Lifeboat Foundation

Challenging physics beliefs: Oxford study shows like-charged particles can attract each other over long distances in certain solvents.

Learn all about the difference between regular pneumonia and walking pneumonia in kids and when to take your child to the doctor.

Researchers in Lithuania present the molecular structure of a new, more-versatile CRISPR system for gene editing.

Cooling systems are an integral part of many modern technologies, as heat tends to wear down materials and decrease performance in several ways. In many cases, however, cooling can be an inconvenient and energy-intensive process. Accordingly, scientists have been seeking innovative and efficient methods to cool substances down.

Solid-state optical cooling is a prominent example that leverages a very unique phenomenon called anti-Stokes (AS) emission. Usually, when materials absorb photons from incoming light, their electrons transition into an “excited” state.

Under ideal conditions, as electrons return to their original state, part of this excess energy is released as light, while the rest is converted into heat.

On a cool morning this summer, I visited a former shopping mall in Mountain View, California, that is now a Google office building. On my way inside, I passed a small museum of the company’s past “moonshots,” including Waymo’s first self-driving cars. Upstairs, Jonathan Tompson and Danny Driess, research scientists in Google DeepMind’s robotics division, stood in the center of what looked like a factory floor, with wires everywhere.

At a couple of dozen stations, operators leaned over tabletops, engaged in various kinds of handicraft. They were not using their own hands—instead, they were puppeteering pairs of metallic robotic arms. The setup, known as ALOHA, “a low-cost open-source hardware system for bimanual teleoperation,” was once Zhao’s Ph.D. project at Stanford. At the end of each arm was a claw that rotated on a wrist joint; it moved like the head of a velociraptor, with a slightly stiff grace. One woman was using her robotic arms to carefully lower a necklace into the open drawer of a jewelry case. Behind her, another woman prized apart the seal on a ziplock bag, and nearby a young man swooped his hands forward as his robotic arms folded a child’s shirt. It was close, careful work, and the room was quiet except for the wheeze of mechanical joints opening and closing. “It’s quite surprising what you can and can’t do with parallel jaw grippers,” Tompson said, as he offered me a seat at an empty station. “I’ll show you how to get started.”

A novel device consisting of metal, dielectric, and metal layers remembers the history of electrical signals sent through it. This device, called a memristor, could serve as the basis for neuromorphic computers-;computers that work in ways similar to human brains. Unlike traditional digital memory, which stores information as 0s and 1s, this device exhibits so-called “analog” behavior. This means the device can store information between 0 and 1, and it can emulate how synapses function in the brain. Researchers found that the interface between metal and dielectric in the novel device is critical for stable switching and enhanced performance. Simulations indicate that circuits built on this device exhibit improved image recognition.

The Impact

Today’s computers are not energy efficient for big data and machine learning tasks. By 2030, experts predict that data centers could consume about 8% of the world’s electricity. To address this challenge, researchers are working to create computers inspired by the human brain, so-called neuromorphic computers. Artificial synapses created with memristor devices are the building blocks of these computers. These artificial synapses can store and process information in the same location, similar to how neurons and synapses work in the brain. Integrating these emergent devices with conventional computer components will reduce power needs and improve performance for tasks such as artificial intelligence and machine learning.

Expression of co-inhibitory receptors or “checkpoint” molecules, such as CTLA-4 and PD-1, on effector T cells is a key mechanism for ensuring immune homeostasis. Dysregulated expression of co-inhibitory receptors on CD4+ T cells promotes autoimmunity while sustained overexpression on CD8+ T cells promotes T cell dysfunction or exhaustion, leading to impaired ability to clear chronic viral infections and cancer. Immune checkpoint blockade (ICB) treatment by blocking CTLA-4 and PD-1 has revolutionized cancer therapies, yet current ICB response rates are still relatively low. This suggests the need to discover novel checkpoint molecules and cell types where checkpoint molecules may be exerting additional or differential effects. We and others have discovered additional checkpoint molecules, including Tim-3, Lag-3, and TIGIT. Using RNA and protein expression profiling at single-cell resolution, we discovered that the checkpoint molecules are expressed as a module that is co-expressed and co-regulated on CD8+ T cells, where they cooperatively induce T cell dysfunction. The same module of checkpoint molecules is also expressed on FoxP3+ Tregs, but their role in regulating immunity and anti-tumor immunity has not been fully appreciated. We have conditionally deleted checkpoint molecules on various cell types including Foxp3+ Tregs and studied their role in regulating autoimmunity, tumor growth, and anti-tumor immunity. Studies with a number of the co-inhibitory molecules on effector T cells, Tregs, and dendritic cells in regulating anti-tumor immunity will be discussed.

Learning Objectives

A nasal spray drug can counteract the cognitive decline and brain damage typical of Alzheimer’s disease in animal models.

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