Science
New Drug Turns Human Blood Into Mosquito-Killing Weapon
An Anopheles gambiae mosquito that has been fed dye to make her glow. Credit: Provided by Lee R. Haines Nitisinone, a drug for rare diseases, kills mosquitoes when present in human blood and may become a new tool to fight malaria, offering longer-lasting, environmentally safer effects than ivermectin. Controlling mosquito populations is a key strategy in the fight against malaria. Currently, several approaches are used to reduce mosquito numbers and limit malaria transmission. One method involves the use of the antiparasitic drug ivermectin. When mosquitoes feed on blood containing ivermectin, their lifespan is shortened, which can reduce the spread of the malaria parasite. However, ivermectin presents challenges. It is toxic to the environment, and its widespread use in both humans and animals to treat parasitic infections raises the risk of drug resistance. Now, a study published in Science Translational Medicine has identified a promising alternative. Researchers discovered that when people take the medication nitisinone, their blood becomes lethal to mosquitoes, offering a potential new tool for mosquito control and malaria prevention. How Nitisinone Works “One way to stop the spread of diseases transmitted by insects is to make the blood of animals and humans toxic to these blood-feeding insects,” said Lee R. Haines, associate research professor of biological sciences at the University of Notre Dame, honorary fellow at the Liverpool School of Tropical Medicine and co-lead author of the study. “Our findings suggest that using nitisinone could be a promising new complementary tool for controlling insect-borne diseases like malaria.” Typically, nitisinone is a medication for individuals with rare inherited diseases — such as alkaptonuria and tyrosinemia type 1 — whose bodies struggle to metabolize the amino acid tyrosine. The medication works by blocking the enzyme 4-hydroxyphenylpyruvate dioxygenase (HPPD), preventing the build-up of harmful disease byproducts in the human body. When mosquitoes drink blood that contains nitisinone, the drug also blocks this crucial HPPD enzyme in their bodies. This prevents the mosquitoes from properly digesting the blood, causing them to quickly die. The researchers analyzed the nitisinone dosing concentrations needed for killing mosquitoes, and how those results would stack up against ivermectin, the gold standard ectoparasitic drug (medication that specifically targets ectoparasites such as mosquitoes). “We thought that if we wanted to go down this route, nitisinone had to perform better than ivermectin,” said Álvaro Acosta Serrano, professor of biological sciences at Notre Dame and co-corresponding author of the study. “Indeed, nitisinone performance was fantastic; it has a much longer half-life in human blood than ivermectin, which means its mosquitocidal activity remains circulating in the human body for much longer. This is critical when applied in the field for safety and economical reasons.” Testing Nitisinone in Humans The research team tested the mosquitocidal effect of nitisinone on female Anopheles gambiae mosquitoes, the primary mosquito species responsible for spreading malaria in many African countries. If these mosquitoes become infected with malaria parasites, they spread the disease when they feast on a human. To evaluate how the drug affected the mosquitoes when fed fresh human blood containing nitisinone, researchers collaborated with the Robert Gregory National Alkaptonuria Centre at the Royal Liverpool University Hospital. The center was performing nitisinone trials with people diagnosed with alkaptonuria, who then donated their blood for the study. Those taking nitisinone were found to have blood that was deadly to mosquitoes, which Haines describes as having a “hidden superpower.” The research team collected data on how the drug was metabolized in peoples’ blood, allowing the team to fine-tune their modeling and provide pharmacological validation of nitisinone as a potential mosquito population control strategy. Nitisinone was shown to last longer than ivermectin in the human bloodstream, and was able to kill not only mosquitoes of all ages — including the older ones that are most likely to transmit malaria — but also the hardy mosquitoes resistant to traditional insecticides. “In the future, it could be advantageous to alternate both nitisinone and ivermectin for mosquito control,” Haines said. “For example, nitisinone could be employed in areas where ivermectin resistance persists or where ivermectin is already heavily used for livestock and humans.” Next Steps and Broader Impacts Next, the research team aims to explore a semi-field trial to determine what nitisinone dosages are best linked to mosquitocidal efficacy in the field. “Nitisinone is a versatile compound that can also be used as an insecticide. What’s particularly interesting is that it specifically targets blood-sucking insects, making it an environmentally friendly option,” Acosta Serrano said. As an unintended benefit, extending the use of nitisinone as a vector control tool could consequently increase drug production and decrease the price of the medication for patients suffering from rare genetic diseases in the tyrosine metabolism pathway. Reference: “Anopheles mosquito survival and pharmacokinetic modeling show the mosquitocidal activity of nitisinone” by Lee R. Haines, Anna Trett, Clair Rose, Natalia García, Marcos Sterkel, Dagmara McGuinness, Clément Regnault, Michael P. Barrett, Didier Leroy, Jeremy N. Burrows, Giancarlo Biagini, Lakshminarayan R. Ranganath, Ghaith Aljayyoussi and Álvaro Acosta-Serrano, 26 March 2025, Science Translational Medicine.DOI: 10.1126/scitranslmed.adr4827 The study was funded by the UK Medical Research Council, Biotechnology and Biological Sciences Research Council, Wellcome Trust Institutional Strategic Support Fund, the Medical Research Council Doctoral Training Partnership and the University of Glasgow Wellcome Centre for Integrative Parasitology.
Stanford Scientists Crack 252-Million-Year-Old Biodiversity Mystery
About 252 million years ago, the end-Permian mass extinction wiped out up to 80% of marine species, leading to a period where marine communities worldwide became unusually similar. Researchers from Stanford created a climate-based model showing that environmental changes, such as warming and deoxygenation, allowed a few hardy species to flourish and spread globally, a finding that could also help explain today’s biodiversity crisis. Stanford scientists found that dramatic climate changes after the Great Dying enabled a few marine species to spread globally, leading to worldwide biological sameness. Scientists don’t call it the “Great Dying” for nothing. Around 252 million years ago, more than 80% of all marine species disappeared during the end-Permian mass extinction—the most extreme event of its kind in Earth’s history. What followed was a mysterious, multimillion-year period that could be called the “Great Dulling,” when marine animal communities looked strikingly similar across the globe, from the equator to the poles. Researchers have long searched for an explanation for this so-called taxonomic homogenization, a pattern that has also emerged after other mass extinctions over the past half-billion years. Now, a team of Stanford scientists has identified a likely explanation. Their research shows that widespread environmental upheaval after the extinction created conditions that allowed a few resilient species to greatly expand their geographic ranges. By analyzing the marine fossil record, the most complete archive of life after the extinction, they developed a model to understand how species such as clams, oysters, snails, and slugs thrived in the planet’s newly warm, low-oxygen seas. Published March 26 in Science Advances, the study sheds new light on how life recovered after Earth’s worst extinction, and offers critical insights into the present-day biodiversity crisis driven by human impact. “For us in the paleobiology field, this model is the equivalent to climate scientists getting computerized climate models to make quantitative predictions of how the world should change based on some simple mathematical representations,” said senior study author Jonathan Payne, the Dorrell William Kirby Professor of Earth and Planetary Sciences in the Stanford Doerr School of Sustainability. “We are now able to study big biogeographic changes of mass extinctions in a new way and get a better sense of why some animal groups made it through while others perished.” Reconstructing the past In addition to the fossil record, scientists understand ancient oceans based on naturally occurring chemical markers that reveal past temperatures and environmental conditions. Toward the end of the Permian period, the planet was reeling from cataclysmic volcanic activity in modern-day Siberia, which ushered in intense global warming, oxygen depletion, and ocean acidification that killed most marine organisms 252 million years ago. But the extinction alone doesn’t explain the bizarre presence of its surviving species – previously constrained to certain specific locations – in every ocean across the globe in the millions of years that followed, known as the earliest Triassic geological period. To convey the surreal concept of taxonomic homogenization on a planetary scale, lead study author Jood Al Aswad, a PhD candidate in Earth and planetary sciences, offered a modern analogy with land animals: “If someone asked you today where you’d find kangaroos, you’d say Australia,” she says. “But now imagine some major disaster happened, like a giant volcano erupted, and afterward you’re finding kangaroos in great numbers all over the globe – they’re all the way out in Antarctica, they’re hopping by the pyramids in Egypt, and they’re even in Stanford, California.” Fossils before and after the end-Permian extinction “go from richly diverse communities to almost boringly alike communities, wherever you look,” Payne said. According to the research, the variety of species across different parts of the world was reduced by more than half after the extinction event. Setting up shop all over Researchers have debated the cause of these stark fossil record differences for nearly 200 years and, in recent decades, proposed multiple mechanisms for why different locations had remarkably similar inhabitants following the end-Permian extinction. One hypothesis is “ecological release,” where the die-offs of certain predator and competitor creatures allow one surviving group of organisms to go gangbusters. Another common theory is that the climate changes in ways that produce a favorable environment for the same few organism groups just about everywhere. The study authors put these hypotheses to the test, using geochemical data that provides information about ancient ocean oxygen levels and temperature conditions to build a climate model for end-Permian environmental change in the oceans. They then applied data from physiological experiments on living marine invertebrate animals such as clams and snails that are related to the survivors and victims of the Great Dying to populate a climate model with simulated species. These virtual species were able to respond to environmental changes of the end-Permian era based on their ability to survive alterations in temperature and oxygen availability. In this way, the model provided a “physiology-only” evaluation of how species’ geographical distribution would be expected to change if oxygen and temperature were the main drivers of where species could go. The results show that the hardy clique of mollusks monopolizing the marine fossil record in the Great Dying’s aftermath were indeed well suited for the conditions of the changed world. As a result, the model did not even have to consider ecosystem-level factors such as loss of predators and competitors, which might have also played a secondary role. “Our study has provided a simple environmental explanation, rather than an ecological one, for why certain survivors of the end-Permian extinction prospered and why homogenization happened on a global scale,” Payne said. Views into the future In addition to illuminating the deep past, the new model can also help scientists and policymakers predict and better understand the presently unfolding biodiversity crisis, an impending mass extinction caused by the planet-altering activities of billions of humans. “The current biodiversity crisis is anticipated to herald changes in ecosystem composition that surpass even those seen in the earliest Triassic, which has been the greatest homogenization event to date,” the study authors wrote. Al Aswad, Payne, and colleagues are now extending their model to examine other past mass extinctions, such as the end-Cretaceous event that famously wiped out the non-avian dinosaurs. “Our model offers a great way of studying how animals respond to extreme changes in the environment,” Al Aswad said. “With anthropogenically spurred climate change, there has been some warning that if we continue, then in the future, we’re going to see taxonomic homogenization of organisms in modern oceans as well.” Reference: “Physiology and climate change explain unusually high similarity across marine communities after end-Permian mass extinction” by Jood A. Al Aswad, Justin L. Penn, Pedro M. Monarrez, Mohamad Bazzi, Curtis Deutsch and Jonathan L. Payne, 26 March 2025, Science Advances.DOI: 10.1126/sciadv.adr4199 Other Stanford co-authors of the study are Pedro Monarrez (previously a postdoctoral fellow at Stanford and now an assistant professor at Virginia Tech) and Mohamad Bazzi, a current postdoctoral scholar in Payne’s lab. Justin Penn and Curtis Deutsch from Princeton University are also co-authors. The research was supported by funding from the National Science Foundation.
Webb Telescope Detects “Impossible” Light From the Dawn of Time
The incredibly distant galaxy JADES-GS-z13-1, observed just 330 million years after the Big Bang, was initially discovered with deep imaging from NASA’s James Webb Space Telescope’s NIRCam (Near-Infrared Camera). Now, an international team of astronomers definitively has identified powerful hydrogen emission from this galaxy at an unexpectedly early period in the universe’s history. JADES-GS-z-13 has a redshift (z) of 13, which is an indication of its age and distance. Credit: NASA, ESA, CSA, Brant Robertson (UC Santa Cruz), Ben Johnson (CfA), Sandro Tacchella (Cambridge), Phill Cargile (CfA), Joris Witstok (Cambridge, University of Copenhagen), P. Jakobsen (University of Copenhagen), Alyssa Pagan (STScI), Mahdi Zamani (ESA/Webb), JADES Collaboration Unexpected, Bright Hydrogen Emission Caught Astronomers by Surprise In the early universe, space was filled with a dense fog of neutral hydrogen gas. Although the first stars and galaxies gave off powerful ultraviolet light, much of that light was trapped by the surrounding hydrogen. It wasn’t until hundreds of millions of years later that this fog gradually cleared, when the hydrogen atoms became ionized, freeing light to travel across the cosmos. Astronomers call this pivotal period the era of reionization, and they’re still working to understand how and when it unfolded. Now, a newly discovered galaxy is offering a surprising clue. Known as JADES-GS-z13-1, it existed just 330 million years after the Big Bang and is emitting bright hydrogen radiation. This type of light, known as Lyman-alpha emission, should have been blocked by the thick hydrogen fog still present at that time. The fact that it’s visible is puzzling scientists, who are now rethinking how quickly the universe may have cleared. This image shows the galaxy JADES GS-z13-1 (the red dot at center), imaged with NASA’s James Webb Space Telescope’s NIRCam (Near-Infrared Camera) as part of the JWST Advanced Deep Extragalactic Survey (JADES) program. These data from NIRCam allowed researchers to identify GS-z13-1 as an incredibly distant galaxy, and to put an estimate on its redshift value. Webb’s unique infrared sensitivity is necessary to observe galaxies at this extreme distance, whose light has been shifted into infrared wavelengths during its long journey across the cosmos. Credit: NASA, ESA, CSA, Brant Robertson (UC Santa Cruz), Ben Johnson (CfA), Sandro Tacchella (Cambridge), Phill Cargile (CfA), Joris Witstok (Cambridge, University of Copenhagen), P. Jakobsen (University of Copenhagen), Alyssa Pagan (STScI), Mahdi Zamani (ESA/Webb), JADES Collaboration Webb Space Telescope Sees Galaxy Mysteriously Clearing Fog of Early Universe Thanks to the powerful infrared capabilities of NASA’s James Webb Space Telescope, scientists are able to study some of the earliest galaxies in the universe. In a surprising discovery, an international team of astronomers has detected bright hydrogen emission from a galaxy that existed much earlier than expected. The finding is raising new questions about how light could have escaped the dense fog of neutral hydrogen that filled the early universe. Discovery of a Distant Galaxy: JADES-GS-z13-1 The galaxy, named JADES-GS-z13-1, was spotted in images captured by Webb’s Near-Infrared Camera (NIRCam) as part of the James Webb Space Telescope Advanced Deep Extragalactic Survey (JADES). It appears to have existed just 330 million years after the Big Bang. Researchers initially estimated its distance, based on how much the galaxy’s light had been stretched by the expansion of space,using its brightness in various infrared filters. The NIRCam data suggested a redshift of 12.9. To confirm this extreme distance, a team led by Joris Witstok of the University of Cambridge, along with colleagues from the Cosmic Dawn Center and the University of Copenhagen, used Webb’s Near-Infrared Spectrograph (NIRSpec) to study the galaxy in more detail. NASA’s James Webb Space Telescope has detected unexpected light from a distant galaxy. The galaxy JADES-GS-z13-1, observed just 330 million years after the Big Bang (corresponding to a redshift of z=13.05), shows bright emission from hydrogen known as Lyman-alpha emission. This is surprising because that emission should have been absorbed by a dense fog of neutral hydrogen that suffused the early universe. In this graphic, the solid blue line shows the cleaned, averaged spectrum while the faint blue shows the error bars. Credit: NASA, ESA, CSA, S. Carniani (Scuola Normale Superiore), P. Jakobsen (University of Copenhagen), Joseph Olmsted (STScI) Unexpected Hydrogen Emission Stuns Astronomers In the resulting spectrum, the redshift was confirmed to be 13.0. This equates to a galaxy seen just 330 million years after the Big Bang, a small fraction of the universe’s present age of 13.8 billion years old. But an unexpected feature stood out as well: one specific, distinctly bright wavelength of light, known as Lyman-alpha emission radiated by hydrogen atoms. This emission was far stronger than astronomers thought possible at this early stage in the universe’s development. “The early universe was bathed in a thick fog of neutral hydrogen,” explained Roberto Maiolino, a team member from the University of Cambridge and University College London. “Most of this haze was lifted in a process called reionization, which was completed about one billion years after the Big Bang. GS-z13-1 is seen when the universe was only 330 million years old, yet it shows a surprisingly clear, telltale signature of Lyman-alpha emission that can only be seen once the surrounding fog has fully lifted. This result was totally unexpected by theories of early galaxy formation and has caught astronomers by surprise.” More than 13 billion years ago, during the Era of Reionization, the universe was a very different place. The gas between galaxies was largely opaque to energetic light, making it difficult to observe young galaxies. What allowed the universe to become completely ionized, or transparent, eventually leading to the “clear” conditions detected in much of the universe today? The James Webb Space Telescope will peer deep into space to gather more information about objects that existed during the Era of Reionization to help us understand this major transition in the history of the universe. Credit: NASA, ESA, Joyce Kang (STScI) Light Escaping Against the Odds Before and during the era of reionization, the immense amounts of neutral hydrogen fog surrounding galaxies blocked any energetic ultraviolet light they emitted, much like the filtering effect of colored glass. Until enough stars had formed and were able to ionize the hydrogen gas, no such light — including Lyman-alpha emission — could escape from these fledgling galaxies to reach Earth. The confirmation of Lyman-alpha radiation from this galaxy, therefore, has great implications for our understanding of the early universe. Rethinking Cosmic Evolution “We really shouldn’t have found a galaxy like this, given our understanding of the way the universe has evolved,” said Kevin Hainline, a team member from the University of Arizona. “We could think of the early universe as shrouded with a thick fog that would make it exceedingly difficult to find even powerful lighthouses peeking through, yet here we see the beam of light from this galaxy piercing the veil. This fascinating emission line has huge ramifications for how and when the universe reionized.” Possible Origins of the Light Signal The source of the Lyman-alpha radiation from this galaxy is not yet known, but may include the first light from the earliest generation of stars to form in the universe. “The large bubble of ionized hydrogen surrounding this galaxy might have been created by a peculiar population of stars — much more massive, hotter and more luminous than stars formed at later epochs, and possibly representative of the first generation of stars,” said Witstok. A powerful active galactic nucleus, driven by one of the first supermassive black holes, is another possibility identified by the team. This research was published on March 26 in the journal Nature. Reference: “Witnessing the onset of reionization through Lyman-α emission at redshift 13” by Joris Witstok, Peter Jakobsen, Roberto Maiolino, Jakob M. Helton, Benjamin D. Johnson, Brant E. Robertson, Sandro Tacchella, Alex J. Cameron, Renske Smit, Andrew J. Bunker, Aayush Saxena, Fengwu Sun, Stacey Alberts, Santiago Arribas, William M. Baker, Rachana Bhatawdekar, Kristan Boyett, Phillip A. Cargile, Stefano Carniani, Stéphane Charlot, Jacopo Chevallard, Mirko Curti, Emma Curtis-Lake, Francesco D’Eugenio, Daniel J. Eisenstein, Kevin N. Hainline, Gareth C. Jones, Nimisha Kumari, Michael V. Maseda, Pablo G. Pérez-González, Pierluigi Rinaldi, Jan Scholtz, Hannah Übler, Christina C. Williams, Christopher N. A. Willmer, Chris Willott and Yongda Zhu, 26 March 2025, Nature.DOI: 10.1038/s41586-025-08779-5 The James Webb Space Telescope is the world’s leading space science observatory, designed to explore the universe in unprecedented detail. Launched through an international collaboration between NASA, the European Space Agency (ESA), and the Canadian Space Agency (CSA), Webb is uncovering new insights across a wide range of cosmic frontiers. From investigating planets in our solar system to studying distant exoplanets, and from exploring the earliest galaxies to probing the structure and origins of the universe itself, Webb is transforming our understanding of the cosmos and our place within it.
Scientists Can Now See the Inner Ear in Stunning Detail Without Cutting
Researchers developed a new terahertz imaging method that was able to visualize internal details of the mouse cochlea with micron-level spatial resolution. An excised mouse cochlea is pictured. Credit: Kazunori Serita, Waseda University Scientists have made a major leap in ear imaging by using terahertz radiation to see inside the cochlea – an impossibly tiny, spiral-shaped organ crucial for hearing – without damaging it. This breakthrough could one day allow doctors to detect hearing problems and inner ear diseases with non-invasive tools, something current imaging tech can’t do. The team created a microscopic terahertz light source that penetrates bone and tissue, giving a 3D view of cochlear structures in unprecedented detail. They’ve already tested it on mouse samples, and with further development, it could be used through the ear canal to catch hearing loss early and even detect cancers. Breakthrough in Cochlear Imaging with Terahertz Technology For the first time, scientists have demonstrated that terahertz imaging can reveal the internal structure of the mouse cochlea with micron-level precision. This non-invasive approach could lead to new ways of diagnosing hearing loss and other conditions affecting the inner ear. “Hearing relies on the cochlea, a spiral-shaped organ in the inner ear that converts sound waves into neural signals,” said research team leader Kazunori Serita from Waseda University in Japan. “Although conventional imaging methods often struggle to visualize this organ’s fine details, our 3D terahertz near-field imaging technique allows us to see small structures inside the cochlea without any damage.” The images acquired using 3D terahertz near-field imaging were used to create 3D reconstructions, allowing visualization of part of the cochlear duct, the spiral structure inside the cochlea. Credit: Kazunori Serita, Waseda University Why Terahertz Waves Are Perfect for Biology Terahertz radiation lies between microwaves and mid-infrared light on the electromagnetic spectrum. It’s especially suited for biological imaging because it’s low-energy, non-damaging to tissue, scatters less than visible or near-infrared light, and can penetrate bone. It’s also sensitive to subtle changes in hydration and cell structure. In a study published today (March 27) in Optica, the journal of the Optica Publishing Group, a team of researchers from multiple institutions describes how their imaging technique captures high-resolution data that can be used to create detailed 3D reconstructions of the inner ear. “With further development, this technique could lead to a new diagnostic method for ear diseases that have been difficult to diagnose until now,” said Serita. “It has the potential to enable on-site diagnosis of conditions like sensorineural hearing loss and other ear disorders. It might also be useful for early detection of hearing impairments, allowing earlier treatment and better outcomes.” [embedded content] The images acquired using 3D terahertz near-field imaging were used to create 3D reconstructions, allowing visualization of part of the cochlear duct, the spiral structure inside the cochlea. Credit: Kazunori Serita, Waseda University Inspired by Medical Challenges Serita was inspired to develop the technique after learning about cochlear measurement challenges from coauthor Takeshi Fujita from the Department of Otolaryngology-Head and Neck Surgery at Kobe University. “That got me thinking — maybe terahertz imaging could help solve these issues,” said Serita. “We decided to collaborate and explore this idea together. The big question was whether we could visualize the tiny internal structures of the cochlea without causing any damage.” Terahertz imaging is typically performed by focusing terahertz waves using a lens made for these wavelengths. However, these lenses are typically limited to focal sizes measuring a few millimeters — too large to image the tiny structures of the cochlea. In the new work, the researchers eliminated the need for a focal lens by using a nonlinear optical crystal to create terahertz light emitting from a very small region within the crystal. Because this terahertz point source had a beam diameter of just 20 microns, the researchers could measure much smaller samples with terahertz waves. “Until now, there was no way to observe the internal structure of the cochlea non-destructively with high resolution,” said Serita. “A key innovation in our work was the use of a nonlinear optical crystal to generate terahertz waves from 1560-nm near-infrared light. This was crucial for our imaging technique.” [embedded content]The non-invasive method could eventually enable new ways of diagnosing hearing loss and other ear-related conditions. The video shows a 3D terahertz imaging scan. Credit: Kazunori Serita, Waseda University Confirming Terahertz Penetration and Precision To test their new approach, the researchers first needed to confirm that the terahertz waves were reaching the inside of the cochlea. They did this by using the terahertz imaging setup to conduct experiments using two different extracted and dried mouse cochlear samples — one with an empty interior and another filled with a metal material that reflects terahertz waves. They observed clear differences between the two samples, confirming that the terahertz waves were penetrating the inside of the cochlea. The researchers then showed that internal structural information could be easily observed and extracted from 2D terahertz time-domain images using an unsupervised learning algorithm. The team also used the setup to successfully carry out 3D terahertz time-of-flight imaging and 3D reconstruction, allowing visualization of part of the cochlear duct, the spiral structure inside the cochlea. Toward Real-World Use: Miniaturizing the System Next, the researchers plan to demonstrate the technique’s feasibility on cochleae in a more realistic biological environment. Since the cochlea is located deep inside the ear and filled with lymphatic fluid, they will first need to miniaturize the system so it can be inserted through the ear canal. They are also developing a stronger terahertz source to reach deeper structures. The researchers say that once the terahertz imaging technology is miniaturized, it could be incorporated into endoscopes and otoscopes, enabling non-invasive in vivo imaging for cochlear diagnostics and early cancer detection in various organs. Reference: “Three-dimensional terahertz near-field imaging evaluation of cochlea” by L. Zheng, H. Chen, T. Fujita, A. Kakigi, N. Allen, H. Murakami, M. Tonouchi, K. Serita, 27 March 2025, Optica.DOI: 10.1364/OPTICA.543436
New AI Sees Gluten Damage Doctors Often Miss – And Diagnoses Celiac in Seconds
Microscopic image showing healthy villi. Credit: Florian Jaeckle/University of Cambridge Cambridge scientists have developed a powerful AI tool that can diagnose celiac disease from biopsy images with over 97% accuracy. Trained on thousands of samples from diverse sources, the algorithm offers a faster, more reliable way to identify the condition, which is especially important given how often symptoms are missed or misdiagnosed. Researchers say this could ease pressure on healthcare systems and help underserved regions. AI Achieves 97% Accuracy in Diagnosing Celiac Disease A machine learning algorithm developed by scientists at the University of Cambridge has been shown to accurately detect coeliac disease in 97 out of 100 cases, based on biopsy samples. Trained on nearly 3,400 scanned biopsies from four NHS hospitals, the AI tool could help speed up diagnosis and reduce the burden on overstretched healthcare systems. It also holds promise for improving access to diagnosis in low-resource settings, where there is a severe shortage of trained pathologists. Digital tools like this one are starting to show real potential in assisting or even automating the analysis of diagnostic tests. While much of the focus so far has been on cancer detection, researchers are now exploring how AI can help diagnose a wider range of diseases. One of those conditions is celiac disease, an autoimmune disorder triggered by eating gluten. Symptoms can vary widely from person to person and may include stomach pain, diarrhea, skin rashes, weight loss, fatigue, and anemia. Because of this variation, getting an accurate diagnosis can be challenging and often takes years. Microscopic image showing diseased villi. Credit: Florian Jaeckle/University of Cambridge Challenges in Identifying Celiac Disease The gold standard for diagnosing celiac disease is via a biopsy of the duodenum (part of the small intestine). Pathologists will then analyze the sample under a microscope or on a computer to look for damage to the villi, tiny hair-like projections that line the inside of the small intestine. Interpreting biopsies, which often have subtle changes, can be subjective. Pathologists use a classification system known as the Marsh-Oberhuber scale to judge the severity of a case, ranging from zero (the villi are normal and the patient is unlikely to have the disease) to four (the villi are completely flattened). Training the AI on Diverse Biopsy Data In research published today (March 27) in the New England Journal of Medicine AI, Cambridge researchers developed a machine learning algorithm to classify biopsy image data. The algorithm was trained and tested on a large-scale, diverse dataset consisting of over 4,000 images obtained from five different hospitals using five different scanners from four different companies. Senior author Professor Elizabeth Soilleux from the Department of Pathology and Churchill College, University of Cambridge, said: “Celiac disease affects as many as one in 100 people and can cause serious illness, but getting a diagnosis is not straightforward. It can take many years to receive an accurate diagnosis, and at a time of intense pressures on healthcare systems, these delays are likely to continue. AI has the potential to speed up this process, allowing patients to receive a diagnosis faster, while at the same time taking pressure off NHS waiting lists.” Strong Results from Independent Testing The team tested their algorithm on an independent data set of almost 650 images from a previously unseen source. Based on comparisons with the original pathologists’ diagnoses, the researchers showed that the model was correct in its diagnosis in more than 97 cases out of 100. The model had a sensitivity of over 95% – meaning that it correctly identified more than 95 cases out of 100 individuals who had celiac disease. It also had a specificity of almost 98% – meaning that it correctly identified in nearly 98 cases out of 100 individuals who did not have celiac disease. Human Pathologists vs AI Performance Previous research by the team has shown that even pathologists can disagree on diagnoses. When shown a series of 100 slides and asked to diagnose whether a patient had celiac disease, did not have the disease, or whether the diagnosis was indeterminate, the team showed that there was disagreement in more than one in five cases. This time round, the researchers asked four pathologists to review 30 slides and found that a pathologist was as likely to agree with the AI model as they were with a second pathologist. A Versatile and Scalable Diagnostic Tool Dr. Florian Jaeckle, also from the Department of Pathology, and a Research Fellow at Hughes Hall, Cambridge, said: “This is the first time AI has been shown to diagnose as accurately as an experienced pathologist whether an individual has celiac or not. Because we trained it on data sets generated under a number of different conditions, we know that it should be able to work in a wide range of settings, where biopsies are processed and imaged differently. “This is an important step towards speeding up diagnoses and freeing up pathologists’ time to focus on more complex or urgent cases. Our next step is to test the algorithm in a much larger clinical sample, putting us in a position to share this device with the regulator, bringing us nearer to this tool being used in the NHS.” Patient Trust and AI Transparency The researchers have been working with patient groups, including through Coeliac UK, to share their approach and discuss with them their receptiveness to technology such as this being used. “When we speak to patients, they are generally very receptive to the use of AI for diagnosing celiac disease,” added Dr. Jaeckle. “This no doubt partly reflects their experiences of the difficulties and delays in receiving a diagnosis. “One issue that comes up frequently with both patients and clinicians is the issue of ‘explainability’ – being able to understand and explain how AI reaches its diagnosis. It’s important for us as researchers and for regulators to bear this mind if we want to ensure there is public trust in applications of AI in medicine.” Pathologists Launch AI Spinout Company Professor Soilleux is a consultant haematopathologist at Cambridge University Hospitals NHS Foundation Trust. Together with Dr. Jaeckle, she has set up a spinout company, Lyzeum Ltd, to commercialize the algorithm. The research was funded by Coeliac UK, Innovate UK, the Cambridge Centre for Data-Driven Discovery and the National Institute for Health and Care Research. Keira Shepherd, Research Officer at Coeliac UK, said: “During the diagnostic process, it’s vital that patients keep gluten in their diet to ensure that the diagnosis is accurate. But this can cause uncomfortable symptoms. That’s why it’s really important that they are able to receive an accurate diagnosis as quickly as possible. “This research demonstrates one potential way to speed up part of the diagnosis journey. At Coeliac UK, we’re proud to have funded the early stages of this work, which initially focused on training a system to differentiate between healthy control biopsies and biopsies of patients with celiac disease. We hope that one day this technology will be used to help patients receive a quick and accurate diagnosis.” Liz Cox’s 30-Year Diagnosis Journey Liz Cox, 80, had been having symptoms including anemia and stomach pains for almost 30 years when a question from a friend – “Are you still losing weight?” – made her realize that she ought to seek help. Born in Tottenham, North London, towards the end of the Second World War, Liz has moved around, spending part of her life in Singapore after getting married before settling down to live in Linton, just outside Cambridge. She had spent most of her life working in libraries and took up a “retirement job” working in Linton’s community library. Liz began with severe stomach pains in her 30s, after having her three children. “Anything that makes the system quicker must be a good thing.” Liz Cox, 80 A Life Changed by Diagnosis “My doctor carried out various tests, but celiac disease wasn’t very well known then, so I wasn’t tested for that. I was quite tired, but I just carried on because you have to when you’ve got three children and a husband, don’t you?” Liz tried not to let her condition get in the way, making sure she found time for activities she enjoyed, such as skiing and dancing, and it wasn’t until her late 50s, prompted by her friend’s question, that she went back to the doctor. This time, her GP in Linton did a blood test, which suggested advanced celiac disease. A biopsy at Addenbrooke’s Hospital confirmed this – but also found pre-cancerous cells. From Diagnosis to Advocacy “I used to see Dr. Jeremy Woodward, my consultant, every year for an endoscopy. Wasn’t I lucky!” she says. After about 10 years, she was given the all-clear for cancer and discharged. Since her diagnosis, Liz has been on a strict, gluten-free diet, which had an effect almost immediately. She isn’t tempted to have even the smallest amount of gluten now. “Some people say, ‘Have a little bit’, but no, it’s a strict diet, because you don’t know what it’s doing to your insides. It’s just mind over matter, isn’t it? You can’t have it, end of story.” She joined a Coeliac UK support group in Bury St Edmunds, which helped her meet others like herself, share tips and find good places to eat that did gluten-free options. She was talked into becoming the Secretary, with her husband agreeing to become Membership Secretary – they have been doing this now for 20 years. Public Engagement with Research It was through this group that Liz met Professor Elizabeth Soilleux from the University of Cambridge. “Elizabeth came to our meeting to talk about her research. It was quite fun because she showed us pictures of biopsies and said could we guess which were celiac and which weren’t? It wasn’t easy.” Liz is impressed with the use of AI to diagnose celiac disease. Her referral for an endoscopy and the subsequent diagnosis happened relatively quickly. Not everyone is as fortunate. “You hear stories from other people, and they’ve waited a long time. They go back and forward to the doctor’s often, with various odd symptoms, and perhaps the doctors don’t always test them for that. “Anything that makes the system quicker must be a good thing, because once you’ve been diagnosed and you know you can’t have gluten, then you know what to do, and you feel so much better.” Reference: “Machine Learning Achieves Pathologist-Level Coeliac Disease Diagnosis” by Jaeckle, F, Denholm, J & Schreiber, B., 27 March 2025, NEJM AI.DOI: 10.1056/AIoa2400738
