Wild rice is different from domesticated rice in that wild rice naturally sheds ripe seeds, shattering them to the ground when they mature, while cultivated rice seeds stay on the plants when they mature.

To harvest rice, some sort of tools would have been needed. In harvesting rice with tools, early rice cultivators were selecting the seeds that stay on the plants, so gradually the proportion of seeds that remain increased, resulting in domestication.

“For quite a long time, one of the puzzles has been that harvesting tools have not been found in southern China from the early Neolithic period or New Stone Age (10,000 — 7,000 Before Present) — the time period when we know rice began to be domesticated,” says lead author Jiajing Wang, an assistant professor of anthropology at Dartmouth. “However, when archaeologists were working at several early Neolithic sites in the Lower Yangtze River Valley, they found a lot of small pieces of stone, which had sharp edges that could have been used for harvesting plants.”

“Our hypothesis was that maybe some of those small stone pieces were rice harvesting tools, which is what our results show.”

In the Lower Yangtze River Valley, the two earliest Neolithic culture groups were the Shangshan and Kuahuqiao.

The researchers examined 52 flaked stone tools from the Shangshan and Hehuashan sites, the latter of which was occupied by Shangshan and Kuahuqiao cultures.

The stone flakes are rough in appearance and are not finely made but have sharp edges. On average, the flaked tools are small enough to be held by one hand and measured approximately 1.7 inches in width and length.

To determine if the stone flakes were used for harvesting rice, the team conducted use-wear and phytolith residue analyses.

For the use-wear analysis, micro-scratches on the tools’ surfaces were examined under a microscope to determine how the stones were used. The results showed that 30 flakes have use-wear patterns similar to those produced by harvesting siliceous (silica-rich) plants, likely including rice.

Fine striations, high polish, and rounded edges distinguished the tools that were used for cutting plants from those that were used for processing hard materials, cutting animal tissues, and scraping wood.

Through the phytolith residue analysis, the researchers analyzed the microscopic residue left on the stone flakes known as “phytoliths” or silica skeleton of plants. They found that 28 of the tools contained rice phytoliths.

“What’s interesting about rice phytoliths is that rice husk and leaves produce different kinds of phytolith, which enabled us to determine how the rice was harvested,” says Wang.

The findings from the use-wear and phytolith analyses illustrated that two types of rice harvesting methods were used — “finger-knife” and “sickle” techniques. Both methods are still used in Asia today.

The stone flakes from the early phase (10,000 — 8,200 BP) showed that rice was largely harvested using the finger-knife method in which the panicles at the top of the rice plant are reaped. The results showed that the tools used for finger-knife harvesting had striations that were mainly perpendicular or diagonal to the edge of the stone flake, which suggests a cutting or scraping motion, and contained phytoliths from seeds or rice husk phytoliths, indicating that the rice was harvested from the top of the plant.

“A rice plant contains numerous panicles that mature at different times, so the finger-knife harvesting technique is especially useful when rice domestication was in the early stage,” says Wang.

The stone flakes however, from the later phase (8,000 — 7,000 BP) had more evidence of sickle harvesting in which the lower part of the plant was harvested. These tools had striations that were predominantly parallel to the tool’s edge, reflecting that a slicing motion had likely been used.

“Sickle harvesting was more widely used when rice became more domesticated, and more ripe seeds stayed on the plant,” says Wang. “Since you are harvesting the entire plant at the same time, the rice leaves and stems could also be used for fuel, building materials, and other purposes, making this a much more effective harvesting method.”

Wang says, “Both harvesting methods would have reduced seed shattering. That’s why we think rice domestication was driven by human unconscious selection.”

Building on that technique, MIT and Harvard University researchers have now devised a way to achieve longer-term changes in neuron activity. With their new strategy, they can use light exposure to change the electrical capacitance of the neurons’ membranes, which alters their excitability (how strongly or weakly they respond to electrical and physiological signals).

Changes in neuron excitability have been linked to many processes in the brain, including learning and aging, and have also been observed in some brain disorders, including Alzheimer’s disease.

“This new tool is designed to tune neuron excitability up and down in a light-controllable and long-term manner, which will enable scientists to directly establish the causality between the excitability of various neuron types and animal behaviors,” says Xiao Wang, the Thomas D. and Virginia Cabot Assistant Professor of Chemistry at MIT, and a member of the Broad Institute of MIT and Harvard. “Future application of our approach in disease models will tell whether fine-tuning neuron excitability could help reset abnormal brain circuits to normal.”

Wang and Jia Liu, an assistant professor at Harvard School of Engineering and Applied Sciences, are the senior authors of the paper, which appears today in Science Advances.

Chanan Sessler, an MIT graduate student in the Department of Chemistry; Yiming Zhou, a postdoc at the Broad Institute; and Wenbo Wang, a graduate student at Harvard, are the lead authors of the paper.

Membrane manipulation

Optogenetics is a tool scientists use to manipulate neuron activity, by engineering them to express light-sensitive ion channels. When those engineered neurons are exposed to light, changes in the flow of ions through the channels suppresses or boosts neuron activity.

“By using light, you can either open or close these ion channels, and that in turn will excite or silence the neurons. That allows for a fast response in real time, but it means that if you want to control these neurons, you have to be constantly illuminating them,” Sessler says.

The MIT and Harvard team set out to modify the technique so that they could generate longer-lasting changes in excitability, rather than transient activation or suppression of activity. To do that, they focused on altering the capacitance of the cell membrane, which is a key determinant of the membrane’s ability to conduct electricity.

When the capacitance of the cell membrane is increased, neurons become less excitable — that is, less likely to fire an action potential in response to input from other cells. When the capacitance is decreased, neurons become more excitable.

“The excitability of neurons is governed by two membrane properties: conductivity and capacitance. While many studies have focused on membrane conductivity executed by ion channels, naturally occurring myelination processes suggest that modulating membrane capacitance is another effective way of tuning neuron excitability during brain development, learning, and aging. So, we wondered if we could tune neuron excitability by changing membrane capacitance,” Liu says.

While a postdoc at Stanford University, Liu and his colleagues showed that they could alter neurons’ excitability by inducing them to assemble either conductive or insulating polymers in their membranes. In that study, published in 2020, Liu used an enzyme called peroxidase to assemble the polymers. However, that approach did not allow for precise control over where the polymers accumulated. It also posed some risk because the reaction requires hydrogen peroxide, which can damage cells.

To overcome those limitations, Liu’s lab at Harvard teamed up with Wang’s MIT lab to try a new approach. Instead of using peroxidase, the researchers made use of a genetically engineered light-sensitive protein that can catalyze the formation of polymers.

Working with neurons grown in a lab dish, the researchers engineered the cells to express this light-sensitive protein, known as miniSOG. When activated by blue wavelengths of light, miniSOG produces highly reactive molecules called reactive oxygen species. At the same time, the researchers expose the cells to building blocks of either a conducting polymer, known as PANI, or an insulating polymer, known as PDAB.

After several minutes of light exposure, the reactive oxygen species spur those building blocks to assemble into either PDAB or PANI.

Using a technique known as whole cell patch clamp, the researchers found that neurons with conducting PANI polymers became less excitable, while neurons with insulating PDAB polymers became more excitable. They also found that longer light exposures produced larger shifts in excitability.

“The advantage of optogenetic polymerization is the precise temporal control over polymerization reaction, which allows the predictable stepwise fine-tuning of membrane properties,” Zhou says.

Long-lasting changes

The researchers showed that the changes in excitability lasted for up to three days, which is as long as they could keep the neurons alive in their lab dish. They are now working on adapting this technique so that it could be used in slices of brain tissue and then, they hope, in the brains of animals such as mice or the worm C. elegans.

Such animal studies could help to shed light on how changes in neuron excitability affect disorders such as multiple sclerosis and Alzheimer’s disease, the researchers say.

“If we have a certain neuron population that we know has higher or lower excitability in a specific disease, then we can potentially modulate that population by transducing mice with one of these photosensitizing proteins that’s only expressed in that neuron type, and then see if that has the desired effect on behavior,” Wenbo Wang says. “In the near future, we’re using it more as a model to investigate those diseases, but you could imagine potential therapeutic applications.”

The research was funded by the Searle Scholars Program, the Stanley Center for Psychiatric Research at the Broad Institute, the Air Force Office of Scientific Research Young Investigator Program, the National Science Foundation through the Harvard University Materials Research Science and Engineering Center, and the Harvard Dean’s Competitive Fund for Promising Scholarship.

“Our lab is always trying to make robots more enduring and agile, so they operate longer with more capabilities,” said Rob Shepherd, associate professor of mechanical and aerospace engineering. “If you make robots operate for a long time, they’re going to accumulate damage. And so how can we allow them to repair or deal with that damage?”

Shepherd’s Organic Robotics Lab has developed stretchable fiber-optic sensors for use in soft robots and related components — from skin to wearable technology.

For self-healing to work, Shepard says the key first step is that the robot must be able to identify that there is, in fact, something that needs to be fixed.

To do this, researchers have pioneered a technique using fiber-optic sensors coupled with LED lights capable of detecting minute changes on the surface of the robot.

These sensors are combined with a polyurethane urea elastomer that incorporates hydrogen bonds, for rapid healing, and disulfide exchanges, for strength.

The resulting SHeaLDS — self-healing light guides for dynamic sensing — provides a damage-resistant soft robot that can self-heal from cuts at room temperature without any external intervention.

To demonstrate the technology, the researchers installed the SHeaLDS in a soft robot resembling a four-legged starfish and equipped it with feedback control. Researchers then punctured one of its legs six times, after which the robot was then able to detect the damage and self-heal each cut in about a minute. The robot could also autonomously adapt its gait based on the damage it sensed.

While the material is sturdy, it is not indestructible.

“They have similar properties to human flesh,” Shepherd said. “You don’t heal well from burning, or from things with acid or heat, because that will change the chemical properties. But we can do a good job of healing from cuts.”

Shepherd plans to integrate SHeaLDS with machine learning algorithms capable of recognizing tactile events to eventually create “a very enduring robot that has a self-healing skin but uses the same skin to feel its environment to be able to do more tasks.”

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Materials provided by Cornell University. Original written by David Nutt, courtesy of the Cornell Chronicle. Note: Content may be edited for style and length.