Specifically, the investigators have improved understanding of the steps that lead to the production of IL-1 beta, a potent inflammatory protein signal released during many inflammatory responses.

“We now have a clearer understanding of the stepwise process that leads to the production of IL-1 beta,” said Andrea Wolf, PhD, assistant professor of Biomedical Sciences and Medicine at Cedars-Sinai, and a senior and corresponding author on the new study. “By understanding the process, we hope to one day find a treatment for diseases associated with this inflammatory response.”

When the innate immune system — the defense system we were born with — identifies a potentially harmful bacterium, virus, or other external invader, it unleashes white blood cells to surround and attack the foreign agent. This can cause swelling, redness, heat and pain in the body’s tissues that — in a healthy body — eventually go away.

Some people, however, get stuck in the inflammation phase. This causes what is known as chronic inflammation. Chronic inflammation can damage healthy cells in the body and is thought to lead to serious conditions like Type 2 diabetes, heart disease and depression.

“Inflammation, in many instances, is vital to a thriving immune system and healthy body,” said David Underhill, PhD, chair of the Department of Biomedical Sciences and the Janis and William Wetsman Family Chair in Inflammatory Bowel Disease, who is also a senior and corresponding author on the study. “However, prolonged inflammation can wreak havoc on the body. This underscores the importance of understanding the cellular process of how inflammation is activated so we can work toward finding new treatments to curb chronic inflammation.”

The study published today is a follow-up to Cedars-Sinai research published in 2016 that explains how cells act to detect an infection. In that study, investigators discovered that an enzyme called hexokinase, typically used by cells to convert glucose into energy, has a second, inflammatory function. They discovered that hexokinase binds to a sugar from the cell wall of bacteria and activates the inflammasomes, leading to the production of IL-1 beta. Inflammasomes are receptors of the innate immune system that recognize microbes and tissue damage.

The current work presents a more complete picture of this process.

The investigators discovered that hexokinase leaves the mitochondria, the part of a cell that generates energy. This jump-starts an immune response: The release of hexokinase destabilizes the mitochondria and alerts the cell that something is wrong. This leads to clustering of a channel called VDAC in the membrane of the mitochondria, which interacts with another protein called NLRP3 to initiate inflammasome assembly. The inflammasomes then produce IL-1 beta, a driver of inflammation.

Investigators studied cells that were derived from laboratory mice to understand the steps involved in the IL-1 beta pathway. The team used substances called inhibitors that block cellular functions as well as gene-editing technology to turn off certain genes and the proteins they express. This allowed them to understand which proteins are vital to triggering inflammation.

Cedars-Sinai postdoctoral scientist Sung Hoon Baik, PhD, used the super-resolution microscope that is part of the Cedars-Sinai Biobank and Research Pathology Resource to visualize and measure the steps of this inflammatory process within individual cells.

“Being able to target specific steps in this pathwayis vital, because in addition to being important for inflammation, the components of this pathway also play a vital role in maintaining energy within the cell,” Wolf said. “We want to home in on its inflammatory role, not just turn it all off, because that would be bad for the cell.”

The investigators are continuing to study the cellular steps leading up to, and resulting from, hexokinase’s role in the activation of inflammasomes. They are also using the results from this study to begin to target this inflammatory pathway in different diseases.

Other Cedars-Sinai investigators who worked on the study include Courtney Becker, manager of the Underhill Laboratory at Cedars-Sinai; Sarah Fett, research associate at Cedars-Sinai; and V. Krishnan Ramanujan, PhD, research associate professor in the Department of Medicine at Cedars-Sinai and director of the Cedars-Sinai Biobank.

Funding: The study was funded by the National Institutes of Health (award numbers R01AI148465, R01GM085796, R01AI071116).

“What we wanted to explore in this article is how social science research practices can be adapted, even reinvented, to harness the power of AI,” said Igor Grossmann, professor of psychology at Waterloo.

Grossmann and colleagues note that large language models trained on vast amounts of text data are increasingly capable of simulating human-like responses and behaviours. This offers novel opportunities for testing theories and hypotheses about human behaviour at great scale and speed.

Traditionally, social sciences rely on a range of methods, including questionnaires, behavioral tests, observational studies, and experiments. A common goal in social science research is to obtain a generalized representation of characteristics of individuals, groups, cultures, and their dynamics. With the advent of advanced AI systems, the landscape of data collection in social sciences may shift.

“AI models can represent a vast array of human experiences and perspectives, possibly giving them a higher degree of freedom to generate diverse responses than conventional human participant methods, which can help to reduce generalizability concerns in research,” said Grossmann.

“LLMs might supplant human participants for data collection,” said UPenn psychology professor Philip Tetlock. “In fact, LLMs have already demonstrated their ability to generate realistic survey responses concerning consumer behaviour. Large language models will revolutionize human-based forecasting in the next 3 years. It won’t make sense for humans unassisted by AIs to venture probabilistic judgments in serious policy debates. I put an 90% chance on that. Of course, how humans react to all of that is another matter.”

While opinions on the feasibility of this application of advanced AI systems vary, studies using simulated participants could be used to generate novel hypotheses that could then be confirmed in human populations.

But the researchers warn of some of the possible pitfalls in this approach — including the fact that LLMs are often trained to exclude socio-cultural biases that exist for real-life humans. This means that sociologists using AI in this way couldn’t study those biases.

Professor Dawn Parker, a co-author on the article from the University of Waterloo, notes that researchers will need to establish guidelines for the governance of LLMs in research.

“Pragmatic concerns with data quality, fairness, and equity of access to the powerful AI systems will be substantial,” Parker said. “So, we must ensure that social science LLMs, like all scientific models, are open-source, meaning that their algorithms and ideally data are available to all to scrutinize, test, and modify. Only by maintaining transparency and replicability can we ensure that AI-assisted social science research truly contributes to our understanding of human experience.”

Promoting national security and economic competitiveness will require America’s researchers to find new ways to obtain the materials that we need for many technologies. These include batteries, magnets in electric motors, catalysts, nuclear reactors and other essential carbon-free energy technologies.

Water represents one underexplored avenue of acquiring these materials. Scientists at the U.S. Department of Energy’s Argonne National Laboratory have recently published a comprehensive review detailing the various mechanisms by which critical materials can be extracted from diverse water streams.

Different types of water offer different kinds of material resources, said Seth Darling, chief science and technology officer for Argonne’s Advanced Energy Technologies directorate. ​”The oceans are such a tremendous resource because the total quantities of many valuable and important materials are vast, but they are also highly dilute,” he said. ​”Wastewater has also been in need of reframing — we want people to see that wastewater is not truly waste, rather, it’s rich with all sorts of valuable stuff.”

Darling also pointed to groundwater aquifers and geothermal brines as other possible sources of valuable materials. These materials include lithium, which is increasingly in demand for electric vehicle batteries and could be used to help decarbonize our economy. ​”Lithium is in the ocean and in geothermal brines; you’d extract it differently from these two sources but it’s important to understand which is cheapest, has the smallest environmental impact, and enables secure supply chains,” Darling said. ​”For many other materials, water is underexplored as a source, and that’s something we’re paying increasingly more attention to.”

The technologies that Darling and his colleagues are exploring to extract critical materials from different types of water range from the traditional (like membranes) to the innovative (like interfacial solar steam generators).

Omar Kazi, a Ph.D. student in molecular engineering at the University of Chicago working with Darling, is studying methods to concentrate wastewater streams to recover valuable materials. ​”Getting rid of the water through evaporation is an energy-intensive and slow process,” Kazi said. ​”In geothermal brines, it can take years for water to evaporate to be able to recover the lithium that’s contained in them, which creates a huge bottleneck. The question we are asking is ​’how we can make the water evaporate faster?'”

One way to do that could be through the use of porous photothermal materials, which convert light to heat efficiently. These light absorbers act like a black T-shirt that heats up on a sunny day. That heat is transferred to the water directly at the interface with the surrounding air, significantly accelerating evaporation.

Overall, Darling noted, Argonne has rich capabilities in supply chain, life cycle and technoeconomic analyses. In addition, the laboratory specializes in the materials, chemistry and process engineering relevant to critical material extraction. This uniquely positions the lab to help achieve a more secure and circular economy of materials, especially when it comes to getting more out of water streams.

A paper based on the study, ​”Material design strategies for recovery of critical resources from water,” appeared online in Advanced Materials on March 31.

In addition to Darling and Kazi, other authors of the study include Argonne’s Wen Chen, Jamila Eatman, Feng Gao, Yining Liu, Yuqin Wang, and Zijing Xia.

This work was supported as part of the Advanced Materials for Energy-Water Systems (AMEWS) Center, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences at Argonne National Laboratory.

At the latest, the Russia-Ukraine conflict revealed loud and clear that the global food supply chain acts as a complex network, connecting nations and facilitating the spread of disruptions from local to distant regions. “However, previous studies often focus on direct dependencies and overlook indirect dependencies resulting from the unavailability of essential inputs, making a comprehensive assessment of the global food system difficult,” emphasizes research director Stefan Thurner of the Complexity Science Hub.

INDIRECT EFFECTS OFTEN EXCEED DIRECT EFFECTS

To bridge this gap, the research team developed a dynamic global food system model, incorporating data from 192 countries and territories and encompassing 125 food and agricultural products. “This model enabled us to simulate shocks to specific products and countries, closely monitoring the subsequent effects across the entire supply chain,” explains Moritz Laber of the Complexity Science Hub. By quantifying the relative reduction in product availability compared to a baseline scenario (without the shock), the researchers gained valuable insights into the magnitude of these shocks. Remarkably, they found that indirect effects often exceeded direct effects. For example, a shock to Ukrainian corn production led to a 13% decline in pork availability in Southern Europe. In comparison, a shock to Ukrainian pork production had a negligible effect of less than 1%.

UP TO 85% LOSS OF MAIZE

In a worst-case scenario simulation, where agricultural production in Ukraine was completely lost due to the Russia-Ukraine conflict, the study unveiled diverse effects on products and regions worldwide. “The loss of grains, particularly maize, reached up to 85%, while edible oils, especially sunflower oil, experienced losses of up to 89%. Additionally, certain meat types, such as poultry, suffered losses of up to 25% in various countries,” says Laber. The number of products for which a region is dependent on Ukraine varies greatly: Southern Europe is the most affected, with 19 out of 125 products with losses of more than 10%, followed by West Asia and North Africa, where this is the case for 15 and 11 products respectively.

These findings emphasize that localized production disruptions have far-reaching implications, extending beyond geographic boundaries through trade relationships and the entire production chain. Consequently, it is imperative to consider both direct and indirect effects when estimating losses and formulating effective interventions.

RISK NOT ONLY FROM WARS

As the Russia-Ukraine conflict enters its second year, food prices are still above 2021 levels, according to the European Council. In addition, various events, including extreme weather events, economic crises, and geopolitical tensions, can trigger similar disruptions. This underscores the importance of exploring interdependencies within global food supply chains and gaining a comprehensive understanding of the direct and indirect impacts of local shocks to raise awareness among policymakers and stakeholders of otherwise overlooked risks within the global food system.

These research findings are a valuable first leap in understanding the complex dynamics of global food supply chains and their vulnerability to local shocks. Further research is needed to map them at a more granular level considering individual products and subnational scales at a higher temporal resolution. Moreover, at present, the model assumes that countries do not change their trading partners after a shock. However, restructuring trade relations may exacerbate existing inequalities, as wealthier countries may secure remaining resources at higher prices from alternative suppliers.

In March, the CSH co-founded the Austrian Supply Chain Intelligence Institute (ASCII) to contribute even more to making supply dependencies visible in the future.