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Gene therapy for deafness approved

The world’s first gene therapy for deafness received approval from the U.S. Food and Drug Administration today. The treatment, from biotech company Regeneron, targets hearing loss caused by inherited mutations in the OTOF gene, which encodes otoferlin, a protein that allows the inner ear’s hair cells to sense and transmit sound to the brain. Patients receive a one-time ear injection containing viral vectors that carry a working copy of the OTOF gene into their cells. In a clinical trial, nine of 12 deaf children who initially received the Regeneron therapy gained enough hearing to stop using cochlear implants; three within that group ended up having normal hearing. Although many gene therapies cost $1 million or more, Regeneron said its treatment, called Otarmeni, will be free in the United States.

Eli Lilly & Co. and researchers in China are also developing gene therapies for OTOF mutations, which account for up to 3% of cases of inherited deafness. One U.S.-Chinese team reported in Nature this week that among 24 patients, including some adults, hearing improvements have lasted more than 2 years in some cases, NPR reports. Researchers eventually hope to treat other types of genetic deafness as well, but those attempts face more challenges. For example, for some disorders, it may be necessary to regenerate lost hair cells. In others, targeting the wrong cell type could damage hearing.

Label-free optical imaging enables automated measurement of human white matter microstructure

White matter pathways allow distant parts of the brain to communicate, supporting memory, emotion, and language. One such pathway, the uncinate fasciculus, connects the front of the temporal lobe with regions of the frontal cortex involved in decision-making and social behavior. Despite its importance, little is known about the microscopic structure of this tract in the human brain.

Traditional techniques such as electron microscopy can reveal fine details, but they often fail when applied to postmortem human tissue, which is frequently degraded.

In a study published in Biophotonics Discovery, researchers report a new way to examine white matter structure in postmortem human brains.

New study bridges the worlds of classical and quantum physics

When you throw a ball in the air, the equations of classical physics will tell you exactly what path the ball will take as it falls, and when and where it will land. But if you were to squeeze that same ball down to the size of an atom or smaller, it would behave in ways beyond anything that classical physics can predict.

Or so we’ve thought.

MIT scientists have now shown that certain mathematical ideas from everyday classical physics can be used to describe the often weird and nonintuitive behavior that occurs at the quantum, subatomic scale.

Ion Clock Experiments Reveal Time Can Go Quantum

PRESS RELEASE — Few concepts in physics are as familiar, yet as enigmatic, as time. In Einstein’s theory of relativity, time is not absolute: its passage depends on motion and gravity. But when combined with quantum physics, this relativistic form of time becomes even more counterintuitive. According to quantum theory, the flow of time itself may exist in a genuine quantum superposition, ticking faster and slower at the same time. Now, a new paper titled Quantum signatures of proper time in optical ion clocks, published on April 20, 2026 in Physical Review Letters, the premier physics research journal, shows that this striking possibility may soon be tested in the laboratory.

In this work, a team led by Assistant Professor of theoretical physics Igor Pikovski at Stevens Institute of Technology, in collaboration with experimental groups of Christian Sanner at Colorado State University and Dietrich Leibfried at the National Institute of Standards and Technology (NIST), explores quantum aspects of the flow of time and how they can be accessed with atomic clocks. Their results suggest that the same quantum technologies being developed for next-generation clocks and quantum computers may soon probe something far more fundamental: When a clock’s motion obeys quantum mechanics, its movement can exist in superposition, and with it the recorded passage of time itself. This is analogous to Schrödinger’s famous thought experiment, where the counterintuitive nature of quantum superposition is illustrated by a cat being both alive and dead; here it is the passage of time itself that is in superposition, like a cat that is both young and old at once.

“Time plays very different roles in quantum theory and in relativity,” says Pikovski. “What we show is that bringing these two concepts together can reveal hidden quantum signatures of time-flow that can no longer be described by classical physics.”

Research Into Naturally Occurring Hair Growth in Skin Nevi May Inform New Regenerative Therapies

An international team of researchers funded in part by NIAMS sought to understand why skin nevi grow long hair. Nevi, which are a type of skin lesion, have an abundance of pigment-producing cells, called melanocytes, that have become aged (or senescent). The team determined that senescent melanocytes within nevi produce large quantities of several signaling molecules. One such molecule, called osteopontin, causes dormant hair stem cells to wake up, which increases hair growth.

The study, which appeared in the journal Nature on June 21, 2023, provides answers as to why nevi are hairy and also uncovers the unexpected growth-promoting potential of senescent cells, which are typically thought to be associated with inhibited tissue growth.

AI Models Mirror Human Logic on Real-World Scenarios

“What we show is that the models actually capture that human uncertainty pretty well,” said Michael Lepori. [ https://www.labroots.com/trending/technology/30475/ai-models…cenarios-2](https://www.labroots.com/trending/technology/30475/ai-models…cenarios-2)

Can AI models distinguish fact from fiction? This is what a new study scheduled to be presented at the International Conference on Learning Representations this weekend hopes to address as a team of scientists investigated how AI models could tell the difference between facts and “fake news”. This study has the potential to help scientists, engineers, and the public better understand how AI models can evolve to meet human needs, which comes at a time when AI is becoming more integrated into our everyday lives.

For the study, the researchers analyzed how AI language models (LMs) were able to differentiate between different topics and information and judge what’s true and what’s fake. The motivation behind this study was to address a knowledge gap regarding whether large language models (LLMs) have a human-like understanding of the world or if they simply make decisions based on what’s given to them.

The goal of the study was to ascertain if the LMs could determine whether an event is real or fake, along with ascertaining when the LM makes this determination during its thought process. For example, the researchers would give the LM simple scenarios like “clean a car”, clean a road”, and “clean a cloud”, and ask the LM to figure out which was real or fake. In the end, the researchers found that large LMs were capable of differentiating between real and fake events or data.

Identification and characterization of BRAF⇔TP53 interactions in melanoma

O’Toole et al. identify novel interactors of both normal BRAF and BRAFV600E and discover TP53 as a BRAFV600E-enhanced interactor in melanoma cells. While TP53 mutations do not frequently occur in melanoma, the authors demonstrate TP53 inactivation and a sequestration of cytoplasmic TP53 after oncogenic BRAF activation.

Why faster AI isn’t always better

In the race to make AI models not just reason better but respond faster, latency—the delay before an answer appears—is often treated as a purely technical constraint, something to minimize and move past. But how is this relentless push for speed actually impacting the people using these systems every day?

There is a rich body of work in human–computer interaction linking faster response times to better usability. But AI models are fundamentally different from the deterministic systems that previous research was built on. When you wait for a file to download or a page to load, the outcome is fixed and predictable.

AI models are probabilistic—you cannot anticipate the precise response. Their conversational interface means users naturally read human social cues into the interaction. A pause might be read as the AI “thinking,” for instance. Users are increasingly asked to choose between faster models and slower, deeper-reasoning ones, without guidance on what that choice actually means for their experience.

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