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Category: chemistry – Page 329

First known gene transfer from plant to insect identified

“The results were surprising, but convincing, says Yannick Pauchet, a molecular entomologist also at the Max Planck Institute for Chemical Ecology. ” According to the data they provide, horizontal gene transfer is the most parsimonious explanation,” he says.

But how the whitefly managed to swipe a plant gene is unclear. One possibility, says Turlings, is that a virus served as an intermediate, shuttling genetic material from a plant into the whitefly genome.

As researchers s… See More.

Discovery that a whitefly uses a stolen plant gene to elude its host’s defences may offer a route to new pest-control strategies.

Turning Wood Into Recyclable, Biodegradable Plastic

Plastics are one of the world’s largest polluters, taking hundreds of years to degrade in nature. A research team, led by YSE professor Yuan Yao and Liangbing Hu from the University of Maryland, has created a high-quality bioplastic from wood byproducts that they hope can solve one of the world’s most pressing environmental issues.

Efforts to shift from petrochemical plastics to renewable and biodegradable plastics have proven tricky — the production process can require toxic chemicals and is expensive, and the mechanical strength and water stability is often insufficient. But researchers have made a breakthrough, using wood byproducts, that shows promise for producing more durable and sustainable bioplastics.

A study published in Nature Sustainability, co-authored by Yuan Yao, assistant professor of industrial ecology and sustainable systems at Yale School of the Environment (YSE), outlines the process of deconstructing the porous matrix of natural wood into a slurry. The researchers say the resulting material shows a high mechanical strength, stability when holding liquids, and UV-light resistance. It can also be recycled or safely biodegraded in the natural environment, and has a lower life-cycle environmental impact when compared with petroleum-based plastics and other biodegradable plastics.

Reinforcement learning with artificial microswimmers

Artificial microswimmers that can replicate the complex behavior of active matter are often designed to mimic the self-propulsion of microscopic living organisms. However, compared with their living counterparts, artificial microswimmers have a limited ability to adapt to environmental signals or to retain a physical memory to yield optimized emergent behavior. Different from macroscopic living systems and robots, both microscopic living organisms and artificial microswimmers are subject to Brownian motion, which randomizes their position and propulsion direction. Here, we combine real-world artificial active particles with machine learning algorithms to explore their adaptive behavior in a noisy environment with reinforcement learning. We use a real-time control of self-thermophoretic active particles to demonstrate the solution of a simple standard navigation problem under the inevitable influence of Brownian motion at these length scales. We show that, with external control, collective learning is possible. Concerning the learning under noise, we find that noise decreases the learning speed, modifies the optimal behavior, and also increases the strength of the decisions made. As a consequence of time delay in the feedback loop controlling the particles, an optimum velocity, reminiscent of optimal run-and-tumble times of bacteria, is found for the system, which is conjectured to be a universal property of systems exhibiting delayed response in a noisy environment.

Living organisms adapt their behavior according to their environment to achieve a particular goal. Information about the state of the environment is sensed, processed, and encoded in biochemical processes in the organism to provide appropriate actions or properties. These learning or adaptive processes occur within the lifetime of a generation, over multiple generations, or over evolutionarily relevant time scales. They lead to specific behaviors of individuals and collectives. Swarms of fish or flocks of birds have developed collective strategies adapted to the existence of predators (1), and collective hunting may represent a more efficient foraging tactic (2). Birds learn how to use convective air flows (3). Sperm have evolved complex swimming patterns to explore chemical gradients in chemotaxis (4), and bacteria express specific shapes to follow gravity (5).

Inspired by these optimization processes, learning strategies that reduce the complexity of the physical and chemical processes in living matter to a mathematical procedure have been developed. Many of these learning strategies have been implemented into robotic systems (7–9). One particular framework is reinforcement learning (RL), in which an agent gains experience by interacting with its environment (10). The value of this experience relates to rewards (or penalties) connected to the states that the agent can occupy. The learning process then maximizes the cumulative reward for a chain of actions to obtain the so-called policy. This policy advises the agent which action to take. Recent computational studies, for example, reveal that RL can provide optimal strategies for the navigation of active particles through flows (11–13), the swarming of robots (14–16), the soaring of birds , or the development of collective motion (17).

Three-dimensional, multifunctional neural interfaces for cortical spheroids and engineered assembloids

Three-dimensional (3D), submillimeter-scale constructs of neural cells, known as cortical spheroids, are of rapidly growing importance in biological research because these systems reproduce complex features of the brain in vitro. Despite their great potential for studies of neurodevelopment and neurological disease modeling, 3D living objects cannot be studied easily using conventional approaches to neuromodulation, sensing, and manipulation. Here, we introduce classes of microfabricated 3D frameworks as compliant, multifunctional neural interfaces to spheroids and to assembloids. Electrical, optical, chemical, and thermal interfaces to cortical spheroids demonstrate some of the capabilities. Complex architectures and high-resolution features highlight the design versatility. Detailed studies of the spreading of coordinated bursting events across the surface of an isolated cortical spheroid and of the cascade of processes associated with formation and regrowth of bridging tissues across a pair of such spheroids represent two of the many opportunities in basic neuroscience research enabled by these platforms.

Progress in elucidating the development of the human brain increasingly relies on the use of biosystems produced by three-dimensional (3D) neural cultures, in the form of cortical spheroids, organoids, and assembloids (1–3). Precisely monitoring the physiological properties of these and other types of 3D biosystems, especially their electrophysiological behaviors, promises to enhance our understanding of the interactions associated with development of the nervous system, as well as the evolution and origins of aberrant behaviors and disease states (4–8). Conventional multielectrode array (MEA) technologies exist only in rigid, planar, and 2D formats, thereby limiting their functional interfaces to small areas of 3D cultures, typically confined to regions near the bottom contacting surfaces.

Humans Contain 42 Mystery Chemicals, Which Is Slightly Concerning

We’re not really sure where they came from.

Just as you contain multitudes, your body contains multiple chemicals—a total of 109, in fact, including 55 that have never been reported in humans before, and 42 “mystery chemicals” that come from unknown environmental sources, according to a new study from UC San Francisco.

In the study, which appears in Environmental Science and Technology, scientists revealed the chemicals found in pregnant women’s bodies. They say the chemicals have likely been in there for a while, but high-resolution spectrometry has only just begun to reveal them in detail. To test chemicals, researchers also rely on pure “standard” samples made by manufacturers, which they can’t always get ahold of.

Plasmonic nanoreactors regulate selective oxidation via energetic electrons and nanoconfined thermal fields

When optimizing catalysis in the lab, product selectivity and conversion efficiency are primary goals for materials scientists. Efficiency and selectivity are often mutually antagonistic, where high selectivity is accompanied by low efficiency and vice versa. Increasing the temperature can also change the reaction pathway. In a new report, Chao Zhan and a team of scientists in chemistry and chemical engineering at the Xiamen University in China and the University of California, Santa Barbara, U.S., constructed hierarchical plasmonic nanoreactors to show nonconfined thermal fields and electrons. The combined attributes uniquely coexisted in plasmonic nanostructures. The team regulated parallel reaction pathways for propylene partial oxidation and selectively produced acrolein during the experiments to form products that are different from thermal catalysis. The work described a strategy to optimize chemical processes and achieve high yields with high selectivity at lower temperature under visible light illumination. The work is now published on Science Advances.

Catalysts

Ideal catalytic processes can produce desired target products without undesirable side effects under cost-effective conditions, although such conditions are rarely achieved in practice. For instance, high efficiency and high selectivity are antagonistic goals, where a relatively high temperature is often necessary to overcome the large barrier of oxygen activation to achieve high reactant conversion. Increasing the functional temperature can also lead to overoxidized and therefore additional byproducts. As a result, researchers must compromise between selectivity and efficiency. For instance, a given molecule typically requires diverse catalysts to generate different products, where each catalyst has different efficiency and selectivity. To circumvent any limitations, they can use surface plasmons (SPs) to redistribute photons, electrons and heat energy in space and time.

Action potentials induce biomagnetic fields in carnivorous Venus flytrap plants

“Previously reported detection of plant biomagnetism, which established the existence of measurable magnetic activity in the plant kingdom, was carried out using superconducting-quantum-interference-device (SQUID) magnetometers1, 5, 16. Atomic magnetometers are arguably more attractive for biological applications, since, unlike SQUIDs34, 35, they are non-cryogenic and can be miniaturized to optimize spatial resolution of measured biological features14, 15, 36. In the future, the SNR of magnetic measurements in plants will benefit from optimizing the low-frequency stability and sensitivity of atomic magnetometers. Just as noninvasive magnetic techniques have become essential tools for medical diagnostics of the human brain and body, this noninvasive technique could also be useful in the future for crop-plant diagnostics—by measuring the electromagnetic response of plants facing such challenges as sudden temperature change, herbivore attack, and chemical exposure.”

Upon stimulation, plants elicit electrical signals that can travel within a cellular network analogous to the animal nervous system. It is well-known that in the human brain, voltage changes in certain regions result from concerted electrical activity which, in the form of action potentials (APs), travels within nerve-cell arrays. Electro-and magnetophysiological techniques like electroencephalography, magnetoencephalography, and magnetic resonance imaging are used to record this activity and to diagnose disorders. Here we demonstrate that APs in a multicellular plant system produce measurable magnetic fields. Using atomic optically pumped magnetometers, biomagnetism associated with electrical activity in the carnivorous Venus flytrap, Dionaea muscipula, was recorded. Action potentials were induced by heat stimulation and detected both electrically and magnetically.

Discovery identifies non-DNA mechanism involved in transmitting paternal experience to offspring

It has long been understood that a parent’s DNA is the principal determinant of health and disease in offspring. Yet inheritance via DNA is only part of the story; a father’s lifestyle such as diet, being overweight and stress levels have been linked to health consequences for his offspring. This occurs through the epigenome—heritable biochemical marks associated with the DNA and proteins that bind it. But how the information is transmitted at fertilization along with the exact mechanisms and molecules in sperm that are involved in this process has been unclear until now.

A new study from McGill, published recently in Developmental Cell, has made a significant advance in the field by identifying how is transmitted by non-DNA molecules in the sperm. It is a discovery that advances scientific understanding of the heredity of paternal life experiences and potentially opens new avenues for studying disease transmission and prevention.