Paleontologists uncovered this finding by studying wear on the fossilized teeth of Maiasaura peeblesorum, a duck-billed dinosaur species that lived about 75 to 80 million years ago during the Late Cretaceous. First discovered in Montana, these large, herbivorous dinosaurs lived in herds and were thought to have been highly social creatures, especially in contrast to those that may have had different reproductive strategies. 

Extensive fossil findings of preserved Maiasaura nests have since made them a key species for understanding the reproductive behaviors and ecology of many other types of duck-billed dinosaurs. Now, closer analysis of their dental wear patterns has revealed that while juvenile Maiasaura teeth had significantly more crushing wear, adults exhibited more shearing wear, suggesting parents could have been bringing softer, higher-protein food to their children than they themselves ate. 

Today, this behavior is typical of birds whose young are confined to the nest for a time after hatching, said John Hunter, lead author of the study and an associate professor in evolution, ecology and organismal biology at The Ohio State University, meaning that these dinosaurs could have exhibited a level of parental care unusual for most species on Earth at the time.  

“The urge for a bird to feed a youngster is a very old behavior,” said Hunter. “What we’re providing is that evidence for that behavior probably goes much further than the origin of birds, perhaps to the origin of dinosaurs.”

Learning more about which social behaviors may have endured throughout evolutionary history can give scientists a better glimpse into how organisms made a living tens of millions of years ago, as well as help predict traits modern animals might pass on to their descendants. 

The study was recently published in the journal Palaeogeography, Palaeoclimatology, Palaeoecology.

Researchers specifically detail that juvenile Maiasaura likely ate more nutritious low-fiber foods like fruit while their caretakers consumed a greater proportion of tougher, nutritionally poor high-fiber plant parts. In mammals today, the same patterns of shearing wear would likely be present in grazers like horses, antelopes and cows, while low-fiber diet eaters like tapirs would have dental patterns similar to the young dinosaurs. 

In comparing the types of wear on dinosaur teeth, researchers also suggested that shifts in diet may have also performed an important role in early growth and development. In this instance, their results show that the diet of juvenile Maiasaura may have caused them to grow particularly fast in their first year.

The study also considers other interpretations of their results. Instead of consuming completely different fare, dinosaur parents could have been feeding their young partially regurgitated food, yet another behavior now common in birds. Alternatively, juveniles could also have left the nest to forage for themselves, an activity now seen in modern herbivorous lizards.  

While that solution is less likely as juveniles were helpless, and probably dependent on their parents to feed them during the first weeks after hatching, learning more about their remains can widen scientists’ perspectives of what sophisticated biological and social systems dinosaurs may have had, said Hunter.

“The further back in time you go, the less of a fossil record you have, so paleontologists have to draw from different sources of inspiration from different parts of the living,” he said. “So even among closely related dinosaurs, there is probably still quite a bit to learn about them.”

If possible, future studies could examine other fossils of the very youngest dinosaurs for dental microwear to test other hypotheses regarding dinosaur embryos and hatchlings.

Christine Janis from the University of Bristol and the University of Brown was a co-author. This work was supported by Brown University.

Overall, the analysis of nearly 3,000 species showed more diversity of body types among the pelagic fishes, those that swim in open water, than among the benthic species spending their life on the ocean floor. Pelagic fish body types span from the round anglerfish to skinny eels, while benthic fishes generally share a common elongated, tapered shape. 

“We found that evolution pushes and pulls fish body shape in different directions depending on whether they’re benthic or pelagic,” said lead study author Elizabeth Santos, assistant professor of evolution, ecology and organismal biology at The Ohio State University. 

“We talk about the deep sea as if it is sort of all one thing, when really it is not – it is actually quite diverse,” she said. “There are very different types of environments in the deep sea that have their own different effects on evolution.” 

The study was published recently in the journal Evolution.

Santos and colleagues analyzed shape characteristics among ray-finned fishes living 200 or more meters below the surface, the portion of the world’s oceans constituting almost 90% of their volume. 

Using previously published datasets of fish body shape measurements, evolutionary relationships and habitats, the researchers included 2,882 deep-sea species in this study. 

They found that increasing ocean depth promoted diversification in body shape, and that evolution occurred more rapidly at deeper depths than in shallower waters. 

The faster rate of evolution – essentially, a lot of change in a relatively short period of time – was most common in bottom-dwellers, suggesting their similar body shapes resulted from more closely related species adapting in place. In contrast, the higher diversity of body shapes in open-water fishes hinted at the possibility that colonization by invading species has resulted in a community of more distantly related species. 

“Colonization of the deep pelagic seems to be a more typical route for achieving diversity than the benthic,” Santos said. “In the water column, you see more lineages that are very distantly related from each other that probably colonized that habitat at all different times. And that’s why you get a lot of diversity. 

“Whereas in the benthic environments, that’s true to some extent but not to the same level. You get fewer lineages that have been in that habitat a little longer – and that’s potentially why you see less variety in body shape.” 

The findings also shed light on how living in the dark affects the evolution of marine life. Only trace amounts of sunlight can reach the 200-meter depth, but it’s not enough to enable photosynthesis – making the deep sea a dividing line that has an impact on how fishes spend their time hunting for food, one driver of evolutionary change. 

For example, Santos said, compare with a well known shallow-water pelagic fish like the tuna, a very active species. 

“In the deep water column, you don’t see a lot of big, powerful swimmers because it’s a very different kind of environment. It’s dark,” she said. “And so you tend to see fishes that sit in the water and wait for food to find them. Being pelagic in the deep sea seems to be fine for many different types of body shapes, from the blobby all the away to the skinny.” 

The lack of sunlight and photosynthesis in the deep sea also affects the ocean floor environment. 

“In shallow water, oftentimes you’ll be in an environment like a coral reef or a kelp forest, which has organisms undergoing photosynthesis. There are a lot of things to interact with, and that creates a diversity of body shapes because fish are designed to interact with different things,” Santos said. 

“The deeper bottom tends to be more plain and boring and muddy, so the fishes that live there don’t tend to be shaped in different ways.” 

Overall, the study’s rare look at life in Earth’s largest habitat shows that the different body types of deep-sea fishes are products of multiple evolutionary pathways defined largely by location. 

“The one place that humans have not dominated on this planet is the deep sea – and there is still so much to learn about the mystery of what all is there,” Santos said. “This paper moves us forward with a recognition that evolution can work really differently depending on where exactly in the deep sea the fishes are.” 

Co-authors of the paper include Sarah Friedman of the NOAA Alaska Fisheries Science Center and Christopher Martinez of the University of California, Irvine.

This suite of open-source tools, called ECODATA, was designed to support the analysis and visualization of complex datasets, as valuable observations about animal movement are often made by analyzing massive amounts of wildlife tracking data. 

Their tool accomplishes this by creating animations that help ecologists study animal movement, such as how extreme weather conditions or seasonal vegetation growth might influence a species’ normal activities, said Gil Bohrer, co-author of the study and a professor in civil engineering and geodetic engineering at The Ohio State University.

“We’re not creating new information, but we are taking data that ecologists typically find hard to utilize and making it easy and accessible,” said Bohrer. “This can help users understand an ecosystem and quickly identify what’s going on, or test a good hypothesis they have.”

ECODATA works by combining direct wildlife location observations with complex remote sensing and geospatial data to process image frames into multiple layers of customizable maps.

For example, in one case study, the researchers used the software to animate movements of elk and wolves in relation to roads, wildlife crossing structures and changes in seasonal vegetation near Banff National Park in Canada.

Although interpreting and integrating large datasets into research and other wildlife applications can be a difficult and tedious process, ECODATA makes it easy to create animations that act as powerful tools for illustrating study results, supporting animal exploration in uncharted territories, and even aiding wildlife managers in garnering support for conservation efforts, said Bohrer. 

“These animations are very effective,” he said. “They can process and plot lots of changing environmental conditions and corresponding animal movement in a really temporally dynamic way.”

The study was recently published in the journal Methods in Ecology and Evolution.

Previous attempts at creating user-friendly research software required scientists to have some programming skills, but what makes ECODATA unique is that it is flexible enough that scientists don’t need technical skills to employ it, said Justine Missik, lead author of the study and a researcher in civil, environmental and geodetic engineering at Ohio State.

“There are all sorts of environmental datasets that are out there that are difficult for people to work with,” she said. “Our project was helping address those research gaps.”

In this paper, researchers demonstrated ECODATA’s abilities through two case studies, both of which answered very different questions about its potential uses, said Bohrer. 

In the case study of elk and wolves in Banff, the animation researchers developed showed that both species migrate from the northeast during late spring to their summer range, where some spend considerable time near highways, including during times that coincide with peak annual traffic volumes. 

The second case illustrated how the software could be used in wildlife management, as ECODATA’s animation could inform wildlife managers about the timing and location of caribou movements during their birthing season. These visual insights helped reveal territory in the caribou’s seasonal range that management hadn’t previously recognized. This can help wildlife managers understand the conservation impacts of caribou movements.  

That ECODATA can help identify such situations makes it a valuable resource for many purposes, most notably as an asset for protecting all kinds of wildlife. “These animations are tools to explore the data in a different way, by many different users in many different contexts,” said Bohrer. 

Moving forward, the team hopes that the custom animations ECODATA provides work as a complement to existing research tools and inspire more detailed explorations of ecological models used for impactful, sustainable decision-making. 

Other Ohio State co-authors include Sarah Davidson and Madeline Scyphers, as well as Mark Hebblewhite from the University of Montana, Allicia Kelly from the Government of Northwest Territories in Canada, John Fieberg from the University of Minnesota, Roland Kays from the North Carolina State University, Ashley Lohr from the North Carolina Museum of Natural Sciences, and Kelsey Russell and Mike Suitor from the Government of the Yukon in Canada. This work was supported by NASA and the MathWorks MATLAB Community Toolbox Program.

Drones, or unmanned aerial systems (UAS), are often used to collect massive amounts of high-quality aerial footage of unique places. 

While most of these state-of-the-art technologies rely on human pilots to operate them, researchers have developed WildWing, a complete hardware and software open-source UAS for independently collecting dense animal behavioral data. 

This single-drone system, which has so far collected about 37,000 images of various endangered animals, was created to help scientists automate and standardize data for better behavioral analysis, said Jenna Kline, lead author of the study and a graduate student in computer science and engineering at The Ohio State University. 

“Animals and their habitats are changing rapidly, so if we want insights about them in real time, remote sensing technologies like drones and AI can play a big part in that,” she said.

Studying how animals behave in the wild can be challenging, in part due to how disruptive human noise may be to the creatures living in the region. Yet a drone’s ability to gather data much more quietly across challenging terrains and complete complex tracking and positioning tasks makes them powerful tools for studying the natural world, said Kline.  

“By automating a mission, the data you collect is more reliable and consistent, which is really important if you want to build a data set to train a computer vision model,” she said.

Initially trained on data gathered at Mpala Research Center in Kenya, the WildWing drone is programmed to move forward until its computer vision model detects the species of interest, and once spotted, will keep the chosen animals within the center of its camera until commanded otherwise. This marked shift to automated classification and data handling allows researchers to focus on scaling up research objectives rather than the technical demands of piloting.

The study was recently published in the journal Methods in Ecology and Evolution.

The complete WildWing system costs $650 and incorporates drone hardware with custom software. The researchers used a Parrot Anafi drone, but said other drone models could be used.

Field tests to examine the accuracy of the drone’s navigation system took place at The Wilds conservation park in Ohio, where the device was tasked with tracking groups of zebras, giraffes and Przewalski’s horses. In simulations where autonomous navigation was implemented, the team’s drone was able to match target tracking by a UAS operated by a human pilot 87% of the time. 

Additionally, the number of usable frames, or images with adequate resolution to assess each animal’s behavior, approached nearly 100% using the WildWing system. These results are significant performance improvements over human-driven attempts, said Kline. 

Tanya Berger-Wolf, co-author of the study and faculty director of Ohio State’s Translational Data Analytics Institute, said that this adaptive approach will most certainly help scientists overcome current limitations to exploring wild environments as well as advance other fields reliant on large amounts of visual data, like imageomics. 

“Drones provide an opportunity for scientists to expand their reach into the wild by studying animals in their natural habitats in the least invasive way possible,” said Berger-Wolf, who is also a professor of computer science and engineering, evolution, ecology and organismal biology, and electrical and computer engineering. “It’s that adaptability that is the big advantage of a system like this.”

While the study builds on previous work that addresses key questions about the pros and cons of autonomous technologies, what makes this particular project unique is that it demonstrates how researchers might turn commercial, off-the-shelf drone technologies into custom research tools, said Christopher Stewart, another co-author of the study and a professor of computer science and engineering at Ohio State. 

“Historically, it’s been prohibitively expensive to create this type of tailored software, but making WildWing an open-source tool makes these advanced features available very broadly,” he said. 

Since the system’s data and tracking algorithm will be made available to researchers and citizen scientists alike, the plan to continue improving WildWing’s capabilities should include developing it in a way that will keep future drone swarms both cost-effective and efficient, said Stewart. 

To ensure this, the team’s next steps will be aimed at integrating more complex, long-term datasets into WildWing, as well as deploying the system into new environments to test its broader ability to advance other types of ecological research. 

“Technology can give us a bigger piece of the puzzle to understand what’s happening in our ecosystem,” said Kline. “So I’m excited to keep pushing the boundaries of it to better understand and protect our natural world.”

Co-authors include Alison Zhong and Kevyn Irizarry from Ohio State, Charles V. Stewart from the Rensselaer Polytechnic Institute and Daniel I. Rubenstein from Princeton University. The study was supported by The National Science Foundation through Ohio State’s ICICLE Institute and the Imageomics Institute.

Researchers found that a pain receptor called TRPA1 becomes less sensitive in mosquitoes when exposed to heat, meaning that the chemical cues that typically trigger insect avoidance behaviors are prevented from activating as strongly. 

TRPA1, also known as the “wasabi receptor,” helps animals detect noxious heat and harmful chemicals. In humans, this receptor can induce eye and skin irritation. In mosquitoes, it influences which hosts the insects find most alluring – specifically, those unprotected by repellents that drive them away, said Peter Piermarini, co-author of the paper and a professor of entomology at The Ohio State University.

“What we found was that the chemicals were not able to activate the mosquito wasabi receptor as effectively when temperatures exceeded the heat activation threshold,” said Piermarini. “So the mosquito would find certain repellents less irritating in hotter weather.”

Typical insect repellents create a chemical barrier that discourages proximity and prevents mosquitoes from reaching their target. Yet because their receptors are desensitized in warmer temperatures, natural substances like citronellal and catnip oil, known for their repellent properties, would be less effective. 

“Products with those ingredients may be less effective if you’re using them at temperatures that are considered extreme heat events,” said Piermarini. Additionally, as the climate warms, more extended breeding periods per season will worsen the spread of mosquito-borne disease. 

The study was recently published in the journal Pesticide Biochemistry and Physiology. 

Piermarini and Yeaeun Park, co-author of the study and a graduate student in environmental sciences at Ohio State, discovered the changes by removing TRPA1 mosquito receptors and injecting them into frog egg cells, a technique often used for making receptor proteins in the lab. 

Then, they tested how the receptors would react to citronellal and catnip oil under normal and high temperatures. The receptors were activated, but were less sensitive to the substances at higher temperatures. “It was very close to what we predicted,” said Piermarini. 

In a second experiment, the researchers studied how fully grown female mosquitoes reacted when confronted with either repellent at different temperatures. When temperatures exceeded 32 degrees Celsius, the mosquitoes were less likely to avoid the substances, suggesting they might behave similarly in the wild. 

Still, there is some defense against mosquito bites. When the team tested a synthetic mosquito repellent called DEET, they found that because it does not interact with the wasabi receptor to repel mosquitos, its efficacy was not impacted by higher temperatures.

“This suggests that during the hottest days of the year you’d probably want to stick with a more conventional synthetic repellent and avoid using a natural product with citronella or catnip oil,” said Piermarini. 

Piermarini said the team will continue to investigate the specific mechanisms behind temperature-induced desensitization of the TRPA1 receptor, and they hope to study the phenomenon in a more comprehensive manner, potentially with the help of human participants. 

“The more we learn about the mechanisms by which these natural products work, it can help us determine which ones might be better to use under certain conditions,” said Piermarini. “Understanding these limitations can potentially save lives.”

This research was supported by Ohio State, the Sigma Xi Grants in Aid of Research (GIAR) program, and the National Institutes of Health. 

Researchers monitoring coyotes in Chicago found that habitat – areas with relatively high levels of vegetation cover and low levels of human infrastructure – did not influence coyote survival in positive or negative ways. Instead, areas densely populated with humans were associated with longer coyote lifespans. 

“What we found was really interesting, in that the societal characteristics seem to play a much more important role in predicting coyote survival time than the environmental characteristics,” said Emily Zepeda, first author of the study and a postdoctoral scholar in the School of Environment and Natural Resources at The Ohio State University. 

“And then we found this positive effect of human population density on survival time. Both of those things are unexpected because we usually associate human activity with detrimental effects on wildlife.” 

The study was published recently in the journal Urban Ecosystems. 

The data comes from the Urban Coyote Research Project, a long-term study of coyote ecology in the Chicago Metropolitan Area led by Stan Gehrt, a wildlife ecologist at Ohio State and senior author of the new paper. 

Gehrt and colleagues estimate that 4,000 coyotes live in Chicago, one of the largest metropolitan areas in North America. Gehrt’s previous behavioral, genetics and biological studies offer hints at how coyotes have adjusted to life in the city. This new work sought to identify the diverse urban factors that help or hinder their ability to survive. 

Tracking data on the movement of 214 coyotes living in the Chicago area between 2013 and 2021 was used for the study. The duration of each coyote’s tracking period served as a proxy of its survival time. 

Potential factors the researchers predicted would affect urban coyote survival included a mix of societal and environmental characteristics: neighborhood median income, human density and demographics; and road density, parks and golf courses, and “disturbed” regions dominated by infrastructure and vacant land. These factors were analyzed alongside the coyote monitoring data in a statistical model to determine their relationships with survival time. 

The results showed a positive relationship between survival rate and human population density – at low human densities, coyote survival was generally low. The data also revealed an interaction between neighborhood income and density: In areas with low human density, median income was not significantly associated with survival, likely due to the absence of humans. However, at moderate and high levels of human density, coyotes in lower-income areas were 1 1/2 times more likely to survive to age 2 than coyotes in high-income areas.

“We’ve hypothesized that population density may have a positive effect because it’s actually providing resources like human-related structures or food that allow coyotes to weather the harsh conditions of the winter, which is a major mortality factor for Chicago coyotes,” Zepeda said. 

Plentiful resources might become problematic, she said, when the food and shelter, combined with more vegetation and less pollution in high-income areas, draws a crowd of coyotes – which leads to higher disease transmission and fighting over territory. 

“There might be more individuals in those areas, but survival time may be shorter there,” she said. “You might die younger in an area where there are a lot of competitors.” 

The findings build on growing evidence that societal processes that benefit and marginalize human populations trickle down to urban ecosystems – suggesting that the presence, or lack, of humans, and the conditions in which they live, has potential to override natural influences on urban wildlife. 

And yet, it was surprising not to find a connection between natural habitats and longer survival, Zepeda said, because “anecdotally, we see really high densities of coyotes in nature preserves and urban parks. That’s often where you see coyotes in the city if you see them at all.” 

Researchers can only speculate, but Zepeda said it could mean the habitat categories on city maps aren’t specific enough or that hunting and trapping is more common in natural settings. Or it could simply be a sign of how crafty coyotes are. 

“It could speak to how adaptable they are that they might prefer natural habitat, but at least in terms of survival, they can do just as well in more urbanized areas,” she said. 

This work was supported by Cook County Animal and Rabies Control, the Max McGraw Wildlife Foundation, the Forest Preserve District of Cook County, and a National Science Foundation Graduate Research Fellowship. 

Andrew Sih of the University of California, Davis and Christopher Schell of the University of California, Berkeley were also co-authors.

The study, recently published in the journal Molecular Phylogenetics and Evolution, suggests that the genetic variation of two species, the Brazilian sibilator frog and the granular toad, both amphibians native to northeastern Brazil, were shaped by different processes.  

Results showed that the genetic variation in the sibilator frog was shaped mostly by population demographic events in response to habitat changes that occurred over the last 100,000 years.   In contrast, genetic diversity in the granular toad was mostly shaped by contemporary landscape factors – toads that are relatively more isolated, either by geographic distance or inhospitable habitat, were more likely to be genetically different.

While previous investigations have explored the effects of historical demographic and landscape factors on genetic diversity of these amphibians, they were conducted with separate sets of data for these factors, making it difficult to discern which was the most important. Now, researchers involved with this paper are the first to use artificial intelligence to consider how both processes shape genetic diversity equally, rather than making manual assumptions about which may have been more vital. 

“Prior to this work, we had to ask questions independently because you couldn't investigate both influences in the same framework,” said Bryan Carstens, co-author of the study and a professor in evolution, ecology and organismal biology at The Ohio State University. “What AI allows us to do is to simulate processes that are both happening ecologically in the present and during deep-time evolutionary events and compare those findings to the actual data that we collect from these frogs.”   

Due to the sheer amount of data that’s become available to geneticists and other wildlife biologists over the past few decades, it can be challenging for researchers to identify specific factors that might be important in certain experiments, said Carstens. But by integrating large swaths of information into simulations that can account for those elements in a single analysis, it’s possible to get a much more complete chronicle of a species’ development. 

“It takes a long time to build and train our AI models, but we wanted one l that could capture the range of potential variation in the species’ histories in a way that was as faithful as we could be to what we knew about the biology of the system,” said Carstens. 

For example, while the species this study investigated dwell in the same region, there are many differences in their natural histories. Despite both their eggs and larvae being fully aquatic, the sibulator frog reproduces continuously throughout the wet season and in underground chambers, while the granular toad’s reproductive events happen explosively because they are dependent on heavy rainfall. 

Combined with their machine learning approach, the researchers’ simulation determined their model scenarios were 100% supported regarding historical explanations for the sibilator frog’s expansion, and over 99% supported for those of the granular toad. 

One of the reasons their model is so accurate is due to its ability to account for recent demographic events, including measuring how events like human development or habitat change may have affected animal genetic diversity over a long period of time. 

But even when using AI, researchers have to be careful to avoid deceptive patterns in their results, said Carstens. 

“No analysis that we do is going to capture every single factor that has been important to these species over millions of years,” he said. “So we have to allow for a range of possibilities without making it so broad that essentially any model would be able to fit the data.”

That said, as technological strides allow researchers to answer niche ecological questions and test new hypotheses, their work is a precursor to creating an upgraded machine learning framework that could be applied to unique investigations of other species, said Carstens. 

“We’re likely to continue using different combinations of these AI tools in different ways to try to understand evolutionary history,” said Carstens. “And as we keep learning, the tools we’re using will change, and they’ll evolve to be even better.”

Emanuel M. Fonseca, who earned his doctorate from Ohio State in 2022, was a co-author. The study was supported by the Ohio Supercomputer Center, the U.S. National Science Foundation and the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior in Brazil.

Utilizing electromagnetic coils and lidar technology, the prototype was able to consistently deliver a projectile to a target with enough controlled kinetic energy to suggest that it could deliver drugs successfully without so much force as to injure animals, said John LaRocco, lead author of the study and a research scientist in psychiatry at The Ohio State University College of Medicine.

“Normally, if you launch a projectile without any kind of control, its initial velocity drops off because of gravity, wind resistance and other factors,” said LaRocco. “We can modulate that velocity at specific distances so it arrives with the correct amount of kinetic energy.”

Many types of dart launchers, like ones that use compressed air to operate, are used by biologists and veterinarians to aid in the capture and treatment of pets and wildlife. However, these common machines do carry a measure of risk, as coilgun syringe darts can often fail to inject a target by being too slow or cause injury or death by puncturing an animal too forcefully.

But in experiments where they tested their launcher by firing at a wooden target at distances of 1 to 8 meters, the team was surprised to find that their launcher could control a dart’s velocity so well that it only had a very narrow deviation from what the researchers intended, said LaRocco. 

The total energy of the dart is comparable to a Nerf dart, instead of a firearm or air gun.

“This is a novel control system capable of delivering consistent mechanical control outcomes,” he said. “It’s not something we were expecting to see with the materials we used, so it’s far beyond our expectations.”  

The study was recently published in the journal Technologies.

The prototype consisted of a single-stage coilgun with a soft dart. The lidar calculated the distance to the target and a voltage controller then determined the proper dart velocity.

John Simonis, co-author of the study and an undergraduate student in electrical and computer engineering, noted that what will likely be the most valuable of the system’s future applications will be its ability to enhance existing manufacturing technologies and machine controls. 

“We’ve created a far more accessible type of mechanical and electronic control scheme that can be delivered with high consistency at low cost,” he said. “The benefit is if you have more precise control systems in your machines that are much cheaper, that’s going to directly result in more precise parts for the consumer at a lower  price.”

And because a great deal of the prototype’s parts were either 3D printed or made with commercial components, their device is something that could easily be reproduced by other researchers, said Qudsia Tahmina, another co-author of the study and an associate professor in electrical and computer engineering.

“By aiming to mitigate the risks associated with the availability of the materials and providing a low cost option for people interested in doing research in this area, this work addresses real-world supply chain issues in a practical way,” she said. 

Though the precision of the current design is remarkable, with iterative modifications like improving the system’s sensors and making their darts follow more complex trajectories, the team expects that its continued improvement combined with its widespread commercial availability could usher in a new era of industrial mechanical engineering. 

“Feedback from the research community who would utilize this mechanism can allow us to adapt the project into something that’s a little more targeted,” said Simonis. One future step would be to test the prototype on live animals, the researchers said.

Zooplankton, aquatic microorganisms that reside in nearly all bodies of water, are extremely sensitive to changes in their ecosystem. This hypersensitivity makes them important bioindicators of water quality, and studying how they interact with their environment can provide researchers with detailed snapshots of a region’s present ecological condition. 

By taking a new look at more than two decades of plankton monitoring data, researchers at The Ohio State University found that in western Lake Erie, zooplankton communities are undergoing a substantial change in the timing of certain events in their life cycles. 

Using data collected from previous studies, the team examined the behavior patterns of four common types of zooplankton populations in Lake Erie between 1995 and 2022. Their analysis showed that due to factors like rising temperatures, the presence of invasive species and the availability of high-quality food, the period when zooplankton concentrations are at their highest now varies by as much as three weeks in the summer months.  

“Warming is making natural events happen earlier, as we can see across basically all ecosystems,” said Jim Hood, lead author of the study and an associate professor in evolution, ecology and organismal biology at Ohio State. “These systems are really complex, and any disruption is likely to have unseen negative effects.”

Even in lakes, zooplankton play a central role in the local freshwater food web, from determining which types of algae thrive to helping sustain local fish populations, said Hood. Yet as the research notes, early warming can often advance the emergence of spring plankton while delaying fall populations, which can have a big impact. Because of their vital place in the food chain, major changes in plankton behavior could cause damage to other top-down and bottom-up processes that rely on them.  

The study, recently published in the journal Limnology and Oceanography Letters, marks one of  the first times scientists have tried to unpack the complexity of these dynamics in Lake Erie and the Great Lakes region. 

Some of the most dominant changes observed in the timing of zooplankton emergence were caused by temperature variation as well as an invasive phytoplankton species called B. longimanus, which was likely carried over from Europe by shipping boats, said Hood. 

“It’s this invasive predator and the increase in harmful algae blooms that are really altering the timing of zooplankton concentrations,” he said. “In some cases, they’re causing them to move in earlier, in some cases, they’re moving them in later.” 

Though Lake Erie has been plagued by harmful algal blooms for decades, warmer temperatures during the summer cause the organisms to grow thicker and faster. Because large blooms release toxins that endanger the health of humans and other animals and threaten important utility infrastructures, environmental scientists have been steadily working toward ways of addressing the multiple causes of their excess growth. 

“It’s not just climate change,” said Hood. “All of the things humans are doing to these systems, like bringing in invasive species, are creating a complex series of interactions that are going to influence big things that people care about, like harmful algal blooms and fisheries.”

This study’s analysis period took place between May and September of each year when the four zooplankton species whose behavioral patterns being surveyed were especially abundant. Though they all had different diets and life histories, they surprisingly each had varying reactions to B. longimanus and its effects on the ecosystem, revealing that the mechanisms that drive the timing of certain plankton behaviors are more sophisticated than they seem, said Hood. 

“It was really noteworthy how these four taxa that we focused on all had different responses to this invasive species, which really highlights the need for more research on them,” he said. 

Hood and co-author Jenna Bailey suggested that further research should aim to extend monitoring in temperate lakes to learn how winter conditions influence zooplankton life cycles, offering insight into other freshwater ecology issues related to climate change. 

“It’s difficult to predict the effects human activity has on our ecosystems,” said Hood. “But we need to step back and understand how all of these things that we’re doing are interacting with one another and incorporate that into our management.”

This study was supported by the U.S. Fish and Wildlife Service, the Ohio Department of Natural Resources’ Division of Wildlife, and the U.S. Environmental Protection Agency.

The new model predicts several useful new drug combinations that may one day help treat heart attacks, according to researchers at The Ohio State University.

Typically caused by blockages in the coronary arteries — or the vessels that supply blood to the heart — these cardiovascular events are experienced by more than 800,000 Americans every year, and about 30% end up dying. But even for those who survive, the damage these attacks inflict on the muscles of the heart is permanent and can lead to dangerous inflammation in the affected areas of the heart.

Treatment to restore blood flow to these blocked passages of the heart often includes surgery and drugs, or what’s known as reperfusion therapy. Nicolae Moise, lead author of the study and a postdoctoral researcher in biomedical engineering at Ohio State, said the study uses mathematical algorithms to assess the efficacy of the drugs used to combat the potentially lethal inflammation many patients experience in the aftermath of an attack.

“Biology and medicine are starting to become more mathematical,” Moise said. “There's so much data that you need to start integrating it into some kind of framework.” While Moise has worked on other mathematical models of animal hearts, he said that the framework detailed in the current paper is the most detailed schematic of myocardial infarctions in mice ever made.

The research is published in the Journal of Theoretical Biology.

Represented by a series of differential equations, the model Moise’s team created was made using data from previous animal studies. In medicine, differential equations are often used to monitor the growth of diseases in graph form.

But this study chose to model how certain immune cells like myocytes, neutrophils and macrophages — cells imperative to fighting infection and combating necrosis (toxic injury to the heart) — react to four different immunomodulatory drugs over a period of one month. These drugs are designed to suppress the immune system so that it doesn’t cause as much damaging inflammation in parts of the heart that were damaged.

This research focused on the drugs’ efficacy an hour after the mice were treated. 

Their findings showed that certain combinations of these drug inhibitors were more efficient at reducing inflammation than others. “In medicine, math and equations can be used to describe these systems,” Moise said. “You just need to observe, and you’ll find rules and a coherent story between them.

“With the therapies that we’re investigating in our model, we can make the patient outcome better, even with the best available medical care,” he said.

Depending on their health beforehand, it can take a person anywhere from six to eight months to heal from a heart attack. The quality of care patients receive in those first few weeks could set the tone for how long their road to recovery will be. 

Because Moise’s simulation is purely theoretical, it won’t lead to improved therapies anytime soon. More precise mouse data is needed before their work can become an asset to other scientists, but Moise said he does envision the model as a potential tool in the fight against the ravages of heart disease.

“Its going to be some years before we can actually integrate this kind of approach into actual clinical work,” Moise said. “But what we’re doing is the first step towards that.”

The co-author of the study was Avner Friedman, professor of mathematics at Ohio State. This research was supported by Ohio State’s Mathematical Biosciences Institute and the National Science Foundation.