Saturday, September 05, 2026

 

Not a cheetah: Ancient DNA reveals the surprising Arctic life of extinct North American cat



New paleogenomics research by UC Santa Cruz reveals how the so-called American 'cheetah’ adapted to harsh Arctic conditions by preying on fish




University of California - Santa Cruz

Illustration of Miracinonyx trumani chasing prey 

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Illustration of a Miracinonyx trumani chasing after a Saiga antelope

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Credit: By Velizar Simeonovski

 

SANTA CRUZ, Calif. – A new study led by researchers at the University of California, Santa Cruz, has overturned decades of assumptions about Miracinonyx trumani, the extinct predator popularly known as the American cheetah.” By analyzing nuclear paleogenomes and stable isotopes from fossils found as far north as the Yukon, scientists have discovered that this iconic cat was not a true cheetah, but a highly adaptable relative of the puma that specialized in eating fish to survive the Arctic.

The findings, published on September 4 in Current Biology, reveal that the species’ range extended 20 degrees of latitude further north than previously recognized. While southern populations in regions like Wyoming and Florida lived as generalist predators in temperate grasslands, their northern counterparts in the Arctic Yukon carved out a unique niche as tertiary consumers, likely specializing in anadromous fish such as salmon.

With slender bodies and long front legs that may have helped them move efficiently across the open landscapes of Pleistocene North America, an adult Miracinonyx trumani was thought to weigh around 150 pounds on average and stand about 3 feet tall and measure about 8 feet long to the tip of its tail. Despite its cheetah-like appearance, this and other recent research suggest they were a versatile predator, capable of both terrestrial pursuit and grasping prey with powerful forelimbs. 

“These cats were remarkably flexible, much like pumas are across their range today,” said Molly Cassatt-Johnstone, a Ph.D. candidate in the Paleogenomics Lab at UC Santa Cruz and lead author of the study. “We found loss-of-function mutations in certain genes that regulate circadian rhythms, suggesting they may have adapted to the extreme light cycles of summers and winters in northern latitudes.”

The ghosts of predators past

For decades, M. trumani has been a staple of North American paleoecology, often cited as the evolutionary reason why the American pronghorn is so fast. This “ghosts of predators past” hypothesis suggested that the pronghorn’s extreme speed was a co-evolved defense against the high-speed pursuit of a cheetah-like hunter.

However, the new genomic data confirm that M. trumani was actually a sister species to the modern puma, having diverged from that lineage roughly 2.6 million years ago. Its slender, “cheetah-like” body is now understood as a striking example of evolutionary convergence, where two unrelated species evolve similar traits to survive in similar environments.

Arctic adaptations and a lost sense of taste

By sequencing high-coverage genomes from fossils dating back 23,000 to 31,000 years, the team identified specific genetic blueprints that allowed these cats to thrive in the extreme environments of the Late Pleistocene.

Fossil specimens analyzed in this study from Yukon Territory were recovered from the Tr’ondëk Hwëch’in and Vuntut Gwitchin Traditional Territories, with respect for their deep-rooted relationship to and stewardship of these lands.

The study also revealed a unique sensory loss: M. trumani and all lineages of felids sampled in this study lacked a functional gene that encodes a receptor for sour taste. While all cats are known to lack a “sweet tooth,” this is the first recorded instance in felids of inactivation of genes involved in perception of sour flavors, a trait sometimes associated with highly specialized diets.

“This species of carnivore has this massive range, all the way from the Arctic to the Lower 48,” said co-author Matthew Wooller, a professor in the College of Fisheries and Ocean Sciences at the University of Alaska Fairbanks (UAF). “They’re demonstrating uber-specialization at two ends of their range, while also feeding on two completely different food sources.”

A legacy of low diversity

Beyond its diet and appearance, the study offers sobering insights into the species’ extinction at the end of the Pleistocene. The researchers found that M. trumani in Wyoming and the Yukon had low genetic diversity. But unlike pumas, their modern relatives, they didn’t show any signs of inbreeding or sharp bottlenecks—just a slow, long-term decline from the early to the late Pleistocene, which may explain their scarcity in the fossil record and ultimate extinction vulnerability.

Low genetic diversity didn’t doom this species by itself, said senior author Beth Shapiro, professor of ecology and evolutionary biology at UC Santa Cruz and co-director of the Paleogenomics Lab. “Miracinonyx persisted for a very long time without the signs of inbreeding we’d expect before a collapse,” she explained. “The decline was slow, not sudden, and that may be what left it unable to adapt when the climate shifted.”

The research highlights the danger of naming extinct species based solely on how they look. According to the authors, the name American "cheetah” is doubly misleading, as it implies a close relationship and a shared specialized hunting style that the data simply do not support.

This study was a collaborative effort involving researchers from UAF, the Yukon Palaeontology Program, and Des Moines University.

Miracinonyx radius recovered from Natural Trap Cave, Wyo.

Miracinonyx skull samples from Natural Trap Cave, Wyoming.

Credit

Julie Meachen

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Gerontological Society of America supports new immunization guidance




The Gerontological Society of America





The Gerontological Society of America (GSA) supports the 2026-27 respiratory season vaccine evidence review released on September 2, 2026, by the Vaccine Integrity Project (VIP) in collaboration with the American Medical Association. VIP’s rigorous and independent vaccine evidence review also helped inform recommendations released at the same time by its participating medical organizations, including the American College of Obstetricians & Gynecologists, the American Academy of Pediatrics, the American Academy of Family Physicians, and the Infectious Diseases Society of America.

VIP states that “the latest, high-quality scientific evidence found that immunizations against influenza, COVID-19 and respiratory syncytial virus (RSV) continue to provide meaningful protection against severe illness, hospitalization and death.”

VIP’s vaccine evidence review reinforces the importance of evidence-based immunization recommendations across the life course, which are reflected in GSA’s Concentric Value of Vaccination As We Age platform.

The cornerstone of GSA’s platform is the report, “Concentric Value of Vaccination: Intersecting Health, Economic, and Societal Benefits,” which provides evidence on the advantages of immunization for individual and population health, economic outcomes, and societal well-being.

“Vaccines remain the most consistently effective intervention against infectious diseases such as smallpox, rabies, polio, and various childhood illnesses,” the report concludes. “Their multifaceted impact highlights how vaccines not only prevent illness and reduce health care costs but also enable individuals to remain active contributors in the workforce, support caregiving roles, and sustain community engagement.”

GSA is a longstanding advocate for age-appropriate immunizations, supporting the evidence that vaccinations prevent disease and save lives.

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The Gerontological Society of America (GSA), founded in 1945, is the oldest and largest interdisciplinary organization focused on aging. It serves more than 6,000 members in over 50 countries. GSA’s vision, meaningful lives as we age, is supported by its mission to foster excellence, innovation, and collaboration to advance aging research, education, practice, and policy. GSA is home to the National Academy on an Aging Society (a nonpartisan public policy institute) and the National Center to Reframe Aging.

 

U.S. Employment among people with disabilities ties all-time high



nTIDE September 2026 Jobs Report


Kessler Foundation

nTIDE Month-to-Month Comparison of Labor Market Indicators for People with and without Disabilities 

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From July 2026 to August 2026, the employment-to-population ratio increased from 38.3 to 39.8 percent for people with disabilities and decreased from 75.0 to 74.6 percent for people without disabilities. The labor force participation rate increased from 42.4 to 43.4 percent for people with disabilities and decreased from 78.2 to 77.9 percent for people without disabilities.

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Credit: Kessler Foundation






East Hanover, NJ – September 4, 2026 – More Americans with disabilities were working in August, tying the record high reached in November 2025, even as employment among people without disabilities declined, according to today’s National Trends in Disability Employment–Jobs Report (nTIDE), issued by Kessler Foundation and the University of New Hampshire’s Institute on Disability. nTIDE tracks employment and labor force trends for people with and without disabilities.

Based on data from today’s BLS Jobs Report and nTIDE analysis, the employment-to-population ratio for people with disabilities (ages 16-64) increased from 38.3 percent in July 2026 to 39.8 percent in August 2026 (up 3.9 percent or 1.5 percentage points). In contrast, for people without disabilities (ages 16-64), the employment-to-population ratio decreased from 75.0 percent in July 2026 to 74.6 percent in August 2026 (down 0.5 percent or 0.4 percentage points). The employment-to-population ratio, a key indicator, is the percentage of people who are working relative to the total population (the number of people working divided by the total population, then multiplied by 100).

“In August, the percentage of people with disabilities who are working, 39.8 percent, tied the all-time high set in November 2025,” said John O’Neill, PhD, director of the Center for Employment and Disability Research at Kessler Foundation. “In July we found that more people with disabilities were actively looking for work, relative to people without disabilities. The increase in employment in August suggests that many of those job seekers found work,” he added.

Month-to-Month nTIDE Numbers (comparing July 2026 to August 2026)

Similarly, the labor force participation rate for people with disabilities (ages 16-64) increased from 42.4 percent in July 2026 to 43.4 percent in August 2026 (up 2.4 percent, or 1 percentage point). For people without disabilities (ages 16-64), the labor force participation rate decreased from 78.2 percent in July 2026 to 77.9 percent in August 2026 (down 0.4 percent, or 0.3 percentage points). The labor force participation rate reflects the percentage of people who are in the labor force (working, actively looking for work in the last four weeks, or on temporary layoff/furlough) relative to the total population (the number of people in the labor force divided by the number of people in the total population multiplied by 100).

“The labor force participation rate for people with disabilities reached a new all-time high, 43.4 percent, breaking the 42.8 percent mark set in November 2025,” said Andrew Houtenville, PhD, professor of economics and director of the UNH-IOD. “While it is generally a positive sign to see more people with disabilities in the labor market, cost-of-living prices continue to rise.
With many people with disabilities living at or below the poverty line, it is not surprising to find rising labor force participation, as people with disabilities and their families struggle with these rising prices,” he added.

Year-to-Year nTIDE Numbers (comparing August 2025 to August 2026)

Compared with the same time last year, the employment-to-population ratio for people with disabilities (ages 16-64) increased from 38.5 percent in August 2025 to 39.8 percent in August 2026 (up 3.4 percent or 1.3 percentage points). For people without disabilities (ages 16-64), the employment-to-population ratio slightly increased from 74.5 percent in August 2025 to 74.6 percent in August 2026 (up 0.1 percent or 0.1 percentage points).

The labor force participation rate for people with disabilities (ages 16-64) increased from 42.2 percent in August 2025 to 43.4 percent in August 2026 (up 2.8 percent or 1.2 percentage points). For people without disabilities (ages 16-64), the labor force participation rate stayed the same, 77.9 percent in August 2025 and 2026.

In August, among workers ages 16-64, the 6,788,000 workers with disabilities represented 4.5 percent of the total 150,913,000 workers in the U.S.

Ask Questions about Disability and Employment
On the same day nTIDE is issued, the team hosts an nTIDE Lunch and Learn webinar. This live Zoom broadcast gives attendees a chance to ask questions about the latest findings, hear news and updates from the field, and learn from invited panelists who discuss current disability-related research and events.

On September 4, 2026, guest presenter Ellice Switzer of Cornell University joins Drs. O’Neill and Houtenville, and Lillie Heigl, director of policy at the Association of University Centers on Disabilities. Visit the nTIDE archives at ResearchonDisability.org/nTIDE to see a recording of this nTIDE Lunch and Learn episode.

About National Trends in Disability Employment (nTIDE)
nTIDE is a joint effort of Kessler Foundation and the University of New Hampshire’s Institute on Disability. The nTIDE team tracks employment trends for people with and without disabilities, issuing monthly reports that reflect the impact of economic changes on the workforce. These reports use data from the U.S. Bureau of Labor Statistics but are customized by UNH-IOD to focus on working-age adults (ages 16 to 64). nTIDE is funded by the National Institute on Disability, Independent Living and Rehabilitation Research (NIDILRR; 90RTGE0005) and Kessler Foundation.

About the Institute on Disability at the University of New Hampshire
The Institute on Disability at the University of New Hampshire, founded in 1987, seeks to expand access and opportunity for people with disabilities in ways that strengthen communities locally and nationally. As part of a Carnegie Classification R1 university, the IOD accelerates disability inclusion through research, education, and collaboration. Its Center for Research on Disability delivers trusted analysis and tools that make disability data more accessible and actionable.

About Kessler Foundation
Kessler Foundation, founded in 1985, is a New Jersey-based nonprofit and global leader in rehabilitation research committed to changing the lives of people with disabilities. By conducting groundbreaking research, Kessler Foundation advances recovery and fosters independence to build a more inclusive and accessible world.

Our team of award-winning scientists develop and test novel interventions to transform care and optimize mobility, cognition, and quality of life for people with traumatic brain injury, spinal cord injury, stroke, multiple sclerosis, autism, and other neurological and developmental disabilities. By analyzing community and workforce participation, developing evidence-based solutions, and funding impactful community initiatives that expand employment opportunities, Kessler Foundation also addresses barriers to inclusion for people with disabilities.

Powered by a dedicated team of over 175 professionals funded by federal and state grants and private philanthropy, Kessler Foundation is redefining what is possible in rehabilitation care and recovery. For more information, visit kesslerfoundation.org.

Press Contact at Kessler Foundation:
Carmen Cusido, ccusido@kesslerfoundation.org

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New probabilistic method helps robots improve localization and object mapping



A new probabilistic semantic SLAM approach improves trajectory and map accuracy, strengthening robustness against perceptual aliasing and classifier errors



Japan Advanced Institute of Science and Technology

BPDA-GMM system overview 

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Schematic illustration showing how each semantic detection is first filtered by a semantic-geometric gate, then assigned CRP-weighted association probabilities. These weights update semantic Gaussian landmarks in the front-end, while the dominant mixture component is converted into a max-mixture semantic factor for the decoupled back-end. 

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Credit: Prof. Nak Young Chong from Japan Advanced Institute of Science and Technology, Japan Image Source Link: https://doi.org/10.1109/LRA.2026.3726389





Reliable navigation, place recognition, and object interaction require autonomous robots to maintain precise environmental maps. Semantic simultaneous localization and mapping (SLAM) add meaning to a robot’s map by representing landmarks as recognizable objects rather than only as geometric points. By adding contextual meaning into spatial maps, semantic SLAM enables robots to successfully execute complex downstream tasks like autonomous inspection, asset tracking, and human–robot assistance. 

A major challenge is deciding which mapped object produced a new observation. If several objects belong to the same category, such as multiple chairs, a robot must determine whether a new detection belongs to one of those existing objects or represents a previously unseen object. Existing probabilistic data-association approaches can assume a fixed number of landmarks, require repeated computation as a map grows, or depend on manually tuned settings for deciding when a new landmark should be created. A recent publication in IEEE Robotics and Automation Letters introduces Bayesian Probabilistic Data Association via Gaussian Mixture Models (BPDA-GMM), which formulates data association and new-object creation as a joint probabilistic inference problem. 

Professor Nak Young Chong at the Japan Advanced Institute of Science and Technology (JAIST) in Japan, along with Thanh Nguyen Canh, a doctoral student at JAIST, and other team members, developed BPDA-GMM for semantic SLAM. Their findings were published online on August 21, 2026. 

“We wanted the robot to treat object association as an evolving probabilistic decision rather than a sequence of separate yes-or-no choices. By accumulating evidence over time and assigning probability to both existing and new landmarks, our approach can make the object-level map more stable as the environment becomes more complex,” explains Prof. Chong.  

The team’s central idea is to use a statistical model known as Dirichlet-process to keep a running record of how strongly observations support existing landmarks. These counts are updated incrementally, allowing the robot to carry forward information from its previous observations without having to recalculate everything from the beginning. At the same time, the likelihood of creating another new object automatically changes as the map grows. This helps prevent duplicate registrations in increasingly crowded maps. 

For each semantic detection, BPDA-GMM first narrows the possible matches using both object-class and geometric information. It then combines the likelihood of each candidate with the Bayesian prior to calculate association probabilities. Object landmarks are represented as semantic Gaussian distributions, which together form a Gaussian mixture model.  

When evidence is ambiguous, an additional α-divergence tempering step can sharpen the association decision. The back-end also decouples semantic landmark refinement from direct pose updates, helping prevent noisy detections from corrupting the robot’s estimated trajectory. 

Experiments in simulation and on a real indoor sequence showed that BPDA-GMM improved trajectory accuracy, semantic mapping quality, and robustness to perceptual aliasing and classifier errors compared to conventional methods. The improvements were particularly pronounced in difficult outdoor simulations where correctly matching objects was challenging. The best conventional method had a median position error of about 29.57 meters, whereas BPDA-GMM reduced this to 8.15 meters. In the indoor experiment, BPDA-GMM correctly mapped 77 of the 84 ground-truth objects and achieved an F1 score of 0.749. By comparison, one competing approach produced 101 mapped objects, creating multiple duplicate entries.  

Any robot that must maintain a reliable object level map over long periods can benefit from this approach. Home-assistance robots that remember furniture and appliance locations, warehouse and factory transport robots, inspection drones, and autonomous platforms that map objects such as parked cars, poles, and trees can all benefit from this framework.  

“Our goal is to make object-level maps reliable enough for robots to use over long periods and across practical settings. Because these maps are understandable to both people and robots, more reliable association could support spoken instructions, shared maps across robot fleets, and autonomous systems. Any robot that must maintain a reliable object level map over long periods can benefit from this approach,” explains Prof. Chong.  

By reducing duplicate landmarks and improving the handling of ambiguous observations, BPDA-GMM offers a way to make semantic maps more stable while retaining real-time operation on embedded hardware. The researchers identify future directions including richer multi-modal object representations, open-vocabulary semantics, active planning for resolving ambiguous associations, and integration into multi-robot systems. 


Reference  
Title of original paper: Bayesian Probabilistic Data Association via Gaussian Mixture Models for Semantic SLAM   
Authors: Thanh Nguyen Canh; Haolan Zhang; Antonio Sgorbissa; Xiem HoangVan; Nak Young Chong   
Journal: IEEE Robotics and Automation Letters   
DOI: 10.1109/LRA.2026.3726389   

About Japan Advanced Institute of Science and Technology, Japan  
Founded in 1990 in Ishikawa prefecture, the Japan Advanced Institute of Science and Technology (JAIST) was the first independent national graduate university that has its own campus in Japan. Now, after 30 years of steady progress, JAIST has become one of Japan’s top-ranking universities. JAIST strives to foster capable leaders with a state-of-the-art education system where diversity is key; about 40% of its alumni are international students. The university has a unique style of graduate education based on a carefully designed coursework-oriented curriculum to ensure that its students have a solid foundation on which to carry out cutting-edge research. JAIST also works closely both with local and overseas communities by promoting industry–academia collaborative research.      
Website: https://www.jaist.ac.jp/english/  

About Professor Nak Young Chong from Japan Advanced Institute of Science and Technology, Japan  
Dr. Nak Young Chong is a Professor at the Japan Advanced Institute of Science and Technology (JAIST), where he serves as the Director of the Intelligent Robotics Laboratory. He completed his PhD in 1994 at Hanyang University in Seoul, South Korea. His core research focus encompasses human–robot interaction (HRI), networked robotics, and autonomous intelligent systems, including humanoid stability and assistive technologies. Throughout his prolific academic career, Professor Chong has made extensive contributions to the field of robotics, authoring and co-authoring a total of over 320 academic publications.   

Funding information  
The research was supported by JST SPRING, Japan (Grant Number JPMJSP2102) and Asian Office of Aerospace Research and Development (Grant Number FA2386-25-1-4034)