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Blog – Page 22

Sophie Cohen-Bodénès and Peter Neri, neuroscientists at École Normale Supérieure, in France, report possible evidence of cuttlefish communicating by waving their ‘arms’ at one another. Their paper is posted on the bioRxiv preprint server.

Prior research has shown that cuttlefish can change their on demand and use that ability as a form of communication. Cuttlefish have also been observed moving their arms in certain ways when confronting other males. They possess eight arms lined with suckers, along with a pair of situated close to their mouths. In this new effort, the researchers took a closer look at the ways cuttlefish move their arms, possibly as a means of communicating with others of their kind.

The researchers put several specimens in a tank in their lab to observe them as they interacted with one another. They also videotaped several as they moved their arms and played the videos back to the cuttlefish to see how they would react. They found four waving patterns that appeared to be consistent—up, side, roll, and crown.

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Two thousand years before the Inca empire dominated the Andes, a lesser-known society known as the Chavín Phenomenon shared common art, architecture, and materials throughout modern-day Peru. Through agricultural innovations, craft production, and trade, Chavín shaped a growing social order and laid the foundations for a hierarchical society among the high peaks.

But one of their most powerful tools wasn’t farming. It was access to altered states of consciousness.

That’s according to a new study that uncovered the earliest-known direct evidence of the use of psychoactive plants in the Peruvian Andes. A team of archaeologists from the University of Florida, Stanford University and South American institutions discovered ancient snuff tubes carved from hollow bones at the heart of monumental stone structures at Chavín de Huántar, a prehistoric ceremonial site in the mountains of Peru.

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Birmingham scientists have identified an essential genetic code for a method called plasmid curing, which aims to “displace” antibiotic-resistance genes from bacteria.

Plasmids, which are small, circular strands of DNA, play a crucial role in allowing to share beneficial genes rapidly in a changing environment, most concerningly when they carry genes conferring resistance to antibiotics.

Professor Chris Thomas from Birmingham’s School of Biosciences has investigated plasmid curing for many years, and engineered useful “multi-copy” (many copies in each bacterium) plasmids for this purpose, resulting in a patented, efficient way to displace unwanted plasmids that carry resistance.

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Whether designing a window in an airliner or a cable conduit for an engine, manufacturers devote a lot of effort to reinforcing openings for structural integrity. But the reinforcement is rarely perfect and often creates structural weaknesses elsewhere.

Now, engineers at Princeton and Georgia Institute of Technology have developed a technique that can maintain by essentially hiding the opening from the surrounding forces. Rather than reinforcing the opening to protect against a few select forces, the new approach reorganizes nearly any set of forces that could affect the surrounding material to avoid the opening.

In an article, titled “Unbiased Mechanical Cloaks” in the Proceedings of the National Academy of Sciences, the researchers said they surrounded openings with microstructures designed to protect against many loads—external forces that cause , movement or deformation. The microstructures’ shape and orientation are calibrated to work with the most challenging loads facing the structure, allowing designers to counter multiple stresses at once.

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While text-to-video artificial intelligence models like OpenAI’s Sora are rapidly metamorphosing in front of our eyes, they have struggled to produce metamorphic videos. Simulating a tree sprouting or a flower blooming is harder for AI systems than generating other types of videos because it requires the knowledge of the physical world and can vary widely.

But now, these models have taken an evolutionary step.

Computer scientists at the University of Rochester, Peking University, University of California, Santa Cruz, and National University of Singapore developed a new AI text-to-video model that learns real-world physics knowledge from time-lapse videos. The team outlines their model, MagicTime, in a paper published in IEEE Transactions on Pattern Analysis and Machine Intelligence.

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Investigating muscle activity and coactivation with surface electromyography (sEMG) gives insight into pathological muscle function during activities like walking in people with neuromuscular impairments, such as children with cerebral palsy (CP). There is large variation in the amount of coactivation reported during walking in children with CP, possibly due to the inconsistent handling of sEMG and in calculating the coactivation index. The aim of this study was to evaluate how different approaches of handling sEMG may affect the interpretation of muscle activity and coactivation, by looking at both absolute and normalized sEMG. Twenty-three ambulatory children with CP and 11 typically developing (TD) children participated. We conducted a three-dimensional gait analysis (3DGA) with concurrent sEMG measurements of tibialis anterior, soleus, gastrocnemius medialis, rectus femoris, and hamstring medialis. They walked barefoot at a self-selected, comfortable speed back and forth a 7-m walkway. The gait cycle extracted from the 3DGA was divided into six phases, and for each phase, root mean square sEMG amplitude was calculated (sEMG-RMS-abs), and also normalized to peak amplitude of the linear envelope (50-ms running RMS window) during the gait cycle (sEMG-RMS-norm). The coactivation index was calculated using sEMG-RMS-abs and sEMG-RMS-norm values and by using two different indices. Differences between TD children’s legs and the affected legs of children with CP were tested with a mixed model. The between-subject muscle activity variability was more evenly distributed using sEMG-RMS-norm; however, potential physiological variability was eliminated as a result of normalization. Differences between groups in one gait phase using sEMG-RMS-abs showed opposite differences in another phase using sEMG-RMS-norm for three of the five muscles investigated. The CP group showed an increased coactivation index in two out of three muscle pairs using sEMG-RMS-abs and in all three muscle pairs using sEMG-RMS-norm. These results were independent of index calculation method. Moreover, the increased coactivation indices could be explained by either reduced agonist activity or increased antagonist activity. Thus, differences in muscle activity and coactivation index between the groups change after normalization. However, because we do not know the truth, we cannot conclude whether to normalize and recommend incorporating both.

Surface electromyography (sEMG) is used to measure muscle activity and may be used clinically to investigate muscle function during activities such as walking in conditions affecting the neuromuscular system (1). In children with cerebral palsy (CP), three-dimensional gait analysis (3DGA) with simultaneous sEMG measurements is often conducted to get insight into muscle activity as part of treatment prescriptions and evaluation of treatment effect. Cerebral palsy, the most common cause of physical disability in childhood, is characterized by insufficient motor activity such as reduced muscle strength and poor balance, but also increased motor activity such as spasticity and excessive muscle coactivation (2, 3). Those features of children with CP may impair function in general and gait in particular. Compared to typically mature gait, children with CP have shown deviations in different gait phases and greater physiological variability during walking (4, 5).

Muscle coactivation, defined as simultaneous activity of agonist and antagonist muscles crossing the same joint, is a normal motor control strategy to increase joint stability and coordination (6, 7). During complex tasks, such as walking, coactivation occurs prominently at certain phases during the gait cycle, ensuring stability and allowing efficient walking. Excessive and/or prolonged coactivation, however, may cause inefficient movements by reducing flexibility and adaptability and increasing the loading of the joints, and thus, energy cost (6, 7, 9, 10). Therefore, a main treatment goal for ambulatory children with CP is to make walking easier, through, for example, normalizing altered muscle activity and coactivation (11). However, the role of the increased coactivation in children with CP has been questioned in several studies, and the findings are conflicting (9, 12–14).

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Recent discoveries of glymphatics and meningeal lymphatics have redefined our understanding of CNS immunosurveillance. Kim and Kipnis illustrate how the clearance of brain-derived antigens creates an “immune code” that, when presented by meningeal antigen-presenting cells, instructs T cells to safeguard neural homeostasis. They review how inflammation, aging, and neurodegeneration disrupt this finely tuned process and highlight emerging therapeutic opportunities.

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An innovative way to image atoms in cold gases could provide deeper insights into the atoms’ quantum correlations.

The macroscopic properties of objects that we encounter in everyday life are ultimately determined by the behavior of these objects’ microscopic constituents. For instance, the way that atoms move is key to understanding the pressure of the gas in our tires or the flow of our morning coffee into a cup. However, equally important is how the positions of these particles are correlated—how the particles “dance” together. This dance has already been imaged in highly confined systems in which particles can move only between discrete sites [1]. Now three separate experimental groups, one from École Normale Supérieure in Paris and two from MIT, have imaged the positions of individual atoms in a cold, uniform gas, exposing the atoms’ quantum correlations [2– 4].

The fundamental quantum nature of particles leads to counterintuitive behavior in a collection of particles, even if there are no forces acting between them. Because quantum particles are indistinguishable, the probability of detecting one at a particular position is independent of which particle is observed. This feature implies that there are two classes of particle: bosons, which can change places without affecting the system’s quantum state; and fermions, which flip the sign of the state upon their exchange. The result is that photons and other bosons tend to bunch together, whereas electrons and other fermions tend to avoid each other.

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