The researchers, led by Natalie Bareis, Ph.D., with Columbia University Irving Medical Center and New York State Psychiatric Institute, examined national data that were collected from Oct. 2020 to Oct. 2022 on 4,764 adults aged 18 to 65 in the Substance Abuse and Mental Health Services Agency-sponsored U.S. Mental and Substance Use Disorders Prevalence Study (MDPS). Using sampling weights, the authors compared sociodemographic characteristics and comorbid behavioral health conditions of individuals with or without schizophrenia spectrum disorders (schizophrenia, schizoaffective, and schizophreniform disorders).

Among 114 adults with schizophrenia spectrum disorders, the most common comorbid conditions were major depressive episode (52%) and alcohol use (23%), cannabis use (20%), and posttraumatic stress disorders (17%). Both suicidal ideation and suicide attempts in the past year were significantly more likely among individuals with schizophrenia spectrum disorders than among those without them.

While almost everyone with schizophrenia spectrum disorders in this sample had health care coverage, about 70% had any type of mental health treatment in the past year and only about 30% were currently taking an antipsychotic. While many individuals with schizophrenia spectrum disorders may recover, most of the individuals in the survey were unemployed and most had serious functional impairment.

Available, effective treatments and services include antipsychotic medications, individual placement and support, programs to promote employment, assertive community treatment, and coordinated specialty care for first-episode psychosis.

“The MDPS is an update to decades old surveys of psychiatric disorders in the U.S. It had a focus on identifying schizophrenia spectrum disorders by administering the Structured Clinical Interview for the DSM-5 to all participants,” Bareis noted. “We had hoped that during this period, with the advent of new treatments and services, the circumstances of individuals with schizophrenia spectrum disorders would have improved. Instead, persistent high rates of poverty, unemployment, and poor functioning suggest that existing treatment and social welfare approaches are not meeting the needs of many people with schizophrenia spectrum disorders. Policies to improve access to and use of existing evidence-based interventions are essential.”

Ling Li, an associate professor in the MSU Department of Biological Sciences, has spent more than a decade studying rice and soybean crops, with the goal of providing a new strategy for crop improvement to increase protein content. Her work offers a potential solution to combat global protein deficiency, a condition affecting millions, particularly children, contributing to cognitive impairments, stunted growth and susceptibility to diseases like Kwashiorkor, a severe form of malnutrition caused primarily by a deficiency in dietary protein.

“With rising concerns about protein deficiency and the environmental impact of animal-based protein sources, boosting plant protein content is crucial for improving both human health and sustainability,” Li said.

Li’s research — which includes more than 10 years of field work and field data to support her findings — focuses on optimizing the genetic expression of rice and soybean plants, resulting in increased protein levels and reduced carbohydrate content. Her novel approach uses gene editing to remove repressor elements from noncoding DNA sequences, unlocking the potential for higher protein production in crops. This strategy not only offers improved nutritional value but also promotes more sustainable agricultural practices by reducing the reliance on animal-derived proteins.

The U.S. Department of Agriculture’s Animal Plant Health Inspection Service determined Li’s gene-edited high-protein crops can be listed as nonregulatory soybean and rice, she said.

The findings provide a promising blueprint for enhancing crop productivity and nutritional quality through precise genome editing, with far-reaching implications for global food security and environmental sustainability.

Li’s research includes collaboration with the Bing Yang Lab at the University of Missouri and the Dan Voytas Lab at the University of Minnesota.

The answer, according to archaeologists from the University of Colorado Boulder: It’s complicated. In a new study, the team drew on a wide range of evidence — from medical studies of modern equestrians to records of human remains across thousands of years.

The researchers concluded that horseback riding can, in fact, leave a mark on human skeletons, such as by subtly altering the shape of the hip joint. But those sorts of changes on their own can’t definitively reveal whether people have ridden horses during their lives. Many other activities, even sitting for long periods of time, can also transform human bones.

“In archaeology, there are vanishingly few instances in which we can tie a particular activity unequivocally to skeletal changes,” said Lauren Hosek, lead author of the study and an assistant professor in the Department of Anthropology at CU Boulder.

She and her colleagues reported their findings Sept. 20 in the journal Science Advances.

The results may have implications for researchers who study the origins of when humans first domesticated horses — and also cast doubt on a long-standing theory in archaeology known as the Kurgan hypothesis.

The first equestrians

The research lies at the center of what is among the old debates in archaeology, said William Taylor, a co-author of the new study and curator of archaeology at the CU Museum of Natural History.

He explained that the earliest, incontrovertible evidence of humans using horses for transport comes from the region around the Ural Mountains of Russia. There, scientists have uncovered horses, bridles and chariots dating back to around 4,000 years ago.

But the Kurgan hypothesis, which emerged in the early 20th century, argues that the close relationship between humans and horses began much earlier. Proponents believe that around the fourth millennium B.C., ancient humans living near the Black Sea called the Yamnaya first began galloping on horseback across Eurasia. In the process, the story goes, they may have spread a primordial version of the languages that would later evolve into English, French and more.

“A lot of our understanding of both the ancient and modern worlds hinges on when people started using horses for transportation,” Taylor said. “For decades, there’s been this idea that the distribution of Indo-European languages is, in some way, related to the domestication of the horse.”

Recently, scientists have pointed to human remains from the Yamnaya culture dating back to about 3500 B.C. as a key piece of evidence supporting the Kurgan hypothesis. These ancient peoples, the group argued, showed evidence of wear and tear in their skeletons that likely came from riding horses.

Hips can lie

But, in the new study, Hosek and Taylor argue that the story isn’t so simple.

Hosek has spent a lot of time poring over human bones to learn lessons about the past. She explained that the skeleton isn’t static but can shift and change shape over an individual’s lifetime. If you pull a muscle, for example, a reaction can emerge at the site where the muscle attaches to the underlying bone. In some cases, the bone can become more porous or raised ridges may form.

Reading those sorts of clues, however, can be murky at best. The hip joint is one example.

Hosek noted that when you flex your legs at the hip for long periods of time, including during long horse rides, the ball and socket of the hip joint may rub together along one edge. Over time, that rubbing can cause the round socket of the hip bone to become more elongated, or oval in shape. But, she said, other activities can cause the same kind of elongation.

Archaeological evidence shows that humans used cattle, donkeys and even wild asses for transport in some areas of western Asia centuries before they first tamed horses. Ancient peoples likely yoked these beasts of burden to pull carts or even smaller, two-wheeled vehicles that looked something like a chariot.

“Over time, this repetitive, intense pressure from that kind of jostling in a flexed position could cause skeletal changes,” Hosek said.

She’s seen similar changes, for example, in the skeletons of Catholic nuns from the 20th century. They never rode horses, but did take long carriage rides across the American West.

Ultimately, Hosek and Taylor say that human remains on their own can’t be used to put a date on when people first started riding horses — at least not with currently available science.

“Human skeletons alone are not going to be enough evidence,” Hosek said. “We need to couple that data with evidence coming out of genetics and archaeology and by looking at horse remains, too.”

Taylor added that the picture doesn’t look good for the Kurgan hypothesis:

“At least for now, none of these lines of evidence suggest that the Yamnaya people had domestic horses.”

Their tool, the Framework for Narrative Storylines and Impact Classification (FRNSIC), can help decision-makers explore many plausible futures and identify consequential scenario storylines — or descriptions of what critical futures might look like — to help planners better address the uncertainties and impacts presented by climate change. They reported their findings Sept. 19 in the journal Earth’s Future.

“One of the ways states like Colorado are preparing for the future is by making plans for how things might evolve based on the available science and inputs from various stakeholders,” said Antonia Hadjimichael, assistant professor in the Department of Geosciences at Penn State and lead author of the study. “This scenario planning process recognizes that planning for the future comes with many uncertainties about climate and water needs. So, planners have to consider different possibilities, such as a high-warming or a low-warming scenario.”

Hadjimichael said that both the scientific community and decision makers around the world often turn to scenarios to describe what conditions may look like in the future, but this approach may regard only a few possibilities and discount other alternatives.

These scenario planning approaches often feature a relatively small number of scenarios — for example what drought conditions might look like under different levels of warming — and may fail to capture the complexity of all the factors involved.

Alternatively, scientists use a technique called exploratory modeling, where models simulate thousands to millions of possible futures to discover which are consequential. But this approach is often not practical for use by decision makers, the scientists said.

“We wanted to provide something in the middle,” Hadjimichael said. “We wanted to create something that bridges the two — that considers the complexities but also boils it down to something that’s a little more actionable and a little less daunting.”

Their tool, FRNSIC, uses exploratory modeling first to investigate a large number of hypothesized plausible future conditions. It then uses that data to classify and identify relevant and locally meaningful storylines, the scientists said.

“Our approach essentially explores plausible future impacts and then says, ‘for this stakeholder, this is the storyline that would matter the most — and then for this other stakeholder, there is a different storyline they should be worried about,” Hadjimichael said. “It’s adding a little bit more pluralism and a little bit more nuance into how planning scenarios are established.”

In the Colorado River basin, decision makers face a complex set of factors, including how to supply enough water for growing populations and farmers while ensuring their state is not using more than their allowed share of the river’s flow, Hadjimichael said.

“The problem is there is not a single criterion that captures everybody and what they care about,” she said. “Maybe you have a very large farm, and maybe I have a very small farm. And maybe we grow different things. It’s hard to use a single factor to find out scenarios that would make us all happy, or make us all unhappy.”

The storylines produced by FRNSIC can be used in future work in the Colorado River basin — for example, how drought events are impacted when populations adapt and make changes.

“This allows policymakers to explore different states the world and helps review how different interventions might affect the basin under each storyline,” Hadjimichael said. “These drought scenarios can be used to illuminate potential consequences, and therefore be used in negotiations or when asking stakeholders for their input.”

Also contributing were Patrick Reed, professor at Cornell University; Julianne Quinn, assistant professor at the University of Virginia; and Chris Vernon, geospatial scientist, and Travis Thurber, software engineer, at Pacific Northwest National Laboratory

The U.S. Department of Energy, Office of Science, as part of research in MultiSector Dynamics, in the Earth and Environmental System Modeling Program supported this research.

“Lasso peptides are interesting because they are basically linear molecules that have been tied into a slip knot-like shape,” said Susanna Barrett, a graduate student in the Mitchell lab (MMG). “Due to their incredible stability and engineerability, they have a lot of potential as therapeutics. They have also been shown to have antibacterial, antiviral, and anti-cancer properties.”

Lasso peptides are ribosomally synthesized and post-translationally modified molecules. The peptide chains are formed from joining amino acids together in the form of a string, which is done by the ribosome. Two enzymes, a peptidase and a cyclase, then collaborate to convert a linear precursor peptide into the distinctive knotted lasso structure. Since their discovery over three decades ago, scientists have been trying to understand how the cyclase folds the lasso peptide.

“One of the major challenges of solving this problem has been that the enzymes are difficult to work with. They are generally insoluble or inactive when you attempt to purify them,” Barrett said.

One rare counterexample is fusilassin cyclase, or FusC, which the Mitchell lab characterized in 2019. Former group members were able to purify the enzyme, and since then, it has served as a model to understand the lasso knot-tying process. Yet, the structure of FusC remained unknown, making it impossible to understand how the cyclase interacts with the peptide to fold the knot.

In the current study, the group used the artificial intelligence program AlphaFold to predict the FusC protein structure. They used the structure and other artificial intelligence-based tools, like RODEO, to pinpoint which cyclase active site residues were important for interacting with the lasso peptide substrate.

“FusC is made up of approximately 600 amino acids and the active site contains 120. These programs were instrumental to our project because they allowed us to do ‘structural studies’ and whittle down which amino acids are important in the active site of the enzyme,” Barrett said.

They also used molecular dynamics simulations to computationally understand how the lasso is folded by the cyclase. “Thanks to the computing power of Folding@home, we were able to collect extensive simulation data to visualize the interactions at the atomic level,” said Song Yin, a graduate student in the Shukla lab. “Before this study, there were no MD simulations of the interactions between lasso peptides and cyclases, and we think this approach will be applicable to many other peptide engineering studies.”

From their computational efforts, the researchers found that among different cyclases, the backwall region of the active site seemed to be especially important for folding. In FusC, this corresponded to the helix 11 region. The researchers then carried out cell-free biosynthesis where they added all the cell components that are necessary for the synthesis of the lasso peptides to a test tube with enzyme variants that had different amino acids in the helix 11 region. Ultimately, they identified a version of FusC with a mutation on helix 11 that could fold lasso peptides which cannot be made by the original cyclase. This data confirms the model for lasso peptide folding that the researchers developed with their computational approaches.

“How enzymes tie a lasso knot is a fascinating question. This study provides a first glimpse of the biophysical interactions responsible for producing this unique structure,” said Diwakar Shukla, an associate professor of chemical and biomolecular engineering.

“We also showed that these molecular contacts are the same in several different cyclases across different phyla. Even though we have not tested every system, we believe it’s a generalizable model,” Barrett said.

Collaborating with the San Diego-based company Lassogen, the researchers showed that the new insights can guide cyclase engineering to generate lasso peptides that otherwise cannot be made. As a proof-of-concept, they engineered a different cyclase, called McjC, to efficiently produce a potent inhibitor of a cancer-promoting integrin.

“The ability to generate lasso peptide diversity is important for optimizing drugs,” said Mark Burk, CEO of Lassogen. “The enzymes from nature do not always allow us to produce the lasso peptides of interest and the ability to engineer lasso cyclases greatly expands the therapeutic utility of these amazing molecules.”

“Our work would not have been possible without access to powerful computing and recent advances in artificial intelligence and cell-free biosynthetic methods,” said Douglas Mitchell, John and Margaret Witt Professor of Chemistry. “This work is an extraordinary example of how interdisciplinary collaborations are catalyzed at the Carl R. Woese Institute for Genomic Biology. I am grateful to the MMG theme at IGB and our external colleagues at Lassogen for their participation in solving this complicated problem.”

Most recently, the team applied this new computational tool to analyze pollutants in seawater in Southern California. The team swiftly captured the chemical profiles of coastal environments and highlighted potential sources of pollution.

“We are interested in understanding how such pollutants get introduced in the ecosystem,” said Daniel Petras, an assistant professor of biochemistry at UC Riverside, who led the research team. “Figuring out which molecules in the ocean are important for environmental health is not straightforward because of the ocean’s sheer chemical diversity. The protocol we developed greatly speeds up this process. More efficient sorting of the data means we can understand problems related to ocean pollution faster.”

Petras and his colleagues report in the journal Nature Protocols that their protocol is designed not only for experienced researchers but also for educational purposes, making it an ideal resource for students and early-career scientists. This computational workflow is accompanied by an accessible web application with a graphical user interface that makes metabolomics data analysis accessible for non-experts and enables them to gain statistical insights into their data within minutes.

“This tool is accessible to a broad range of researchers, from absolute beginners to experts, and is tailored for use in conjunction with the molecular networking software my group is developing,” said coauthor Mingxun Wang, an assistant professor of computer science and engineering at UCR. “For beginners, the guidelines and code we provide make it easier to understand common data processing and analysis steps. For experts, it accelerates reproducible data analysis, enabling them to share their statistical data analysis workflows and results.”

Petras explained the research paper is unique, serving as a large educational resource organized through a virtual research group called Virtual Multiomics Lab, or VMOL. With more than 50 scientists participating from around the world, VMOL is a community-driven, open-access community. It aims to simplify and democratize the chemical analysis process, making it accessible to researchers worldwide, regardless of their background or resources.

“I’m incredibly proud to see how this project evolved into something impactful, involving experts and students from across the globe,” said Abzer Pakkir Shah, a doctoral student in Petras’ group and the first author of the paper. “By removing physical and economic barriers, VMOL provides training in computational mass spectrometry and data science and aims to launch virtual research projects as a new form of collaborative science.”

All software the team developed is free and publicly available. The software development was initiated during a summer school for non-targeted metabolomics in 2022 at the University of Tübingen, where the team also launched VMOL.

Petras expects the protocol will be especially useful to environmental researchers as well as scientists working in the biomedical field and researchers doing clinical studies in microbiome science.

“The versatility of our protocol extends to a wide range of fields and sample types, including combinatorial chemistry, doping analysis, and trace contamination of food, pharmaceuticals, and other industrial products,” he said.

Petras received his master’s degree in biotechnology from the University of Applied Science Darmstadt and his doctoral degree in biochemistry from the Technical University Berlin. He did postdoctoral research at UC San Diego, where he focused on the development of large-scale environmental metabolomics methods. In 2021, he launched the Functional Metabolomics Lab at the University of Tübingen. In January 2024 he joined UCR, where his lab focuses on the development and application of mass spectrometry-based methods to visualize and assess chemical exchange within microbial communities.