It’s possible that I shall make an ass of myself. But in that case one can always get out of it with a little dialectic. I have, of course, so worded my proposition as to be right either way (K.Marx, Letter to F.Engels on the Indian Mutiny)
Australia’s Major Skink (Bellatorias frerei) has evolved the same venom resistance mutation as the honey badger (Mellivora capensis) which is found across Africa, Southwest Asia, and the Indian subcontinent.
“What we saw in skinks was evolution at its most ingenious,” Professor Fry said.
“Australian skinks have evolved tiny changes in a critical muscle receptor, called the nicotinic acetylcholine receptor.
“This receptor is normally the target of neurotoxins which bind to it and block nerve-muscle communication causing rapid paralysis and death.
“But in a stunning example of a natural counterpunch, we found that on 25 occasions skinks independently developed mutations at that binding site to block venom from attaching.
“It’s a testament to the massive evolutionary pressure than venomous snakes exerted after their arrival and spread across the Australian continent, when they would have feasted on the defenceless lizards of the day.
“Incredibly, the same mutations evolved in other animals like mongooses which feed on cobras.
“We confirmed with our functional testing that Australia’s Major Skink (Bellatorias frerei) has evolved exactly the same resistance mutation that gives the honey badger it’s famous resistance to cobra venom.
“To see this same type of resistance evolve in a lizard and a mammal is quite remarkable – evolution keeps hitting the same molecular bullseye.”
The muscle receptor mutations in the skinks included a mechanism to add sugar molecules to physically block toxins and the substitution of a protein building block (amino acid arginine at position 187).
The laboratory work validating the mutations was carried out at UQ’s Adaptive Biotoxicology Laboratory by Dr Uthpala Chandrasekara who said it was incredible to witness.
“We used synthetic peptides and receptor models to mimic what happens when venom enters an animal at the molecular level and the data was crystal clear, some of the modified receptors simply didn’t respond at all,” said Dr Chandrasekara.
“It’s fascinating to think that one tiny change in a protein can mean the difference between life and death when facing a highly venomous predator.”
The findings could one day inform the development of novel antivenoms or therapeutic agents to counter neurotoxic venoms.
“Understanding how nature neutralises venom can offer clues for biomedical innovation,” Dr Chandrasekara said.
“The more we learn about how venom resistance works in nature, the more tools we have for the design of novel antivenoms.”
The project included collaborations with museums across Australia.
The research has been published in International Journal of Molecular Sciences.
If your home was destroyed by a sudden disaster that you couldn't control, you would hope that at the very least, your insurance would cover your losses. However, disaster risk financing systems are struggling to keep pace with growing economic losses. Natural catastrophic (NatCat) events are becoming increasingly costly, and recent global warming could potentially worsen the situation. Researchers at Tohoku University worked together with Swiss RE International SE (Japan Branch) to come up with solutions for more sustainable and cost-effective parametric insurance that supports both victims and disaster risk financing policymakers.
The key problem is that although insured NatCat losses have been rising, the protection gap - the difference between total economic losses and insured losses - continues to widen. This divergence is primarily due to the slow uptake of insurance coverage for NatCat events, which leaves victims without proper compensation.
"Tsunami events are rare, which may be why they are overlooked," explains Anawat Suppasri (Tohoku University). "However, when they occur, they can cause some of the greatest, most devastating losses - even compared to other NatCat events. Despite this, they're often treated as secondary risks in disaster risk financing."
Coming up with an ideal coverage plan is difficult. Typically, a system called parametric insurance is used. The benefits are that it covers losses often excluded from traditional indemnity policies, and that payment is received rapidly, enabling businesses to recover more quickly after disasters. However, the downside is that there is a basis risk: the potential mismatch between actual losses and the insurance payout. They want to compensate disaster victims fairly - not too much (which could drive up premiums and still negatively impact the policyholder), and not too little (falling short of what was destroyed or lost).
To optimize this balancing act, the research team suggested a customized revamp of a system called parametric insurance. They incorporated Probabilistic Tsunami Risk Assessment (PTRA) into their model to quantify tsunami losses, payouts, and the corresponding basis risk, considering the uncertainty of future tsunami scenarios. In their study, several tsunami indices - such as tsunami height at tide gauges and inundation depth on land - were examined. They identified the optimal payouts and the corresponding thresholds for these indices, which determine when payouts are triggered.
For example, when applied to Sendai Port in Japan, their model reduced overpayment to policyholders by 60.9% while maintaining a reduction in shortfall. This suggests that, for a comparable level of tsunami risk reduction for policyholders, the cost of parametric insurance could be reduced by 60.9%. This means that victims get paid fairly more often and companies can operate efficiently without overpayment errors.
The proposed framework may aid financial institutions in developing more robust parametric insurance products for tsunami events and support their expansion into other tsunami-prone regions. Given the destructive aftermath of tsunami events, an efficient insurance plan may not just mean saving money - but also saving lives.
The findings were published in npj Natural Hazards on July 21, 2025.
Change in residual risk before and after the introduction of parametric insurance. Values for each building indicate the average expected loss ratio (calculated as repair cost divided by replacement cost) if an extremely rare event--one with only a 0.1% chance of occurring in any given year--were to happen.
Reduction of the expected overpayment (unnecessary insurance payouts) when using different indices for the payment.
A proposed approach towards minimizing basis risk in tsunami parametric insurance scheme
Residential care increases social participation but gaps remain
Study shows many older adults participate more in social activities after moving into a long-term care community but potential disparities reveal need for more inclusive community-building
A new study from the University of Colorado Anschutz Medical Campus finds that older adults become more socially active after moving into long-term care communities like nursing homes or assisted living facilities but we might not all benefit equally.
The study was published today in JAMA Internal Medicine.
Researchers analyzed data from more than 600 Americans aged 65 and older who moved into a nursing home or assisted living facility between 2011 and 2019 through the National Health and Aging Trends Study. The average participant was 85-years-old when they moved.
“Long-term care communities can be an important source of help as we get older, but many are afraid of how moving to one could affect their social life,” said lead author Kenneth Lam, MD, assistant professor of geriatric medicine at the University of Colorado School of Medicine. “This made us want to look at the data to see what actually happens to social participation when people move.”
Researchers examined five aspects of social participation including visiting friends or family, going out for enjoyment, attending religious services, joining clubs or group activities and volunteering. Before moving into a facility, engagement in all five areas declined steadily. But after moving, participation in group activities rose by 15.6%, and attendance at religious services increased by 12.6%. Going out for enjoyment decreased by 14.1%.
“The overall picture is that people move after their world had already started to get smaller. Facilities provide structured social opportunities that residents may have struggled to access when they were living at home,” said Lam. “These can include on-site religious services, clubs or organized events that can reduce isolation.”
But the gains weren’t shared equally. Participation remained lower among men and among, nursing home residents identifying as Black, Hispanic or other racial and ethnic groups. Women, by contrast, were more likely to maintain family and friend connections. They also began attending religious services after moving in. Nursing home residents were also less likely to go out for enjoyment or attend religious services.
“Facilities have the potential to be vibrant and inclusive communities,” said Lam. “But access to those social opportunities is not evenly distributed.”
Lam said social participation isn’t just a preference. It’s also a public health issue.
“Loneliness has been declared a national health crisis by the former U.S. Surgeon General. Despite the stigma facing long-term care communities, our study shows that they are a key part of the solution.” he said. “But we need to do more to make sure that access is equitable and activity is meaningful.”
The team hopes their findings will help families, care providers and policymakers think differently about long-term care. Patients and other participants in Lam's studies have told him that connection with others is more important than physical health. “That’s what motivated this study. This is about dignity, quality of life and making sure that we help people live rather than just not die,” said Lam.
About the University of Colorado Anschutz Medical Campus
The University of Colorado Anschutz Medical Campus is a world-class medical destination at the forefront of transformative science, medicine, education and patient care. The campus encompasses the University of Colorado health professional schools, more than 60 centers and institutes and two nationally ranked independent hospitals - UCHealth University of Colorado Hospital and Children's Hospital Colorado – which see more than two million adult and pediatric patient visits yearly. Innovative, interconnected and highly collaborative, the CU Anschutz Medical Campus delivers life-changing treatments, patient care and professional training and conducts world-renowned research fueled by $910 million in annual research funding, including $757 million in sponsored awards and $153 million in philanthropic gifts.
Journal
JAMA Internal Medicine
Plan, prepare, conquer: predicting mountain accident risks with deep learning and pre-climb data
Researchers develop a robust framework using deep learning and contextual data to accurately predict mountaineering accident risks in advance
To address the high number of mountaineering accidents in Japan, researchers developed a deep learning model that uses contextual information such as time of day, environmental conditions, and climbers’ details to accurately predict the risk of four major categories of climbing accidents. This holds immense potential to significantly improve mountain safety measures in Japan and worldwide.
Credit: Dr. Yusuke Fukazawa from Sophia University, Japan
Japan is famous for its beautiful mountain landscapes as well as for the challenges it offers to avid mountaineers. However, these mountains can get so treacherous that Japan actually records one of the highest numbers of mountain accidents globally. In fact, Japan had 3,126 mountain accidents in 2023, the highest annual total since 1961.
In particular, Nagano Prefecture, which has many mountains popular among climbers, is one of the regions with a high number of mountaineering accidents due to its rugged terrain and severe weather conditions.
Therefore, there is a dire need to accurately predict mountaineering accidents and estimate the risks in advance. This could help climbers and rescue teams prepare better while reducing the likelihood of future accidents.
While traditional machine learning has proven effective in predicting traffic accidents and natural disasters, its application to mountain accident prediction is limited by several factors: small datasets, the complex nature of accidents, and missing variables of environmental conditions and demographics.
To address this issue, Associate Professor Yusuke Fukazawa, together with graduate student Taeko Sato—both affiliated with the Graduate Program in Applied Data Sciences at Sophia University, Japan—developed a predictive model to assess mountaineering accident risks during the expedition planning stage. “Mountain accidents fall into four major categories: falls from height, ground-level falls, fatigue, and disorientation. However, these do not occur under uniform conditions; rather, they are closely related to factors such as time of day, terrain, weather conditions, and climber demographics,” explains Dr. Fukazawa.
Accordingly, they trained BERT, a deep learning model, with such contextual data to enable it to classify accident risks into the four key categories using climb-related information at the time of planning. The dataset consisted of 2,596 mountaineering accidents that occurred between 2014 and 2023 in the Nagano Prefecture. Furthermore, the researchers used SHAP analysis, an explainable AI technique, to visualize the relationships between the input features and predicted risks for each of the four accident categories. The results of this entire endeavor were published online in the International Journal of Data Science and Analytics on June 16, 2025.
The dataset had a stable number of annual accidents, with a notable decline only in 2020 due to the COVID-19 pandemic. However, there were distinct seasonal, temporal, and demographic patterns observed. For instance, more accidents were recorded during summer months, on weekends, and in the afternoon. Similarly, ground-level falls mainly occurred among women, whereas higher incidents of falls from height and disorientation were observed in men. Falls from height accounted for the greatest number of accidents, followed by ground-level falls, fatigue, and disorientation.
The BERT model accurately identified and predicted the four accident categories with over 60% accuracy achieved for two types: fall from height and disorientation. The SHAP analysis further aided in interpreting the model’s prediction to successfully classify the key predictors contributing to each category’s risk. Time of day, mountain location, weather conditions, and demographic factors were found to be critical predictors for all four categories. For example, “morning” and “Hotaka” were identified as strong predictors of falls from height, while “noon” and “Yatsugatake range” were for ground-level falls. Fatigue was linked to elderly climbers and the afternoon period, and disorientation was associated with conditions like snow and fog, as well as solo hiking. This matched with the patterns observed in the input dataset, which confirmed the robustness of the model.
“Our high-accuracy, multi-class predictive model provides climbers a better understanding of the specific risks associated with their planned actions and conditions, enabling safer decision-making and preparation. By tailoring risk assessments to each climber’s unique situation, our model offers personalized safety recommendations, a more practical and effective form of mountaineering support instead of the traditional, one-size-fits-all warnings,” says Dr. Fukazawa. “We also believe that our research can be used for developing mobile applications and web-based services that offer planning and safety solutions at people’s fingertips. This way we hope to improve risk management not only for mountaineering but also for other outdoor activities and encourage more people to step outside and safely enjoy nature.”
Interestingly, these results highlight the power of deep learning and explainable AI in making risk assessments more reliable. In fact, this approach has the potential to extend beyond mountaineering, with potential applications in other domains where AI-driven decision support can aid in risk prediction and safety planning.
About Sophia University
Established as a private Jesuit affiliated university in 1913, Sophia University is one of the most prestigious universities located in the heart of Tokyo, Japan. Imparting education through 29 departments in 9 faculties and 25 majors in 10 graduate schools, Sophia hosts more than 13,000 students from around the world.
Conceived with the spirit of “For Others, With Others,” Sophia University truly values internationality and neighborliness, and believes in education and research that go beyond national, linguistic, and academic boundaries. Sophia emphasizes on the need for multidisciplinary and fusion research to find solutions for the most pressing global issues like climate change, poverty, conflict, and violence. Over the course of the last century, Sophia has made dedicated efforts to hone future-ready graduates who can contribute their talents and learnings for the benefit of others, and pave the way for a sustainable future while “Bringing the World Together.”
Yusuke Fukazawa is an Associate Professor at the Department of Graduate Degree Program of Applied Data Sciences at Sophia University, Japan. His research focuses on machine learning, supervised learning, and predictive modeling and analytics. He completed his PhD from the Department of Precision Mechanical Engineering, The University of Tokyo. Prior to joining Sophia University, Dr. Fukazawa was a Senior Manager at NTT Docomo, Inc., and a visiting researcher at the University of Tokyo. He has 93 published articles and 274 industrial patents to his name, with 10 awards bestowed upon him for his research and student mentorship.
About Sophia University
Established as a private Jesuit affiliated university in 1913, Sophia University is one of the most prestigious universities located in the heart of Tokyo, Japan. Imparting education through 29 departments in 9 faculties and 25 majors in 10 graduate schools, Sophia hosts more than 13,000 students from around the world.
Conceived with the spirit of “For Others, With Others,” Sophia University truly values internationality and neighborliness, and believes in education and research that go beyond national, linguistic, and academic boundaries. Sophia emphasizes on the need for multidisciplinary and fusion research to find solutions for the most pressing global issues like climate change, poverty, conflict, and violence. Over the course of the last century, Sophia has made dedicated efforts to hone future-ready graduates who can contribute their talents and learnings for the benefit of others, and pave the way for a sustainable future while “Bringing the World Together.”
Yusuke Fukazawa is an Associate Professor at the Department of Graduate Degree Program of Applied Data Sciences at Sophia University, Japan. His research focuses on machine learning, supervised learning, and predictive modeling and analytics. He completed his PhD from the Department of Precision Mechanical Engineering, The University of Tokyo. Prior to joining Sophia University, Dr. Fukazawa was a Senior Manager at NTT Docomo, Inc., and a visiting researcher at the University of Tokyo. He has 93 published articles and 274 industrial patents to his name, with 10 awards bestowed upon him for his research and student mentorship.
Journal
International Journal of Data Science and Analytics
Over the past decade, the number of picture books that parents can read to young children about personal boundaries and saying “no” to inappropriate touching has ballooned, as attention to preventing sexual abuse grows.
But many of the books contain “key gaps” in teaching concepts experts recommend to help children begin to understand consent, according to a study by a pair of Washington State University researchers.
They analyzed more than 100 picture books for children ages 3-8, comparing them against key tenets of consent education and child abuse prevention identified in past research. Most of the books conveyed messages aligned with some of those tenets, such as the concepts of bodily autonomy and setting personal boundaries, while providing parents a range of options for introducing the subject to their children.
“These books really provide a good resource for parents,” said Stacey J.T. Hust, professor and associate dean of faculty affairs and college operations in the Murrow College of Communication, who co-authored the paper. “I think parents should explore these books and identify which ones are consistent with their preferences, and then add them in to their family reading time.”
However, most books also fell short in some areas: an absence of specific anatomical terms for body parts, for example, and a failure to depict adults helping to set boundaries. The books tended to place the burden of refusing inappropriate contact on the children themselves, while presenting a “mean world” scenario filled with shadowy threats from perpetrators and lacking in trusted adults.
An accumulation of those messages could create fear, rather than emphasizing personal autonomy and safety.
“As much as it is important to tell children to be aware of appropriate and inappropriate touching, it’s also important to tell them not everyone is out there to get you,” said Opeyemi Victoria Johnson, a PhD student in the Murrow College and lead author on the paper.
The study, which was published in The Journal of Children and Media, sheds new light on an important question: What are the best ways to begin to teach children about boundaries and consent, so they recognize inappropriate touching and feel empowered to report it? One answer that has gained ground in recent years is to introduce the subject at younger ages, which has led to a proliferation of picture books addressing the topic.
“This market is just ballooning, for a couple of reasons,” Hust said. “One, there’s a large interest in talking to children about consent arising from the MeToo movement — parents want to protect their children from suffering sexual assault when they’re older, so they want to start conversations early. There’s also been a movement for parents to acknowledge and talk about consent that’s not sexual.”
Hust and Johnson focused on this relatively new category of books, many of which address questions of consent in non-sexual contexts—emphasizing the ability to say no to touches like hand-holding or kissing relatives goodbye.
“Consent-oriented books tend to focus more broadly on any kind of touching,” Hust said.
For the study, the researchers used a structured coding framework to evaluate 102 picture books published between 2013 and 2023 for key concepts such as body ownership, use of anatomical language, identifying trusted adults, empowering language, and depictions of both perpetrators and parents. While many books supported important ideas like bodily autonomy and boundary-setting, the researchers found gaps in areas such as shared adult responsibility and the inclusion of grooming behaviors, highlighting both the strengths and limitations of current children’s literature on consent.
Despite the shortcomings, many offered good general advice, and there was a range of approaches to suit different families. For instance, while researchers would encourage the use of specific anatomical terms for body parts, some of the books used other language, such as “swimsuit region.”
For families who want to avoid the specific terms for body parts, such books can still be effective in conveying messages about bodily autonomy. Forty-two percent of the books included specific tips for parents in how to better talk with their children about consent.
