source,” Dr. Naidu said.

“But it made us wonder if we were seeing a new kind of ‘stellar atmosphere,’ but on a spectacular scale.”

“What’s more, the red dot’s light contained almost no signature of metals or any elements other than hydrogen and helium. It was truly singular in so many ways.”

To explain the pattern, the researchers modeled the object as a massive black hole, with a mass on the order of 100,000 to 10 million times that of the Sun, wrapped in an extraordinarily dense, turbulent envelope of hydrogen gas roughly 10 to 100 astronomical units across — about the scale of our Solar System.

Radiation from the black hole’s accretion disk filters through this gas cocoon, which absorbs and scatters the light to produce the object’s odd spectral fingerprint, while essentially no dust is needed to explain its redness.

Notably, MoM-BH*-1’s light output vastly exceeds what nuclear fusion could generate at that size, ruling out a normal star as the source and instead implicating an actively feeding black hole, possibly growing at or above the Eddington limit — the theoretical cap on how fast a black hole can accrete matter while still being pushed outward by its own radiation.

The scientists also detected tentative evidence the object brightened by around 30% over roughly two months, another hallmark of active black hole feeding...

Solar eclipse as seen from space!

From its vantage point in space, the Meteosat Third Generation Imager satellite (MTG-I1) captured the Moon’s dark shadow as it passed over Earth’s surface – converging with the advancing twilight shadow as dusk fell over Europe.
esa.int/ESA_Multimedia…

Adjusting to a new time zone or work schedule can leave the body's internal clock out of sync for days, contributing to sleep disruption, metabolic changes and other health consequences. Researchers at Rice University and Northwestern University have developed an implantable cell therapy that may help the body adapt more quickly to these disruptions.

In a recent study titled "Encapsulated Leptin-Producing Cells Facilitate Entrainment of Circadian Rhythms in Rodents and Nonhuman Primates," encapsulated cells engineered to continuously produce the metabolic hormone leptin reduced the time required for animals to adjust to shifts in the light-dark cycle that mimic jet lag and shift work. Published in Advanced Science, the study's findings demonstrate a new approach to regulating circadian rhythms through metabolic signaling and provide early evidence that engineered cell therapies could be used to address circadian disruption.

A temporary metabolic nudge
"Current approaches for adjusting circadian rhythms rely heavily on precisely timed behaviors such as light exposure, meal schedules or melatonin administration," said Omid Veiseh, professor of bioengineering at Rice. "We wanted to explore whether a temporary cell therapy could provide a more practical way to help the body adapt to changing schedules."

The therapy consists of human retinal pigment epithelial cells engineered to produce leptin, a hormone best known for regulating appetite and metabolism. The cells are encapsulated within microscopic alginate spheres that protect them from the immune system while allowing therapeutic proteins to diffuse into the body. Following a simple subcutaneous injection, the encapsulated cells temporarily elevate circulating leptin levels before naturally losing viability over time.

"Metabolism and circadian rhythms are closely connected, but the therapeutic potential of that relationship remains largely unexplored," said Martha Hotz Vitaterna, professor of neurobiology at Northwestern University and co-corresponding author on the study. "These findings suggest that metabolic signals can be leveraged to accelerate adaptation to circadian disruptions."

Faster adjustment across species
In mouse studies, animals receiving the leptin-producing cell therapy adjusted significantly faster following both phase advances and phase delays in the light-dark cycle. Mice treated with the therapy adapted to a four-hour schedule delay 50% faster than control animals.

Long-term memories may not "stick" in the brain for the reasons we thought, a study of mice in artificial hibernation reveals.

Instead of relying on many individual, strong links between neurons — which would typically be pared down during hibernation — long-lasting memories seem to require higher-level patterns in connectivity, the study found.

"This topological architecture of the broader network seems to be more important" than individual, sturdy connections, said study co-author Kazumasa Tanaka, head of the Memory Research Unit at the Okinawa Institute of Science and Technology.

The findings, published Thursday (Aug. 13) in the journal Science, may complicate the picture of how memory retention works.

Tanaka and colleagues used hibernation to study memory because past studies of hibernating animals have found that their brains shrink and pare down cell-to-cell connections during these extended periods of low metabolic activity. At the same time, the brain's activity slows to a crawl, and the loss of connections is thought to be related to this energy-saving mechanism.

Despite this brain shrinkage, hibernating animals, such as alpine marmots (Marmota marmota) and European ground squirrels (Spermophilus citellus), still retain memories they formed before they went into hibernation. "Some studies report their memories are intact, even after, so they can remember conspecifics [members of the same species], like their friends, or they can remember the locations of their food," Tanaka told Live Science.

The new study aimed to tackle the question of what allows those memories to stick around even after many connections between brain cells disappear.

What is the Nancy Grace Roman Space Telescope? Why do we need it? What will it unveil?

Learn more about Roman and how it will help us investigate some of the many mysteries of the universe. ⬇️

Roman is set to launch Aug 30th at 7:26 am ET. Stay up to date on the mission: go.nasa.gov/45skR6q

A tiny UK-developed satellite, roughly the size of a small carry-on suitcase, could help answer one of the biggest questions in cosmology: What happened during the roughly 150 million years of the cosmic dark ages, before the universe's first stars appeared?

An international team of scientists led by the University of Cambridge will use the far side of the moon as a "shield" so the satellite—called CosmoCube—can block out all the noise from Earth and listen for a faint whisper from the very early universe.

This whisper, known as the 21-centimeter line, is a signal emitted by hydrogen atoms in the period between the afterglow of the Big Bang and cosmic dawn, when nuclear fusion lit up the first stars. No one has directly observed this era before.

Detecting this signal from more than 13.5 billion years ago is extremely difficult with Earth-based telescopes because Earth's ionosphere blocks the right frequencies, and interference from FM radio, satellites and telecommunications drowns it out.

However, the moon provides a natural shield. As CosmoCube orbits the far side of the moon, it will be shielded from all the noise from Earth for roughly 40 minutes of each 2-hour orbit. Over an expected 2-year mission, it will build up 1,000 hours of data on one of the last unexplored periods of the universe, helping us understand how the universe transitioned from dark and nearly empty to the complexity we see today.

From smartphones to data centers, modern electronics rely on billions of tiny switches that consume electricity every time they turn on or off. As global demand for computing continues to grow, so does the energy required to power it. Scientists are therefore searching for alternatives that can perform the same tasks while using far less energy.

One promising approach uses clusters of tiny magnets, each thousands of times smaller than a grain of sand. A new study led by the U.S. Department of Energy's (DOE) Argonne National Laboratory, with contributions from the DOE's Los Alamos National Laboratory and Adolfo Ibáñez University in Chile, has uncovered a geometric rule that determines whether clusters of nanomagnets behave predictably or probabilistically as they relax toward a stable state. The finding challenges standard modeling assumptions and opens new possibilities for ultralow-energy computing.

Nanomagnetic devices have already demonstrated the potential to operate using extremely small amounts of energy—possibly millions of times less than conventional electronic components. If such systems can be made reliable and scalable, they could help reduce the growing energy demands of computing infrastructure worldwide.

The new research offers a practical step toward that goal.

"We've shown that geometry alone can determine how energy moves through these magnetic systems," Arava said, "and that insight gives us a new way to design computing devices."

Over the past two decades, researchers using functional magnetic resonance imaging (fMRI), which tracks the iron in the hemoglobin supplying oxygen to neurons, have been building up increasingly detailed maps and inventories of the mammalian cortex. Thanks to huge advances in machine-learning artificial intelligence—computer algorithms that are able to sort through enormous amounts of information and use statistical methods to make classifications and predictions—fMRI scans can now be used to identify everything from depressive thoughts to the nuanced feelings of envy and schadenfreude. Other algorithms have been able to accurately piece together reconstructions of movie clips watched by subjects, just by analyzing their brain scans; or have detected, in probing the brain activity of swing voters in the US presidential election, responding to photographs and videos of presidential candidates, which candidates provoked anxiety or even disgust, and which elicited positive responses or feelings of empathy

In just the last few years, neuroscience researchers have progressed from decoding images and emotions as they play across the cortex to sounds, words, phrases, and even language. In 2023, in a remarkable demonstration of this emerging technology, a woman called Ann Johnson, who had been paralyzed for 18 years by a brain-stem stroke, was able to speak again through the insertion of a grid of 253 electrodes onto the surface of her brain, which translated her neuronal signals into sentences, in real time, at a rate of 78 words per minute (just about half the speed of standard conversation). The research team at the University of California, led by neurosurgeon Edward Chang, had combined this brain-computer interface with an animated avatar of Johnson’s head, which spoke in her own voice, as reconstructed from a recording of a 15-minute toast she had given at her wedding. Just as the avatar’s mouth spoke Johnson’s words as she thought them, so its expressions were similarly influenced by the nuances of her brain activity, which turned her thoughts about facial gestures into displays of emotion—from smiles to pursed lips and frowns...