One person is injured after glue factory explosion, which sparked school evacuations and road closures.
Category: chemistry – Page 103
A combined team of biomedical researchers from Novartis Institutes for Biomedical Research and Microsoft Research AI4Science has made inroads into teaching AI systems how to find new medicines. In their study, reported in the journal Nature Communications, the group used feedback from chemists in the field to provide intuition guidelines for an AI model.
Finding new medicines is a notoriously difficult and laborious task. The process for finding new therapies typically involves experts in a variety of fields working on different parts of the problem. Doctors and other medical researchers, for example, must first uncover the roots of a given illness to find its cause. Chemists or other medical researchers must then find a chemical that might reverse the problem or stop it from happening in the first place.
Both parts of the process take time and effort. In this new project, the research team sought to determine whether AI applications might make the second part easier.
Scientists at Oak Ridge National Laboratory have used their expertise in quantum biology, artificial intelligence and bioengineering to improve how CRISPR Cas9 genome editing tools work on organisms like microbes that can be modified to produce renewable fuels and chemicals.
CRISPR is a powerful tool for bioengineering, used to modify genetic code to improve an organism’s performance or to correct mutations. The CRISPR Cas9 tool relies on a single, unique guide RNA that directs the Cas9 enzyme to bind with and cleave the corresponding targeted site in the genome.
Existing models to computationally predict effective guide RNAs for CRISPR tools were built on data from only a few model species, with weak, inconsistent efficiency when applied to microbes.
In 2018, researchers reported that they had managed to get a coral larva to survive freezing and thawing for the first time. The scientists had added gold nanoparticles to their antifreeze to help the corals warm evenly during reheating. However, the thawed larvae were unable to settle and develop into adults. Instead, they kept swimming until they died.
When Narida began her experiments with hood corals in 2021, she included gold in her antifreeze recipe and combined several different antifreeze chemicals to reduce the solution’s toxicity. To thaw the animals quickly and minimize damage, Narida used a high-powered laser designed for welding jewelry. Then, she carefully washed the antifreeze away with seawater, rehydrating the corals. In the end, a whopping 11 percent of larvae in the experiment survived thawing, then settled, and developed into adults.
Leandro Godoy, a coral cryobiologist at the Federal University of Rio Grande do Sul in Brazil, is impressed by how many larvae survived after settling. “It’s a huge step,” he says, considering that, in the wild, only about five percent of corals make it that far.
An enzyme that may help some breast cancers spread can be stopped with an antibody created in the lab of Cold Spring Harbor Laboratory Professor Nicholas Tonks. With further development, the antibody might offer an effective drug treatment for those same breast cancers.
The new antibody targets an enzyme called PTPRD that is overabundant in some breast cancers. PTPRD belongs to a family of molecules known as protein tyrosine phosphatases (PTPs), which help regulate many cellular processes. They do this by working in concert with enzymes called kinases to control how other proteins inside cells behave. Kinases add small chemical regulators called phosphates to proteins. PTPs take them off.
Disruptions in the addition or removal of phosphates can contribute to inflammation, diabetes, and cancer. Some disruptions can be corrected with kinase-blocking drugs.
A new way to simulate supernovae may help shed light on our cosmic origins. Supernovae, exploding stars, play a critical role in the formation and evolution of galaxies. However, key aspects of them are notoriously difficult to simulate accurately in reasonably short amounts of time. For the first time, a team of researchers, including those from The University of Tokyo, apply deep learning to the problem of supernova simulation. Their approach can speed up the simulation of supernovae, and therefore of galaxy formation and evolution as well. These simulations include the evolution of the chemistry which led to life.
When you hear about deep learning, you might think of the latest app that sprung up this week to do something clever with images or generate humanlike text. Deep learning might be responsible for some behind-the-scenes aspects of such things, but it’s also used extensively in different fields of research. Recently, a team at a tech event called a hackathon applied deep learning to weather forecasting. It proved quite effective, and this got doctoral student Keiya Hirashima from the University of Tokyo’s Department of Astronomy thinking.
“Weather is a very complex phenomenon but ultimately it boils down to fluid dynamics calculations,” said Hirashima. “So, I wondered if we could modify deep learning models used for weather forecasting and apply them to another fluid system, but one that exists on a vastly larger scale and which we lack direct access to: my field of research, supernova explosions.”
Researchers at the University of Chicago’s Pritzker School of Molecular Engineering, led by Giulia Galli, have conducted a computational study predicting the conditions necessary to create specific spin defects in silicon carbide. These findings, detailed in a paper published in Nature Communications
<em> Nature Communications </em> is a peer-reviewed, open-access, multidisciplinary, scientific journal published by Nature Portfolio. It covers the natural sciences, including physics, biology, chemistry, medicine, and earth sciences. It began publishing in 2010 and has editorial offices in London, Berlin, New York City, and Shanghai.
Researchers have uncovered that proteins use a common chemical label as a shield to protect them from degradation, which in turn affects motility and aging. Proteins are key to all processes in our cells and understanding their functions and regulation is of major importance.
“For many years, we have known that nearly all human proteins are modified by a specific chemical group, but its functional impact has remained undefined,” says professor Thomas Arnesen at the Department of Biomedicine, University of Bergen.
Scientists from the University of California Davis (UC Davis) Comprehensive Cancer Center have recently published in Cell Death and Disease, identifying a critical protein that causes cells to die. The protein is described as an epitope, which is a section of the protein that is recognized by the immune system to activate a response. This epitope was distinctly found on the CD95 receptor, known to trigger programmed cell death. The report demonstrates a new mechanism to trigger cell death and provide further insight into improved disease treatments.
CD95 receptors, also referred to a “Fas”, are cell death receptors which are present on cell membranes. Once Fas is activated, it generates a signaling cascade which elicits cell death. The mechanism by which cells self-destruct has been an important research topic. By understanding cell death, scientists can generate better therapies for different diseases, including cancer.
Currently, cancer is treated by surgery, chemotherapy, or radiotherapy. Despite initial success, these treatments are unable to fully eradicate tumor cells. Immunotherapy is a new approach to target cancer. Immunotherapy refers to therapeutics modulating the immune system to elicit an effective immune response. This is a more indirect approach compared to lysing tumors with a chemical. One specific immunotherapy referred to as chimeric antigen receptor (CAR) T-cell therapy is a treatment in which T cells, or cytotoxic immune cells, are engineered to lyse tumor cells. Unfortunately, CAR T-cell therapy is limited due to the tumor’s ability to prevent T cell activation.
Awkward name aside, the Lexus LF-ZC Concept that debuted at the Japan Mobility Show last week is a very big deal. When it goes into production in 2026, it will be the first electric vehicle on an all-new, ground-up Toyota platform; will do some very next-level things with the company’s steer-by-wire technology; and an alleged 620 miles of electric range.
It is not, however, going to do that with some huge battery pack that weighs as much as an apartment building. Instead, it’s going to rely mostly on chemistry to deliver on those big range claims.
As part of the auto show festivities, Toyota invited several international media outlets, including InsideEVs, to Japan last week. There, the world’s largest automaker previewed a number of emerging technology concepts, including a simulated “manual transmission” for electric cars, an advanced in-car AI assistant and its EV battery plans for the next few years.