Lifeboat Foundation

The lack of a universal platform for PROTAC development remains a major bottleneck. Here, the authors report modular DNA framework-based PROTACs (DbTACs) that enable precise control of the linker length and selective degradation of diverse targets in different cellular compartments using various warheads.

Researchers have used 3D nanotechnology to successfully grow human retinal cells, opening the door to a new way of treating age-related macular degeneration, a leading cause of blindness in the developed world.

In age-related macular degeneration (AMD), the macula, the part of the retina that controls sharp, straight-ahead vision, deteriorates and causes blurring in the central field of vision.

There are two types of AMD, ‘dry’ and ‘wet.’ Dry AMD is where the RPE cells in the macula break down, causing vision loss over time. It’s the most common type and mostly affects older people. In the rarer wet AMD, abnormal blood vessel growth into the macula causes fluid and blood leakage, damaging the retina and destruction of the RPE cells, leading to a rapid loss of vision.

Quantum memory that depends on quantum-band integration is a key building block used to develop quantum networks that are compatible with fiber communication infrastructures. Quantum engineers and IT specialists have yet to create such a network with large capacity to form an integrated multimode photonic quantum memory at telecom band.

In a new report in Science Advances, Xueying Zhang and a research team in electronic science, physics, and information technology described fiber-integrated multimode storage of a single photon at telecom band on a laser-written chip.

The storage device made of fiber-pigtailed erbium (Er³⁺) doped lithium niobate (Er³⁺:LiNbO₃), presented a memory system integrated with telecom-band fiber-integrated on-chip components. The outcomes of the study highlight a pathway for future quantum networks to come in to being, based on integrated photonics devices.

Other commentators, though, were not convinced. Noam Chomsky, a professor of linguistics, dismissed ChatGPT as “hi-tech plagiarism”.

For years, I was relaxed about the prospect of AI’s impact on human existence and our environment. That’s because I always thought of it as a guide or adviser to humans. But the prospect of AIs taking decisions – exerting executive control – is another matter. And it’s one that is now being seriously entertained.

One of the key reasons we shouldn’t let AI have executive power is that it entirely lacks emotion, which is crucial for decision-making. Without emotion, empathy and a moral compass, you have created the perfect psychopath. The resulting system may be highly intelligent, but it will lack the human emotional core that enables it to measure the potentially devastating emotional consequences of an otherwise rational decision.

We know that humans are an intelligent species. But this biologist breaks down the intelligence of each of our cells — and it will blow your mind.

Neurons are the cells that constitute neural circuits and use chemicals and electricity to receive and send messages that allow the body to do everything, including thinking, sensing, moving, and more. Neurons have a long fiber called an axon that sends information to the subsequent neurons. Information from axons is received by branch-like structures that fan out from the cell body, called dendrites.

Dendritic refinement is an important part of early postnatal brain development during which dendrites are tailored to make specific connections with appropriate axons. In a recently published paper, researchers present evidence showing how a mechanism within the neurons of a rodent involving the Golgi apparatus initiates dendritic refinement with the help of the neuronal activity received by a receptor of a neurotransmitter called N-methyl-D-aspartate-type glutamate receptor (NMDAR).

The paper was published in Cell Reports on July 28.

The Rydberg state is prevalent across various physical mediums such as atoms, molecules, and solid materials. Rydberg excitons, which are highly energized, Coulomb-bound electron-hole pair states, were initially identified in the 1950s within the semiconductor material, Cu2O.

In a study published in Science, Dr. Xu Yang and his colleagues from the Institute of Physics (IOP) of the Chinese Academy of Sciences (CAS), in collaboration with researchers led by Dr. Yuan Shengjun of Wuhan University, have reported observing Rydberg moiré excitons, which are moiré-trapped Rydberg excitons in the monolayer semiconductor WSe2 adjacent to small-angle twisted bilayer graphene.

Graphene is an allotrope of carbon in the form of a single layer of atoms in a two-dimensional hexagonal lattice in which one atom forms each vertex. It is the basic structural element of other allotropes of carbon, including graphite, charcoal, carbon nanotubes, and fullerenes. In proportion to its thickness, it is about 100 times stronger than the strongest steel.

On a rush-hour train or a crowded flight, you might draw your limbs in close, shrinking as people fill the space. As it turns out, living cells behave similarly in confinement, adjusting their size while growing alongside other cells in sheets of tissue.

John Devany, then a graduate student in the lab of biophysicist Margaret Gardel, had been studying epithelial monolayers—sheets of cells that form barriers in skin and coat internal organs —when he noticed something interesting about how the cells were dividing.

“The way people think about division is that a cell will grow to twice its size, divide, and repeat the cycle,” says Devany, the first author of the study, published in Developmental Cell. But in the epithelial tissue he was observing, division was proceeding as usual, but the daughter cells were ending up smaller than the mother. The team, collaborating with researchers from New York University, decided to investigate the mechanisms that control cell growth and cycle duration in tissue and discovered that the two processes are not directly coupled.

Technological advancements like autonomous driving and computer vision are driving a surge in demand for computational power. Optical computing, with its high throughput, energy efficiency, and low latency, has garnered considerable attention from academia and industry. However, current optical computing chips face limitations in power consumption and size, which hinders the scalability of optical computing networks.

Thanks to the rise of nonvolatile integrated photonics, optical computing devices can achieve in-memory computing while operating with zero static power consumption. Phase-change materials (PCMs) have emerged as promising candidates for achieving photonic memory and nonvolatile neuromorphic photonic chips. PCMs offer high refractive index contrast between different states and reversible transitions, making them ideal for large-scale nonvolatile optical computing chips.

While the promise of nonvolatile integrated optical computing chips is tantalizing, it comes with its share of challenges. The need for frequent and rapid switching, essential for online training, is a hurdle that researchers are determined to overcome. Forging a path towards quick and efficient training is a vital step on the journey to unleash the full potential of photonic computing chips.