The James Webb Space Telescope (JWST) has unlocked the depths of interstellar space with unprecedented clarity, offering humanity a high-resolution window into the cosmos. Harnessing this newfound capability, an international team of researchers set out to investigate how polycyclic aromatic hydrocarbons (PAHs)—organic molecules and key players in cosmic chemistry—survive the harsh conditions of space and uncover the mechanism behind their resilience.
All humans who have ever lived were once each an individual cell, which then divided countless times to produce a body made up of about 10 trillion cells. These cells have busy lives, executing all kinds of dynamic movement: contracting every time we flex a muscle, migrating toward the site of an injury, and rhythmically beating for decades on end.
Cells are an example of active matter. As inanimate matter must burn fuel to move, like airplanes and cars, active matter is similarly animated by its consumption of energy. The basic molecule of cellular energy is adenosine triphosphate (ATP), which catalyzes chemical reactions that enable cellular machinery to work.
Caltech researchers have now developed a bioengineered coordinate system to observe the movement of cellular machinery. The research enables a better understanding of how cells create order out of chaos, such as during embryonic development or in the organized movements of chromosomes that are a prerequisite to faithful cell division.
Scientists from the Natural History Museum have unraveled the geological mysteries behind jadarite, a rare lithium-bearing mineral with the potential to power Europe’s green energy transition which, so far, has only been found in one place on Earth, Serbia’s Jadar Basin.
Discovered in 2004 and described by museum scientists Chris Stanley and Mike Rumsey, jadarite made headlines for its uncanny resemblance to the chemical formula of Kryptonite, the fictional alien mineral which depletes Superman’s powers. However, today its value is more economic and environmental, offering a high lithium content and lower-energy route to extraction compared to traditional sources like spodumene.
A team of researchers at the museum have uncovered why this white, nodular mineral is so rare. Their findings show that to form, jadarite must follow an exact set of geological steps in highly specific conditions. This involves a strict interplay between alkaline-rich terminal lakes, lithium-rich volcanic glass and the transformation of clay minerals into crystalline structures which are exceptionally rare.
Imagine being tasked with baking a soufflé, except the only instruction provided is an ingredient list without any measurements or temperatures.
It would likely take an enormous amount of time, effort and ingredients to bake the perfect soufflé. It would require trial and error—tweaking ingredient measurements, altering the temperature and baking duration—but what if you had a model that could predict the final product before anything ever went into the mixing bowl? It would not only save weeks’ worth of time and resources but could also provide useful details like why and how the soufflé rose and collapsed when it did or why the texture didn’t turn out how you expected.
Researchers at the Beckman Institute for Advanced Science and Technology aren’t quite baking soufflés. Instead, they developed a computational model that digs into the chemical “recipe” of polymer manufacturing to provide predictive control over how materials self-organize to give rise to new textures and properties.
IBM has just unveiled its boldest quantum computing roadmap yet: Starling, the first large-scale, fault-tolerant quantum computer—coming in 2029. Capable of running 20,000X more operations than today’s quantum machines, Starling could unlock breakthroughs in chemistry, materials science, and optimization.
According to IBM, this is not just a pie-in-the-sky roadmap: they actually have the ability to make Starling happen.
In this exclusive conversation, I speak with Jerry Chow, IBM Fellow and Director of Quantum Systems, about the engineering breakthroughs that are making this possible… especially a radically more efficient error correction code and new multi-layered qubit architectures.
We cover:
- The shift from millions of physical qubits to manageable logical qubits.
- Why IBM is using quantum low-density parity check (qLDPC) codes.
- How modular quantum systems (like Kookaburra and Cockatoo) will scale the technology.
- Real-world quantum-classical hybrid applications already happening today.
- Why now is the time for developers to start building quantum-native algorithms.
00:00 Introduction to the Future of Computing.
01:04 IBM’s Jerry Chow.
01:49 Quantum Supremacy.
02:47 IBM’s Quantum Roadmap.
04:03 Technological Innovations in Quantum Computing.
05:59 Challenges and Solutions in Quantum Computing.
09:40 Quantum Processor Development.
14:04 Quantum Computing Applications and Future Prospects.
20:41 Personal Journey in Quantum Computing.
24:03 Conclusion and Final Thoughts.
Rare methanol isotopes were found in young star HD 100453, offering new insights into the chemistry that could seed planets with life.
N6-methyladenosine (m6A) is the most common and abundant endogenous mRNA methylation in eukaryotic cells (Huang et al., 2020; Wang et al., 2014). The regulation of this modification is achieved through the coordinated action of three distinct protein groups. The “writers” (methyltransferase complex), which include METTL3, METTL14, and WTAP, are responsible for adding the m6A modification. In contrast, the “erasers” (demethylases), which consist of FTO and ALKBH5, remove this chemical mark. Lastly, the “readers,” a group of proteins including YTHDF1/2/3 and YTHDC1/2, recognize and bind to m6A-modified RNA, thereby modulating diverse RNA metabolic processes. The m6A reader proteins YTHDFs exhibit distinct canonical functional roles: YTHDF1 primarily boosts the efficiency of mRNA translation, YTHDF2 enhances mRNA degradation, and YTHDF3 exerts dual functions by supporting both translation and degradation of mRNA, with its role varying depending on the specific biological context (Roundtree et al., 2017; Shi et al., 2017; Wang et al., 2014; Wang et al., 2015; Zaccara et al., 2019). Recent studies have revealed that YTHDF proteins can influence the efficacy of RT through mechanisms, such as modulating DNA repair and shaping the tumor immune microenvironment (TIME) (Du et al., 2023; Shao et al., 2023; Shi et al., 2023; Wang et al., 2023a; Wang et al., 2023c; Wen et al., 2024a; Yin et al., 2023). Elucidating the functions and mechanisms of YTHDF proteins within the context of radiation biology holds significant potential for advancing therapeutic strategies in cancer RT.
This review provides an overview of recent progress in elucidating the mechanisms by which YTHDF proteins in tumor and immune cells modulate the therapeutic efficacy of RT. By synthesizing current knowledge on the functions of YTHDF proteins in the context of IR, we emphasize their indispensable role in shaping RT outcomes.
A team of chemists at the University of Cambridge has developed a powerful new method for adding single carbon atoms to molecules more easily, offering a simple one-step approach that could accelerate drug discovery and the design of complex chemical products.
The research, recently published in the journal Nature under the title “One-carbon homologation of alkenes,” unveils a breakthrough method for extending molecular chains—one carbon atom at a time. This technique targets alkenes, a common class of molecules characterized by a double bond between two carbon atoms. Alkenes are found in a wide range of everyday products, from anti-malarial medicines like quinine to agrochemicals and fragrances.
Led by Dr. Marcus Grocott and Professor Matthew Gaunt from the Yusuf Hamied Department of Chemistry at the University of Cambridge, the work replaces traditional multi-step procedures with a single-pot reaction that is compatible with a wide range of molecules.
Sarin (isopropyl methyl fluorophosphonate) is an organophosphorus nerve agent regulated by the Convention on the Banning of Chemical Weapons. It can enter the body through the respiratory system, skin, or eyes, paralyzing the central nervous system by inhibiting acetylcholinesterase, which can lead to death. Therefore, rapid and sensitive detection of trace sarin is vital for safety and environmental protection.
Due to its high toxicity, sarin’s use is strictly controlled, leading researchers to use diethyl chlorophosphate (DCP) as a safer simulant. The common fluorescence detection method takes advantage of DCP’s strong electrophilicity, using recognition sites like hydroxyl oxime and imine for fluorescence quenching to identify the target.
However, this method is affected by photobleaching, acid, and other environmental factors, limiting its application.
As artificial intelligence (AI) tools shake up the scientific workflow, Sam Rodriques dreams of a more systemic transformation. His start-up company, FutureHouse in San Francisco, California, aims to build an ‘AI scientist’ that can command the entire research pipeline, from hypothesis generation to paper production.
Today, his team took a step in that direction, releasing what it calls the first true ‘reasoning model’ specifically designed for scientific tasks. The model, called ether0, is a large language model (LLM) that’s purpose-built for chemistry, which it learnt simply by taking a test of around 500,000 questions. Following instructions in plain English, ether0 can spit out formulae for drug-like molecules that satisfy a range of criteria.
