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Current & Future Role of Anktiva (N-803): Dr. Patrick Soon-Shiong

In this episode of the Oncology Brothers podcast, we engaged in a thought-provoking discussion with Dr. Patrick Soon-Shiong, a pioneer in oncology and the innovator behind the approval of nab-paclitaxel (Abraxane). We delved into the exciting potential of Anktiva (N-803), an IL-15 receptor super agonist designed to expand and activate natural killer (NK) cells and CD8 T cells, with the hope of revolutionizing cancer treatment.

Dr. Soon-Shiong shared insights into the mechanism of action of Anktiva, its current approvals in non-muscle invasive bladder cancer, and extended approval in non-small cell lung cancer in Saudi Arabia, and the promising clinical trial data that suggests a significant increase in overall survival for patients. The conversation also touched on the importance of restoring lymphocyte counts and the implications for treating various tumor types.

Join us as we explore the future of immunotherapy, the challenges of regulatory approval, and the potential for Anktiva to change the landscape of cancer treatment.
Key Topics:
• Mechanism of action of Anktiva.
• Current approvals and clinical trial data.
• The role of lymphocyte counts in cancer treatment.
• Future directions for immunotherapy.

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Seeing the Quantum Butterfly Effect

A combined experimental and theoretical study reveals the emergence of quantum chaos in a complex system, suggesting that it can be described with a universal theoretical framework.

Consider the following thought experiment: Take all the air molecules in a thunderstorm and evolve them backward in time for an hour, effectively rewinding a molecular movie. Then slightly perturb the velocity directions of a few molecules and evolve the system forward again to the current moment. Because such systems are chaotic, microscopic perturbations in the past will lead to dramatically different futures. This “butterfly effect” also occurs in quantum systems. To observe it, researchers measure a mathematical entity called the out-of-time-ordered correlator (OTOC). Loosely speaking, the OTOC measures how quickly a system “forgets” its initial state. Unfortunately, the OTOC is notoriously difficult to measure because it typically requires experimental protocols that implement an effective many-body time reversal.

Building blocks of life discovered in Bennu asteroid rewrite origin story

Amino acids, the building blocks necessary for life, were previously found in samples of 4.6-billion-year-old rocks from an asteroid called Bennu, delivered to Earth in 2023 by NASA’s OSIRIS-REx mission. How those amino acids—the molecules that create proteins and peptides in DNA—formed in space was a mystery, but new research led by Penn State scientists shows they could have originated in an icy-cold, radioactive environment at the dawn of Earth’s solar system.

According to the researchers, who published new findings in the Proceedings of the National Academy of Sciences, some amino acids in the asteroid Bennu samples likely formed in a different way than was previously thought, in the harsh conditions of the early solar system.

Leading AI models struggle to solve original math problems

Mathematics, like many other scientific endeavors, is increasingly using artificial intelligence. Of course, math is the backbone of AI, but mathematicians are also turning to these tools for tasks like literature searches and checking manuscripts for errors. But how well can AI perform when it comes to solving genuine, high-level research problems?

To date, there is still no widely accepted realistic methodology for assessing AI’s capabilities to solve math at this level. So a group of mathematicians decided to put the machines to the test as they detail in a study available on the arXiv preprint server.

Previous attempts at testing AI have used math contest problems and questions already found in textbooks. What makes this study different is that the questions the programs faced were drawn from mathematicians’ own research. They had never been posted or published online, which means AI couldn’t memorize answers from its training data.

Supercomputer simulations test turbulence theories at record 35 trillion grid points

Using the Frontier supercomputer at the Department of Energy’s Oak Ridge National Laboratory, researchers from the Georgia Institute of Technology have performed the largest direct numerical simulation (DNS) of turbulence in three dimensions, attaining a record resolution of 35 trillion grid points. Tackling such a complex problem required the exascale (1 billion billion or more calculations per second) capabilities of Frontier, the world’s most powerful supercomputer for open science.

The team’s results offer new insights into the underlying properties of the turbulent fluid flows that govern the behaviors of a variety of natural and engineered phenomena—from ocean and air currents to combustion chambers and airfoils. Improving our understanding of turbulent fluctuations can lead to practical advancements in many areas, including more accurately predicting the weather and designing more efficient vehicles.

The work is published in the Journal of Fluid Mechanics.

A long-lost Soviet spacecraft: AI could finally solve the mystery of Luna 9’s landing site

Using an advanced machine-learning algorithm, researchers in the UK and Japan have identified several promising candidate locations for the long-lost landing site of the Soviet Luna 9 spacecraft. Publishing their results in npj Space Exploration, the team, led by Lewis Pinault at University College London, hope that their model’s predictions could soon be tested using new observations from India’s Chandrayaan-2 orbiter.

In 1966, the USSR’s Luna 9 mission became the first human-made object to land safely on the moon’s surface and to transmit photographs from another celestial body. Compared with modern missions, the landing was dramatic: shortly before the main spacecraft itself struck the lunar surface, it deployed a 58-cm-wide, roughly 100-kg spherical landing capsule from above, then maneuvered away to crash at a safe distance.

Equipped with inflatable shock absorbers, the capsule bounced several times before coming to rest, stabilizing itself by unfurling four petal-like panels. Although Luna 9 operated for just three days, it transmitted a wealth of valuable data back to Earth, helping to inspire confidence in crewed space exploration, that would see humanity take its first steps on the moon just three years later.

Bioengineers build branched, perfusable kidney collecting ducts using 3D bioprinting

The human kidney filters about a cup of blood every minute, removing waste, excess fluid, and toxins from it, while also regulating blood pressure, balancing important electrolytes, activating Vitamin D, and helping the body produce red blood cells. This broad range of functions is achieved in part via the kidney’s complex organization. In its outer region, more than a million microscopic units, known as nephrons, filter blood, reabsorb necessary nutrients, and secrete waste in the form of urine.

To direct urine produced by this enormous number of blood-filtering units to a single ureter, the kidney establishes a highly branched three-dimensional, tree-like system of “collecting ducts” during its development. In addition to directing urine flow to the ureter and ultimately out of the kidney, collecting ducts reabsorb water that the body needs to retain, and maintain, the body’s balance of salts and acidity at healthy levels.

Finding ways to recreate this system of collecting ducts is the focus of researchers and bioengineers who are interested in understanding how duct defects cause certain kidney diseases, underdeveloped kidneys, or even the complete absence of a kidney. Being able to fabricate the kidney’s plumbing system from the bottom up would be a giant step toward tissue replacement therapies for many patients waiting for a kidney donation: In the U.S. alone, 90,000 patients are on the kidney transplant waiting list. However, rebuilding this highly branched fluid-transporting ductal system is a formidable challenge and not possible yet.

Intense sunlight reduces plant diversity and biomass across global grasslands, study finds

The sun is the basis for photosynthesis, but not all plants thrive in strong sunlight. Strong sunlight constrains plant diversity and plant biomass in the world’s grasslands, a new study shows. Temperature, precipitation, and atmospheric nitrogen deposition have less impact on plant diversity. These results were published in the Proceedings of the National Academy of Sciences by a research team led by Marie Spohn from the Swedish University of Agricultural Sciences.

The steppes of North America, the Serengeti savanna, the Svalbard tundra and natural pastures in the Alps are examples of habitats that are described as grasslands, with the common feature that there are no trees and the vegetation is dominated by grasses and other herbaceous plants. The diversity of plant species in these grasslands varies considerably, but the question of what controls plant diversity has challenged researchers for decades.

Last year, in a study on grasslands, Spohn from SLU and colleagues found that soil properties and climate factors, such as temperature, did not explain variations in plant diversity. “This finding surprised me,” says Spohn. “And that’s when I started wondering about the importance of sunlight for plant diversity in grasslands and decided to start a new project that would explore this relationship.”

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