Does the cause of tricuspid regurgitation (TR) affect survival?
A new analysis of nearly 13K patients finds that survival in Primary TR is better than in Secondary or Lead-associated TR. @JabbarMMS
BackgroundTricuspid regurgitation (TR) is a common valvular disorder that can affect patients’ quality of life and survival. The impact of TR etiology on overall survival and the associated risk factors in each subgroup are not well studied.
Read it in the RedJournal: @NRGOnc
: Intensity-modulated radiation therapy (IMRT) is increasingly used for total body irradiation (TBI) due to its ability to deliver myeloablative doses while sparing radiosensitive organs. To enable consistent evaluation in future National Clinical Trials Network (NCTN) studies, the xxx Hematologic Malignancies Working Group (HMWG) convened IMRT-TBI experts and NCTN leaders to develop consensus recommendations for standardized multi-institutional implementation.
In a randomized clinical trial including older bereaved adults, group-format grief-focused cognitive behavioral therapy (ProlongedGriefDisorder) was noninferior to individual therapy for reducing symptoms of prolonged grief, posttraumatic stress disorder, depression, and anxiety at 6 months.
Both formats produced large reductions in symptom burden, suggesting either delivery method is effective for older adults seeking treatment after loss.
This study examines whether cognitive behavioral therapy delivered in a group format is noninferior to cognitive behavioral therapy delivered in an individual format in reducing prolonged grief disorder symptoms in older adults.
Humanoid robots, robotic systems with a human-like body structure, have the potential of tackling various real-world tasks that are currently being completed by humans. In recent years, many robotics researchers and computer scientists have been trying to broaden these robots’ capabilities and improve how they move in their surroundings.
A research team at Amazon Frontier AI & Robotics (FAR) and University of California Berkeley (UC Berkeley) recently introduced perceptive humanoid parkour (PHP), a framework that could allow humanoid robots to move with remarkable agility, running, jumping and climbing over obstacles in urban or natural environments. Their proposed approach, outlined in a paper published on the arXiv preprint server, entails training computational models on recordings of humans engaging in parkour, a popular urban sport that allows practitioners to rapidly navigate environments using their agility and body strength.
“While recent advances in humanoid locomotion have achieved stable walking on varied terrains, capturing the agility and adaptivity of highly dynamic human motions remains an open challenge,” wrote Zhen Wu, Xiaoyu Huang and their colleagues in their paper.
The human body continuously generates a rich spectrum of vibrations—often without us ever noticing. Everyday unconscious activities such as breathing, speaking, and swallowing all produce subtle yet distinct mechanical signals. Although these faint vibrations carry valuable information about physiological state, they have long been difficult to capture accurately using conventional wearable devices.
Recently, a research team led by Professor Kilwon Cho of the Department of Chemical Engineering at Pohang University of Science and Technology (POSTECH), along with Ph.D. candidate Kang Hyuk Cho and postdoctoral researcher Dr. Jeng-Hun Lee, has developed a wearable vibration sensor capable of precisely detecting these subtle yet highly dynamic signals, without requiring any external power source. This breakthrough opens new possibilities for wearable medical and health care technologies and demonstrates strong potential as a core sensing platform for next-generation smart devices. The work was published in the inaugural issue of Nature Sensors.
Sounds produced by the human body span a wide range of frequencies. Physiological signals such as breathing, swallowing, and speech typically occur at lower frequencies, while sounds such as coughing or groaning emerge at relatively higher frequencies. Accurately capturing these signals requires precise detection of the minute vibrations transmitted to the skin surface across a broad frequency spectrum.
What if the thermal noise that hinders the efficiency of both classical and quantum computers could, instead, be used as a power source? What if computers could make use of the noise instead of suppressing or overcoming it? These are the goals of a relatively new branch of computing known as thermodynamic computing. A collaboration between researchers at the Molecular Foundry and the National Energy Research Scientific Computing Center (NERSC), both U.S. Department of Energy (DOE) user facilities located at Lawrence Berkeley National Laboratory (Berkeley Lab), is bringing them closer to reality.
In a paper published in Nature Communications, the researchers have proposed a design and training framework for a type of thermodynamic computer that mimics a neural network, which could drastically reduce the energy requirements of machine learning.
Modern computing requires energy: a single Google search, for example, consumes enough energy to power a six-watt LED for three minutes. This is partly because computers must contend with thermal noise—that is, the vibration of charge carriers, mostly electrons, within electronically conductive materials. In classical computers, even the smallest devices, such as transistors and gates, operate at energy scales thousands of times larger than that of this vibration.
To misquote a famous song, “Diamonds are industry’s best friend.” Cubic diamond is the hardest mineral on Earth and is used in everything from precision cutting tools to high-performance semiconductors as well as expensive jewelry. But there is a rare and potentially tougher form called hexagonal diamond (HD), which has long been the subject of theories and debate over its actual existence. But now researchers from China claim to have created this elusive form of carbon in the lab.
Hexagonal diamond (also known as lonsdaleite) is usually found at sites of meteorite impacts. But because the quantities are so small and mixed with minerals, some scientists doubted it was a distinct material. In a paper published in the journal Nature, researchers describe how they made a bulk piece of pure HD using extreme pressure and heat.