Major Advance In Cancer Therapy

Immune checkpoint inhibitors such as Keytruda and Opdivo work by unleashing the immune system’s T cells to attack tumor cells. Their introduction a decade ago marked a major advance in cancer therapy, but only 10% to 30% of treated patients experience long-term improvement. In a paper published online today in The Journal of Clinical Investigation (JCI), scientists at Albert Einstein College of Medicine describe findings that could bolster the effectiveness of immune-checkpoint therapyRather than rally T cells against cancer, the Einstein research team used different human immune cells known as natural killer (NK) cells—with dramatic results.

“We believe the novel immunotherapy we’ve developed has great potential to move into clinical trials involving various types of cancer,” said study leader Xingxing Zang, M.Med., Ph.D., Professor of microbiology  at Einstein and a member of the Cancer Therapeutics Program of the Montefiore Einstein Cancer Center.

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Quantum Entanglement Wins 2022’s Nobel Prize

For generations, scientists argued over whether there was truly an objective, predictable reality for even quantum particles, or whether quantum “weirdness” was inherent to physical systems. In the 1960s, John Stewart Bell developed an inequality describing the maximum possible statistical correlation between two entangled particles: Bell’s inequality. But certain experiments could violate Bell’s inequality, and these three pioneers —  John Clauser, Alain Aspect, and Anton Zeilinger — helped make quantum information systems a bona fide science.

There’s a simple but profound question that physicists, despite all we’ve learned about the Universe, cannot fundamentally answer:What is real?” We know that particles exist, and we know that particles have certain properties when you measure them. But we also know that the very act of measuring a quantum state — or even allowing two quanta to interact with one another — can fundamentally alter or determine what you measure. An objective reality, devoid of the actions of an observer, does not appear to exist in any sort of fundamental way.

But that doesn’t mean there aren’t rules that nature must obey. Those rules exist, even if they’re difficult and counterintuitive to understand. Instead of arguing over one philosophical approach versus another to uncover the true quantum nature of reality, we can turn to properly-designed experiments. Even two entangled quantum states must obey certain rules, and that’s leading to the development of quantum information sciences: an emerging field with potentially revolutionary applications. 2022’s Nobel Prize in Physics was just announced, and it’s awarded to John Clauser, Alain Aspect, and Anton Zeilinger for the pioneering development of quantum information systems, entangled photons, and the violation of Bell’s inequalities. It’s a Nobel Prize that’s long overdue, and the science behind it is particularly mind-bending.

There are all sorts of experiments we can perform that illustrate the indeterminate nature of our quantum reality.

Place a number of radioactive atoms in a container and wait a specific amount of time. You can predict, on average, how many atoms will remain versus how many will have decayed, but you have no way of predicting which atoms will and won’t survive. We can only derive statistical probabilities.
Fire a series of particles through a narrowly spaced double slit and you’ll be able to predict what sort of interference pattern will arise on the screen behind it. However, for each individual particle, even when sent through the slits one at a time, you cannot predict where it will land.
Pass a series of particles (that possess quantum spin) through a magnetic field and half will deflect “up” while half deflect “down” along the direction of the field. If you don’t pass them through another, perpendicular magnet, they’ll maintain their spin orientation in that direction; if you do, however, their spin orientation will once again become randomized.
Certain aspects of quantum physics appear to be totally random. But are they really random, or do they only appear random because our information about these systems are limited, insufficient to reveal an underlying, deterministic reality? Ever since the dawn of quantum mechanics, physicists have argued over this, from Einstein to Bohr and beyond.

Source: https://bigthink.com/

Roboticists Discover alternative Physics

Energy, mass, velocity. These three variables make up Einstein‘s iconic equation E=MC2. But how did Einstein know about these concepts in the first place? A precursor step to understanding physics is identifying relevant variables. Without the concept of energy, mass, and velocity, not even Einstein could discover relativity. But can such variables be discovered automatically? Doing so could greatly accelerate scientific discovery. This is the question that researchers at Columbia Engineering posed to a new AI program. The program was designed to observe  through a , then try to search for the minimal set of fundamental variables that fully describe the observed dynamics. The study was published on July 25 in Nature Computational Science. The researchers began by feeding the system raw video footage of phenomena for which they already knew the answer. For example, they fed a video of a swinging double pendulum known to have exactly four “state variables”—the angle and of each of the two arms. After a few hours of analysis, the AI produced the answer: 4.7.

We thought this answer was close enough,” said Hod Lipson, director of the Creative Machines Lab in the Department of Mechanical Engineering, where the work was primarily done. “Especially since all the AI had access to was raw video footage, without any knowledge of physics or geometry. But we wanted to know what the variables actually were, not just their number.”

The researchers then proceeded to visualize the actual variables that the program identified. Extracting the variables themselves was not easy, since the program cannot describe them in any intuitive way that would be understandable to humans. After some probing, it appeared that two of the variables the program chose loosely corresponded to the angles of the arms, but the other two remain a mystery.

We tried correlating the other variables with anything and everything we could think of: angular and linear velocities, kinetic and , and various combinations of known quantities,” explained Boyuan Chen Ph.D., now an assistant professor at Duke University, who led the work. “But nothing seemed to match perfectly.” The team was confident that the AI had found a valid set of four variables, since it was making good predictions, “but we don’t yet understand the mathematical language it is speaking,” he explained.

Source: https://phys.org/

The Quantum Gravity

How can Einstein‘s theory of gravity be unified with quantum mechanics? It is a challenge that could give us deep insights into phenomena such as black holes and the birth of the universe. Now, a new article in Nature Communications, written by researchers from Chalmers University of Technology, Sweden, and MIT, U.S., presents results that cast new light on important challenges in understanding quantum gravity.

We strive to understand the laws of nature and the language in which these are written is mathematics. When we seek answers to questions in physics, we are often led to new discoveries in mathematics too. This interaction is particularly prominent in the search for quantum gravity—where it is extremely difficult to perform experiments,” explains Daniel Persson, Professor at the Department of Mathematical Sciences at Chalmers university of technology.

An example of a phenomenon that requires this type of unified description is . A black hole forms when a sufficiently heavy star expands and collapses under its own gravitational force, so that all its mass is concentrated in an extremely small volume. The quantum mechanical description of black holes is still in its infancy but involves spectacular advanced mathematics.

The challenge is to describe how gravity arises as an ’emergent’ phenomenon. Just as everyday phenomena—such as the flow of a liquid—emerge from the chaotic movements of individual droplets, we want to describe how gravity emerges from quantum mechanical system at the microscopic level,” says Robert Berman, Professor at the Department of Mathematical Sciences at Chalmers University of Technology.

In an article recently published in the journal Nature Communications, Daniel Persson and Robert Berman, together with Tristan Collins of MIT in the U.S., showed how gravity emerges from a special quantum mechanical system in a simplified model for quantum gravity called the holographic principle.

Using techniques from the mathematics that I have researched before, we managed to formulate an explanation for how gravity emerges by the holographic principle, in a more precise way than has previously been done,” explains Robert Berman.

The new article may also offer new insight into mysterious dark energy. In Einstein’s general theory of relativity, gravity is described as a geometric phenomenon. Just as a newly made bed curves under a person’s weight, heavy objects can bend the geometric shape of the universe. But according to Einstein’s theory, even the empty space—the “vacuum state” of the universe—has a rich geometric structure. If you could zoom in and look at this vacuum on a microscopic level, you would see quantum mechanical fluctuations or ripples, known as dark energy. It is this mysterious form of energy that, from a larger perspective, is responsible for the accelerated expansion of the universe.

Source: Nature Communications.com