Neighborhood conditions linked to childhood cancer survivors’ long-term health

Survivors living in communities with high social, physical and healthcare-access vulnerability are more likely to develop chronic health conditions, indicating a need for community-level support

St. Jude Children's Research Hospital

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(L to R) First author Jaesung Choi, PhD, and I-Chan Huang, PhD, both of the St. Jude Department of Epidemiology & Cancer Control

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Credit: Courtesy of St. Jude Children's Research Hospital

(MEMPHIS, Tenn. – October 14, 2026) Survivors of childhood cancer can make lifestyle changes to reduce later-in-life chronic health conditions, such as diabetes and heart disease. Still, some survivors report local environmental barriers to taking these actions. According to a new study from St. Jude Children’s Research Hospital scientists, survivors from the most vulnerable neighborhoods — those with features including low income per capita, poor walkability, a lack of access to nearby healthcare or fewer healthy food options — have a significantly elevated risk. The findings, published recently in eClinicalMedicine, identify a need to consider these community-level factors to better support survivors.

 

Scientists already knew that individual socioeconomic factors were linked to survivors’ long-term health, but the role of the surrounding social and physical environment was less clear. To investigate, the researchers compared neighborhood indicators of vulnerability, such as socioeconomic status, minority status and access to healthcare and food, with repeated clinical assessments of survivors enrolled in the St. Jude Lifetime Cohort Study (St. Jude LIFE) since 2007 to track changes in chronic health conditions over time.

 

“We’ve found that neighborhood conditions likely play a significant role in how survivors’ health outcomes evolve,” said corresponding author I-Chan Huang, PhD, St. Jude Department of Epidemiology & Cancer Control. “That means that we have the beginning of what we need to find effective, accessible and affordable support and interventions to overcome these barriers and improve survivors’ health trajectory.”

 

The researchers revealed that living in the most socially or environmentally vulnerable neighborhoods is associated with a doubled risk of overall chronic health condition burden compared to the least vulnerable neighborhoods. However, they also identified new opportunities to support survivors.

 

“Over the past decades, the substantial efforts made to improve outcomes for children with cancer have focused on limiting therapies with strong links to chronic health problems,” said co-author Melissa Hudson, MD, Department of Oncology. “These findings remind us that it is essential to consider other factors, such as access to food, safe walking venues and primary medical care, in our management of survivors living in disadvantaged neighborhoods.”

 

Finding an intervention target

 

Neighborhood-level interventions will likely require substantial time, money and effort. The study provides first-of-its-kind information to help researchers decide which community barriers to investigate further. When the researchers dug into disease-specific associations, instead of total disease burden, they found larger effects that may help prioritize future testing. For example, poor walkability was associated with a fivefold increased risk of metabolic disease and a tenfold increased risk of a heart attack.

 

These neighborhood factors also intersected with individual risk factors, such as survivors on public insurance who also live in one of the most vulnerable neighborhoods, who had a sevenfold increased risk of muscle and cardiac issues. The complex nature of this means that finding the best way to support patients to decrease their risk of chronic health conditions will require further study.

 

“While treatment history is the most significant determinant of survivors’ chronic disease risk, we found that access to everyday resources in their neighborhoods also matters,” Huang said. “That is promising, as we can’t change what cancer therapy survivors received decades ago, but we can start changing and testing community-level supports for them today.”

 

Authors and funding

The study’s first author is Jaesung Choi, St. Jude. The study’s other authors are Sedigheh Mirzaei, Deo Kumar Srivastava, Nickhill Bhakta, Stephanie Dixon, Matthew Ehrhardt, Carmen Wilson, Angela Delaney, Daniel Mulrooney, Heather Brandt, Kirsten Ness, Gregory Armstrong and Melissa Hudson, St. Jude; Madeline Horan, Wake Forest University School of Medicine; and Yikyung Park, Washington University in St. Louis.

 

The study was supported by grants from the National Cancer Institute (U01CA195547, U01CA301480 and P30CA021765) and the American Lebanese Syrian Associated Charities (ALSAC), the fundraising and awareness organization of St. Jude.

 

St. Jude Media Relations Contact

Michael Sheffield
Desk: (901) 595-0221
Cell: (901) 379-6072
michael.sheffield@stjude.org
media@stjude.org

 

St. Jude Children's Research Hospital

St. Jude Children’s Research Hospital is leading the way the world understands, treats, and cures childhood catastrophic diseases. As the only National Cancer Institute-designated Comprehensive Cancer Center devoted solely to children, St. Jude advances groundbreaking research and shares its discoveries worldwide to accelerate progress in pediatric medicine. Treatments developed at St. Jude have helped push the overall childhood cancer survival rate from 20% to more than 80% since the hospital opened more than 60 years ago. Through collaboration and innovation, St. Jude is working to ensure that children everywhere have access to the best possible care. To learn more, visit stjude.org, read St. Jude Progress, a digital magazine, and follow St. Jude on social media at @stjuderesearch.

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Journal

EClinicalMedicine

Method of Research

Experimental study

Subject of Research

People

Article Title

Neighborhood disadvantages and longitudinal progression of multimorbidity among adult survivors of childhood cancer: A single-center St. Jude Lifetime Cohort Study in the U.S.

 

Fine particles from aircraft exhaust become more harmful over time

University of Basel

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Battist Utinger is studying the oxidative potential of fine particulate matter in the laboratory. A device developed at the University of Basel can measure how much these particles can trigger harmful oxidative reactions.

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Credit: Christine Möller, University of Basel, Swiss Nanoscience Institute

Fine particulate matter consists of tiny particles with diameters in the nanometer range. They are produced, for example, by fuel combustion, remain suspended in the air and can penetrate deep into the respiratory tract. There, they can trigger oxidative stress, a process that promotes inflammation and, over the long term, can lead to serious health problems such as respiratory or cardiovascular diseases. Scientists call this harmful property the particles' oxidative potential.

However, fine particles usually remain in the atmosphere for hours or even several days before people inhale them. Little is known about how these particles' harmful properties change over time. A research team led by Professor Markus Kalberer therefore investigated how the oxidative potential, and thus the toxicity, of fine particles emitted by a small aircraft jet engine and a marine diesel engine develops over time.

Aircraft emissions become more toxic

Using a photochemical reactor, the researchers simulated what happens to the particles in the atmosphere over 1 to 12 days. To investigate the oxidative properties of fresh and aged exhaust emissions, they used a measuring instrument developed specifically for this purpose at the University of Basel: the Online Oxidative Potential Ascorbic Acid Instrument (OOPAAI).

The results were remarkable: While the health-related properties of ship engine emissions remained largely stable over time, the oxidative potential of aircraft emissions increased significantly as the particles aged. This was due to changes in the chemical composition of the particles as they reacted with components of the air under sunlight over an extended period.

Fresh exhaust emissions are not the only concern

Dr. Battist Utinger, one of the two first authors of the study from the Department of Environmental Sciences and the Swiss Nanoscience Institute at the University of Basel, explains: “Our study shows that it is important to look beyond freshly emitted exhaust particles. Atmospheric processes can significantly alter the oxidative properties of the particles and thus their potential to harm human health.”

Markus Kalberer adds: “This study clearly shows that current legal frameworks, such as the Swiss Ordinance on Air Pollution Control, do not adequately account for the most toxic sources of fine particulate matter and their properties.”

The World Health Organization WHO estimates that more than 7 million premature deaths occur annually due to exposure to high concentrations of air pollution particles – more than twice the number of global deaths from AIDS, malaria and tuberculosis combined.

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Journal

Environmental Science Atmospheres

DOI

10.1039/d5ea00174a

Article Title

Online characterisation of oxidative potential and reactive oxygen species of fresh and aged aircraft turbine and ship engine particulate emissions

 

Google.org awards $2.3 million USD to University of Toronto researchers to advance AI-powered peptide drug discovery

Research team, led by Joseph Brown, will generate experimental data and develop AI model to create open access peptide research tool

University of Toronto - Leslie Dan Faculty of Pharmacy

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From left: Chris Ing, co-founder ProteinQure; Joseph Brown, Assistant Professor, Leslie Dan Faculty of Pharmacy, University of Toronto; Philip Kim, Professor, Department of Molecular Genetics, University of Toronto; Keith Pardee, Associate Professor, Leslie Dan Faculty of Pharmacy, University of Toronto

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Credit: Steve Southon

A group of scientists led by Joseph Brown, assistant professor at the Leslie Dan Faculty of Pharmacy, has received $2.3 million USD in funding to develop a database and AI training model to identify peptides with therapeutic potential. The project is funded through the Google.org Impact Challenge: AI for Science initiative.

The newly funded initiative, OpenPep, will lead to an open access database that will allow researchers to use artificial intelligence (AI) to predict which peptides will bind to target proteins.

“Peptides are having a moment:  Many adults have tried a peptide drug, and 8% of newly approved drugs are peptides. They are no longer a niche class of drugs,” says Brown, who is also a Scientific Advisor for the University of Toronto’s Acceleration Consortium. “The real challenge is that we don’t have a lot of existing data for peptide discovery, so developing peptide medicines is still remarkably slow. That challenge inspired us to gather large amounts of data so we can build chemically-informed models and speed up the pace of discovery.”

Peptides are short chains of amino acids, smaller than a protein but larger than a conventional small molecule drug. When engineered, they can be stable, precise and selective in modulating biological targets and they hold a lot of promise as drugs.

AI has become an important part of biological research and drug discovery, as researchers can leverage AI models where data exists to make predictions and speed up the research process by prioritizing which wet-lab experiments to complete. However, data is the foundation from which AI is built. For example, AlphaFold, one of the most prominent AI models for protein structure prediction, was built from open-source data developed over decades of research.

But no similar database and AI model exist for peptides. Peptide discovery almost exclusively progressed by experiments, with the precious data scattered across various labs, projects, and companies.

To tackle this gap, Brown and his co-investigators – Associate Professor Keith Pardee from the Leslie Dan Faculty of Pharmacy, Professor Phil Kim from U of T’s Donnelly Centre for Cellular and Biomolecular Research, and Chris Ing, co-founder and chief scientific officer of ProteinQure – decided to team up to build a database and matching AI model for peptide binding that researchers around the world can use and contribute to.

“AI has the potential to transform how we understand biology and accelerate the discovery of new therapeutics,” said Leslie Yeh, Director of Scientific Progress, Google.org. “By pairing our targeted, early-stage funding with advanced AI, we can give researchers the runway to take bold risks on foundational science that traditional sources of capital may overlook. OpenPep aims to do just that—breaking down fragmented data barriers so scientists around the world can openly share knowledge and build on one another’s discoveries. We’re proud to support the University of Toronto in building this resource and advancing a more open, collaborative approach to AI-powered scientific discovery.”

Research team will crowd-source suggestions of disease-relevant proteins to target

OpenPep leverages the expertise of the co-investigators across peptide discovery, design, and AI/machine learning to generate large amounts of data and build models to predict peptide-protein binding.

Pardee’s group will leverage their expertise in accessible cell-free systems from synthetic biology to produce up to 500 disease-relevant proteins, a snapshot of the human proteome. Brown’s team will use specialized mass spectrometry to experimentally test large libraries of peptides against the target proteins and measure which peptides bind and their binding strength.

The team will then use the experimental data to build and train AI models that can predict how well peptides bind to proteins that have not been tested experimentally. As the researchers test and validate those predictions, the data can be added to the model to further refine and improve predictions.

“AI can turn thousands of individual peptide experiments into generalizable rules about how peptides interact with proteins,” says Ing. “With OpenPep, the goal is to use those insights to predict and design peptides for targets we haven’t experimentally explored yet, allowing the value of each experiment to extend well beyond the specific peptide and target that were measured.”

As the team starts working on generating experimental data, they will be crowd-sourcing suggestions of proteins for peptide discovery from collaborators at hospitals, pharmaceutical companies, and research institutes with particular interest in pediatric and rare diseases, cancer, neurodegeneration and cardiovascular disease. Any researcher interested in nominating a target for discovery can submit suggestions via a webform found on the team’s website openpep.com.

Once established, OpenPep will be an open database that the team and other researchers can continue to contribute toward further model improvements. “Some of the biggest advances in biology have been built on open scientific resources. No single laboratory can explore the full diversity of peptide chemistry and disease biology, so making the resource open also gives it the potential to grow through contributions from the broader scientific community,” says Ing.

“OpenPep will give peptide drug-discovery teams around the world a head start. Researchers will be able to build on a large body of experimental data to find and optimize promising peptide molecules more efficiently. Ultimately, we hope this makes peptide discovery more predictive and shortens the path from a disease target to a potential therapeutic.”

Brown says the significant investment from the Google.org Impact Challenge Award is key to ensuring that the researchers are able to deliver on their ambitious goal.

“This funding gives us the momentum to deliver on committing to dedicated data generation efforts required to advance the field in this way,” says Brown. “The scale of data that we’re going to put together doesn’t exist anywhere else, and this support is going to help us lead in the space and unlock a completely different AI-powered paradigm for peptide discovery.”

“AI won’t replace experiments, but it will help us choose better ones by identifying the peptides most worth testing,” says Brown. The team further states that “by turning experiments into open data, and open data into AI, we hope to give more scientists a better place to start --- and accelerate the discovery of new peptides for the benefit of everyone.”

CA Skip navigation Search Create Avatar image OpenPep: A Breakthrough for AI-Driven Peptide Drug Discovery [VIDEO] 

 

UBC researchers uncover new cyber threat to water and energy networks

Hackers could identify and block vital communications to essential infrastructure without ever breaking its encryption, researchers warn

University of British Columbia

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University of British Columbia researchers have uncovered a vulnerability that could allow hackers to target and disrupt critical infrastructure such as water treatment plants and energy grids without needing to break into a facility’s own systems or crack its encryption.

The technique targets facilities that communicate with cloud-based monitoring and control systems over encrypted connections. An attacker would first need to compromise a router carrying traffic between the facility and the cloud.

The findings suggest that encryption alone may not be enough to protect vital public facilities. By analyzing everyday traffic patterns like the timing and size of digital messages, an attacker could identify when critical commands or data are likely to be transmitted, even when their actual contents remain hidden.

Industrial control systems rely on computers to run physical machinery such as pumps, valves and generators. Unlike attacks that compromise equipment inside a plant or overwhelm a network with traffic, the new technique uses patterns in encrypted communications to predict critical moments and selectively block a small fraction of messages. This allows it to disrupt operations without entering the plant’s own systems and evade the attack detectors tested by the researchers during the attack.

“What makes this attack concerning is that an attacker doesn’t need to read the messages being exchanged,” said Dr. Aastha Mehta, a UBC computer science professor who leads the Principled Systems Security Group and is a co-investigator on the project. “Even when the contents are encrypted, patterns in the communication can reveal enough information to identify and target critical communications.”

How a ‘sniper’ could target a water-treatment plant

The researchers call their attack framework “ICS-Sniper” because, like a sniper, it can selectively target critical communications with a small footprint.

In laboratory tests, the team successfully demonstrated the attack on a cloud-adapted version of a water-treatment research testbed at Singapore University of Technology and Design. They used two models of the testbed, one using software-based controllers and the other using standard industrial control hardware; both models simulated the physical processes.

In one test, the attack delayed the start of clean-water pumping by about 15 minutes. Another left a simulated valve open for more than nine minutes longer than intended — a failure that could cause treated-water loss in a real plant.

“An attacker doesn’t necessarily need to crack your encryption to cause disruption,” said Dr. Karthik Pattabiraman, a UBC professor of electrical and computer engineering and co-investigator on the project who leads the Dependable Systems Lab. “By simply watching traffic patterns, they can identify when critical messages are likely to be sent and selectively block them. That means blocking a small amount of traffic could trigger a much larger operational disruption.”

The researchers chose water treatment because public schematics were available to replicate the facility’s control systems. They also tested their traffic-analysis method across several industrial communication protocols, including a power-grid dataset, although the operational disruptions were demonstrated in the water-treatment models.

“As industrial systems increasingly connect to cloud-hosted services, their exposure to network-based attacks like ICS-Sniper could grow,” said first author Dr. Gargi Mitra, who conducted the research as a postdoctoral researcher at UBC. “Our goal is to uncover new vulnerabilities before attackers do, so the security community can address them while these services are still in the early stages of adoption.”

Making critical systems harder to disrupt

The team is already working on ways to safeguard critical infrastructure against this type of attack.

One approach involves making network communications less predictable — for example, by padding message sizes or adjusting their timing to make it harder for attackers to distinguish critical commands from routine system chatter. Such changes would need to preserve the timing requirements of industrial equipment. Another is to make plant controls and coordination more resilient to network disruptions, including by providing alternative routes for critical communications.

“Our goal is to build defence in depth and make these systems more resilient to attacks like this,” said Dr. Mehta.

The team has also released its research code, instructions for reproducing the laboratory testbeds, and network traffic data from those testbeds so other security researchers can reproduce the findings and develop and test defences.

As society relies more heavily on interconnected technology to run essential services, the researchers say security strategies need to protect not only the privacy of data, but also the safe operation of physical machinery during an attack.

The paper, “ICS-Sniper: A Targeted Blackhole Attack on Encrypted ICS Traffic,” has been accepted for presentation at the 2027 Network and Distributed System Security Symposium, a leading computer security research conference, in Seoul, South Korea.

Chanyuan Liu, Pritam Dash, Elaine Yao and Alain Zhiyanov also contributed to the paper.

The project is supported by the National Cybersecurity Consortium.

Interview languages: English (Mehta, Mitra, Pattabiraman)

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Method of Research

Computational simulation/modeling

 

Ebola vaccine induces T cell cross-reactivity against Bundibugyo virus in humans

German Center for Infection Research

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The rVSVΔG-ZEBOV-GP (Ervebo; Merck Sharp & Dohme) is a highly efficacious vaccine against Ebola virus.

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Credit: Deutsches Museum/Alexander Goettert

The ongoing Bundibugyo ebolavirus (BDBV) outbreak in the Democratic Republic of the Congo is the second-largest Ebolavirus outbreak globally, with more than 6,000 confirmed cases and a mortality rate of 48 percent. Currently, no licensed BDBV vaccine is available. The VSV-EBOV vaccine, developed against the related Ebola virus (EBOV) and licensed under the name Ervebo, has shown partial cross-protection against BDBV in non-human primates and induces BDBV-reactive antibodies in vaccinated individuals. However, the extent and potential protective role of this cross-reactivity in humans remain unclear. Now, a study led by researchers of the German Center for Infection Research (DZIF) and published in The Lancet Infectious Diseases shows that a single immunization with the licensed EBOV vaccine can induce T cell responses that recognize BDBV.

T-cell responses contribute to viral control and protection against severe disease for diverse types of viruses. Because T cells can recognize conserved viral epitopes, they may potentially cross-react between related viruses. However, whether VSV-EBOV vaccination also induces T cells that recognize BDBV in humans has remained unknown.

A DZIF research team led by Dr. Leonie Mayer and Prof. Marylyn Addo from the Institute for Infection Research and Vaccine Development at the University Medical Center Hamburg-Eppendorf and Prof. Christof Geldmacher and Dr. Rolanda Londt from the Institute of Infectious Diseases and Tropical Medicine at the LMU University Hospital Munich therefore analyzed and mapped T-cell responses against EBOV, BDBV and Sudan virus (SUDV) in VSV-EBOV-vaccinated individuals. The glycoproteins of the three viruses are phylogenetically distant, with EBOV and BDBV sharing 66.3 percent amino acid identity, compared with 56.3 percent between EBOV and SUDV.

“Using multiple sequence alignments—the parallel comparison of multiple amino acid sequences—we identified several sequences that are highly conserved among the glycoproteins of EBOV, BDBV, and SUDV, and tested these regions for their interactions with the immune systems of vaccine recipients,” says first author Mayer. The researchers then assessed cross-reactive T cell responses in 20 vaccine recipients at day 28 after VSV-EBOV vaccination. Of these vaccine recipients, 16 showed EBOV-glycoprotein-specific T cell responses, 13 showed BDBV-glycoprotein-reactive T cell responses and seven showed SUDV-glycoprotein-reactive T cell responses at day 28 after vaccination. Most vaccinees with a positive EBOV-glycoprotein response also had BDBV-reactive T cells.

The study demonstrates that a single immunization with the available, licensed EBOV vaccine can induce T cell cross-reactivity against BDBV and—to a lesser extent—against SUDV. While it is not known, whether these T cells can contribute to improved clinical outcomes upon infection with BDBV, preclinical studies in non-human primates suggest that T cell responses are required for vaccine-mediated protection.

“Our findings provide the first evidence that VSV-EBOV vaccination against ebolavirus induces BDBV-cross-reactive T cell responses,” says Geldmacher. “While the study has limitations due to its small sample size, in the absence of a BDBV-specific vaccine, the study supports the systematic evaluation of the EBOV vaccine within clinical trials during the current BDBV outbreak,” he concludes.

This study was supported by the DZIF, the European Vaccines Hub for Pandemic Readiness (EVH), and the DFG-funded Collaborative Research Center 1648 “Emerging Viruses: Pathogenesis, Structure, Immunity”. 

Electron microscope image of an Ebola virus using negative contrast.

Credit

Dr. Martin Schauflinger/Institut für Virologie, Philipps-Universität Marburg

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Journal

The Lancet Infectious Diseases

DOI

10.1016/S1473-3099(26)00529-3

Method of Research

Experimental study

Subject of Research

People

Article Title

Cross-reactive T-cell responses against BDBV in humans after rVSVΔG-ZEBOV-GP vaccination

Article Publication Date

13-Oct-2026