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Study Reveals a Turning Point When Men’s Heart Attack Risk Accelerates

Screening at an earlier age can help identify risk factors sooner, enabling preventive strategies that reduce long-term risk.

Screening for heart attack risk should be happening earlier for men, according to a new study that found the risk of cardiovascular disease starts climbing when men are in their mid-30s – significantly earlier than a similar trend is seen in women.

The US-based researchers behind the study followed the health of 5,112 people for an average of around 34 years. As the participants were healthy and aged 18–30 when the study started in the mid-1980s, the researchers could chart cases of cardiovascular disease (including strokes and heart failure) over time.

According to the data, 35 is the critical age when disparities between male and female cardiovascular disease risk start to appear. Most of the difference is driven by coronary heart disease (CHD), the most common cause of heart attacks, where fatty deposits clog up arteries, blocking blood flow.

Exposing Nuclear Magic

Calculations show how the mysterious “magic numbers” that stabilize nuclear structures emerge naturally from nuclear forces—once these are described with appropriate spatial resolution.

Atomic nuclei have been studied for over a century, yet some of nuclear physics’ most basic questions remain unanswered: How many bound combinations of protons and neutrons, or isotopes, can exist? Where do the limits of nuclear existence lie? How are chemical elements synthetized in the Universe? Clues to solving these puzzles lie in the vast phenomenology of nuclear structure—the measured properties of tens of thousands of nuclear states, their decays, and their reactions. In this bedlam of information, patterns and irregularities in data provide crucial hints. One such irregularity was spotted as early as 1934 [1]: Nuclei containing specific numbers of protons and neutrons (2, 8, 20, 28, 50, 82…) are unexpectedly stable. These “magic numbers” (Fig.

91-qubit Processor Accurately Simulates Many-Body Quantum Chaos

Quantum chaos describes chaotic classical dynamical systems in terms of quantum theory, but simulations of these systems are limited by computational resources. However, one team seems to have found a way by leveraging error mitigation and specialized circuits on a 91-qubit superconducting quantum processor. Their results are published in Nature Physics.

While useful quantum simulations require an ability to eliminate errors, full quantum error correction requires large overheads in qubits and control. Previous work has gotten around this problem by simulating limited quantum many-body systems mostly at smaller scales or with integrable—or less chaotic—models.

The research team involved in the new study opted for a different method. Instead, they used error mitigation, which accepts noise and then corrects errors later, saving computational resources in the process.

Newly identified RNA molecule may drive cancer patient survival

In a recent study, researchers at the Texas A&M University Health Science Center (Texas A&M Health) identify a novel RNA molecule that plays a crucial role in preserving the integrity of a key cellular structure, the nucleolus. Their findings also suggest this molecule may influence patient survival in certain blood cancers. The work is published in the Proceedings of the National Academy of Sciences.

Real-time view inside microreactor reveals 2D semiconductor growth secrets

As the miniaturization of silicon-based semiconductor devices approaches fundamental physical limits, the electronics industry faces an urgent need for alternative materials that can deliver higher integration and lower power consumption. Two-dimensional (2D) semiconductors, which are only a single atom thick, have emerged as promising candidates due to their unique electronic and optical properties. However, despite intense research interest, controlling the growth of high-quality 2D semiconductor crystals has remained a major scientific and technological challenge.

A research team led by Research Associate Professor Hiroo Suzuki from the Department of Electrical and Communication Engineering at Okayama University, Japan, together with Dr. Kaoru Hisama from Shinshu University and Dr. Shun Fujii from Keio University, has now overcome a key barrier by directly observing how these materials grow at the atomic scale. Using an advanced in situ observation system, the researchers captured real-time images of monolayer transition metal dichalcogenides (TMDCs) forming inside a micro-confined reaction space. The study was published on December 12, 2025, in the journal Advanced Science.

The work builds on earlier success by the team in synthesizing large-area monolayer TMDC single crystals using a substrate-stacked microreactor. While that method consistently produced high-quality materials, the mechanisms governing crystal growth inside the confined space were poorly understood.

Machine learning accelerates plasma mirror design for high-power lasers

Plasma mirrors capable of withstanding the intensity of powerful lasers are being designed through an emerging machine learning framework. Researchers in Physics and Computer Science at the University of Strathclyde have pooled their knowledge of lasers and artificial intelligence to produce a technology that can dramatically reduce the time it takes to design advanced optical components for lasers—and could pave the way for new discoveries in science.

High-power lasers can be used to develop tools for health care, manufacturing and nuclear fusion. However, these are becoming large and expensive due to the size of their optical components, which is currently necessary to keep the laser beam intensity low enough not to damage them. As the peak power of lasers increases, the diameters of mirrors and other optical components will need to rise from approximately one meter to more than 10 meters. These would weigh several tons, making them difficult and expensive to manufacture.

Two-step approach creates more sustainable protein nanostructures for advanced sensing and therapeutics

Gas vesicles are among the largest known protein nanostructures produced and assembled inside microbial cells. These hollow, air-filled cylindrical nanostructures found in certain aquatic microbes have drawn increasing interest from scientists due to their potential for practical applications, including as part of novel diagnostic and therapeutic tools. However, producing gas vesicles is a difficult task for cells in the lab, hindering the development of applications.

In a study recently published in Nature Communications, a team of researchers led by Rice University bioengineer George Lu reports the development of a new genetic regulatory system to improve cell viability during the production of gas vesicles.

“In the past few years, studies have shown that gas vesicles’ ability to reflect sound makes them useful as unique and versatile acoustic reporter systems for biomedical research and clinical applications,” said Lu, an assistant professor in the Department of Bioengineering at Rice’s George R. Brown School of Engineering and Computing.

Long-period Jupiter-like exoplanet discovered with TESS

Using NASA’s Transiting Exoplanet Survey Satellite (TESS), an international team of astronomers has discovered a new extrasolar planet transiting a distant star. The newfound alien world, designated TOI-6692 b, is the size of Jupiter and has an orbital period of about 130 days. The discovery was presented in a paper published January 22 on the arXiv pre-print server.

TESS is conducting a survey of about 200,000 bright stars near the sun with the aim of searching for transiting exoplanets. To date, more than 7,800 potential planets (known as TESS Objects of Interest) have been cataloged using this satellite, with 733 of those discoveries officially verified.

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