Lifeboat Foundation

Microbial sequence databases contain a wealth of information about enzymes and other molecules that could be adapted for biotechnology. But these databases have grown so large in recent years that they’ve become difficult to search efficiently for enzymes of interest.

Now, scientists at the Broad Institute of MIT and Harvard, the McGovern Institute for Brain Research at MIT, and the National Center for Biotechnology Information (NCBI) at the National Institutes of Health have developed a new search algorithm that has identified 188 kinds of new rare CRISPR systems in bacterial genomes, encompassing thousands of individual systems. The work appears in Science.

The algorithm, which comes from the lab of CRISPR pioneer Feng Zhang, uses big-data clustering approaches to rapidly search massive amounts of genomic data. The team used their algorithm, called Fast Locality-Sensitive Hashing-based clustering (FLSHclust) to mine three major public databases that contain data from a wide range of unusual bacteria, including ones found in coal mines, breweries, Antarctic lakes, and dog saliva.

Cell toxicity and genomic instability are potential side effects from the use of CRISPR-Cas9. The gene editing tool can also cause large rearrangements of DNA through retrotransposition to theoretically trigger tumor development.

While rare, the fact that CRISPR is used to edit millions of cells for some therapies means precautionary steps are warranted given the potential increase in cancer risk. However, retrotransposition is much rarer during base editing, a more precise technique that chemically changes just one “letter” of the genetic code without causing a double-strand break in DNA.

Although MHRA decided that the benefits of Casgevy outweigh its risks, the U.K. regulator granted a one-year conditional marketing authorization of the world-first gene therapy based on the findings of two global clinical trials, noting that no significant safety concerns were identified during the trials.

University of Missouri researchers’ conceptual design of a nanomaterial could potentially pave the way for new uses of nanotechnology in medicine and science.

In a recent study, scientists at the University of Missouri developed a proof of concept for a nanocapsule — a microscopic container — capable of delivering a specific “payload” to a targeted location.

While beyond the scope of this study, the discovery has the potential to revolutionize the delivery of drugs, nutrients, and other chemicals in humans and plants. The power of the forward-thinking idea for this tiny delivery mechanism comes from its inventive structure, said Gary Baker, an associate professor in the Department of Chemistry and study co-author.

In a recent study published in Nature Communications, researchers aimed to develop a model of rumination, a mental process characterized by persistent negative self-reflective thoughts that can lead to depression and anxiety. Using resting-state functional magnetic resonance imaging (rsfMRI) — a technique that captures brain activity when a person is at rest — they identified a specific region of the brain, the dorsal medial prefrontal cortex (dmPFC), as playing a pivotal role in these ruminative thoughts.

Recognizing that rumination can be an early risk factor for depression, the researchers aimed to develop methods for subclinical detection and intervention before clinical episodes of depression occur. Early detection and intervention can be crucial for preventing the development of more severe mental health conditions.

The default mode network (DMN), a large-scale resting-state network, had been consistently linked to rumination in previous research. But the precise brain regions responsible for variations in individual levels of rumination have remained elusive. The researchers wanted to investigate the specific role of the DMN and its subsystems in rumination, as it is involved in various processes related to self-referential thought, autobiographical memory, emotional experience, and more.

An algorithm that can analyse hundreds of millions of genetic sequences has identified DNA-cutting genes and enzymes that are extremely rare in nature.

Human chromosomes are long polymer chains that store genetic information. The nucleus of each cell contains the entire human genome (DNA) encoded on 46 chromosomes with a total length of about 2 meters. To fit into the microscopic cell nucleus and at the same time provide constant access to genetic information, chromosomes are folded in the nucleus in a special, predetermined way. DNA folding is an urgent task at the intersection of polymer physics and systems biology.

A few years ago, as one of the mechanisms of chromosome folding, researchers put forward a hypothesis of active extrusion of loops on chromosomes by molecular motors. Although the ability of motors to extrude DNA in vitro has been demonstrated, observing loops in a living cell experimentally is a technically very difficult, almost impossible, task.

A team of scientists from Skoltech, MIT, and other leading scientific organizations in Russia and the U.S. have presented a physical model of a polymer folded into loops. The analytical solution of this model allowed scientists to reproduce the universal features of chromosome packing based on the experimental data—the image shows the peak-dip derivative curve of the contact probability.

Biological computing machines, such as micro and nano-implants that can collect important information inside the human body, are transforming medicine. Yet, networking them for communication has proven challenging. Now, a global team, including EPFL researchers, has developed a protocol that enables a molecular network with multiple transmitters.

First, there was the Internet of Things (IoT) and now, at the interface of computer science and biology, the Internet of Bio-Nano Things (IoBNT) promises to revolutionize medicine and health care. The IoBNT refers to biosensors that collect and process data, nano-scale Labs-on-a-Chip that run medical tests inside the body, the use of bacteria to design biological nano-machines that can detect pathogens, and nano-robots that swim through the bloodstream to perform targeted drug delivery and treatment.

“Overall, this is a very, very exciting research field,” explained Assistant Professor Haitham Al Hassanieh, head of the Laboratory of Sensing and Networking Systems in EPFL’s School of Computer and Communication Sciences (IC). “With advances in bio-engineering, synthetic biology, and nanotechnology, the idea is that nano-biosensors will revolutionize medicine because they can reach places and do things that current devices or larger implants can’t,” he continued.

The COVID-19 pandemic supply shortfalls and geopolitical issues cast a bright light on the decline of semiconductor manufacturing in the United States, down from 37 percent of the global total in 1993 to about 12 percent now. The Creating Helpful Incentives to Produce Semiconductors and Science Act of 2022 (CHIPS Act) directed $280 billion in spending, with the bulk on scientific research and development.

America needs better computer chips.

Mobile devices are ubiquitous; we carry them around in a pocket or purse and use them for everyday tasks. However, they are connected to centralized servers and thus cannot learn much about or adjust to their complicated and changing environments independently.

They are faster than ambulances in situations where timing is key.

Karolinska Institutet researchers have been investigating the idea of sending drones equipped with automated external defibrillators (AEDs) to patients in cardiac arrest instead of ambulances and have now found that, in more than half of the cases, the drones were three minutes ahead of the vehicles. In addition, in the majority of cases where the patient was in cardiac arrest, the drone-delivered defibrillator was employed to stop the condition from getting worse or leading to death.

The most simple factor

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