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Revolutionizing Quantum Communication: Direct Connections Between Multiple Processors

Researchers developed a scalable interconnect that facilitates all-to-all communication among many quantum processor modules by enabling each to send and receive quantum information on demand in a user-specified direction. They used the interconnect to demonstrate remote entanglement, a type of correlation that is key to creating a powerful, distributed network of quantum processors.

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Quantum computers have the potential to solve complex problems that would be impossible for even the most powerful classical supercomputers. To achieve this, multiple quantum processors need to communicate with each other directly.

The current architecture used to interconnect superconducting quantum processors is “point-to-point” in connectivity, requiring a series of transfers between network nodes, with compounding error rates. Researchers at MIT have developed a new device that enables scalable, “all-to-all” communication among multiple quantum processors.

Their interconnect device includes a superconducting wire, or waveguide, that shuttles photons between processors and can be routed as far as needed. The researchers used this interconnect to demonstrate remote entanglement, a type of correlation between quantum processors that are not physically connected.

“This is a crucial step toward building a large-scale quantum processor from smaller-scale modules,” says Aziza Almanakly, lead author of the paper on the interconnect. “In the future, a quantum computer will probably need both local and nonlocal interconnects.”

The researchers previously developed a quantum computing module that enabled them to send information-carrying microwave photons in either direction along a waveguide. In their new work, they took that architecture a step further by connecting two modules to a waveguide.

Each module is composed of four qubits, which serve as an interface between the waveguide carrying the photons and the larger quantum processors. The researchers use a series of microwave pulses to add energy to a qubit, which then emits a photon. Carefully controlling the phase of those pulses enables a quantum interference effect that allows them to emit the photon in either direction along the waveguide.

Reversing the pulses in time enables a qubit in another module any arbitrary distance away to absorb the photon. “Pitching and catching photons enables us to create a ‘quantum interconnect’ between nonlocal quantum processors,” explains William D. Oliver, senior author of the paper.

The researchers used this architecture to generate remote entanglement among two modules, demonstrating that even after the photon is gone, there is still a correlation between the two distant qubits. Remote entanglement allows them to take advantage of these correlations and perform parallel operations between two qubits, even though they are no longer connected and may be far apart.

However, transferring a photon between two modules is not enough to generate remote entanglement. The researchers needed to prepare the qubits and the photon so that the modules “share” the photon at the end of the protocol. They did this by halting the photon emission pulses halfway through their duration.

Once the receiver module absorbs that “half-photon,” the two modules become entangled. But as the photon travels, joints, wire bonds, and connections in the waveguide distort the photon and limit the absorption efficiency of the receiving module.

To generate remote entanglement with high enough fidelity, the researchers needed to maximize how often the photon is absorbed at the other end. They used a reinforcement learning algorithm to learn how the propagating photon would be distorted in advance. Then, they “predistorted” the photon, so it was shaped in the best way possible to maximize emission and absorption as it was transmitted between modules.

When they implemented this optimized absorption protocol, they were able to show photon absorption efficiency greater than 60 percent. This absorption efficiency is high enough to prove that the resulting state at the end of the protocol is entangled, a major milestone in this demonstration.

The researchers are now working on improving the absorption efficiency by optimizing the path over which the photons propagate and making the protocol faster so there are fewer chances for errors to accumulate. They believe that their remote entanglement generation protocol can also be expanded to other kinds of quantum computers and bigger quantum internet systems.

This work was funded, in part, by the U.S. Army Research Office, the AWS Center for Quantum Computing, and the U.S. Air Force Office of Scientific Research.

Brain Tumor

“Revolutionizing Lymphoma Treatment: Enhanced CAR T Cell Therapy Shows Promise in Small Study”

A phase I study of a next-generation CAR T cell therapy showed a 52 percent complete remission rate for patients with relapsed/refractory lymphoma.

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The article describes a groundbreaking study that has shown promising results in treating lymphoma patients who have resisted multiple rounds of other cancer treatments, including commercially available CAR T cell therapies. The new enhanced CAR T cell therapy, dubbed huCART19-IL18, was found to be highly effective in 81% of patients and resulted in complete remission in 52%. This is a significant improvement over traditional CAR T cell therapies, which have been shown to result in long-term remission in only around 50% of patients.

The study, led by researchers at the University of Pennsylvania, used a new process that shortens the manufacturing time for the CAR T cells to just three days. This means that patients with aggressive, fast-growing cancers can begin CAR T cell therapy quicker than is currently possible with standard manufacturing times of nine to 14 days.

The addition of interleukin 18 (IL18) to the CAR T cells enhanced their ability to attack cancer cells and protected them from immune suppression and T cell exhaustion. The researchers also found that the type of CAR T cell therapy patients previously received may impact the efficacy of huCART19-IL18.

This study represents a significant development in the ongoing evolution of CAR T cell therapy, as it is the first time a cytokine-enhanced CAR T has been tested in patients with blood cancer. The researchers believe that incorporating cytokine secretion into CAR T cell design will have broad implications for enhancing cellular therapies, even beyond blood cancers.

The study has already led to several other clinical trials being planned, including studies for acute lymphocytic leukemia (ALL) and chronic lymphocytic leukemia (CLL). Another trial for non-Hodgkin’s lymphoma using a similar IL18-armored CAR T cell product is currently enrolling patients. On the manufacturing side, the team is partnering with a Penn spinout company to improve the process for how these CAR T cells are created and expanded in the laboratory before being reinfused into the patient.

Overall, this study has shown promise in treating lymphoma patients who have resisted multiple rounds of other cancer treatments, and further research is needed to fully understand its potential.

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Breast Cancer

Early Cancer Detection: New Algorithms Revolutionize Primary Care

Two new advanced predictive algorithms use information about a person’s health conditions and simple blood tests to accurately predict a patient’s chances of having a currently undiagnosed cancer, including hard to diagnose liver and oral cancers. The new models could revolutionize how cancer is detected in primary care, and make it easier for patients to get treatment at much earlier stages.

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Early Cancer Detection: New Algorithms Revolutionize Primary Care

Two groundbreaking predictive algorithms have been developed to help General Practitioners (GPs) identify patients who may have undiagnosed cancer, including hard-to-detect liver and oral cancers. These advanced models use information about a patient’s health conditions and simple blood tests to accurately predict their chances of having an undiagnosed cancer.

The National Health Service (NHS) currently uses algorithms like the QCancer scores to combine relevant patient data and identify individuals at high risk of having undiagnosed cancer, allowing GPs and specialists to call them in for further testing. Researchers from Queen Mary University of London and the University of Oxford have created two new algorithms using anonymized electronic health records from over 7.4 million adults in England.

The new models are significantly more sensitive than existing ones, potentially leading to better clinical decision-making and earlier cancer diagnosis. Crucially, these algorithms incorporate the results of seven routine blood tests as biomarkers to improve early cancer detection. This approach makes it easier for patients to receive treatment at much earlier stages, increasing their chances of survival.

Compared to the QCancer algorithms, the new models identified four additional medical conditions associated with an increased risk of 15 different cancers, including liver, kidney, and pancreatic cancers. The researchers also found two additional associations between family history and lung cancer and blood cancer, as well as seven new symptoms of concern (itching, bruising, back pain, hoarseness, flatulence, abdominal mass, dark urine) associated with multiple cancer types.

The study’s lead author, Professor Julia Hippisley-Cox, said: “These algorithms are designed to be embedded into clinical systems and used during routine GP consultations. They offer a substantial improvement over current models, with higher accuracy in identifying cancers – especially at early, more treatable stages.”

Dr Carol Coupland, senior researcher and co-author, added: “These new algorithms for assessing individuals’ risks of having currently undiagnosed cancer show improved capability of identifying people most at risk of having one of 15 types of cancer based on their symptoms, blood test results, lifestyle factors, and other information recorded in their medical records.”

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Brain Injury

Uncovering the Aggressive Nature of Glioblastoma: ZIP4’s Role in Brain Tumor Growth

Researchers detail their discoveries about why the brain tumor glioblastoma is so aggressive. Their findings center on ZIP4, a protein that transports zinc throughout the body and sets off a cascade of events that drive tumor growth.

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In a groundbreaking study published in the Proceedings of the National Academy of Sciences (PNAS), University of Oklahoma researchers have made a significant discovery about what makes glioblastoma, the deadliest form of brain cancer, so aggressive. The findings center on ZIP4, a protein that transports zinc throughout the body and sets off a chain reaction that drives tumor growth.

Glioblastomas account for about half of all malignant brain tumors, with a median survival rate of 14 months. Surgery is often challenging, and patients almost always experience a relapse. By better understanding why these brain tumors are so aggressive, researchers hope to open up paths for new treatments.

In normal conditions, ZIP4 plays a positive role, transporting and maintaining the right amount of zinc for good health. However, when brain cancer is present, ZIP4 takes on a different role. In the case of glioblastoma, it triggers a series of events that contribute to the tumor’s aggressive growth.

“Everything starts with the fact that ZIP4 is overexpressed in glioblastoma,” says senior author Min Li, Ph.D., a professor of medicine, surgery, and cell biology at the University of Oklahoma College of Medicine. “That triggers all these downstream events that help the tumor to grow.”

Li’s research team tested a small-molecule inhibitor that targets ZIP4 and TREM1, a protein involved in immune responses. The inhibitor attached to both proteins, stopping their actions and slowing tumor growth. This suggests that ZIP4 and TREM1 may be promising therapeutic targets.

Neurosurgeon Ian Dunn, M.D., executive dean of the OU College of Medicine and co-author of the study, says the findings are an encouraging step toward combating this debilitating cancer. “These results are really exciting in such a debilitating cancer. The hope and promise is to translate these findings to novel treatment approaches to improve the lives of our patients.”

This discovery is significant not only for glioblastoma but also for pancreatic cancer research, as ZIP4 has been a focus of Li’s work on this disease for many years. He found that overexpression of ZIP4 causes pancreatic cancer cells to be more resistant to chemotherapy and prompts tumor cells to transform themselves so they can stealthily travel to the body’s other organs.

The researchers hope that their findings will lead to new treatment approaches for glioblastoma and potentially other types of cancer, improving the lives of patients affected by these devastating diseases.

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