Male fruit flies don’t usually like each other. Socially, they reject their fellow males and zero in on the females they discern via chemical receptors—or so scientists thought.
New research from Cornell University biologists suggests the fruit fly’s visual system, not just chemical receptors, are deeply involved with their social behaviors. The work sheds light on the possible origin of differences in human social behaviors, such as those seen in people with bipolar disorder and autism.
A study of a genetic mouse model of schizophrenia supports two long-debated hypotheses, and unveils additional new clues about the biological roots of the disorder.
Active matter is any collection of materials or systems composed of individual units that can move on their own, thanks to self-propulsion or autonomous motion. They can be of any size—think clouds of bacteria in a petri dish, or schools of fish.
Roman Grigoriev is mostly interested in the emergent behaviors in active matter systems made up of units on a molecular scale—tiny systems that convert stored energy into directed motion, consuming energy as they move and exert mechanical force.
“Active matter systems have garnered significant attention in physics, biology, and materials science due to their unique properties and potential applications,” Grigoriev, a professor in the School of Physics at Georgia Tech, explains.
A molecular assembler, as defined by K. Eric Drexler, is a “proposed device able to guide chemical reactions by positioning reactive molecules with atomic precision”. A molecular assembler is a kind of molecular machine. Some biological molecules such as ribosomes fit this definition. This is because they receive instructions from messenger RNA and then assemble specific sequences of amino acids to construct protein molecules. However, the term “molecular assembler” usually refers to theoretical human-made devices.
Beginning in 2007, the British Engineering and Physical Sciences Research Council has funded development of ribosome-like molecular assemblers. Clearly, molecular assemblers are possible in this limited sense. A technology roadmap project, led by the Battelle Memorial Institute and hosted by several U.S. National Laboratories has explored a range of atomically precise fabrication technologies, including both early-generation and longer-term prospects for programmable molecular assembly; the report was released in December, 2007. In 2008 the Engineering and Physical Sciences Research Council provided funding of 1.5 million pounds over six years for research working towards mechanized mechanosynthesis, in partnership with the Institute for Molecular Manufacturing, amongst others. Likewise, the term “molecular assembler” has been used in science fiction and popular culture to refer to a wide range of fantastic atom-manipulating nanomachines, many of which may be physically impossible in reality. Much of the controversy regarding “molecular assemblers” results from the confusion in the use of the name for both technical concepts and popular fantasies. In 1992, Drexler introduced the related but better-understood term “molecular manufacturing”, which he defined as the programmed “chemical synthesis of complex structures by mechanically positioning reactive molecules, not by manipulating individual atoms”.This article mostly discusses “molecular assemblers” in the popular sense. These include hypothetical machines that manipulate individual atoms and machines with organism-like self-replicating abilities, mobility, ability to consume food, and so forth. These are quite different from devices that merely (as defined above) “guide chemical reactions by positioning reactive molecules with atomic precision”. Because synthetic molecular assemblers have never been constructed and because of the confusion regarding the meaning of the term, there has been much controversy as to whether “molecular assemblers” are possible or simply science fiction. Confusion and controversy also stem from their classification as nanotechnology, which is an active area of laboratory research which has already been applied to the production of real products; however, there had been, until recently, no research efforts into the actual construction of “molecular assemblers”. Nonetheless, a 2013 paper by David Leigh’s group, published in the journal Science, details a new method of synthesizing a peptide in a sequence-specific manner by using an artificial molecular machine that is guided by a molecular strand. This functions in the same way as a ribosome building proteins by assembling amino acids according to a messenger RNA blueprint. The structure of the machine is based on a rotaxane, which is a molecular ring sliding along a molecular axle. The ring carries a thiolate group which removes amino acids in sequence from the axle, transferring them to a peptide assembly site. In 2018, the same group published a more advanced version of this concept in which the molecular ring shuttles along a polymeric track to assemble an oligopeptide that can fold into a α-helix that can perform the enantioselective epoxidation of a chalcone derivative (in a way reminiscent to the ribosome assembling an enzyme). In another paper published in Science in March 2015, chemists at the University of Illinois report a platform that automates the synthesis of 14 classes of small molecules, with thousands of compatible building blocks. In 2017 David Leigh’s group reported a molecular robot that could be programmed to construct any one of four different stereoisomers of a molecular product by using a nanomechanical robotic arm to move a molecular substrate between different reactive sites of an artificial molecular machine. An accompanying News and Views article, titled ‘A molecular assembler’, outlined the operation of the molecular robot as effectively a prototypical molecular assembler.
If modern artificial intelligence has a founding document, a sacred text, it is Google’s 2017 research paper “Attention Is All You Need.” This paper introduced a new deep learning architecture known as the transformer, which has gone on to revolutionize the field of AI over the past half-decade.
The generative AI mania currently taking the world by storm can be traced directly to the invention of the transformer. Every major AI model and product in the headlines today—ChatGPT, GPT-4, Midjourney, Stable Diffusion, GitHub Copilot, and so on—is built using transformers.
In a recently published article featured on the cover of the Biophysical Journal, Dr. Rafael Bernardi, assistant professor of biophysics at the Department of Physics at Auburn University, and Dr. Marcelo Melo, a postdoctoral researcher in Dr. Bernardi’s group, shed light on the transformative capabilities of the next generation of supercomputers in reshaping the landscape of biophysics.
The researchers at Auburn delve into the harmonious fusion of computational modeling and experimental biophysics, providing a perspective for a future in which discoveries are made with unparalleled precision. Rather than being mere observers, today’s biophysicists, with the aid of advanced high-performance computing (HPC), are now trailblazers who can challenge longstanding biological assumptions, illuminate intricate details, and even create new proteins or design novel molecular circuits.
One of the most important aspects discussed in their perspective article is the new ability of computational biophysicists to simulate complex biological processes that range from the subatomic to whole-cell models, in extraordinary detail.
Rice University scientists are starting small as they begin to figure out how to build an artificial brain from the bottom up.
Electrical and computer engineer Jacob Robinson of Rice’s Brown School of Engineering and Celina Juliano, an assistant professor of molecular and cellular biology at the University of California, Davis, have won a $1 million Keck Foundation grant to advance the team’s synthetic neurobiology effort to define the connections between neurons and muscles that drive programmed behaviors in living animals.
To begin with, Robinson and his colleagues are putting their faith in a very small animal, the freshwater cnidarian Hydra vulgaris, a tiny tentacled creature that has long been a focus of study in the Robinson and Juliano labs. Because they are small, squishy and transparent, they’re easy to manipulate and measure through Robinson’s custom microfluidic platforms.
A neonatal hypoxic-injury animal model revealed that CK2α mediated Daam2 phosphorylation, which plays a protective role in developmental and behavioral recovery after neonatal hypoxia, a form of brain injury seen in cerebral palsy and other conditions. Additionally, it facilitates remyelination after white matter injury in adult animals.
Together, these findings have identified a novel regulatory node connecting CK2α and Daam2 in the Wnt pathway that regulates stage-specific oligodendrocyte development and offers insights into a new biological mechanism to regenerate myelin.
“This study opens exciting therapeutic avenues we could develop in the future to repair and restore myelin, which has the potential to alleviate and treat several neurological issues that are currently untreatable,” Lee said.
Researchers from Queen Mary University of London have made a discovery that could change our understanding of the universe. In their study published on August 23 in the journal Science Advances.
<em>Science Advances</em> is a peer-reviewed, open-access scientific journal that is published by the American Association for the Advancement of Science (AAAS). It was launched in 2015 and covers a wide range of topics in the natural sciences, including biology, chemistry, earth and environmental sciences, materials science, and physics.
