Monday, April 28, 2025

Updated equestrian helmet ratings system adds racing and high-speed events

Building on previous research, the Virginia Tech Helmet Lab released an updated set of equestrian ratings that considers impact scenarios where the horse and rider are moving with horizontal velocity, which typically occurs in racing and cross-country eve

Virginia Tech

equestrian helmet — image:
The Virginia Tech Helmet Lab's updated equestrian ratings incorporate head impacts during falls at high speed.
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Credit: Photo by Lee Friesland for Virginia Tech.

Falling off a horse at high-speed changes the impact to the rider’s head and the parameters for a quality helmet, according to new research from the Virginia Tech Helmet Lab.

Published on April 28 in the Annals of Biomedical Engineering, the findings from researchers Steve Rowson and Lauren Duma indicate that head impacts during falls at high speed generate unique head rotation, which in turn, directly affects helmet behavior.

“Rotational motion of the head is very important,” said Rowson, helmet lab director. “While our testing already incorporated rotational head motion, falling off a horse at high speed can put a large force across the helmet and generate rotation in a different way than our previous testing. This means that the helmets behave a little differently during low-speed and high-speed impact scenarios.”

Lauren Duma, a Ph.D. student and member of the lab, was the lead author of the study.

The new study builds on the lab’s previous work that documented video-captured falls in a wide array of equestrian disciplines, where riders fell from varying heights on the front, side, and back of the helmet. Horse racing and other high-speed accidents were not included with the initial research project.

The testing now includes impact scenarios where the horse and rider are moving with horizontal velocity, which typically occurs in racing and cross-country events.

The additional testing criteria were motivated by the Federation Equestre Internationale's (FEI) technical report on new testing protocols for improved equestrian helmet performance, which included horse racing accidents. The added tests were used to update the lab’s original helmet ratings, which were released in December 2022.

“FEI suggested a new testing standard where the head is dropped on an angled surface, which is very similar to how we already test bicycle helmets in the lab,” Rowson said. “This test does a great job of simulating high-speed falls, so we worked to include tests similar to the FEI specification to have a more comprehensive test protocol.”

In addition to various fall scenarios, the lab also performed a large computational modeling analysis of the head impacts to identify the best method for quantifying injury risk to the rider.

Previously, the lab’s STAR ratings only incorporated one method of testing – either the pendulum impactor used for football helmets or the oblique drop tower used for bike and snow sport helmets. This was the first time ratings have been generated using both tests and with 49 helmets tested, the lab’s largest study on equestrian helmets to date.

Ratings reflect the concussion risk associated with each model and are meant to inform consumer decisions about helmet purchasing. Helmets are rated on a scale of one to five stars, with a one-star helmet offering the least head protection, making it more likely for an individual to develop a concussion, and a five-star helmet offering the most protection and reducing concussion risk.

Updated ratings are available on the helmet lab website. Early research was funded by Jacqueline Mars, the United States Hunter Jumper Association, the United States Equestrian Federation, the United States Eventing Association, and an anonymous private donor.

Original Study DOI: 10.1007/s10439-025-03723-0

Lauren Duma, a Ph.D. student in neuroscience, prepares an equestrian helmet for oblique testing on the lab's drop tower.
Credit
Photo by Lee Friesland for Virginia Tech.

Journal

Annals of Biomedical Engineering

DOI

10.1007/s10439-025-03723-0

Article Title

Equestrian STAR: Development of an Experimental Methodology for Assessing the Biomechanical Performance of Equestrian Helmets

Article Publication Date

28-Apr-2025

Want to understand grasslands? Look at the bigger picture

Michigan State University

Grassland field — image:
Some plots became dominated by a small number of species, reducing biodiversity. Regional processes can help experts better understand how species populate an environment.
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Credit: Chris Catano

Which factors do you consider when moving to a new area: school districts, home size or distance from work? If hundreds of people are competing for a spot, what determines who gets in?

Communities are ultimately shaped by an interplay of local factors, such as home size, and regional ones, such as school districts. New research appearing in the journal Ecology Letters asks how local and regional factors determine the makeup of plant species in grasslands.

Michigan State University researchers from the Brudvig Restoration Ecology lab are attempting to solve a longstanding question in community ecology: how do regional and local factors jointly determine biodiversity?

The authors argue that while both influence biodiversity, the effects of regional factors need to be better understood to help combat biodiversity loss.

Most prior research in the field has focused on how local factors — including competition for resources like soil nutrients or moisture — shape ecological communities.

This has resulted in a disproportionate understanding of how processes within communities shape biodiversity compared to those that span large regions and multiple communities. Such studies, the authors explain, have relied on observation alone – and have often been conducted under controlled conditions. “Such non-experimental approaches make it very challenging to draw cause-and-effect conclusions,” Brudvig explained.

Helping to fill the gap, this research demonstrates that regional conditions alter the makeup of communities, providing a more nuanced picture of how biodiversity is determined.

To study this, the researchers seeded plots across 12 grassland sites with varying soil moisture levels with mixes of native grass seeds ranging from highly diverse (30 species) to minimally diverse (8 species). The quantity of seeds dispersed ranged from 270 to 970 seeds per square meter.

This allowed the researchers to parse out how the influx of species into communities influences their makeup over time, relative to the impact of soil moisture, which influences plant growth and competition between species at the local level.

How many species and individuals were introduced to the plots altered the makeup of species expected based on soil moisture alone. This revealed that local factors which drive inter-species competition can only partially explain shifts in biodiversity when studied alone.

Across study sites where immigration was high, initial diversity within each site began high, but diversity across sites remained low. Over time, the variety of species within individual sites declined as well, as species best suited to the environment gained dominance. Communities stemming from an influx of many individuals from a small number of species were shaped more decisively by local factors.

In sites where highly diverse seed mixes were distributed, species variety remained higher in and across the study sites, resulting in greater local species diversity, and limiting diversity loss over time.

Essentially, local factors are more influential when a particularly well-adapted species can thrive. However, in systems where high biodiversity takes root early on, this variation helps limit one species — even if it has an advantage — from gaining dominance.

These findings suggest that immigration from a highly varied group of species helps maintain species diversity over time, overcoming local ecological factors which would otherwise encourage a single well-adapted species to assert dominance.

This interplay between factors at different scales has long gone understudied and undervalued. Now, these findings may help deepen scientists’ understanding of the complex interplay of factors at the regional and local levels which shape ecological communities.

Understanding how these processes shape a region’s ecology can better equip scientists to develop powerful conservation strategies, including approaches that could mitigate further biodiversity loss worldwide.

“We wanted to find a way to combine the power of experimental manipulations with the realism and complexity of nature,” Brudvig said.

By Caleb Hess

Journal

Ecology Letters

DOI

10.1111/ele.70095

Article Title

Regional Processes Mediate Ecological Selection and the Distribution of Plant Diversity Across Scales

Study using simulations highlights power of pooled data in environmental health research

Combining study data is key to understanding chemical exposure risks

Columbia University's Mailman School of Public Health

April 28, 2025-- Conflicting findings in environmental epidemiology have long stalled consensus on the health effects of toxic chemicals. A new study by Columbia University Mailman School of Public Health published in the American Journal of Epidemiology suggests that one major reason for these inconsistencies may be the limited exposure ranges in individual studies—leading to underpowered results and unclear conclusions.

Researchers used simulated data to examine how well individual and pooled studies can identify dose-response relationships between chemical exposure and health outcomes. Their findings point to a clear solution: pooling data across studies should be prioritized, even when confounding variables vary between cohorts.

“Underpowered studies—especially those with narrow exposure ranges—may produce misleading results about whether and how a chemical affects human health,” said lead author Eva Siegel, PhD in the Department of Environmental Health Sciences. “Our simulations show that combining data across multiple cohorts is a natural and necessary step to strengthen conclusions in environmental health research.”

The research focused on polychlorinated biphenyls (PCBs), a class of persistent organic pollutants (POPs). Specifically, the study explored the relationship between maternal exposure to PCB-153—the most commonly detected PCB congener in human blood—and birthweight, an association that has been inconsistently reported in previous studies.

“Some chemicals, like endocrine-disrupting POPs, may interfere with the body’s systems even at very low doses,” Siegel noted. “Understanding how health risks vary across the full exposure range is essential—but that requires broader data than most single studies can offer.”

To address this gap, researchers created five hypothetical populations with different exposure distributions—from low to high—based on real data from three well-known birth cohorts: The Columbia Children’s Center for Environmental Health (CCCEH) in New York City, The Environmental Health Fund (EHF) cohort in Israel, and The Child Health and Development Studies (CHDS) in California.

By simulating these distinct exposure environments and analyzing them both individually and collectively, the team assessed how well each approach could recover a "true" dose-response curve. Their results were clear: studies with limited exposure variability often failed to detect effects, while pooled data more accurately reflected the expected relationship.

“Our results show that despite potential differences in confounding factors across studies, the benefits of data pooling outweigh the challenges especially when every effort is made to fully harmonize data between studies.,” said Pam Factor-Litvak, PhD, professor of Epidemiology at Columbia Mailman School, and senior author. “To emphasize, this approach is especially crucial in understanding low-dose chemical effects, where many individual studies lack sufficient range to detect patterns.”

Other co-authors are Matt Lamb, Jeff Goldsmith, and Andrew Rundle, Columbia University Mailman School of Public Health; Andreas Neophytou, Colorado State University, Matitiahu Berkovitch, Tel Aviv University; and Barbara Cohn, Public Health Institute.

The study was supported by the National Institute of Environmental Health Sciences (grants F31ES032331 and T32ES023772.

Columbia University Mailman School of Public Health

Founded in 1922, the Columbia University Mailman School of Public Health pursues an agenda of research, education, and service to address the critical and complex public health issues affecting New Yorkers, the nation and the world. The Columbia Mailman School is the third largest recipient of NIH grants among schools of public health. Its nearly 300 multi-disciplinary faculty members work in more than 100 countries around the world, addressing such issues as preventing infectious and chronic diseases, environmental health, maternal and child health, health policy, climate change and health, and public health preparedness. It is a leader in public health education with more than 1,300 graduate students from 55 nations pursuing a variety of master’s and doctoral degree programs. The Columbia Mailman School is also home to numerous world-renowned research centers, including ICAP and the Center for Infection and Immunity. For more information, please visit www.mailman.columbia.edu.

Journal

American Journal of Epidemiology

DOI

10.1093/aje/kwaf020

Article Title

Using simulations to explore the conditions under which “true” dose-response relationships are detectable for environmental exposures: polychlorinated biphenyls (PCBs) and birthweight: a case study

How math helps to protect crops from invasive disease

UTA research unveils a math model to predict toxic crop fungi, potentially saving Texas farmers billions in losses

University of Texas at Arlington

image:
“Our research focuses on predicting aflatoxin outbreaks in Texas using remote sensing satellites, soil properties and meteorological data,” said coauthor Angela Avila, a postdoctoral fellow in mathematics at UTA. “One of the key challenges is that contamination can be present with no visible signs of fungal infection. This makes early risk prediction especially important for allowing targeted prevention and mitigation strategies.”
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Credit: UTA

New research from The University of Texas at Arlington and the U.S. Department of Agriculture demonstrates how mathematical modeling can predict outbreaks of toxic fungi in Texas corn crops—offering a potential lifeline to farmers facing billions in harvest losses.

“Our research focuses on predicting aflatoxin outbreaks in Texas using remote sensing satellites, soil properties and meteorological data,” said coauthor Angela Avila, a postdoctoral fellow in mathematics at UTA. “One of the key challenges is that contamination can be present with no visible signs of fungal infection. This makes early risk prediction especially important for allowing targeted prevention and mitigation strategies.”

Aflatoxins are toxic compounds produced by certain fungi in the mycotoxin family and are commonly found on crops such as corn (maize) and some nuts. They are carcinogenic and can pose serious health risks to humans and animals.

The research team included Jianzhong Su, professor and chair of UT Arlington’s Department of Mathematics and Dr. Avila’s former doctoral mentor. Together, they developed the aflatoxin risk index (ARI) and applied multiple machine learning methods to predict aflatoxin outbreaks in Texas. ARI is a predictive model that measures the cumulative risk of contamination during crop development.

“My main contribution was calculating historical planting dates for each county in Texas using time-series satellite imagery,” Avila said. “Because maize is most susceptible to aflatoxin contamination at specific growth stages, having precise planting dates is critical. My contributions for planting date estimations significantly improved our risk assessment, enhancing the accuracy of our machine learning models by 20% to 30%.”

“As part of her contributions to our mycotoxin research, Dr. Avila integrated a new input. She used the normalized difference vegetation index, acquired from satellite imagery, to predict planting times,” said Lina Castano-Duque, lead author of the study in Frontiers in Microbiology and plant pathologist at the USDA Agricultural Research Service Southern Regional Research Center in New Orleans. “She will continue growing her model to apply it to the rest of the U.S.”

Avila noted that the study has wide-reaching implications for farmers, processors and consumers, as mycotoxin contamination leads to billions of dollars in economic losses each year.

“Our research will allow farmers to make informed decisions to implement effective mitigation strategies, helping protect crops, food security, sustainability and economic stability,” Avila said.

“This cutting-edge research will revolutionize the management of mycotoxin contamination in corn, addressing its associated challenges,” Dr. Castano-Duque said. “Farmers will benefit from expert guidance on the risk levels of mycotoxin contamination that will aid in future crop selection and the ability to adapt input variables, such as fungicide and biocontrol application, as needed.”

Support for this research was provided by the U.S. Department of Agriculture’s Agricultural Research Service.

Journal

Frontiers in Microbiology

DOI

10.3389/fmicb.2025.1528997

Method of Research

Data/statistical analysis

Subject of Research

Not applicable

Article Title

Prediction of aflatoxin contamination outbreaks in Texas corn using mechanistic and machine learning models

The research team included Jianzhong Su, professor and chair of UT Arlington’s Department of Mathematics and Dr. Avila’s former doctoral mentor. Together, they developed the aflatoxin risk index (ARI) and applied multiple machine learning methods to predict aflatoxin outbreaks in Texas. ARI is a predictive model that measures the cumulative risk of contamination during crop development.

Credit

UTA

COI Statement

Funding The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work was supported by the U.S. Department of Agriculture, Agricultural Research Service. USDA is an equal opportunity provider and employer. Research at USDA-ARS is supported by the CRIS# 6054-42000-027-000D. Research collaboration with ARS and UT-Arlington was supported by NACA# 58-6054-3-024 and NACA 58-6066-2-035. This research also used resources provided by the SCINet project and/or the AI Center of Excellence of the USDA Agricultural Research Service, ARS project numbers 0201-88888-003-000D and 0201-88888-002-000D. We appreciate the constant support and encouragement from our stakeholders - National Corn Growers Association and Texas Corn Board. Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

A new method identifies rancid hazelnuts without removing them from the bag

Research led by the URV uses infrared light to determine the oxidation status of hazelnut fatty acids without destroying them, a technology that could provide the sector with new quality standards

Universitat Rovira i Virgili

No more rancid hazelnuts: a research team at the URV has developed a method that can identify nuts that have gone bad due to oxidation. The technique uses infrared light to determine the chemical composition of hazelnuts without even removing them from their shells. The new system overcomes the limitations of traditional methods and makes it possible to identify the condition of all the hazelnuts in a packet in a single analysis, without the need to prepare or destroy the sample. The authors argue that the application of this technology would help to improve packaging techniques and distribution systems and significantly reduce losses in the nut trade, while offering new quality standards to the sector.

Catalonia is a land of nuts, especially in the southern regions of the country. Although the sector is dominated principally by almonds, the hazelnut is second in terms of annual production. In Catalonia, there are more than 90 cooperatives producing nuts with an overall worth of more than 75 million euros and the sector is strongly export-oriented. Most of the cooperatives that produce hazelnuts are in the Tarragona area, according to data from the Catalan Federation of Agricultural Cooperatives.

Good practices in the processing, packaging and distribution of this product are crucial in order to prevent losses and guarantee its long-term quality. In hazelnuts, the oxidation of the unsaturated fatty acids they contain causes them to turn rancid. Contact with oxygen and the action of light increase these reactions, "This means that the speed of oxidation increases when the nuts are not properly packed," says Jokin Ezenarro, a researcher at the URV's Department of Analytical and Organic Chemistry and lead author of the research.

Hyperspectral cameras

With this in mind, the research team has developed a system for monitoring the oxidation of hazelnuts, which would allow producers and traders to determine their quality before buying or selling them. The method developed by Ezenarro uses a hyperspectral camera, a device capable of determining the state of oxidation throughout the package: "It is a spectrophotometer; it applies a beam of light at each point and provides information on the composition of the sample depending on how it interacts".

The device uses infrared radiation, which has a longer wavelength than visible light and a lower frequency than green light, which makes it invisible to the human eye. "All organic molecules absorb infrared light; the frequencies at which they do so and how intensely they do so vary according to their composition," points out the URV researcher. This is what allows them to identify nuts with chemical compounds that have been caused by oxidation.

While spectrometers were traditionally designed to study a single point in a sample, hyperspectral cameras are changing this paradigm. In the same way that in a conventional camera, where many points of light - pixels - make up the image, these devices determine the infrared spectrum of an entire surface. In this case it is a competitive advantage that makes it possible to determine the oxidation state of a whole bag of hazelnuts, without even removing them from the bag. —

According to Ezenarro, in analytical chemistry there is a move away from destructive and laborious analysis methods: "These new techniques are greener; they do not need reagents and do not require sample preparation; in fact, with this method the measuring instrument does not even need to come into contact with the sample". The correct functioning of the technique will depend on variables such as the material or the thickness of the packaging, which can affect the infrared spectrum. In order to establish a relationship between the electromagnetic spectrum captured by the camera and the quality - and oxidation status - of the hazelnuts, the research team had to calibrate the device. To do that, the hazelnuts were incubated for 78 days in various conditions, some of which were more conducive than others to preservation. These included being vacuum packed, storage in a protective nitrogen atmosphere, exposure to the atmosphere and exposure to various degrees of light. With these data they constructed a mathematical model capable of comparing the analytical data of the sample with its conservation status.

The new method has allowed the researchers to confirm that the main causes of hazelnut oxidation are the atmosphere that they are in contact with and the light to which they are exposed, with storage time being the main driving force behind the oxidation process. "We were able to prove that the vacuum packaging process was the most effective and that exposure to light significantly affects the stability of the product," explains Ezenarro.

Despite having demonstrated that there are measurable chemical changes on the surface of hazelnuts due to oxidation processes, the team wanted to go a step further and determine whether these have an impact on the consumer's sensory experience. According to Ezenarro,the purpose here was more about "validating the methodology; that is, determining whether what we measure is also perceptible by humans". The results of the sensory tests showed that there is a relationship between the data observed with spectroscopy and the sensory experience of people: the samples stored in contact with the atmosphere and exposed to light were significantly more rancid.

The new trend towards developing methods to control the quality of products without destroying them offers a competitive advantage to companies in many different sectors. In fact, in the nut sector, it would help to improve packaging techniques, storage and distribution systems and to significantly reduce losses, while offering new quality standards. Although the technology is not yet available to everyone (the instruments needed can cost more than 50,000 euros) systems are beginning to appear that, with processes very similar to the one developed by Ezenarro's team, can distinguish between bitter and sweet almonds or between plastics in a recycling chain. In the words of the researcher himself, "the hyperspectral camera is here to stay".

Reference: Jokin Ezenarro, Ines Saouabi, Ángel García-Pizarro, Daniel Schorn-García, Montserrat Mestres, Jose Manuel Amigo, Olga Busto, Ricard Boqué, NIR-HSI for the non-destructive monitoring of in-bag hazelnut oxidation, Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, Volume 333, 2025, 125906, ISSN 1386-1425, https://doi.org/10.1016/j.saa.2025.125906

Journal

Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy

DOI

10.1016/j.saa.2025.125906

Method of Research

Experimental study

Subject of Research

Not applicable

Article Title

NIR-HSI for the non-destructive monitoring of in-bag hazelnut oxidation

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Monday, April 28, 2025

Updated equestrian helmet ratings system adds racing and high-speed events

Credit

Journal

DOI

Article Title

Article Publication Date

Want to understand grasslands? Look at the bigger picture

Journal

DOI

Article Title

Study using simulations highlights power of pooled data in environmental health research

Journal

DOI

Article Title

How math helps to protect crops from invasive disease

Journal

DOI

Method of Research

Subject of Research

Article Title

Credit

UTA

COI Statement

A new method identifies rancid hazelnuts without removing them from the bag

Journal

DOI

Method of Research

Subject of Research

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