Tuesday, March 31, 2026

Vaping likely to cause cancer: New findings

University of New South Wales

Nicotine-based vapes, or e-cigarettes, are likely to cause cancers of the lung and oral cavity, according to a new study led by UNSW Sydney and published today in Carcinogenesis.

The study analyses a wide body of global research and was led by UNSW cancer researcher Adjunct Professor Bernard Stewart AM, with investigators from The University of Queensland, Flinders University, The University of Sydney, as well as Royal North Shore, The Prince Charles and Sunshine Coast University hospitals.

The team brought together experts from multiple disciplines, including pharmacists, epidemiologists, thoracic surgeons and public health researchers. Together, they examined the evidence from different scientific perspectives.

“To our knowledge, this review is the most definitive determination that those who vape are at increased risk of cancer compared to those who don’t,” Prof. Stewart says.

This assessment of carcinogenicity – or, cancer causation – review argues that while researchers have long focused on vaping as a gateway to smoking, less attention has been paid to whether the devices might cause cancer on their own.

It is one of the most detailed attempts yet to determine whether vaping itself may cause cancer, independent of tobacco smoking. The analysis draws together clinical studies, animal experiments and laboratory research examining the chemicals produced by e-cigarettes.

“Considering all the findings – from clinical monitoring, animal studies and mechanistic data – e-cigarettes are likely to cause lung cancer and oral cancer,” Prof. Stewart says.

He says though the consistency of findings across those disciplines was striking, the exact number of attributable cancer cases remains unclear.

“Our assessment is qualitative and does not involve a numerical estimate of cancer risk or burden. We’ll only be able to determine the precise risk once longer-term studies are available.”

Growing public health concerns

E-cigarettes were first sold in the early 2000s and became available in Australia around 2008. Early marketing framed them as a ‘safer’ alternative to tobacco cigarettes, as well as a possible aid for quitting smoking.

But the colourful, flavoured devices of today have spread quickly and widely, particularly among young people. Vaping is now a common sight outside schools, bars and train stations across Australia, despite the Australian Government introducing new laws to regulate vapes in 2023. Disposable vapes and non-therapeutic vapes are banned, while therapeutic vapes can only be sold in pharmacies, and only to help people quit smoking.

“E-cigarettes are known to be a gateway to smoking and hence cancer,” says co-author UNSW Associate Professor Freddy Sitas.

“But the extent to which they may cause cancer in their own right has not received as much attention in research,” he says.

“The evidence was remarkably consistent across fields,” he says. “It dictated an unequivocal finding now, though human studies that estimate the risk will take decades to accumulate.”

A clear outcome

Smoking has been studied for more than a century. Though e-cigarettes are relatively new, inhaling nicotine-laced aerosols is already linked to addiction, poisoning, inhalation injuries and burns.

While researchers wait for long-term population studies showing whether people who vape are more likely to develop cancer, they must rely on multiple other forms of evidence.

The team identified numerous carcinogenic compounds in e-cigarette aerosols, including volatile organic chemicals and metals released from heating coils.

They examined several types of evidence: biomarkers in people showing DNA damage, oxidative stress and tissue inflammation; experiments in mice that caused lung tumours; and laboratory studies showing cellular damage and disrupted biological pathways linked to cancer.

Taken together, the researchers say the evidence points strongly in one direction.

A compounding problem

There is also growing evidence that many smokers who switch to vaping don’t quit cigarettes.

“Most of those who use e-cigarettes to quit smoking end up in ‘dual-use-limbo’, unable to shake off either habit,” says A/Prof. Sitas.

“What we do know from recent epidemiological evidence from the USA is that those who both vape and smoke are at an additional four-fold increased risk of developing lung cancer.”

This was described in commentary also published today by A/Prof. Sitas and Prof. Stewart in Cancer Epidemiology.

History repeating

A/Prof. Sitas and Prof. Stewart traced parallels between the early scientific evidence linking smoking to disease and emerging concerns about vaping.

It took nearly a century of scientific investigation – from the mid-1800s to the landmark US Surgeon General’s report in 1964 – before smoking was officially recognised as a cause of lung cancer.

During that time, early warning signs were often dismissed or overlooked.

“Early reports linked smoking to infectious diseases such as tuberculosis, followed by cardiovascular disease, stroke and lung cancer,” A/Prof Sitas says.

He says the same pattern may now be unfolding with vaping – and that researchers should not repeat the delay that occurred with cigarettes.

“E-cigarettes were introduced about 20 years ago. We should not wait another 80 years to decide what to do.”

MULTIMEDIA

Embeddable video short: https://youtu.be/ITBmOZTxcwU
Hi-res media reel available on request via the media contact listed.

Journal

Carcinogenesis

DOI

10.1093/carcin/bgag015

Method of Research

Systematic review

Article Title

The carcinogenicity of e-cigarettes: a qualitative risk assessment

Article Publication Date

30-Mar-2026

SwRI supports novel industrial heat production system

Joule Hive™ Thermal Battery system can generate and store heat up to 1,800 degrees Celsius

Southwest Research Institute

SAN ANTONIO — March 30, 2026 — Southwest Research Institute (SwRI) is home to the first full-scale system showcasing a novel and commercially scaled method of industrial heat production, the Joule Hive™ Thermal Battery. The project is funded by the U.S. Department of Energy and led by Electrified Thermal Solutions. SwRI designed key support systems and oversaw construction of the system on its San Antonio campus.

Industrial processes typically burn fossil fuels for heat, emitting significant amounts of carbon dioxide (CO2). This contributes a significant percentage of global CO2 output, and most cannot switch to cleaner energy sources because they require temperatures and energy densities that are difficult to achieve without combustion.

“The technology SwRI will help to demonstrate is a purely electric system that could use renewable energy to generate and store heat up to 1,800 degrees Celsius with direct 13.2 kV (medium voltage) integration,” said SwRI’s Josh Schmitt, one of the project’s leaders. “This would eliminate the need for fossil fuels and cut gas bills creating a pathway for zero-emissions industrial heat in building heat, steel, cement, chemicals and other industrial applications.”

The core of the system uses fire bricks designed to withstand intense heat, specifically made to line firepits, kilns and stoves. These bricks are modified with conductive materials to retain large amounts of thermal energy and generate heat through electrical resistance.

“Electricity flows through the bricks at high voltages, generating resistive heat, which the bricks absorb,” Schmitt explained. “This thermal energy is stored inside the bricks until it’s needed, allowing the system to separate importing energy from the process of delivering heat to customers. The heat is delivered by blowing hot air, or any process gas, directly over the heated bricks with a blower, which goes into the process.”

The system’s thermal energy storage capabilities make it possible for industrial sites to use renewable energy flexibly. During especially sunny or windy periods, the system can charge itself by heating the firebricks. This makes it possible for sites to rely on renewable energy sources such as solar or wind, as they can store power for use when the sun isn’t shining or the wind isn’t blowing. The SwRI unit has a capacity of 20 megawatt-hours of heat.

“To host the system, SwRI expanded the infrastructure of its pre-existing High-Temperature Energy Conversion and Storage laboratory to include a 12,000 square-foot heavy-duty outdoor slab and 600 amps of electric power at 13.2 kV,” said Dr. Tim Allison, director of SwRI’s Machinery Department. “Our strategic investment in facility infrastructure supporting the Joule Hive project has established the capability to deploy zero-carbon heat at the MW scale. We are actively assessing the system’s output to validate pathways for integration into future site operations.”

“This project demonstrates a significant step forward in decarbonizing industrial heat systems, which have traditionally relied on carbon-based fuels,” Schmitt said. “By demonstrating a purely electric heating solution that can deliver temperatures up to 1,800 degrees Celsius, we’re not only providing a cleaner, more efficient alternative but also paving the way for industries to integrate renewable energy seamlessly into their operations. Additionally, it provides flexibility for industrial heat applications. It allows owners of the thermal storage to produce process heat from electricity when gas prices are high or provide an industrial site access to high-temperature heat when gas is not available.”

SwRI’s broad expertise in thermal energy systems has been key to providing the engineering, infrastructure and operational requirements necessary to develop, construct and test the technology. This includes designing and building the supporting infrastructure and integrating utilities required to operate the system as well as overseeing project testing and commissioning, addressing operational challenges and fine-tuning system performance. Additionally, SwRI developed innovative air transport, mixing and exhaust systems to ensure precise heat delivery for industrial applications.

Construction of the system began in August 2025 and was completed in December 2025.

For more information, visit https://www.swri.org/markets/energy-environment/power-generation-utilities/conventional-power-generation/thermal-energy-storage.

BD² releases largest multi‑modal psychiatric dataset to accelerate breakthroughs in bipolar disorder

New integrated dataset combines clinical, biological, neuroimaging, and real‑world behavioral data to transform understanding and improve care for people living with bipolar disorder.

BD²: Breakthrough Discoveries for thriving with Bipolar Disorder

Highlights:

Historic Scale: Data from 615 participants across initial six sites, forming the most comprehensive multimodal dataset ever created for a psychiatric condition.
Integrated Modalities: Includes clinical assessments, MRI neuroimaging, blood-based biomarkers, and continuous wearable sensor data.
Designed for Impact: Embedded within a Learning Health Network to rapidly translate discoveries into improved patient care.
Open Science: Curated dataset available to qualified researchers, with all identifiable information removed.

Washington, D.C. – BD²: Breakthrough Discoveries for thriving with Bipolar Disorder today announced the first public release of data from the BD² Integrated Network Longitudinal Cohort Study (LCS). This marks the launch of the largest integrated dataset in the history of psychiatry, designed to accelerate progress toward personalized and more effective care for people living with bipolar disorder.

Cara Altimus, PhD, CEO of BD², highlighted how BD2 is transforming the bipolar disorder research and treatment landscape:

“For decades, bipolar disorder research has been severely underfunded and deeply fragmented. Without shared standards or shared data, meaningful progress was nearly impossible. BD² was created to fundamentally change that ecosystem so that we can make a positive change in the lives of those living with bipolar disorder. This initial data release unifies the field and provides a new foundation and actual infrastructure for understanding the complexity of bipolar disorder.”

The BD² Integrated Network’s LCS follows participants over five years, allowing researchers to observe how the disorder evolves, identify factors that can predict patient outcomes, and track biological changes before, during, and after mood episodes. The study is embedded in a Learning Health Network (LHN), which ensures that research insights can be shared with clinicians and rapidly fed back into care practices, while real-world observations from clinics simultaneously shape future research questions.

BD² prioritizes an open science model, sharing data widely with qualified researchers to encourage innovation and generate insights. Ekemini A.U. Riley, PhD, Founder and CEO of the Coalition for Aligning Science and BD² Program Board Member, noted:

“This is a pivotal step forward in the broader quest to advance brain and mental health science. Too often, discoveries stall between the lab and the people who need them. BD² is changing that paradigm. With open science as a priority and uniting multimodal data, clinical practice, and the lived experience of those with bipolar disorder, we are building the foundation required to move from scientific insight to sustained, real-world impact.”

Unprecedented Scale and Depth

The release includes data from 615 participants from the initial six sites in the BD² Integrated Network. The dataset integrates multiple modalities to show the most comprehensive picture of how bipolar disorder presents in individuals:

Clinical Assessments: Comprehensive clinician and self-reported measures covering mood, cognition, and social determinants of health.
High-Resolution Brain Imaging (MRI): To study how brain structure and function link to clinical outcomes.
Wearable Sensor Data (Fitbit): Capturing daily sleep and wake patterns, circadian rhythms, and activity cycles.
Biological Samples: Standardized blood bioassays to explore inflammation, stress, and metabolic function.

To ensure immediate utility for the scientific community, BD2 provides rigorous quality control and expert curation. The data has been standardized by dedicated working groups, reducing the technical burden for those analyzing complex imaging or wearable sensor data.

“What makes this release especially transformative is the depth and diversity of the data. This level of richness enables researchers across the bipolar disorder field to move beyond isolated observations and begin asking complex, cross-cutting questions about how bipolar disorder evolves.” said Emily Baxi, PhD, BD² Integrated Network Program Director.

Because bipolar disorder varies widely across individuals, deep phenotyping at scale is essential for discovering measurable indicators of disease progression and treatment response. Katherine E. Burdick, PhD, BD² Integrated Network Scientific Director; Diane Goldman Kemper Family Professor of Medical Psychology; Vice Chair of Research, Department of Psychiatry Vagelos College of Physicians and Surgeons, Columbia University; and Director of Research New York State Psychiatric Institute, emphasized:

“The deep phenotyping enabled by this multi-modal dataset is critical because it captures the immense biological and clinical variety of bipolar disorder. For the first time, we have the scale and breadth of data required to identify modifiable treatment targets and generate findings that can be directly translated into better care and improved lives.”

Mark Frye, MD, BD² Integrated Network Scientific Director and Stephen & Shelley Jackson Family Professor of Individualized Medicine, Mayo Clinic, added:

“The depth of science and the level of rigorous, standardized data collection within the BD² Integrated Network is truly unparalleled in the field of psychiatry. By bridging the gap between biological discovery and clinical practice, we can finally address long-standing care gaps and identify the precise factors that allow individuals with bipolar disorder to truly thrive.”

Access the Dataset: Qualified researchers may apply using this link.

Watch the Announcement: To hear more from BD² leadership about the future of bipolar disorder research and the impact of this data release, watch the full recorded briefing.

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About BD²: Breakthrough Discoveries for thriving with Bipolar Disorder is an independent nonprofit organization and the first organization focused on funding and advancing research and care for bipolar disorder on a global scale. Our collaborative, open-science approach is designed to transform and shorten the time it takes for scientific breakthroughs to make a meaningful difference in the lives of the tens of millions of people with bipolar disorder. The BD² Discovery Grants, Brain Omics, Genetics Platforms, and the Integrated Network are designed to share data, methods, and resources across initiatives and the bipolar disorder research community. For more information, please visit bipolardiscoveries.org.

Emotions in motion: How movement may signal mental health issues

University of Texas at Dallas

Dr. Kang lab 1 — image:
Biomedical engineering senior Ian Y. Kim wears a motion capture suit during an experiment in the Neuromuscular and Musculoskeletal Biomechanics Lab at The University of Texas at Dallas.
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Credit: The University of Texas at Dallas

New University of Texas at Dallas research shows the potential for detecting mental health disorders by analyzing the way a person moves.

Using 3D motion capture and machine-learning models, researchers were able to identify elevated depression and anxiety symptoms in subjects from the way they walked and got up from a chair. The findings, published online in the May issue of Gait & Posture, demonstrate the potential for developing wearable devices that one day could give users early warnings about their mental health.

“Our study showed that depression and anxiety can be identified from human movement,” said Dr. Gu Eon Kang, assistant professor of bioengineering in the Erik Jonsson School of Engineering and Computer Science. “Gait analysis could offer an objective method for evaluating mental health.”

Using gait analysis to identify mental health issues and emotional states is an emerging area of research. Kang cautioned, however, that wearable mental health-screening technology could serve as an indicator — not a replacement — for a professional diagnosis.

“If we can detect potential issues, people can seek treatment early and outcomes could be much better,” he said.

Kang said the research could have other applications such as helping animators better illustrate emotion.

Researchers in Kang’s Neuromuscular and Musculoskeletal Biomechanics Lab recruited 30 young adults for the study and assessed their levels of depression and anxiety using standardized questionnaires. Participants performed walking and sit-to-walk tasks while wearing a black form-fitting motion capture suit covered with 68 reflective markers. Their movements were recorded by a 16-camera motion capture system.

Researchers trained a machine-learning model using data from participants’ movements combined with information about whether they fell into higher- or lower-symptom groups for depression or anxiety, based on their questionnaires. Then, they asked the model to predict the mental state of other participants on whose data the system had not been trained.

The model correctly classified walking participants about 75% of the time, and using sit-to-walk tasks, 77% of the time.

Angeloh Stout BS’20, MS’23, a biomedical engineering doctoral student in Kang’s lab and a first author of the study, said that as a former high school student athlete, he became interested in the research after taking Kang’s biomechanics class. Stout, who helped set up Kang’s lab, said he was surprised by the changes in how people walked depending on their emotional state.

“You expect someone to walk slower when they’re sad. But what’s interesting to see is the different body responses that occur,” Stout said. “Subjects with higher depression and anxiety scores showed subtle but measurable differences from subjects with lower scores in how their joints moved along with greater hesitation during transitions like standing up to walk.”

Stout and other researchers in Kang’s lab published another recent study, in the February edition of Gait & Posture, that found a person’s gait also can provide insight into their emotional state.

In that study, participants were asked to recall memories to elicit five emotions: anger, sadness, joy, fear and a neutral state. Then, researchers captured their gait patterns in the lab. The model was about 59% accurate in distinguishing between emotional states and detected sadness with 66% accuracy.

While additional research with more subjects needs to be done to improve the method, Kang said the team’s study demonstrates the possibility for an objective measure of human emotion.

“Believe it or not, gait may be the most reliable modality for detecting emotion,” he said.

Kang said he became interested in studying gait as a way to combine his longtime interest in psychology with engineering. His goal is to determine whether gait analysis also can be used to provide early warnings about other mental health issues such as bipolar disorder and neurodevelopmental conditions such as attention-deficit/hyperactivity disorder.

Other authors of the study to detect depression and anxiety through gait analysis include several biomedical engineering students: graduate student Marvin Alvarez BS’25 and seniors Macie Kauffman, Mehreen Dawood, Ashley T. Adams, Ian Y. Kim, Mrigank Maharana and Luke Fisanick, who conducted related research through the Hobson Wildenthal Honors College Undergraduate Research Apprenticeship Program. Kaye Mabbun MS’25, Dr. Yunhui Guo, assistant professor of computer science, and Dr. Chuan-Fa Tang, assistant professor of mathematical sciences in the School of Natural Sciences and Mathematics, also contributed.

In addition to Kang, co-authors of the study to gauge emotions by studying gait include Justin MacNeal Cadenhead BS’23, MS’24; Maharana; Ashley Guzman BS’23, MS’24; Kauffman; and Katherine Brown PhD’21, assistant professor of instruction in bioengineering. The UT Dallas researchers collaborated with colleagues from McGovern Medical School at UT Health Houston.

The research was funded by the National Science Foundation (grant 2513070).

The computer screen shows the marker trajectory during a motion capture experiment at The University of Texas at Dallas.

Credit

The University of Texas at Dallas