Research on identifying and measuring risk. Covers rock-avalanche modeling, cardiovascular risk, food-toxin safety, and heart calcium scans.
Researchers at ETH Zurich have created a 3D-printed model of a rock avalanche to study the movement of mixtures of water, ice, and rock. The model, which is 1:577 in scale, was used to test various scenarios and measure parameters such as depth of runoff and impact dynamics.
A new ERC-funded project at Aarhus University aims to investigate how hormones, stress, and genetic factors influence women's coronary arteries. The project will develop new models to explain why certain cardiovascular diseases affect women differently from men, and may lead to personalized rupture-risk maps and improved diagnosis and ...
A survey by the BfR Federal Institute for Risk Assessment found that mould toxins in food are not destroyed during cooking or baking. The survey also revealed gaps in knowledge about mould and its potential health risks, with many people unaware that mycotoxins can occur in food without visible signs of mould.
A new study from Northwestern University found that coronary calcium scans are most valuable for patients with borderline cardiovascular risk. The scans added relatively little to risk prediction from existing risk calculators, but provided a clearer picture for those at intermediate risk. The study suggests that not everyone needs a c...
A U-shaped association exists between LVEDD and mortality in HF, suggesting high risk for both abnormally small and large ventricles. The findings support integrating LV size assessment into routine risk stratification to guide personalized management.
Researchers developed an open-source tool RIME-X to generate regional climate and impact projections while capturing uncertainties. The new method combines simple climate models with regional information from multi-model climate and impact model ensembles, producing scenario- and time-dependent probability distributions.
Researchers introduce a new metric W² to complement traditional measures of predictive accuracy, revealing hidden patterns of systematic bias in AI models. By combining Q² with a penalty for angular difference from the ideal line, W² provides a more comprehensive evaluation of model reliability.
Two Lehigh University AI projects have been selected for funding from the Department of Energy's Genesis Mission. The RIVER-AI project will improve flood- and water-level prediction, while the REACT project aims to accelerate reactor-scale fusion energy by developing an AI-enabled digital twin. These awards strengthen Lehigh University...
Researchers are engineering biochar-based composites to overcome limitations, such as insufficient adsorption capacity and limited selectivity for certain emerging pollutants. The new review highlights the importance of balancing treatment performance with environmental safety throughout the material's life cycle.
A new study uses machine learning to predict chemical toxicity in rare and endangered species, reducing the need for direct biological testing. The model achieved strong performance predicting acute and chronic toxicity, with life stage being a key factor.
Researchers from Rutgers University analyzed US insurance claims data to compare the risk of ischemic optic neuropathy among initiators of GLP-1 RAs versus SGLT-2is or DPP-4is. A small increase in risk was observed, but absolute risk remained very low.
Researchers develop a comprehensive framework to predict drilling instability in backfilled ground, considering strength differences and asymmetry. The proposed design criterion aims to reduce inclined drilling deviations by at least 10 millimeters per meter of depth.
The BfR conducts health risk assessments for food, feed, chemicals, and products, providing scientific advice to federal governments. The institute's research-driven approach informs consumer health protection policies both domestically and internationally.
The BfR Federal Institute for Risk Assessment investigates how PFAS enter food via feed, drinking water, and soil. High concentrations of PFAS in the body have been linked to increased blood lipid levels and liver enzyme elevations. The magazine also explores other topics such as omega-3 fatty acids, raw milk, and food colour safety.
The BfR2GO magazine now offers up-to-date information on consumer health protection and laboratory animal protection. Readers can subscribe to the digital or printed edition for free of charge.
A new children's book from the German Federal Institute for Risk Assessment aims to educate kids about food safety, highlighting common pathogens like Campylobacter. The book provides tips on how to avoid cross-contamination and stay safe in the kitchen.
Researchers used an open-source AI model called Mirai to quickly identify high-risk patients and expedite their diagnostic process. This led to a significant reduction in wait times, with some women receiving biopsy results within days of having their mammograms done.
The study found that population-based pathogenic variant testing reveals different subsets of high-risk women than clinical risk factors and polygenic risk scores. This highlights the importance of incorporating PV testing into risk-based screening for breast cancer.
The German Federal Institute for Risk Assessment presents a strategic research agenda for safe advanced materials, covering areas like data collection and state-of-the-art laboratories equipment. The initiative aims to inform policy makers and innovators on regulatory relevant research needs for safer materials.
A recent study published in PNAS has found no meaningful health impacts from exposure to wind turbines. The researchers analyzed data from over 120,000 households and found no correlations between turbine installation and health problems such as headaches, depression, or sleep disturbances.
A new study suggests that both very low and very high resting heart rates are associated with an increased risk of stroke. The research found a U-shaped pattern, with stroke risk lowest at heart rates of 60-69 bpm and highest at below 50 bpm or above 90 bpm.
Hospital-based shootings in the US have increased over 25 years, with large hospitals and urban areas being high-risk settings. The study emphasizes the need for hospital-specific prevention strategies, including weapons screening technology, to address rising firearm violence.
Dan M. Frangopol has been awarded the third ASCE Wellington Prize for his groundbreaking study on probabilistic connectivity assessment of road networks subjected to ground motion and tsunamis. The research provides a more realistic assessment of network performance under extreme conditions, helping engineers and planners identify vuln...
A comprehensive survey of 4,000 adults in northern China reveals alarming gaps in public knowledge about preventing tick-borne diseases. Rural residents and high-risk groups paradoxically show the lowest protective awareness, highlighting a critical need for targeted health education interventions.
Adolescents who follow social media tipsters report higher gambling intention and increased frequency. The study highlights the need for stronger regulation of tipster-related marketing and media literacy programmes to address persuasive strategies and improve risk awareness.
A new study by Florida Atlantic University researchers highlights the role of urban planning in increasing pedestrian and bicyclist fatalities in the US. The study reveals that everyday destinations like grocery stores and pharmacies along busy roads significantly increase risk of serious injury or death.
A new study by Femida Handy and Sara Konrath found that voting is associated with reduced mortality risk in older adults for up to 15 years. Voting predicts a lower risk of mortality, even when the candidate loses, suggesting that voting itself is more important than who was voted for.
Researchers propose new method to capture complex human movement in public spaces, addressing limitations of traditional approaches. By standardizing data measurement, they aim to improve crowd safety predictions and design safer spaces.
The CA-MTransU-Net architecture achieves superior mIoU of 87.00% and faster inference speeds compared to benchmark algorithms, providing a scalable solution for post-fire damage assessment in cloud-prone landscapes.
Researchers propose a foundational framework to help multi-agent, connected systems decide what information they can trust before acting. The 'cy-trust' concept assigns a numerical trust value between 0 and 1 to data from other agents based on sensing, context, network behavior, and past experience.
Researchers evaluated the performance of the Phoenix Sepsis Score for predicting in-hospital mortality among pediatric ICU patients in China. They found that a modified version, PSS+, showed substantially improved discrimination without sacrificing clinical usability.
Researchers used machine learning methods to identify safe time windows for outpatient stem cell therapy in multiple myeloma patients. The study found that this approach can predict adverse events and enable more precise risk assessment.
Researchers developed a machine learning model to predict 28-day mortality in patients with sepsis complicated by acute respiratory failure. The model demonstrated strong discrimination for predicting mortality, with key variables including oxygenation indices, serum albumin levels, and disease severity scores.
Researchers developed an AI tool to predict patients at risk of intimate partner violence, using data from medical visits. The tool achieved high accuracy in detecting IPV among patients, with the multimodal fusion model outperforming others, detecting risk 88% of the time.
A new study found that high levels of air pollution can amplify the risk of suicide associated with heat stress, especially during the warm season. The researchers analyzed 7,500 suicide cases in Utah and found a strong synergistic effect of heat and nitrogen dioxide.
A new study proposes a framework for connecting AI risk prediction systems with scheduling platforms to detect emerging risks and adjust project plans before delays occur. This approach aims to close the gap between early warning and actionable response, enabling more resilient project delivery.
AI language models can extract and integrate information from vast amounts of unstructured environmental data, identifying pollutants and their toxic effects. While still in its early stages, the application of LLMs in aquatic risk assessment has the potential to support more dynamic and data-driven risk management strategies.
A new multicenter study by Kumamoto University and National Cerebral and Cardiovascular Center found that working-age adults with shorter sleep durations are more likely to develop atrial fibrillation. In contrast, retirees showed no significant association between sleep duration and AF risk.
A groundbreaking study found that frail men have a significantly higher risk of dying within one year after a heart attack, challenging the prevailing narrative that high clinical risk is predominantly a female issue. The research highlights the need for sex-informed care pathways to address this disparity.
Researchers are using advanced DNA sequencing technologies to monitor environmental reservoirs of antibiotic resistance genes and assess their impact on human health. The study highlights the importance of integrating gene detection, host identification, and quantitative analysis to evaluate environmental antibiotic resistance.
A new 3D model of the fault beneath the Marmara Sea reveals where a future major earthquake could take place, helping improve earthquake forecasts. The study uses magnetotelluric measurements to identify distinct high-resistivity and low-resistivity zones, shedding light on ongoing processes of fault mechanics.
The BfR children's book aims to educate children from grade 1 upwards about the dangers of contaminated food and how to avoid cross-contamination. The book features colorful illustrations and teaches kids how to defeat 'Campys' and other bacteria and viruses.
A new review highlights the challenges of composite pollution in facility agriculture, where heavy metals, microplastics, and antibiotic resistance genes interact to affect soil organisms, crop growth, and consumer health. The authors call for more integrated assessment frameworks and sustainable control strategies.
Researchers have combined molecular imprinting technology with biochar to create materials that can selectively target specific molecules, achieving high adsorption capacity and selectivity. These smart sorbents show promise for efficient pollution control in complex mixtures and at low concentrations.
A recent study published in JAMA Internal Medicine found that a significant majority of Americans will experience cost burdens due to healthcare expenses throughout their lives. The study suggests that policies aiming to reduce out-of-pocket costs could potentially improve the well-being of individuals in the US.
The German Federal Institute for Risk Assessment (BfR) is launching a new study module to investigate the influence of parental nutrition on children's eating habits. The study aims to provide insights into how plant-based diets of parents affect the eating habits and food consumption of children.
A new study found that calcium accumulation in breast arteries and its progression on mammograms can predict future cardiovascular disease. Women with more severe calcification and those whose calcification worsened over time had a higher risk of heart-related events, such as heart attack, stroke, and death.
A new AI-driven framework reimagines chemical risk assessment by merging high-throughput screening, AI-enabled toxicity mapping, and quantitative in vitro–to–in vivo risk modeling. This unified approach enables rapid identification of hazardous chemicals and prediction of risk thresholds.
A breakthrough AI system called OmniPredict can predict human pedestrian behaviors with unprecedented accuracy, revolutionizing self-driving cars and urban mobility. The model combines visual cues with contextual information to anticipate pedestrians' next moves, reducing the risk of accidents and improving traffic safety.
Heavy metals in soil can overestimate real risk to crops, ecosystems, and human health due to low bioavailability. A new review provides a practical framework using tools such as chemical extractants, biological assays, and models to estimate the accessible fraction of metals.
Bahaa Eltahawy's dissertation highlights the importance of integrated cybersecurity strategies for protecting critical infrastructure. The study reveals that current standards have limitations and proposes a model that expands protection into seven domains.
A new genetic study found that people without prior suicidal thoughts or behaviors have fewer psychiatric diagnoses and genetic risk factors for psychiatric conditions compared to those with known suicidality. This suggests that conventional wisdom on how to reduce suicide may need to be rethought.
The BfR is part of a nationwide interdisciplinary surveillance system, OHIS, to monitor antibiotic resistance. The goal is to identify trends and develop targeted measures.
The BfR Federal Institute for Risk Assessment warns of flawed scientific studies and advises critical evaluation. Experts emphasize the need to consider study results in context, as laboratory tests on cells cannot be directly applied to humans.
The Hepatitis E virus has been found to be transmissible between rats and humans, with cases reported in Germany. The virus is primarily transmitted through contaminated food products from pigs and game animals, but its transmission via rat feces is still being investigated.
Researchers found high-engagement social media posts lack essential risk information and promotional elements, potentially eroding patient decision-making. The study highlights the need for fair balance in online advertising to maintain informed consent.
Risk-adjusted mortality declined significantly following the COVID-19 pandemic, resuming prior improvement trends. Patient acuity, measured by case mix index, remained elevated, suggesting a new postpandemic baseline.
Researchers developed two risk prediction models to estimate the risk of death and illicit drug overdose in patients discharged against medical advice. Multimorbidity, heart disease, cancer, homelessness, and opioid use disorder were strong predictors of death and overdose, respectively.
The increasing use of unregulated psilocybin mushrooms poses a pressing need for public education, potency testing, and age-specific risk assessment. Existing clinical data are insufficient to guide harm reduction or policy, highlighting the need for real-world research on psilocybin use.
Researchers found that providing feedback to everyone after the entire simulation ends leads to better learning outcomes. The study's findings suggest that companies can design more effective software tools using this approach, which has been implemented by KnowBe4.