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A s the world moves away from gas towards electricity as a greener power source, the to-do list goes beyond cars. The vast global manufacturing network that makes everything from our batteries to our fertilizers needs to flip the switch, too.

A study from UChicago chemists found a way to use electricity to boost a type of chemical reaction often used in synthesizing new candidates for pharmaceutical drugs.

Published Jan. 2 in Nature Catalysis, the research is an advance in the field of electrochemistry and shows a path forward to designing and controlling reactions—and making them more sustainable.

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Microbes living in our guts ooze a substance that could help protect us against excessive weight gain, according to observations in mice.

The bacteria-derived compound may explain why early exposure to antibiotics can play a role in childhood obesity, a condition which is rising globally.

Vanderbilt University biochemist Catherine Shelton and colleagues discovered this by giving young mice a high or low fat diet, with or without exposure to antibiotics. Mice only given penicillin antibiotics did not gain weight, but those also on a high fat diet did.

In a new study published in Cancer Cell, YSM researchers at Yale Cancer Center find immunotherapy could benefit thousands of additional patients with colorectal and endometrial cancers who are not currently being offered it:


A new study shows thousands more patients diagnosed with colorectal and endometrial cancers could benefit from immunotherapy than are currently offered it. Researchers showed the importance of looking at DNA Mismatch Repair Deficiency (MMR-D) as a guiding marker for treatment decisions using immune checkpoint inhibitors (ICIs). MMR-D is associated with an increased risk of developing several types of cancer and is the most common cause of hereditary endometrial cancer.

The study, which published in Cancer Cell on December 28, compared two lab testing methods to diagnose cancers— traditional immunohistochemistry (IHC) (a lab technique that uses antibodies to detect antigens in tissues) and next-generation sequencing (NGS) — a new technology used for DNA sequencing that can detect specific patterns of mutations. The researchers discovered that NGS offers a more accurate assessment of MMR status.

Scientists at the Max Planck Institute have developed a synthetic pathway that can capture CO2 from the air more efficiently than in nature, and shown how to implement it into living bacteria. The technique could help make biofuels and other products in a sustainable way.

Plants are famous for their ability to convert carbon dioxide from the air into chemical energy to fuel their growth. With way too much CO2 in the atmosphere already and more being blasted out every day, it’s no wonder scientists are turning to this natural process to help rein levels back in, while producing fuels and other useful molecules on the side.

In the new study, Max Planck scientists developed a brand new CO2-fixation pathway that works even better than nature’s own tried-and-true method. They call it the THETA cycle, and it uses 17 different biocatalysts to produce a molecule called acetyl-CoA, which is a key building block in a range of biofuels, materials and pharmaceuticals.

READ MORE: Suspected cyberattack renders most gas stations in Iran out of service

The hacking of the Municipal Water Authority of Aliquippa is prompting new warnings from U.S. security officials at a time when states and the federal government are wrestling with how to harden water utilities against cyberattacks.

The danger, officials say, is hackers gaining control of automated equipment to shut down pumps that supply drinking water or contaminate drinking water by reprogramming automated chemical treatments. Besides Iran, other potentially hostile geopolitical rivals, including China, are viewed by U.S. officials as a threat.

Artificial intelligence (AI) has been advancing rapidly, but its inner workings often remain obscure, characterized by a “black box” nature where the process of reaching conclusions is not visible. However, a significant breakthrough has been made by Prof. Dr. Jürgen Bajorath and his team, cheminformatics experts at the University of Bonn. They have devised a technique that uncovers the operational mechanisms of certain AI systems used in pharmaceutical research.

Surprisingly, their findings indicate that these AI models primarily rely on recalling existing data rather than learning specific chemical interactions for predicting the effectiveness of drugs. Their results have recently been published in Nature Machine Intelligence.

Which drug molecule is most effective? Researchers are feverishly searching for efficient active substances to combat diseases. These compounds often dock onto protein, which usually are enzymes or receptors that trigger a specific chain of physiological actions.

Integrating large language models (LLMs) into various scientific domains has notably reshaped research methodologies. Among these advancements, an innovative system named Coscientist has emerged, as outlined in the paper “Autonomous chemical research with large language models,” authored by researchers from Carnegie Mellon University and Emerald Cloud Lab. This groundbreaking system, powered by multiple LLMs, is a pivotal achievement in the convergence of language models and laboratory automation technologies.

Coscientist comprises several intricately designed modules, with its cornerstone being the ‘Planner.’ This module operates using a GPT-4 chat completion instance, functioning as an interactive assistant capable of understanding user commands such as ‘GOOGLE,’ ‘PYTHON,’ ‘DOCUMENTATION,’ and ‘EXPERIMENT.’ Additionally, the ‘Web Searcher’ module, fueled by GPT-4, significantly enhances synthesis planning. Notably, it has exhibited exceptional performance in trials involving acetaminophen, aspirin, nitroaniline, and phenolphthalein. The ‘Code execution’ module, triggered by the ‘PYTHON’ command, facilitates experiment preparation calculations. Meanwhile, the ‘Automation’ command, guided by the ‘DOCUMENTATION’ module, implements experiment automation via APIs.

The prowess of the GPT-4-powered Web Searcher module in synthesis planning is evident in its success across diverse trials, demonstrating a capacity for efficient exploration and decision-making in chemical synthesis. Furthermore, the documentation search module equips Coscientist with the ability to utilize tailored technical documentation efficiently, enhancing its API utilization accuracy and improving overall experiment automation performance.

In a comprehensive review, researchers from Soochow University, Beijing Graphene Institute and Xiamen Silan Advanced Compound Semiconductor Co., Ltd. have collaborated to provide a systematic overview of the progress and potential applications of graphene as a buffer layer for nitride epitaxial growth.

The paper brings together perspectives from academia, , and semiconductor industry professionals to propose solutions for critical issues in semiconductor technology.

Graphene, a two-dimensional material known for its exceptional electrical and , has garnered significant interest for its prospective use in the growth of nitride semiconductors. Despite notable advancements in the (CVD) growth of graphene on various insulating substrates, producing and achieving optimal interface compatibility with Group III-nitride materials remain major challenges in the field.