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Category: biological

Mushrooms and other kinds of fungi are often associated with witchcraft and are the subjects of longstanding superstitions. Witches dance inside fairy rings of mushrooms according to German folklore, while a French fable warns that anyone foolish enough to step inside these ‘sorcerer’s rings’ will be cursed by enormous toads with bulging eyes. These impressions come from the poisonous and psychoactive peculiarities of some species, as well as the overnight appearance of toadstool ring-formations.

Given the magical reputation of the fungi, claiming that they might be conscious is dangerous territory for a credentialled scientist. But in recent years, a body of remarkable experiments have shown that fungi operate as individuals, engage in decision-making, are capable of learning, and possess short-term memory. These findings highlight the spectacular sensitivity of such ‘simple’ organisms, and situate the human version of the mind within a spectrum of consciousness that might well span the entire natural world.

Before we explore the evidence for fungal intelligence, we need to consider the slippery vocabulary of cognitive science. Consciousness implies awareness, evidence of which might be expressed in an organism’s responsiveness or sensitivity to its surroundings. There is an implicit hierarchy here, with consciousness present in a smaller subset of species, while sensitivity applies to every living thing. Until recently, most philosophers and scientists awarded consciousness to big-brained animals and excluded other forms of life from this honour. The problem with this favouritism, as the cognitive psychologist Arthur Reber has pointed out, is that it’s impossible to identify a threshold level of awareness or responsiveness that separates conscious animals from the unconscious. We can escape this dilemma, however, once we allow ourselves to identify different versions of consciousness across a continuum of species, from apes to amoebas. That’s not to imply that all organisms possess rich emotional lives and are capable of thinking, although fungi do appear to express the biological rudiments of these faculties.

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As work in real and model embryos movesforward, scientists are keen to know how similar the two really are. Finding out how models differ in their molecular details, and how their cells behave, is the main reason researchers wish to push beyond 14 days in real embryos. “We can learn a lot from a model,” says Jesse Veenvliet, a developmental biologist at the Max Planck Institute of Molecular Cell Biology and Genetics in Dresden, Germany. “But it’s important to know where it goes wrong.”

Researchers are now permitted to grow human embryos in the lab for longer than 14 days. Here’s what they could learn.

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Quantum mechanics generally refers to the wave-like properties of things that are commonly considered to be particles, such as electrons. This article discusses evidence of a quantum mechanical switching function that is performed by strictly biological structures—ferritin protein layers that are found in cells including neural tissue.

Many scientists are investigating quantum biology, which is the application of quantum mechanics to investigate biological functions. It has recently been used to answer a number of previously unanswered questions, such as the mechanisms behind photosynthesis and the way birds can perceive magnetic fields. These quantum biological effects generally involve electrons hopping or tunneling over distances of several nanometers, behavior that is incompatible with particles but which makes sense with waves.

Ferritin is a spherical iron storage protein that is found in plants and animals. Early studies of ferritin to look for quantum mechanical effects were conducted at cryogenic temperatures, because it was thought that biological structures were too “warm and wet” to exhibit such effects. Those studies were somewhat inconclusive. But when ferritin was subsequently electrically tested at room temperature, it was discovered that electron tunneling was occurring.

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Would you wear clothing made of muscle fibers? Use them to tie your shoes or even wear them as a belt? It may sound a bit odd, but if those fibers could endure more energy before breaking than cotton, silk, nylon, or even Kevlar, then why not?

Don’t worry, this muscle could be produced without harming a single animal.

Researchers at the McKelvey School of Engineering at Washington University in St. Louis have developed a synthetic chemistry approach to polymerize proteins inside of engineered microbes. This enabled the microbes to produce the high molecular weight muscle protein, titin, which was then spun into fibers.

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A plant fossil from a geological formation in Scotland sheds light on the development of the earliest known form of roots. A team led by researchers at GMI – the Gregor Mendel Institute of Molecular Plant Biology of the Austrian Academy of Sciences, the University of Edinburgh, and the University of Oxford realize the first 3D reconstruction of a Devonian plant based exclusively on fossil evidence. The findings demonstrate that the appearance of different axis types at branching points resulted in the evolution complexity soon after land plants evolved sometime before 400 million years ago. The results are published in eLife.

New research demonstrates how the oldest known root axed developed more than 400 million years ago. The evolution of roots at this time was a dramatic event that impacted our planet and atmosphere and resulted in transformative ecological and climate change.

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AI and Machine Learning systems have proven a boon to scientific research in a variety of academic fields in recent years. They’ve assisted scientists in ripe for cutting-edge treatments, of potent and, and even. Throughout this period, however, AI/ML systems have often been relegated to simply processing large data sets and performing brute force computations, not leading the research themselves.

But Dr. Hiroaki Kitano, CEO of Sony Computer Science Laboratories, “hybrid form of science that shall bring systems biology and other sciences into the next stage,” by creating an AI that’s just as capable as today’s top scientific minds. To do so, Kitano seeks to launch the and.

“The distinct characteristic of this challenge is to field the system into an open-ended domain to explore significant discoveries rather than rediscovering what we already know or trying to mimic speculated human thought processes,” Kitano. “The vision is to reformulate scientific discovery itself and to create an alternative form of scientific discovery.”

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Physics World

An ultra-precise quantum sensor based on trapped beryllium ions is up to 20 times better at detecting weak electric fields than previous atomic devices. By introducing entanglement between the collective motion of the ions and their electronic spin, a collaboration led by the US National Institute of Standards and Technology (NIST) demonstrated that the ion displacement sensitivity in the presence of an electric field was an order of magnitude greater than for classical protocols with trapped ions. With further improvements, the technology could even be used in the search for dark matter.

Quantum sensors can detect and measure signals that are undetectable with their classical counterparts. They are thus a promising tool in many areas of fundamental science, including biological imaging as well as physics. Of the many different systems being pursued as quantum sensors, trapped ions could be particularly favourable due to experimenters’ precise control over their parameters and their ability to introduce entanglement into the system.

The Ion Storage Group at NIST, led by John Bollinger, decided to exploit these properties for measuring very weak electric fields. “We realized our ion crystal can be incredibly sensitive to electric fields,” explains Kevin Gilmore, a former graduate research assistant at NIST and the lead author of a paper describing the research. “We found a protocol that exploits our ability to produce quantum entangled states and is very sensitive to small displacements of the ions driven by weak electric fields. It’s a neat demonstration of how quantum effects can be used to gain an advantage over classical systems.”

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Water is the most abundant yet least understood liquid in nature. It exhibits many strange behaviors that scientists still struggle to explain. While most liquids get denser as they get colder, water is most dense at 39 degrees Fahrenheit, just above its freezing point. This is why ice floats to the top of a drinking glass and lakes freeze from the surface down, allowing marine life to survive cold winters. Water also has an unusually high surface tension, allowing insects to walk on its surface, and a large capacity to store heat, keeping ocean temperatures stable.

Now, a team that includes researchers from the Department of Energy’s SLAC National Accelerator Laboratory, Stanford University and Stockholm University in Sweden have made the first direct observation of how in water tug and push neighboring water molecules when they are excited with laser light. Their results, published in Nature today, reveal effects that could underpin key aspects of the microscopic origin of water’s strange properties and could lead to a better understanding of how water helps proteins function in living organisms.

“Although this so-called nuclear quantum effect has been hypothesized to be at the heart of many of water’s strange properties, this experiment marks the first time it was ever observed directly,” said study collaborator Anders Nilsson, a professor of chemical physics at Stockholm University. “The question is if this quantum effect could be the missing link in theoretical models describing the anomalous properties of water.”

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AI has finally come full circle.

A new suite of algorithms by Google Brain can now design computer chips —those specifically tailored for running AI software —that vastly outperform those designed by human experts. And the system works in just a few hours, dramatically slashing the weeks-or months-long process that normally gums up digital innovation.

At the heart of these robotic chip designers is a type of machine learning called deep reinforcement learning. This family of algorithms, loosely based on the human brain’s workings, has triumphed over its biological neural inspirations in games such as Chess, Go, and nearly the entire Atari catalog.

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The attachment of the small protein ubiquitin to other proteins (ubiquitination) regulates numerous biological processes, including signal transduction and metabolism / Scientists at the University of Cologne discover the link to aging and longevity.

Scientists have discovered that the protein ubiquitin plays an important role in the regulation of the aging process. Ubiquitin was previously known to control numerous processes, such as signal transduction and metabolism. Prof. Dr. David Vilchez and his colleagues at the CECAD Cluster of Excellence for Aging Research at the University of Cologne performed a comprehensive quantitative analysis of ubiquitin signatures during aging in the model organism Caenorhabditis elegans, a nematode worm which is broadly used for aging research.

This method — called ubiquitin proteomics — measures all changes in ubiquitination of proteins in the cell. The resulting data provide site-specific information and define quantitative changes in ubiquitin changes across all proteins in a cell during aging. A comparison with the total protein content of a cell (proteome) showed which changes have functional consequences in protein turnover and actual protein content during aging. The scientists thus discovered new regulators of lifespan and provide a comprehensive data set that helps to understand aging and longevity. The article, ‘Rewiring of the ubiquitinated proteome determines aging in C. elegans,‘has now been published in Nature.

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