Lifeboat Foundation

For instance, the pegRNA molecules used in prime editing are difficult and expensive to chemically synthesise or laborious to clone, which hampers the crucial optimisation of prime-editing efficiency. Additionally, the reverse transcriptase (RT) enzymes used in prime editing are relatively error-prone and have low processivity, which may limit the precision and size of edits that can be introduced. Furthermore, RTs have a low affinity for dNTPs, which can impact prime-editing efficiency in non-dividing and differentiated cells.

To address these issues, two research groups led by Dr. Ben Kleinstiver at Mass General Hospital (MGH) & Harvard Medical School, and Dr. Erik Sontheimer at the RNA Therapeutics Institute (UMass Chan Medical School) have independently developed new approaches that build upon prime editing by replacing RT with another type of enzyme, namely a DNA-dependent DNA polymerase. This change permits the use of DNA instead of RNA as a template for editing, potentially addressing some of the main limitations of prime editing by allowing higher efficiency and adaptability.

Signal processing is key to communications and video image processing for astronomy, medical diagnosis, autonomous driving, big data and AI. Menxi Tan and colleagues report a photonic processor operating at 17Tb/s for ultrafast robotic vision and machine learning.

A research team led by Prof. Sun Zhong at Peking University has reported an analog hardware solution for real-time compressed sensing recovery. It has been published as an article titled, “In-memory analog solution of compressed sensing recovery in one step” in Science Advances.

In this work, a design based on a resistive memory (also known as memristor) array for performing instantaneous matrix-matrix-vector multiplication (MMVM) is introduced. Based on this module, an analog matrix computing circuit that solves compressed sensing (CS) recovery in one step (within a few microseconds) is disclosed.

CS has been the cornerstone of modern signal and image processing, across many important fields such as medical imaging, wireless communications, object tracking, and single-pixel cameras. In CS, sparse signals can be highly undersampled in the front-end sensor, which breaks through the Nyquist rate and thus significantly improving sampling efficiency.

A game-changer in prosthetics has been introduced to the world, and for the first time, amputees are regaining sensation through an electrical signal from their prosthetic arm. Max Ortiz-Catalan, a professor of bionics, explains the process of implanting these mind-controlled bionic arms through direct skeletal attachment. The researcher takes us through every step of this groundbreaking advancement in bionic medicine, from surgically implanting electrodes to fitting the prosthesis and training for everyday use.\r\
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Harvard researchers have realized a key milestone in the quest for stable, scalable quantum computing, an ultra-high-speed technology that will enable game-changing advances in a variety of fields, including medicine, science, and finance.

The team, led by Mikhail Lukin, the Joshua and Beth Friedman University Professor in physics and co-director of the Harvard Quantum Initiative, has created the first programmable, logical quantum processor, capable of encoding up to 48 logical qubits, and executing hundreds of logical gate operations, a vast improvement over prior efforts.

Published in Nature, the work was performed in collaboration with Markus Greiner, the George Vasmer Leverett Professor of Physics; colleagues from MIT; and QuEra Computing, a Boston company founded on technology from Harvard labs.

Scientists have now leveraged deep learning to discover a new class of compounds that can kill a drug-resistant bacterium.

Using deep learning models, scientists have identified a new class of antibiotic compounds that can work against resistant strains like MRSA.

A team of international scientists have developed an ultra-high speed signal processor that can analyze 400,000 real time video images concurrently, according to a paper published in Communications Engineering.

The team, led by Swinburne University of Technology’s Professor David Moss, have developed a processor that operates more than 10,000 times faster than typical electronic processors that operate in Gigabyte/s, at a record 17 Terabits/s (trillion bits per second).

The technology has profound implications for the safety and efficiency of driverless cars, medical imaging and could help find habitable planets beyond our solar system.

A system called Coscientist scours the Internet for instructions, then designs and executes experiments to synthesize molecules.

A “chaperone” molecule that slows the formation of certain proteins reversed disease signs, including memory impairment, in a mouse model of Alzheimer’s disease, according to a study from researchers at the Perelman School of Medicine at the University of Pennsylvania.

In the study, published in Aging Biology, researchers examined the effects of a compound called 4-phenylbutyrate (PBA), a fatty-acid molecule known to work as a “chemical chaperone” that inhibits protein accumulation. In mice that model Alzheimer’s disease, injections of PBA helped to restore signs of normal proteostasis (the protein regulation process) in the animals’ brains while also dramatically improving their performance on a standard memory test, even when administered late in the disease course.

“By generally improving neuronal and cellular health, we can mitigate or delay disease progression,” said study senior author Nirinjini Naidoo, Ph.D., a research associate professor of Sleep Medicine. “In addition, reducing proteotoxicity— irreparable damage to the cell that is caused by an accumulation of impaired and misfolded proteins—can help improve some previously lost brain functions.”