Deep in the human brain, a very specific kind of cell dies during Parkinson’s disease.

For the first time, researchers have sorted large numbers of human brain cells in the substantia nigra into 10 distinct types. Just one is especially vulnerable in Parkinson’s disease, the team reports May 5 in Nature Neuroscience. The result could lead to a clearer view of how Parkinson’s takes hold, and perhaps even ways to stop it.

The new research “goes right to the core of the matter,” says neuroscientist Raj Awatramani of Northwestern University Feinberg School of Medicine in Chicago. Pinpointing the brain cells that seem to be especially susceptible to the devastating disease is “the strength of this paper,” says Awatramani, who was not involved in the study.

Parkinson’s disease steals people’s ability to move smoothly, leaving balance problems, tremors and rigidity. In the United States, nearly 1 million people are estimated to have Parkinson’s. Scientists have known for decades that these symptoms come with the death of nerve cells in the substantia nigra. Neurons there churn out dopamine, a chemical signal involved in movement, among other jobs (SN: 9/7/17).

But those dopamine-making neurons are not all equally vulnerable in Parkinson’s, it turns out.

“This seemed like an opportunity to … really clarify which kinds of cells are actually dying in Parkinson’s disease,” says Evan Macosko, a psychiatrist and neuroscientist at Massachusetts General Hospital in Boston and the Broad Institute of MIT and Harvard.
The tricky part was that dopamine-making neurons in the substantia nigra are rare. In samples of postmortem brains, “we couldn’t survey enough of [the cells] to really get an answer,” Macosko says. But Abdulraouf Abdulraouf, a researcher in Macosko’s laboratory, led experiments that sorted these cells, figuring out a way to selectively pull the cells’ nuclei out from the rest of the cells present in the substantia nigra. That enrichment ultimately led to an abundance of nuclei to analyze.

By studying over 15,000 nuclei from the brains of eight formerly healthy people, the researchers further sorted dopamine-making cells in the substantia nigra into 10 distinct groups. Each of these cell groups was defined by a specific brain location and certain combinations of genes that were active.

When the researchers looked at substantia nigra neurons in the brains of people who died with either Parkinson’s disease or the related Lewy body dementia, the team noticed something curious: One of these 10 cell types was drastically diminished.

These missing neurons were identified by their location in the lower part of the substantia nigra and an active AGTR1 gene, lab member Tushar Kamath and colleagues found. That gene was thought to serve simply as a good way to identify these cells, Macosko says; researchers don’t know whether the gene has a role in these dopamine-making cells’ fate in people.

The new finding points to ways to perhaps counter the debilitating diseases. Scientists have been keen to replace the missing dopamine-making neurons in the brains of people with Parkinson’s. The new study shows what those cells would need to look like, Awatramani says. “If a particular subtype is more vulnerable in Parkinson’s disease, maybe that’s the one we should be trying to replace,” he says.

In fact, Macosko says that stem cell scientists have already been in contact, eager to make these specific cells. “We hope this is a guidepost,” Macosko says.

The new study involved only a small number of human brains. Going forward, Macosko and his colleagues hope to study more brains, and more parts of those brains. “We were able to get some pretty interesting insights with a relatively small number of people,” he says. “When we get to larger numbers of people with other kinds of diseases, I think we’re going to learn a lot.”

“Fungi Fridays” could save a lot of trees — and take a bite out of greenhouse gas emissions. Eating one-fifth less red meat and instead munching on microbial proteins derived from fungi or algae could cut annual deforestation in half by 2050, researchers report May 5 in Nature.

Raising cattle and other ruminants contributes methane and nitrous oxide to the atmosphere, while clearing forests for pasture lands adds carbon dioxide (SN: 4/4/22; SN: 7/13/21). So the hunt is on for environmentally friendly substitutes, such as lab-grown hamburgers and cricket farming (SN: 9/20/18; SN: 5/2/19).

Another alternative is microbial protein, made from cells cultivated in a laboratory and nurtured with glucose. Fermented fungal spores, for example, produce a dense, doughy substance called mycoprotein, while fermented algae produce spirulina, a dietary supplement.
Cell-cultured foods do require sugar from croplands, but studies show that mycoprotein produces fewer greenhouse gas emissions and uses less land and water than raising cattle, says Florian Humpenöder, a climate modeler at Potsdam Institute for Climate Impact Research in Germany. However, a full comparison of foods’ future environmental impacts also requires accounting for changes in population, lifestyle, dietary patterns and technology, he says.

So Humpenöder and colleagues incorporated projected socioeconomic changes into computer simulations of land use and deforestation from 2020 through 2050. Then they simulated four scenarios, substituting microbial protein for 0 percent, 20 percent, 50 percent or 80 percent of the global red meat diet by 2050.
A little substitution went a long way, the team found: Just 20 percent microbial protein substitution cut annual deforestation rates — and associated CO2 emissions — by 56 percent from 2020 to 2050.

Eating more microbial proteins could be part of a portfolio of strategies to address the climate and biodiversity crises — alongside measures to protect forests and decarbonize electricity generation, Humpenöder says.

Young kids’ brains are especially tuned to their mothers’ voices. Teenagers’ brains, in their typical rebellious glory, are most decidedly not.

That conclusion, described April 28 in the Journal of Neuroscience, may seem laughably obvious to parents of teenagers, including neuroscientist Daniel Abrams of Stanford University School of Medicine. “I have two teenaged boys myself, and it’s a kind of funny result,” he says.

But the finding may reflect something much deeper than a punch line. As kids grow up and expand their social connections beyond their family, their brains need to be attuned to that growing world. “Just as an infant is tuned into a mom, adolescents have this whole other class of sounds and voices that they need to tune into,” Abrams says.
He and his colleagues scanned the brains of 7- to 16-year-olds as they heard the voices of either their mothers or unfamiliar women. To simplify the experiment down to just the sound of a voice, the words were gibberish: teebudieshawlt, keebudieshawlt and peebudieshawlt. As the children and teenagers listened, certain parts of their brains became active.

Previous experiments by Abrams and his colleagues have shown that certain regions of the brains of kids ages 7 to 12 — particularly those parts involved in detecting rewards and paying attention — respond more strongly to mom’s voice than to a voice of an unknown woman. “In adolescence, we show the exact opposite of that,” Abrams says.

In these same brain regions in teens, unfamiliar voices elicited greater responses than the voices of their own dear mothers. The shift from mother to other seems to happen between ages 13 and 14.

It’s not that these adolescent brain areas stop responding to mom, Abrams says. Rather, the unfamiliar voices become more rewarding and worthy of attention.

And that’s exactly how it should be, Abrams says. Exploring new people and situations is a hallmark of adolescence. “What we’re seeing here is just purely a reflection of this phenomenon.”

Voices can carry powerful signals. When stressed-out girls heard their moms’ voices on the phone, the girls’ stress hormones dropped, biological anthropologist Leslie Seltzer of the University of Wisconsin–Madison and colleagues found in 2011 (SN: 8/12/11). The same was not true for texts from their mothers.

The current results support the idea that the brain changes to reflect new needs that come with time and experience, Seltzer says. “As we mature, our survival depends less and less on maternal support and more on our group affiliations with peers.”

It’s not clear how universal this neural shift is. The finding might change across various mother-child relationships, including those that have different parenting styles, or even a history of neglect or abuse, Seltzer says.

So while teenagers and parents may sometimes feel frustrated by missed messages, take heart, Abrams says. “This is the way the brain is wired, and there’s a good reason for it.”

Ben Franklin had nothing on trilobites.

Roughly 400 million years before the founding father invented bifocals, the now extinct trilobite Dalmanitina socialis already had a superior version (SN: 2/2/74). Not only could the sea critter see things both near and far, it could also see both distances in focus at the same time — an ability that eludes most eyes and cameras.

Now, a new type of camera sees the world the way this trilobite did. Inspired by D. socialis’s eyes, the camera can simultaneously focus on two points anywhere between three centimeters and nearly two kilometers away, researchers report April 19 in Nature Communications.
“In optics, there was a problem,” says Amit Agrawal, a physicist at the National Institute of Standards and Technology in Gaithersburg, Md. If you wanted to focus a single lens to two different points, you just simply could not do it, he says.

If a camera could see like a trilobite, Agrawal figured, it could capture high-quality images with higher depths of field. A high depth of field — the distance between the nearest and farthest points that a camera can bring into focus — is important for the relatively new technique of light-field photography, which uses many tiny lenses to produce 3-D photos.

To mimic the trilobite’s ability, the team constructed a metalens, a type of flat lens made up of millions of differently-sized rectangular nanopillars arranged like a cityscape — if skyscrapers were one two-hundredth the width of a human hair. The nanopillars act as obstacles that bend light in different ways depending on their shape, size and arrangement. The researchers arranged the pillars so some light traveled through one part of the lens and some light through another, creating two different focal points.
To use the device in a light-field camera, the team then built an array of identical metalenses that could capture thousands of tiny images. When combined, the result is an image that’s in focus closeup and far away, but blurry in between. The blurry bits are then sharpened with a type of machine learning computer program.

Achieving a large depth of field can help the program recover depth information, says Ivo Ihrke, a computational imaging scientist at the University of Siegen in Germany who was not involved with this research. Standard images don’t contain information about the distances to objects in the photo, but 3-D images do. So the more depth information that can be captured, the better.

The trilobite approach isn’t the only way to boost the range of visual acuity. Other cameras using a different method have accomplished a similar depth of field, Ihrke says. For instance, a light-field camera made by the company Raytrix contains an array of tiny glass lenses of three different types that work in concert, with each type tailored to focus light from a particular distance. The trilobite way also uses an array of lenses, but all the lenses are the same, each one capable of doing all the depth-of-focus work on its own — which helps achieve a slightly higher resolution than using different types of lenses.

Regardless of how it’s done, all the recent advances in capturing depth with light-field cameras will improve imaging techniques that depend on that depth, Agrawal says. These techniques could someday help self-driving cars to track distances to other vehicles, for example, or Mars rovers to gauge distances to and sizes of landmarks in their vicinity.

Leonardo da Vinci was wrong about trees.

The multitalented, Renaissance genius wrote down his “rule of trees” over 500 years ago. It described the way he thought that trees branch. Though it was a brilliant insight that helped him to draw realistic landscapes, Leonardo’s rule breaks down for many types of trees. Now, a new branching rule — dubbed “Leonardo-like” — works for virtually any leafy tree, researchers report in a paper accepted April 13 in Physical Review E.

“The older Leonardo rule describes the thickness of the branches, while the length of the branch was not taken into account,” says physicist Sergey Grigoriev of the Petersburg Nuclear Physics Institute in Gatchina, Russia. “Therefore, the description using the older rule is not complete.”
Leonardo’s rule says that the thickness of a limb before it branches into smaller ones is the same as the combined thickness of the limbs sprouting from it (SN: 6/1/11). But according to Grigoriev and his colleagues, it’s the surface area that stays the same.

Using surface area as a guide, the new rule incorporates limb widths and lengths, and predicts that long branches end up being thinner than short ones. Unlike Leonardo’s guess, the updated rule works for slender birches as well as it does for sturdy oaks, the team reports.

The connection between the surface area of branches and overall tree structure shows that it’s the living, outer layers that guide tree structure, the researchers say. “The life of a tree flows according to the laws of conservation of area in two-dimensional space,” the authors write in their study, “as if the tree were a two-dimensional object.” In other words, it’s as if just two dimensions — the width of each limb and the distance between branchings on a limb — determine any tree’s structure. As a result, when trees are rendered in two dimensions in a painting or on a screen, the new rule describes them particularly well.
The new Leonardo-like rule is an improvement, says Katherine McCulloh, a botanist at the University of Wisconsin–Madison who was not involved with this study. But she has her doubts about the Russian group’s rationale for it. In most trees, she says, the living portion extends much deeper than the thin surface layer.

“It’s really species-dependent, and even age-dependent,” McCulloh says. “A giant, old oak tree might have a centimeter of living wood … [but] there are certainly tropical tree species that have very deep sapwood and may have living wood for most of their cross sections.”

Still, the fact that the Leonardo-like rule appears to hold for many trees intrigues McCulloh. “To me, it drives home the question of why are [trees] conserving this geometry for their external tissue, and how is that related to the microscopic level differences that we observe in wood,” she says. “It’s a really interesting question.”

To test their rule, Grigoriev and colleagues took photographs of trees from a variety of species and analyzed the branches to confirm that the real-world patterns matched the predictions. The photos offer “a direct measurement of the characteristics of a tree without touching it, which can be important when dealing with a living object,” Grigoriev says.

Though the team hasn’t studied evergreens yet, the rule holds for all of the deciduous trees that the researchers have looked at. “We have applied our methodology to maple, linden, apple,” Grigoriev says, in addition to oak, birch and chestnut. “They show the same general structure and obey the Leonardo-like rule.”

While it’s possible to confirm the rule by measuring branches by hand, it would require climbing into trees and checking all the limbs — a risky exercise for trees and scientists alike. “Note,” the researchers write, “that not a single tree was harmed during these experiments.”