Hunger is a powerful sensation with important biological underpinnings. It signals the body to look for food, which is a crucial behavior to prevent starvation and ensure survival. When we’re hungry, we crave for food — and when we finally get to eat, our body rewards us with pleasant feelings and a general state of happiness.

A network of brain circuits and signaling pathways orchestrates the eating behavior of humans and animals and elicits the associated sensations. One of the central players in this network is the hormone ghrelin. It is released by stomach cells when humans and animals are hungry or fasting, and promotes feeding behavior.

The department of Rüdiger Klein at the Max Planck Institute for Biological Intelligence studies the brain networks that underly feeding behavior in mice. To this end, the researchers conducted a thorough analysis of the different cell types in a brain region known as the central amygdala. “Previously, the amygdala had mostly been studied in the context of feelings like fear and reward, while the regulation of feeding was thought to happen in different parts of the brain, such as the hypothalamus,” says Christian Peters, a postdoctoral researcher in the department.

Nine cell clusters

Peters and his colleagues analyzed individual cells in the central amygdala, studying messenger RNA molecules — the cell’s working copies of their genes. The analysis revealed that the cells are organized into nine different cell clusters. Some of these clusters promote appetite while others inhibit it, and they adjust their production of messenger RNAs when the mice are fed or fasting.

“We now have a much better understanding of the diversity of cell types and the physiological processes that promote feeding in the central amygdala,” says Rüdiger Klein. “Our research uncovers for the first time that the ‘hunger hormone’ ghrelin also acts on cells in the central amygdala.” There, it activates a small subset of cell clusters, collectively marked by the presence of the protein Htr2a, to increase feeding.

Multiple functions for ghrelin

The scientists found that the Htr2a neurons became active after an overnight fast or when stimulated by the hormone ghrelin. The cells also responded when the researchers presented food to the mice. “We think that ghrelin performs multiple functions,” explains Christian Peters. “When mice are hungry, ghrelin activates the appetitive brain regions to predispose the animals for eating. In addition, the hormone enhances the activity in brain circuits, such as the amygdala, that confer rewards, which is likely an incentive to eat additional food.” This way, ghrelin increases the palatability of food in proportion to how satiated the mice currently are.

After a fasting diet, when the animals were very hungry the activity of Htr2a neurons was not needed to start feeding, presumably because the tastiness of food is less important under these conditions. “Other brain circuits, for example the hypothalamus, which regulate the body’s metabolism, take over and signal the mice that it’s important to eat in order to survive,” says Christian Peters.

Feeling hungry or satiated has profound impacts on physical but also on emotional wellbeing, as probably everyone knows by the pleasures associated with eating tasty food. “The neuronal networks that convey these feelings are obviously linked to those that control eating, yet it is not fully understood how exactly they influence each other,” says Rüdiger Klein.

“If we figure out these connections, we will better understand the neuronal processes that are involved in pathological eating behaviors, such as overeating,” concludes Christian Peters. “There are numerous biological factors that contribute to such a complex behavior and we have to look at the physiological processes to understand these factors.” Ultimately, this knowledge might lead to novel therapeutic approaches to alleviate eating disorders. For now, the research lays the groundwork for further studies to investigate how specific neuron populations are involved in the neuronal circuits that control feeding. It also adds another important piece to the puzzle of understanding how the brain orchestrates behavior.

The findings are important because a data center can consume up to 50 times more energy per square foot of floor space than a typical office building, according to the U.S. Department of Energy.

A data center houses an organization’s information technology operations and equipment; it stores, processes and disseminates data and applications. Data centers account for roughly 2% of all electricity use in the United States, the DOE says.

According to the U.S. International Trade Commission, the number of data centers has risen rapidly as data demand has soared. In the United States, home to many firms that produce and consume vast amounts of data including Facebook, Amazon, Microsoft and Google, there are more than 2,600 data centers.

The advance by John Conley of the OSU College of Engineering, former Oregon State colleague Alan Wang, now of Baylor, and OSU graduate students Wei-Che Hsu, Ben Kupp and Nabila Nujhat involves a new, ultra-energy-efficient method to compensate for temperature variations that degrade photonic chips. Such chips “will form the high-speed communication backbone of future data centers and supercomputers,” Conley said.

The circuitry in photonic chips uses photons — particles of light — rather than the electrons that course through conventional computer chips. Moving at the speed of light, photons enable the extremely rapid, energy-efficient transmission of data.

The issue with photonic chips is that up until now, significant energy has been required to keep their temperature stable and performance high. The team led by Wang, however, has shown that it’s possible to reduce the energy needed for temperature control by a factor of more than 1 million.

“Alan is an expert in photonic materials and devices and my area of expertise is atomic layer deposition and electronic devices,” Conley said. “We were able to make working prototypes that show temperature can be controlled via gate voltage, which means using virtually no electric current.”

Presently, Wang said, the photonics industry exclusively relies on components known as “thermal heaters” to fine tune the working wavelengths of high-speed, electro-optic devices and optimize their performance. These thermal heaters consume several milliwatts of electricity per device.

“That might not sound like much considering that a typical LED lightbulb uses 6 to 10 watts,” Wang said. “However, multiply those several milliwatts by millions of devices and they add up quickly, so that approach faces challenges as systems scale up and become bigger and more powerful.”

“Our method is much more acceptable for the planet,” Conley added. “It will one day allow data centers to keep getting faster and more powerful while using less energy so that we can access ever more powerful applications driven by machine learning, such as ChatGPT, without feeling guilty.”

These observations were made directly beneath typhoon No. 11, called “Hinnamnor”/”Henry,” in the summer of 2022. NTT and OIST plan to continue joint research contributing to observation methods that improve the accuracy of typhoon predictions, and to explain the mechanisms of interaction between the atmosphere and ocean using observation data from directly beneath typhoons.

Background

Typhoons, which can have major impacts on society and the environment, have recently been intensifying in strength and causing more damage due to global warming and other climate change effects. To prepare effectively for a typhoon, it is important to have an accurate understanding, as early as possible, of how the storm conditions will be upon landfall. However, there is currently no way to accurately know the state and intensity of a typhoon while it is still over the ocean from available satellite images and other observations. As such, typhoon information in weather reports is estimated based on analysis of weather satellite images with limited accuracy.

In an effort to improve the accuracy of forecasts, a national research project used aircraft to make direct observations in 2017. This project demonstrated that observation data from aircraft can contribute to increasing the accuracy of typhoon forecasts. In 2013, OIST made marine and atmospheric observations directly under a very strong Category 4 typhoon (Typhoon No. 24, “Danas”) using a Wave Glider (model SV2) from Liquid Robotics Inc., an autonomous, unmanned surface vehicle which they nicknamed “OISTER.” This research demonstrated the need-to-know conditions accurately at the ocean’s surface, directly below the typhoon. However, it has not been possible to make such observations accurately with stronger typhoons, because conditions become too severe.

With a warming climate creating conditions conducive to intensification, research on typhoons has become increasingly important, as signified by the establishment of Japan’s only research facility dedicated to the study of typhoons in 2021.

In 2021, NTT and OIST began joint research to implement the observation of factors necessary to predict typhoons, even in the harsh environment of a strong typhoon. In 2022, NTT purchased a new Wave Glider (model SV3) which was called “Seiuchi-san” and began typhoon observations using both Wave Glider devices .

Key results

• Successful observation of various factors important in predicting typhoon intensity.
• Sudden drop in air pressure near the center of the typhoon (violent wind region).
• Drop in seawater temperature in two areas (violent and strong wind regions) due to churning by the typhoon. Sudden increase in significant wave height near the center of the typhoon (in the violent wind region).

These are described in more detail in the next section.

Demonstration overview

Typhoon Hinnamnor began on August 28, 2022, near the island of Minamitorishima, with air pressure dropping to 920 hPa as it moved westward and became a violent, Category 5 typhoon. After checking the predicted path of the typhoon, the two Wave Gliders were put into operation.

Seiuchi-san operated in the violent wind region, not less than 11 km from the typhoon center (with average wind speeds of 25 m/s or more), and OISTER operated in the strong wind region approximately 100 km from the center (with average wind speeds of 15 m/s or more). Both vehicles took atmospheric and ocean measurements simultaneously.

Air pressure is directly related to intensity of a typhoon, and Seiuchi-san was able to capture sudden, rapid changes in air pressure in the violent wind region of the typhoon. It was able to confirm the lowest pressure value at its closest approach to the typhoon, at approximately 20:00 on August 31. In contrast, OISTER made observations in the strong wind region, and was not able to recognize such drops.

These experiments were also able to measure changes in the temperature of sea water, which is important in estimating the intensity of a typhoon. Changes in water temperature affect the supply of energy to the typhoon and correlate with the strength of the typhoon, so it is another essential element in predicting intensity precisely. With Seiuchi-san near the center of the typhoon, the scientists were able to detect that the drop in sea-water temperature (approx. 2°C) occurred more suddenly.

Seiuchi-san also measured a maximum wave height of approximately 9 m. Since waves are caused by wind, knowing the wave height makes it possible to estimate wind strength. As such, it is useful to obtain wave height data from directly below a typhoon, but these data have been difficult to obtain from satellite observations.

The data also showed changes in the speed of ocean currents as the typhoon passed. The researchers also measured ecosystem factors, including salt concentrations related to nutritive salts, and amounts of chlorophyll a, which is useful for analyzing phytoplankton. The team plan to perform more detailed analysis on the effects of typhoons in the future.

These results were published in the May 22, 2023 issue of Scientific Online Letters on the Atmosphere (SOLA), by the Meteorological Society of Japan, which has been leading meteorological research since it was established in 1882.

[Title] Simultaneous Observations of Atmosphere and Ocean Directly under Typhoons Using Autonomous Surface Vehicles

The experiments also collected data on the behavior of the Wave Gliders themselves, in addition to atmospheric and ocean data, including orientation and movement. The scientists will analyze this behavior data and use it to improve observation equipment so that they can continue to make stable observations in the future. They also plan to continue accumulating and verifying observation data, and to develop explanations for the mechanisms of interaction between the atmosphere and the oceans.

Future prospects

The research team aim to improve the accuracy of typhoon predictions by establishing methods for making typhoon observations, and to improve typhoon prediction models by explaining the mechanisms at work within typhoons. This will enable scientists to more accurately analyze and predict the conditions of typhoons before they reach land.

In the future, the researchers also plan to collaborate with various industries and facilities to optimize methods for real-time typhoon observation, and to apply them in Earth Information Analysis Infrastructure Technology using the Space integrated computing network. They will also contribute to realizing a resilient society that can co-exist with typhoons, by adapting proactively to the environment based on highly accurate typhoon prediction.

By using observation data to understand the effects of global warming on typhoons, and conversely, the effects of typhoons on the global environment, the researchers hope to gain a better understanding of the global environment, and be better able to promote changes in our society’ behavior to preserve and regenerate the Earth.