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Living matter remains the quintessential puzzle of biological sciences, a question that embodies the intricate complexity and stunning diversity of life forms. A new study suggests that one viable approach to address this extreme complexity is to conceptualize living matter as a cascade of machines producing machines.

This cascade illustrates how cells are composed of smaller submachines, reaching down to the where molecular machines, such as ion pumps and enzymes, operate. In the other direction, it explains how cells self-organize into larger systems, such as tissues, organs, and populations, cumulating into the biosphere.

This new conceptual framework is a fruit of collaboration between Professors Tsvi Tlusty from the Department of Physics at Ulsan National Institute of Science and Technology (UNIST), South Korea, and Albert Libchaber from the Center for Physics and Biology at Rockefeller University, New York. The study was inspired by the seventeenth-century polymath Gottfried Leibniz, who noted that “the machines of nature, that is living bodies, are still machines in their smallest parts, to infinity.”

The structural design of molecular machines and motors endows them with externally controlled directional motion at the molecular scale. Molecular machines based on both interlocked and non-interlocked molecules and driven by a variety of external stimuli such as light, electrical-or thermal energy, and chemical-or redox processes have been reported. With the field moving forward, they were incorporated into surfaces and interfaces to realize amplified directional molecular motion at the nanoscale which can be applied in the control of macroscopic material properties. More recently, molecular motors and molecular machines based on interlocked molecules have been organized into three dimensional materials to expand their functionality in the solid state and enrich their applicability.

Cis-trans photoisomerization is a key process for many processes in biology and materials science, but only careful and time-consuming quantum chemistry methods can describe such reaction in detail. Here, a predictive tool is presented requiring few and affordable calculations, evaluating the efficiency of paradigmatic and modified photoswitches.

Organic photoredox catalysts enable diverse chemical transformations, but predicting their activity is challenging due to complex properties. Now, a two-step data-driven approach is introduced for targeted organic photoredox catalysts synthesis and reaction optimization. Using Bayesian optimization, promising catalysts can be efficiently identified, yielding competitive results with iridium catalysts.

Computational chemistry has remained largely inaccessible to the experimental chemistry community. Here we report the VIRTUAL CHEMIST, a software suite free for academic use, that enables organic chemists without expertise in computational chemistry to perform virtual screening experiments for asymmetric catalyst discovery and design.

A new study has revealed the universe is expanding too quickly for our current understanding of physics to explain.

The expansion of the universe is described using a unit of measurement called the Hubble constant. Determining the universe’s expansion rate has been a major point of intrigue since 1929, when Edwin Hubble first discovered that our universe is expanding.

The universe began with the Big Bang, a rapid expansion from an initial state of high density and pressure.

OpenAI chief Sam Altman on Friday said his high-profile artificial intelligence company is “on the wrong side of history” when it comes to being open about how its technology works.

Altman’s comments came during an Ask Me Anything session on Reddit where he fielded questions including whether he would consider publishing OpenAI research.

Altman replied he was in favor of the idea and that it is a topic of discussion inside San Francisco-based OpenAI.

Panzeri et al. use a Trim28 +/D9 mouse model with intrinsic developmental heterogeneity to show that ‘heavy’ and ‘light’ developmental morphs exhibit different timing, type and severity of cancer, linked to a relevant DNA hypomethylation signature.