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Why Nanoscale Droplets Don’t Coalesce

A well-shaken mixture of oil and vinegar will separate as the oil droplets eventually coalesce. Droplet growth, or coarsening, usually evolves according to standard rules. But puzzling exceptions persist. When two polymers are mixed in water and the concentration is high enough, droplets containing one or both species form and can remain stable for hours or days. These loose molecular condensates otherwise behave like liquid droplets, and they abound in biological cells. Now Feipeng Chen of the University of Hong Kong and his colleagues have developed a predictive model for coarsening behavior that works across a range of droplet sizes and explains why coarsening may be suppressed in living systems [1].

The researchers derived their model from observations of a solution containing water and two different polymers, opposite in charge and having very different molecular chain lengths. Using light-scattering techniques, the researchers monitored condensate growth over 12 hours. The initial size and subsequent growth rate of the liquid-like droplets, rich in both polymers, turned out to depend on the solution’s overall initial concentration. In the most dilute solutions, condensates tens-of-nanometers in diameter formed and promptly stopped growing for the remaining 12-hour observation period. In solutions having slightly higher concentration, hundreds-of-nanometer condensates formed and remained stable, then underwent abrupt, rapid growth in the later stages. And in the most concentrated solutions, micrometer-scale condensates formed and grew according to a power-law model.

Applying an electric field to the solutions indicated that the nanoscale condensates had significant surface charge. Modeling these measurements revealed that the asymmetric chain lengths of oppositely charged polymers imparted a net charge to the droplet surfaces. These charges led to size-dependent electrostatic barriers that drastically reduced merging efficiency below a critical diameter. The finding offers a principle for controlling size stability in biology, nanotechnology, and soft-matter assembly.

Scientists identify a cell type in the brain that was previously ignored and it may explain why human memory has no known upper limit

The human brain contains roughly 86 billion neurons. That number appears in almost every popular account of memory and intelligence, and it tends to carry an implicit argument: that the scale of human cognition follows from the scale of this cell count. What is less often mentioned is that the brain contains a roughly comparable number of a different cell type entirely, one that researchers have treated, for most of the history of neuroscience, as little more than biological scaffolding.

A paper published on 23 May in the Proceedings of the National Academy of Sciences puts forward a new hypothesis about what those cells, called astrocytes, might actually be doing. The work comes from a team at MIT: lead author Leo Kozachkov, Jean-Jacques Slotine, a professor of mechanical engineering and brain and cognitive sciences, and Dmitry Krotov of the MIT-IBM Watson AI Lab, who is the paper’s senior author. Their claim is not that astrocytes have been misunderstood in any dramatic sense; it is the more careful suggestion that they may be doing computational work that neurons, on their own, cannot account for.

This is a hypothesis supported by a mathematical model. The experimental work needed to test it has not yet been done.

Zoltan Istvan: The Transhumanist Wager Is A Choice We’ll All Have To Make

Thirteen years ago, I sat down with a writer who had just published his first novel.

It was Zoltan Istvan’s very first media interview as a book author.

The book was The Transhumanist Wager. The question behind it was simple and almost unbearable: what would you do, and what would you give up, to live forever?

I loved half of it. I argued with the other half. That tension is exactly why I think it still matters.

Zoltan built his story out of Plato and Nietzsche, out of Thomas More’s Utopia and Zen Buddhism, then wrapped it all in an Atlas Shrugged plot of lone heroes and evil states. The philosophy is sophisticated. The framing is stark. The contradictions are not a flaw. They are the point.

One line from our conversation has stayed with me for more than a decade:

A new origin story for multicellular life points to physics, not genes alone

How did life make the leap from single cells to coordinated, multicellular organisms? And how do genetically identical cells still perform a version of that feat every time an embryo begins to take shape?

In a new Perspective paper appearing in the journal Nature Biotechnology, Bren Professor of Biology and Biological Engineering Magdalena Zernicka-Goetz and collaborator Qi Chen of the University of Utah ask one of biology’s oldest questions in a new way. The paper is titled “Decoding the origins of cellular self-organization for engineered biology.”

Smaller nanoplastics trigger stronger changes in brain neuron activity

Smaller plastic particles have more effects on neurons, the key information processing cells of the brain, new research from the University of Eastern Finland shows. In the study, neuronal cells were exposed to polystyrene nanoplastics at low doses to study subtle changes.

Plastic production continues to rise, despite worldwide concerns. In addition to environmental implications, there is an increasing interest in how exposure to plastics may impact human health, but our understanding is still limited. Only recently it was shown that plastics can accumulate also in the human brain.

Plastic particles smaller than 5,000 nm in diameter are called microplastics, and the smallest plastic particles with a diameter of less than 1,000 nm are called nanoplastics. The small size of nanoplastics enables them to interact with various cell types, and other particles or biological mass, such as bacteria. Compared to microplastics, nanoplastics have larger adsorption capacity and penetrate through biological barriers more easily. This makes them potentially more harmful and a compelling target for research in the field of neurobiology.

‘Molecular movie’ technology reveals a better way to thwart environmental pollutant

The latest production from the “molecular movie” imaging technology developed at Oregon State University is a new, inexpensive way of dealing with a common environmental pollutant. Based on short-pulse lasers, the imaging technology allows chemical and biological actions to be measured as they are occurring, one high-speed frame at a time.

The measurements occur on the level of the femtosecond—one-millionth of one-billionth of a second. A femtosecond is to a second roughly as a second is to 32 million years.

“We’re able to slow down the observation of chemical processes and understand the exact sequences of biochemical reactions,” said Chong Fang, professor of chemistry at OSU, who unveiled the technology in 2014. “It’s a really powerful tool to study, understand and tune biological processes. Now we have extended the tool set to delineate a wide array of chemical processes.”

Light-activated gel could transform wearables, soft robotics, and more

Consider the chief difference between living systems and electronics: the first is generally soft and squishy, while the latter is hard and rigid. Now, in work that could impact human-machine interfaces, biocompatible devices, soft robotics, and more, MIT engineers and colleagues have developed a soft, flexible gel that dramatically changes its conductivity upon the application of light.

Enter the growing field of ionotronics, which involves transferring data through ions, or charged molecules. Electronics does the same with electrons. But while the latter is well established, ionotronics is still being developed, with one huge exception: living systems. The cells in our bodies communicate with a variety of ions, from potassium to sodium.

Ionotronics, in turn, can provide a bridge between electronics and biological tissues. Potential applications range from soft wearable technology to human-machine interfaces.

Photon-driven synapse advances low-power neuromorphic systems

Modern artificial intelligence systems rely on moving large amounts of data between memory and processors, a design that limits speed and increases energy use. The human brain works differently: it combines memory and computation within synapses, allowing fast, efficient learning and perception. Replicating this approach in hardware is a central goal of neuromorphic computing, especially for tasks like vision, where most real-world information is gathered and processed.

In that context, researchers have developed a new type of artificial synapse that operates entirely with light. Unlike most existing devices, which still depend on electrical signals at some stage, this system uses optical signals both to receive information and to update its internal state. Removing electrical conversion steps could lower energy use, reduce noise, and enable faster processing, particularly in vision systems that already rely on light.

As reported in Advanced Photonics, the device is built from a rare-earth-doped crystal that emits a persistent afterglow after being illuminated. This material can store optical information in the form of trapped charge carriers. When light excites the crystal, some of these carriers emit light immediately, while others remain trapped and are released later. The balance between these pathways depends on the history of illumination, allowing the material to mimic how biological synapses change strength based on past activity.

Irregular brain maturation in childhood predicts emotional habits in early adolescence

A new study reveals that the pace of a child’s brain maturation can predict whether they will tend to bottle up their emotions during their teenage years, offering new clues about the biological roots of adolescent mental health.

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