Artificial intelligence: Algorithms improve medical image analysis

Algorithms based on deep learning can detect tumors - KIT researchers among the best teams at the International AutoPET Competition

Karlsruher Institut für Technologie (KIT)

 

image: 

Automated methods enable the analysis of PET/CT scans (left) to accurately predict tumor location and size (right) for improved diagnosis and treatment planning.

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Credit: Gatidis S, Kuestner T. (2022) A whole-body FDG-PET/CT dataset with manually annotated tumor lesions (FDG-PET-CT-Lesions) [Dataset]. The Cancer Imaging Archive. DOI: 10.7937/gkr0-xv29

Imaging techniques play a key role in the diagnosis of cancer. Precisely determining the location, size, and type of tumors is essential for choosing the right therapy. The most important imaging techniques include positron emission tomography (PET) and computer tomography (CT). PET uses radionuclides to visualize metabolic processes in the body. The metabolic rate of malign tumors is considerably higher than that of benign tissues. Radioactively labeled glucose, usually fluorine-18-deoxyglucose (FDG), is used for this purpose. In CT, the body is scanned layer by layer in an X-ray tube to visualize the anatomy and localize tumors.

 

Automation Can Save Time and Improve Evaluation

Cancer patients sometimes have hundreds of lesions, i.e. pathological changes caused by the growth of tumors. To obtain a uniform picture, it is necessary to capture all lesions. Doctors determine the size of the tumor lesions by manually marking 2D slice images – an extremely time-consuming task. “Automated evaluation using an algorithm would save an enormous amount of time and improve the results,” explains Professor Rainer Stiefelhagen, Head of the Computer Vision for Human-Computer Interaction Lab (cv:hci) at KIT.

 

Rainer Stiefelhagen and Zdravko Marinov, a doctoral student at cv:hci, took part in the international autoPET competition in 2022 and came in fifth out of 27 teams involving 359 participants from all over the world. The Karlsruhe researchers formed a team with Professor Jens Kleesiek and Lars Heiliger from the Essen-based IKIM – Institute for Artificial Intelligence in Medicine. Organized by the Tübingen University Hospital and the LMU Hospital Munich, autoPET combined imaging and machine learning. The task was to automatically segment metabolically active tumor lesions visualized on a whole-body PET/CT. For the algorithm training, the participating teams had access to a large annotated PET/CT dataset. All algorithms submitted for the final phase of the competition are based on deep learning methods. This is a variant of machine learning that uses multi-layered artificial neural networks to recognize complex patterns and correlations in large amounts of data. The seven best teams from the autoPET competition have now reported on the possibilities of automated analysis of medical image data in the Nature Machine Intelligence journal.

 

Algorithm Ensemble Excels in the Detection Tumor Lesions

As the researchers explain in their publication, an ensemble of the top-rated algorithms proved to be superior to individual algorithms. The ensemble of algorithms is able to detect tumor lesions efficiently and precisely. “While the performance of the algorithms in image data evaluation partly depends indeed on the quantity and quality of the data, the algorithm design is another crucial factor, for example with regard to the decisions made in the post-processing of the predicted segmentation,” explains Stiefelhagen. Further research is needed to improve the algorithms and make them more resistant to external influences so that they can be used in everyday clinical practice. The aim is to fully automate the analysis of medical PET and CT image data in the near future. (or)

 

Original publication

Sergios Gatidis, Marcel Früh, Matthias P. Fabritius, Sijing Gu, Konstantin Nikolaou, Christian La Fougère, Jin Ye, Junjun He, Yige Peng, Lei Bi, Jun Ma, Bo Wang, Jia Zhang, Yukun Huang, Lars Heiliger, Zdravko Marinov, Rainer Stiefelhagen, Jan Egger, Jens Kleesiek, Ludovic Sibille, Lei Xiang, Simone Bendazzoli, Mehdi Astaraki, Michael Ingrisch, Clemens C. Cyran & Thomas Küstner: Results from the autoPET challenge on fully automated lesion segmentation in oncologic PET/CT imaging. Nature Machine Intelligence, 2024. DOI: 10.1038/s42256-024-00912-9

 

More about the cv:hci of KIT

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Journal

Nature Machine Intelligence

DOI

10.1038/s42256-024-00912-9 

Subject of Research

People

Article Title

Results from the autoPET challenge on fully automated lesion segmentation in oncologic PET/CT imaging.

How good are AI doctors at medical conversations?

Researchers design a more realistic test to evaluate AI's clinical communication skill

Harvard Medical School

Artificial intelligence tools such as ChatGPT have been touted for their promise to alleviate clinician workload by triaging patients, taking medical histories and even providing preliminary diagnoses.

These tools, known as large-language models, are already being used by patients to make sense of their symptoms and medical tests results.

But while these AI models perform impressively on standardized medical tests, how well do they fare in situations that more closely mimic the real world?

Not that great, according to the findings of a new study led by researchers at Harvard Medical School and Stanford University.

For their analysis, published Jan. 2 in Nature Medicine, the researchers designed an evaluation framework — or a test — called CRAFT-MD (Conversational Reasoning Assessment Framework for Testing in Medicine) and deployed it on four large-language models to see how well they performed in settings closely mimicking actual interactions with patients.

All four large-language models did well on medical exam-style questions, but their performance worsened when engaged in conversations more closely mimicking real-world interactions.

This gap, the researchers said, underscores a two-fold need: First, to create more realistic evaluations that better gauge the fitness of clinical AI models for use in the real world and, second, to improve the ability of these tools to make diagnosis based on more realistic interactions before they are deployed in the clinic.

Evaluation tools like CRAFT-MD, the research team said, can not only assess AI models more accurately for real-world fitness but could also help optimize their performance in clinic.

"Our work reveals a striking paradox - while these AI models excel at medical board exams, they struggle with the basic back-and-forth of a doctor's visit," said study senior author Pranav Rajpurkar, assistant professor of biomedical informatics at Harvard Medical School. “The dynamic nature of medical conversations - the need to ask the right questions at the right time, to piece together scattered information, and to reason through symptoms - poses unique challenges that go far beyond answering multiple choice questions. When we switch from standardized tests to these natural conversations, even the most sophisticated AI models show significant drops in diagnostic accuracy."

A better test to check AI’s real-world performance

Right now, developers test the performance of AI models by asking them to answer multiple choice medical questions, typically derived from the national exam for graduating medical students or from tests given to medical residents as part of their certification.

“This approach assumes that all relevant information is presented clearly and concisely, often with medical terminology or buzzwords that simplify the diagnostic process, but in the real world this process is far messier,” said study co-first author Shreya Johri, a doctoral student in the Rajpurkar Lab at Harvard Medical School. “We need a testing framework that reflects reality better and is, therefore, better at predicting how well a model would perform.”

CRAFT-MD was designed to be one such more realistic gauge.

To simulate real-world interactions, CRAFT-MD evaluates how well large-language models can collect information about symptoms, medications, and family history and then make a diagnosis. An AI agent is used to pose as a patient, answering questions in a conversational, natural style. Another AI agent grades the accuracy of final diagnosis rendered by the large-language model. Human experts then evaluate the outcomes of each encounter for ability to gather relevant patient information, diagnostic accuracy when presented with scattered information, and for adherence to prompts.

The researchers used CRAFT-MD to test four AI models — both proprietary or commercial and open-source ones — for performance in 2,000 clinical vignettes featuring conditions common in primary care and across 12 medical specialties.

All AI models showed limitations, particularly in their ability to conduct clinical conversations and reason based on information given by patients. That, in turn, compromised their ability to take medical histories and render appropriate diagnosis. For example, the models often struggled to ask the right questions to gather pertinent patient history, missed critical information during history taking, and had difficulty synthesizing scattered information. The accuracy of these models declined when they were presented with open-ended information rather than multiple choice answers. These models also performed worse when engaged in back-and-forth exchanges — as most real-world conversations are — rather than when engaged in summarized conversations.

Recommendations for optimizing AI’s real-world performance 

Based on these findings, the team offers a set of recommendations both for AI developers who design AI models and for regulators charged with evaluating and approving these tools.

These include:

• Use of conversational, open-ended questions that more accurately mirror unstructured doctor-patient interactions in the design, training, and testing of AI tools
• Assessing models for their ability to ask the right questions and to extract the most essential information
• Designing models capable of following multiple conversations and integrating information from them
• Designing AI models capable of integrating textual (notes from conversations) with and non-textual data (images, EKGs)
• Designing more sophisticated AI agents that can interpret non-verbal cues such as facial expressions, tone, and body language

Additionally, the evaluation should include both AI agents and human experts, the researchers recommend, because relying solely on human experts is labor-intensive and expensive.  For example, CRAFT-MD outpaced human evaluators, processing 10,000 conversations in 48 to 72 hours, plus 15-16 hours of expert evaluation. In contrast, human-based approaches would require extensive recruitment and an estimated 500 hours for patient simulations (nearly 3 minutes per conversation) and about 650 hours for expert evaluations (nearly 4 minutes per conversation). Using AI evaluators as first line has the added advantage of eliminating the risk of exposing real patients to unverified AI tools.

The researchers said they expect that CRAFT-MD itself will also be updated and optimized periodically to integrate improved patient-AI models.

“As a physician scientist, I am interested in AI models that can augment clinical practice effectively and ethically,” said study co-senior author Roxana Daneshjou, assistant professor of Biomedical Data Science and Dermatology at Stanford University.  “CRAFT-MD creates a framework that more closely mirrors real-world interactions and thus it helps move the field forward when it comes to testing AI model performance in health care.”

Authorship, funding, disclosures

Publication DOI 10.1038/s41591-024-03328-5

Additional authors included Jaehwan Jeong and Hong-Yu Zhou, Harvard Medical School; Benjamin A. Tran, Georgetown University; Daniel I. Schlessinger, Northwestern University; Shannon Wongvibulsin, University of California-Los Angeles; Leandra A. Barnes, Zhuo Ran Cai and David Kim, Sandford University; and Eliezer M. Van Allen, Dana-Farber Cancer Institute.

The work was supported by the HMS Dean’s Innovation Award and a Microsoft Accelerate Foundation Models Research grant awarded to Pranav Rajpurkar. SJ received further support through the IIE Quad Fellowship.

Daneshjou reported receiving personal fees from DWA, personal fees from Pfizer, personal fees from L'Oreal, personal fees from VisualDx, stock options from MDAlgorithms and Revea outside the submitted work, and a patent for TrueImage pending. Schlessinger is the co-founder of FixMySkin Healing Balms, a shareholder in Appiell Inc. and K-Health, a consultant with Appiell Inc and LuminDx, and an investigator for Abbvie and Sanofi. Van Allen serves as an advisor to Enara Bio, Manifold Bio, Monte Rosa, Novartis Institute for Biomedical Research, Serinus Bio. E.M.V.A provides research support to Novartis, BMS, Sanofi, NextPoint. Van Allen holds equity in Tango Therapeutics, Genome Medical, Genomic Life, Enara Bio, Manifold Bio, Microsoft, Monte Rosa, Riva Therapeutics, Serinus Bio, Syapse. Van Allen has filed for institutional patents on chromatin mutations and immunotherapy response, and methods for clinical interpretation; intermittent legal consulting on patents for Foaley & Hoag, and serves on the editorial board of Science Advances.

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Journal

Nature Medicine

DOI

10.1038/s41591-024-03328-5 

Method of Research

Computational simulation/modeling

Subject of Research

Not applicable

Article Title

An evaluation framework for clinical use of large language models in patient interaction tasks

Article Publication Date

2-Jan-2025

Balancing renewable energy expansion and biodiversity conservation: new study highlights overlap of solar energy potential and critical habitats in the Southwest

PeerJ

As the climate crisis accelerates, the urgent transition to renewable energy sources is at the forefront of global sustainability efforts. However, a new study by Ms. Kylee Fleckenstein, published in PeerJ Life & Environment, reveals a critical challenge in balancing renewable energy development with biodiversity conservation inthe arid Southwest United States.

The research, titled "Mapping species of greatestconservation need and solar energy potential in thearid Southwest for future sustainable development", explores the intersection of high-priority conservationhabitats and areas suitable for large-scale Solar EnergyDevelopment (SED). With its abundant sunshine andopen landscapes, the Southwest boasts some of thehighest Global Horizontal Irradiance (GHI) values in thecountry, making it a prime location for solar energyexpansion. However, the region is also home to unique and vulnerable species, including the LeConte’s Thrasher (Toxostoma lecontei), Bendire’s Thrasher (Toxostoma bendirei), Sonoran Desert Tortoise (Gopherus morafkai), Mojave Desert Tortoise (Gopherus agassizii), and the Southwestern population of the Burrowing Owl (Athene cunicularia).

Ms. Fleckenstein’s study uses a novel combined approach, employing species distribution modeling (SDM) to map areas of likely species presence and high habitat suitability, alongside a site suitability analysis for potential solar development sites. The findings indicate a significant overlap between high-priority habitats and optimal locations for SED, underscoring the urgent need for strategies that balance renewable energy growth with conservation priorities.

“Our study highlights a paradox: the same landscapes that make the Southwest ideal for solar energydevelopment are also critical for the survival of speciesthat are already facing threats from habitat loss, population growth, and climate change,” said Ms. Fleckenstein. “This research offers a roadmap foridentifying areas where development can proceed sustainably, minimizing impacts on biodiversity.”

The study provides actionable insights forpolicymakers, conservationists, and developers, emphasizing the importance of integrating biodiversity conservation into renewable energy planning. By identifying areas of overlap between conservationpriorities and energy potential, stakeholders can make informed decisions to support both sustainabledevelopment and the protection of the region’s unique ecological heritage.

As the U.S. prepares to scale up renewable energyinitiatives, particularly solar energy projects, the study calls for a collaborative approach to ensure that renewable energy solutions do not come at the cost ofirreplaceable biodiversity.

Key Findings:

• Significant overlap exists between optimal solardevelopment locations and critical habitats forseveral vulnerable species.
• Species distribution modeling (SDM) and site suitability analysis offer effective tools foraligning energy development with conservationpriorities.
• A coordinated, science-based approach is crucial for mitigating the impacts of solar energyprojects on sensitive ecosystems.

This research serves as a call to action for a balanced approach to climate solutions, ensuring that the shift to renewable energy is not only sustainable but also responsible.

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Journal

PeerJ

DOI

10.7717/peerj.18568 

Method of Research

Observational study

Article Title

Mapping species of greatest conservation need and solar energy potential in the arid Southwest for future sustainable development

Article Publication Date

2-Jan-2025

 

Bringing the magic of playing music to the virtual world

University of Birmingham

 

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A musician records themselves and sends the video to another musician.  The software creates a responsive avatar that plays in perfect synchrony with the music partner.  All you need is an iPhone and a VR headset to bring musicians together for performance, practice, or teaching.

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Credit: ARME project

Researchers are aiming to bring the magic of playing music in person to the virtual world. 

The Joint Active Music Sessions (JAMS) platform, created at the University of Birmingham, uses avatars created by individual musicians and shared with fellow musicians to create virtual concerts, practice sessions, or enhance music teaching. 

Dr Massimiliano (Max) Di Luca from the University of Birmingham explains: “A musician records themselves and sends the video to another musician.  The software creates a responsive avatar that plays in perfect synchrony with the music partner.  All you need is an iPhone and a VR headset to bring musicians together for performance, practice, or teaching.”  

The JAMS platform has the potential to develop a social network like Spotify or Myspace, where musicians can interact to learn, connect, perform, develop new music, and create virtual concerts that reach larger audiences. 

JAMS has the distinct flavour of a platform developed with and for musicians whether successful or at an early stage of learning.  

The avatars capture the unspoken moments that are key in musical performance, allowing practice partners or performers to watch the tip of the violinist’s bow, or make eye contact at critical points in the piece.  They also have real-time adaptability and are dynamically responsive to the musician on the VR headset, so delivering a unique, personalised experience.

Delivery by VR headset recreates the musician’s world and provides an immersive backdrop with a realistic rendering of other musicians and cues used in the real-life setting.  It also keeps the faces at eye level, which adds to the feeling of connectedness.  

Critically, there is no ‘latency’ in the JAMS user experience.  Dr Di Luca explains: “Latency is the delay between a sound production and when it reaches the listener, and performers can start to feel the effects of latency as low as 10 milliseconds, throwing them ‘off-beat’, breaking their concentration, or distracting them from the technical aspects of playing.”

JAMS is underpinned by an algorithm created during the Augmented Reality Music Ensemble (ARME) project, that captures dynamic timing adjustments between performers.  The project brought together researchers from six disciplines (psychology, computer science, engineering, music, sport science, and maths), whose input realised the vision of building a computational model that reproduces, with precision, a musician’s body movements and delivers an avatar that meets the needs co-performers.

“We’re aiming to bring the magic of playing music in person to the virtual world.  You can adapt the avatar that other people play with, or learn to play better through practice with a maestro.”

JAMS allows musicians to perform in an interactive virtual group, and can be adapted for lipsyncing or dubbing in media.  It can also gather unique user data to create digital twins of musicians, offering licensing opportunities for various applications, and further exploitation of catalogues and publishing rights.  

Commercial enquiries should be directed to the ARME project website at: https://arme-project.co.uk/contact/

 

Big leap forward for environmentally friendly ‘e-textiles’ technology

University of Southampton

 

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UWE PhD student Marzia Dulal testing the e-textile sensing properties.

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Credit: Marzia Dulal

A research team led by the University of Southampton and UWE Bristol  has shown wearable electronic textiles (e-textiles) can be both sustainable and biodegradable.

A new study, which also involved the universities of Exeter, Cambridge, Leeds and Bath, describes and tests a new sustainable approach for fully inkjet-printed, eco-friendly e-textiles named ‘Smart, Wearable, and Eco-friendly Electronic Textiles’, or ‘SWEET’.

Findings are published in the journal Energy and Environmental Materials.

E-textiles are those with embedded electrical components, such as sensors, batteries or lights. They might be used in fashion, for performance sportwear, or for medical purposes as garments that monitor people’s vital signs.

Such textiles need to be durable, safe to wear and comfortable, but also, in an industry which is increasingly concerned with clothing waste, they need to be kind to the environment when no longer required.

Professor Nazmul Karim at the University of Southampton’s Winchester School of Art,  who led the study, explains: “Integrating electrical components into conventional textiles complicates the recycling of the material because it often contains metals, such as silver, that don’t easily biodegrade. Our potential ecofriendly approach for selecting sustainable materials and manufacturing overcomes this, enabling the fabric to decompose when it is disposed of.”

The team’s design has three layers, a sensing layer, a layer to interface with the sensors and a base fabric. It uses a textile called Tencel for the base, which is made from renewable wood and is biodegradable. The active electronics in the design are made from graphene, along with a polymer called PEDOT: PSS. These conductive materials are precision inkjet-printed onto the fabric.

The researchers tested samples of the material for continuous monitoring of human physiology using five volunteers. Swatches of the fabric, connected to monitoring equipment, were attached to gloves worn by the participants. Results confirmed the material can effectively and reliably measure both heart rate and temperature at the industry standard level.

Dr Shaila Afroj, an Associate Professor of Sustainable Materials from the University of Exeter and a co-author of the study, highlighted the importance of this performance: “Achieving reliable, industry-standard monitoring with eco-friendly materials is a significant milestone. It demonstrates that sustainability doesn’t have to come at the cost of functionality, especially in critical applications like healthcare.”

The project team then buried the e-textiles in soil to measure its biodegradable properties. After four months, the fabric had lost 48 percent of its weight and 98 percent of its strength, suggesting relatively rapid and also effective decomposition. Furthermore, a life cycle assessment revealed the graphene-based electrodes had up to 40 times less impact on the environment than standard electrodes.

Marzia Dulal from UWE Bristol, a Commonwealth PhD Scholar and the first author of the study, highlighted the environmental impact: “Our life cycle analysis shows that graphene-based e-textiles have a fraction of the environmental footprint compared to traditional electronics. This makes them a more responsible choice for industries looking to reduce their ecological impact.”

The ink-jet printing process is also a more sustainable approach for e-textile fabrications, depositing exact numbers of functional materials on textiles as needed, with almost no material waste and less use of water and energy than conventional screen printing.

Professor Karim concludes: “ Amid rising pollution from landfill sites, our study helps to address a lack of research in the area of biodegradation of e-textiles. These materials will become increasingly more important in our lives, particularly in the area of healthcare, so it’s really important we consider how to make them more eco-friendly, both in their manufacturing and disposal.”

The researchers hope they can now move forward with designing wearable garments made from SWEET for potential use in the healthcare sector, particularly in the area of early detection and prevention of heart-related diseases that 640 million people (source: BHF) suffer from worldwide.

Ends

Notes to Editors
 

1. The study Sustainable, Wearable, and Eco-Friendly Electronic Textiles is published in the journal Energy and Environmental Materials, DOI: 10.1002/eem2.12854 and can be viewed here: https://onlinelibrary.wiley.com/doi/full/10.1002/eem2.12854
    
2. For interviews contact Peter Franklin, Media Relations, University of Southampton. press@soton.ac.uk +44 23 8059 3212
    
3. Images and a short video relating to the project, for download, can be found here: https://safesend.soton.ac.uk/pickup?claimID=zcENEKmxubFBFHsY&claimPasscode=DHkPdKPHYHSZZNWq&emailAddr=206376
    
4. Partners on this project include, the University of Southampton, UWE Bristol, University of Bath, University of Leeds, University of Exeter and University of Cambridge.
    
5. For more about the University of Southampton’s Winchester School of Art visit: https://www.southampton.ac.uk/about/faculties-schools-departments/winchester-school-of-art
    
6. The University of Southampton drives original thinking, turns knowledge into action and impact, and creates solutions to the world’s challenges. We are among the top 100 institutions globally (QS World University Rankings 2025). Our academics are leaders in their fields, forging links with high-profile international businesses and organisations, and inspiring a 22,000-strong community of exceptional students, from over 135 countries worldwide. Through our high-quality education, the University helps students on a journey of discovery to realise their potential and join our global network of over 200,000 alumni. www.southampton.ac.uk

Material decomposition (IMAGE)

University of Southampton

Different layers of e-textile after four months of decomposition.

E-textile swatches wired for testing

Strip of e-textile demonstrating the flexible qualities of ink-jet printed graphene.

Gloves with swatches of e-textile attached inside and wired for sensing testing.

Credit

Marzia Dulal

Testing swatches of e-textile [VIDEO] 

Demonstrating testing swatches of e-textile material to monitor heart rate.

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Journal

Energy & Environmental Materials

DOI

10.1002/eem2.12854 

Method of Research

Experimental study

Subject of Research

Not applicable

Article Title

Sustainable, Wearable, and Eco-Friendly Electronic Textiles

 

NIH officials assess threat of H5N1

Balancing enhanced vigilance and “business as usual”

NIH/National Institute of Allergy and Infectious Diseases

 

image: 

Photo of a wild bird. To the right is a colorized transmission electron micrograph of H5N1 virus particles (purple). H5N1 bird flu is widespread in wild birds worldwide, and in 2024 is causing a multistate outbreak in poultry and U.S. dairy cows. Bird photo by NIAID; micrograph, which has been repositioned and recolored by NIAID, is courtesy CDC. 

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Credit: NIAID and CDC

WHAT:
Highly pathogenic H5N1 avian influenza A virus (HPAI H5N1) remains a low risk to the general public, and public health experts in the United States believe that available treatments and vaccines, as well as those in development, are sufficient to prevent severe disease. However, the National Institutes of Health (NIH) and its federal partners remain focused on monitoring the virus and evaluating changes, according to leading officials at the National Institute of Allergy and Infectious Diseases (NIAID), part of the NIH. 

In a commentary published in the New England Journal of Medicine, NIAID Director Jeanne M. Marrazzo, M.D., M.P.H., and Michael G. Ison, M.D., M.S., chief of the Respiratory Diseases Branch in NIAID’s Division of Microbiology and Infectious Diseases, say people should find a balance between enhanced vigilance and “business as usual” with respect to HPAI H5N1.

Since 1996, HPAI H5N1 influenza viruses have circulated in at least 23 countries. In late 2021, HPAI H5N1 spread from Europe to North America causing sporadic infections among wild birds and poultry farms. In 2022, the virus spread to South America where it devastated birds and marine mammals. In March 2024, USDA scientists identified HPAI H5N1 in U.S. dairy cows, and it subsequently reached herds in 16 states. The virus has been detected in dairy herds in three states over the past 30 days, according to USDA/APHIS. In 2024, the virus has caused 66 confirmed and 7 probable cases of influenza in people in the U.S. and one case in Canada. These human cases have been caused by either the H5N1 type circulating in birds (D1.1) or the type circulating in dairy cows (B3.13).

Against this backdrop, Drs. Marrazzo and Ison say there are four keys to controlling the current outbreak. The first imperative is timely, effective collaborations among investigators in human and veterinary medicine, public health, health care, and occupational workers, such as dairy and poultry workers.

This involves cultivating trust not only between numerous entities, but with people seeking care for symptoms of concern, including conjunctivitis, the authors write. Fortunately, so far most U.S. cases of HPAI H5N1 have been mild and resolved on their own without the need for treatment.

Their second key is a focus on the Canadian HPAI H5N1 patient, who developed respiratory failure and required life-saving medical intervention and treatment before recovering. The authors write that mutations found in the virus in this patient highlight an urgent need for vigilant disease surveillance to identify and assess viral changes to evaluate the risk for person-to-person transmission. Effective surveillance, they say, requires that complete genomic sequencing data from animals and people are made rapidly and readily available.

Without information pertaining to where and when isolates were collected, the data cannot be linked phylogenetically to other reported sequences, limiting insight into how the virus is spreading, they write. These data would also provide opportunity for early detection of mutations that might portend avidity for human respiratory epithelium, which may require as little as one mutation in the virus.

Third, researchers must continue to develop and test medical countermeasures—such as vaccines and therapies that eliminate or alleviate disease—against H5N1 and other influenza viruses. Fortunately, current vaccine candidates neutralize the circulating strains, which so far are susceptible to antivirals that could mitigate transmission and severity of illness, they write.

Lastly, Drs. Marrazzo and Ison encourage people to take precautions to prevent exposure to the virus and minimize the risk of infection. For example, people who work with poultry and cows should use personal protective equipment and educate themselves about occupational risks when working with birds and mammals, as CDC and USDA have repeatedly recommended.

Ideally, following these four steps will help scientists and public health officials investigating HPAI H5N1 to answer the many remaining questions more quickly about how the virus is spreading, evolving, and affecting people, other mammals, and birds.

ARTICLE:
M Ison and J Marrazzo. The Emerging Threat of H5N1 to Human Health. NEJM DOI: 10.1056/NEJMe2416323 (2024).

WHO:
NIAID Director Jeanne M. Marrazzo, M.D., M.P.H., and Michael G. Ison, M.D., M.S., chief of the Respiratory Diseases Branch in NIAID’s Division of Microbiology and Infectious Diseases, are available for comment. 

CONTACT:
To schedule interviews, please contact Ken Pekoc, (301) 402-1663, kpekoc@niaid.nih.gov.

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NIAID conducts and supports research—at NIH, throughout the United States, and worldwide—to study the causes of infectious and immune-mediated diseases, and to develop better means of preventing, diagnosing and treating these illnesses. News releases, fact sheets and other NIAID-related materials are available on the NIAID website.
  
About the National Institutes of Health (NIH): NIH, the nation's medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. NIH is the primary federal agency conducting and supporting basic, clinical, and translational medical research, and is investigating the causes, treatments, and cures for both common and rare diseases. For more information about NIH and its programs, visit http://www.nih.gov/.

NIH...Turning Discovery Into Health®

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Journal

New England Journal of Medicine

DOI

10.1056/NEJMe2416323 

Article Title

The Emerging Threat of H5N1 to Human Health

Article Publication Date

31-Dec-2024

 

Study finds physical activity reduces chronic disease risk

Researchers recommend health care providers survey patients on physical activity levels

University of Iowa

 

image: 

Lucas Carr, University of Iowa

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Credit: University of Iowa

University of Iowa researchers are recommending all patients be surveyed about their physical activity levels, after a new study underscores the link between physical activity and chronic disease.

The study, led by Lucas Carr, associate professor in the Department of Health and Human Physiology, examined responses from more than 7,000 patients at University of Iowa Health Care Medical Center who noted their level of physical activity in a questionnaire. 

From patients’ answers to the questionnaire, the researchers found that those who reported the highest level of physical activity — meaning they exercised moderately to vigorously at least 150 minutes per week — were at statistically significant lower risk of having 19 chronic conditions, including cardiovascular disease, cancer, respiratory disease, and diabetes.

The findings further suggest patients who are least active — meaning they reported little to no exercise in a given week — are at increased risk to develop a chronic disease.

Based on those results, the Iowa researchers also recommend health care systems provide information on health and wellness services for physically inactive patients who are at most risk.

“In our health care environment, there's no easy pathway for a doctor to be reimbursed for helping patients become more physically active,” says Carr, the study’s corresponding author. “And so, for these patients, many of whom report insufficient activity, we need options to easily connect them with supportive services like exercise prescriptions and/or community health specialists.”

Most hospitals in the United States do not ask patients about their physical activity, and no hospital system in the Midwest has done so, according to the researchers. In this study, Carr partnered with Britt Marcussen, a family medicine physician in UI Health Care, to offer the questionnaire to patients visiting for annual wellness exam appointments. The study period was from November 2017 to December 2022.

The Exercise Vital Sign survey, as the questionnaire is called, asked patients two questions that they answered on a tablet:

• “On average, how many days per week do you engage in moderate to vigorous exercise (like a brisk walk)?” (0-7 days) 
• “On average, how many minutes do you engage in exercise at this level?” 

Carr and his team propose making the survey available to all patients.

“This two-question survey typically takes fewer than 30 seconds for a patient to complete, so it doesn’t interfere with their visit. But it can tell us a whole lot about that patient’s overall health,” Carr says.

The researchers also compared results from patients who completed the surveys with more than 33,000 patients who weren’t offered the survey in other areas of the hospital. The researchers found patients who took the survey were younger and in better health than the patient population who weren’t given the questionnaire, based on analyzing all patients’ electronic medical records. 

While the link between physical activity and reduced risk of chronic disease has been known, the researchers say the study underscores the value of surveying patients about their physical activity levels.

“We believe this finding is a result of those patients who take the time to come in for annual wellness exams also are taking more time to engage in healthy behaviors, such as being physically active,” Carr says.

In a related study, published this month in the Journal of Physical Activity and Health, Carr’s team found that when healthcare providers billed for providing exercise counseling to patients, those invoices were reimbursed by insurance providers nearly 95 percent of the time. 

“Our findings suggest the recommended physical activity billing codes are reimbursed at a high rate when providers submit them for reimbursement, which reinforces the idea to make physical activity surveys and counseling services available,” Carr says.

Cole Chapman, assistant professor in the College of Pharmacy, is the first author on the study. Chapman, who joined the Pharmacy faculty in 2019 after earning bachelor’s and doctoral degrees at Iowa, collected and analyzed the data from the patients’ electronic medical records. 

Marcussen and Mary Schroeder, associate professor in the Department of Pharmacy Practice and Science in the College of Pharmacy, are study co-authors.

The study, “Screening Patients for Physical Inactivity Helps Identify Patients at Risk for Cardiometabolic and Chronic Diseases,” was published online [INSERT ONLINE PUB DATE HERE] in Preventing Chronic Disease, a journal of the U.S. Centers for Disease Control and Prevention.

UI Health Care Stead Family Children’s Hospital funded the research.

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Journal

Preventing Chronic Disease

Method of Research

Data/statistical analysis

Subject of Research

People

Article Title

Screening Patients for Physical Inactivity Helps Identify Patients at Risk for Cardiometabolic and Chronic Diseases

 

Unraveling climate change-induced compound low-solar-low-wind extremes in China

Science China Press

 

image: 

In the top-left panel, the spatial distribution of compound LSLW extremes is shown, with frequency indicated by color and intensity by shading for the historical period (1961-1990). The top-right panel presents the schematic diagram of physical processes for interdiurnal correlation. East Asia is mainly influenced by two weather systems, namely the western Pacific subtropical high (WPSH) and the Mongolian-Siberian high (MSH). In low latitudes, the westward extension of WPSH induces suppressed activity in situ, resulting in predominantly clear and calm conditions. Meanwhile, prevailing southerly winds in the west flank of the WPSH transport moisture from the tropics to East Asia, leading to cloudy (low solar) and windy (high wind) conditions. In mid-high latitudes, cold front invades East Asia under the northerly wind of MSH accompanied cloudy (low solar) and windy (high wind) weather conditions. While in mountainous regions, such as Qinghai-Tibet Plateau and Hengduan Shan, local obstructive effects lead to decreasing wind speed (low wind) and uplift topography with decreasing temperature leads to cloudy conditions (low solar). The bottom-left panel shows the spatial distribution of interdiurnal correlation between wind and solar resource. The bottom-right panel displays the likelihood multiplication factor of our estimated co-occurrences of compound LSLW extremes relative to the counterfactual cases assuming low-solar and low-wind events are independent.

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Credit: ©Science China Press

This study, led by Dr. Yue Qin and Dr. Tong Zhu from the College of Environmental Sciences and Engineering at Peking University, represents one of the first comprehensive efforts to analyze the spatiotemporal patterns and drivers of compound low-solar-low-wind (LSLW) extremes across China. By coupling multi-model climate simulations with state-of-the-art statistical and diagnostic analyses, the research provides crucial insights into this emerging challenge.

“Our results suggest that under compound LSLW extremes, renewable energy generation could be significantly compromised,” said Dr. Yue Qin, one of the corresponding authors. “Even more concerning, climate change could intensify the frequency of such events, escalating threats to China’s renewable energy supply and potentially hindering progress toward carbon neutrality.”

China has pledged to achieve carbon neutrality by 2060, necessitating a profound transition toward solar and wind energy. Unlike fossil fuels, solar and wind power depend heavily on fluctuating meteorological conditions, making them inherently variable and intermittent, which poses significant risks to the stability of electricity supply.

While individual renewable energy resources have been widely studied, much less is known about the compounded challenges posed by simultaneous low solar and wind energy availability. Despite increasing recognition of compound events—such as drought-heatwave or wind-precipitation extremes—and their impacts, the vulnerability of renewable energy systems to these compound events remains understudied, particularly in China, a global leader in wind and solar energy investments.

The study highlights a strong topographic dependence in the frequency of compound LSLW extremes, with a national average frequency of 16.4 days per year (10th-90th percentile range: 5.3–32.6 days per year). Renewable energy supply in eastern China is particularly affected, with power output during these extremes dropping by ~80% compared to average climate conditions. The researchers also projected changes in compound LSLW extremes under future climate scenarios. They found that the frequency of such events increases nationwide across all scenarios, with the Tibetan Plateau and northwestern China facing high LSLW frequency and projected to experience significant frequency increases.

“In particular, a striking increase of compound LSLW extremes’ frequency occurs under SSP370 scenario with aerosol emissions increase due to the assumption of a lenient air quality policy.” said Licheng Wang, the lead author from Peking University. “It is noteworthy that the distinct increase in aerosol loading under SSP370 scenario, likely plays an important role in driving the most striking increases in compound LSLW extremes’ frequency observed nationwide. The high aerosol loading weakens wind speed by inducing a more stable boundary layer and attenuates radiation by absorbing and scattering incoming solar radiation.”

The researchers also test the inter-grid electricity transmission as an adaptation strategy, and find that it can significantly reduce the potential impacts caused by both the frequency (by over 91%), and the intensity of compound extremes indicating the extent of LSLW power output failures (by 59%-85%) of compound LSLW extremes. Notably, Xizang often demonstrates the largest potential in mitigating LSLW-induced renewable power shortages for other regions via grid interconnection. However, current interregional electricity transmission infrastructure is largely insufficient in Xizang, due to both geographical and economic challenges in developing (ultra-) high-voltage electricity transmission. Therefore, advancing renewable energy infrastructure project in Xizang could potentially play an important role in supporting China’s carbon neutrality targets.

Without a robust understanding of China’s compound LSLW extremes, renewable energy investment and power sector planning could be inadequately informed, jeopardizing China’s pursuit of carbon neutrality—a critical component of global carbon mitigation efforts.

“By revealing the geospatial and temporal evolution of compound LSLW extremes and their underlying physical mechanisms under climate change, our study emphasizes that these events are not random but predictable,” added Dr. Yue Qin. “This underscores the importance of proactive preparation and mitigation to address this pressing challenge.”

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See the article:

Unraveling climate change-induced compound low-solar-low-wind extremes in China

https://doi.org/10.1093/nsr/nwae424

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Journal

National Science Review

DOI

10.1093/nsr/nwae424