We’re used to a lot of different natural things falling out of the sky. These can include snow, rain, and sometimes even frogs (yes, really). All of these relate to weather phenomena. Far more exotic things fall from the sky that are not related to weather. Earth is pelted by about 14 tons of micrometeoritesContinue reading "A meteorite impact may have once rained gold on Western Australia – new study"
Even small asteroids lead complex lives. During its flyby of the asteroid Donaldjohanson last year, NASA’s Lucy spacecraft revealed the asteroid to be a wobbly, peanut-shaped body that has undergone a lot of activity in its relatively short history. Formed as fragments coalesced after a violent collision 155 million years ago, the asteroid was transformed by the small but inexorable force of the Sun’s radiation, all while retaining signs of the brief presence of liquid water in its distant past.
Zooming through the main asteroid belt toward one of the Jupiter Trojan asteroid groups, the Lucy spacecraft collected the first close-up images and other data at Donaldjohanson on April 20, 2025, as it passed 650 miles away from the asteroid. The data revealed that, instead of spinning simply around one axis like most other asteroids and planets, Donaldjohanson has a more complicated two-axis rotation. Scientists also saw Donaldjohanson’s peanut shape and the craters and ridges on its surface.
A timelapse video made from images taken by NASA’s Lucy spacecraft as it approached the asteroid Donaldjohanson on April 20, 2025. The L’LORRI (Lucy Long Range Reconnaissance Imager) instrument, the spacecraft’s high-resolution black-and-white imager, collected these images over two hours as the spacecraft rapidly closed in on the asteroid from an initial separation of more than 58,000 miles (93,000 km), until the spacecraft passed a mere 650 miles (1000 km) from the 5-mile- (8 km-) wide asteroid.
NASA/Goddard/SwRI/JHU-APL
Lucy’s encounter with the asteroid was planned as a dress rehearsal for the spacecraft and mission team before its primary asteroid encounters, which begin with Lucy’s flyby of the Trojan asteroid Eurybates on Aug. 12, 2027. The instruments performed as expected, and, as a bonus, scientists got a rare opportunity to study a previously unexplored asteroid up close and to compare it to two asteroids with similar compositions but different histories: Bennu, the target of NASA’s OSIRIS-REx sample-return mission, and Ryugu, the site of JAXA’s (Japan Aerospace Exploration Agency) Hayabusa2 sample-return mission.
With Earth-based telescopes, observers saw fluctuations in the light Donaldjohanson reflects, regular patterns of peaks and valleys, typical of an elongated object rotating once every 10.5 Earth days. But Lucy’s data revealed another pattern: Donaldjohanson appears to be rotating like a wobbly top. Paper authors reported that the asteroid rotates end-over-end once every 10.5 Earth days, and wobbles back and forth around its long axis once every 26.5 days.
The asteroid Donaldjohanson is shown slowly rotating in a tumbling, non-principal axis motion, with its angular momentum vector and rotation axes indicated. The surface is colored by gravity slope, which measures the angle between the local surface and the direction of gravity. Higher values (warmer colors) indicate steeper terrain relative to the local gravitational pull. Regions with limited stereo image coverage have been masked out where the shape model is less well constrained.
Kel Elkins/NASA’s Science Visualization Studio/DLR
Peanut shape
While the Earth-based observations hinted at Donaldjohanson’s elongated shape, the Lucy flyby revealed a “bilobate” structure: two lobes connected by a neck, like a peanut. These lobes are likely two fragments from an asteroid collision that gently came together afterward by their mutual gravity.
Donaldjohanson likely rotated at least 10 times faster when it formed, having slowed to its current rate in the last 20 to 60 million years, the team estimates. As it slowed, the balance between the centrifugal force pushing things apart and gravity pulling things together changed and loose rocky material slid down slopes creating the worn-down appearance of many craters, as the flyby images showed.
The paper’s authors say that the asteroid’s slowing rotation is likely caused by a subtle consequence of solar heating known as the YORP effect. Each part of the asteroid’s Sun-warmed surface radiates heat away as infrared light, and that radiation imparts a tiny recoil force to the surface. Because the asteroid’s shape isn’t symmetric, this results in a net torque, or twist, that can change the asteroid’s rotation. Thus, YORP can slow asteroid spins down or speed them up, as in the case of Bennu (once every four hours) and Ryugu (once about every seven hours), which both likely used to rotate much slower than they do today.
Fleeting water
As it passed by Donaldjohanson at 30,000 mph, Lucy recorded the signatures of iron-rich clay minerals on the surface. These clays must have formed in the distant past with the help of liquid water. However, the exposure must have been brief, Lucy scientists concluded, because iron in clays tends to be replaced with other elements, such as magnesium, as water lingers.
Indeed, scientists saw magnesium-rich clays at Bennu and Ryugu, which suggested prolonged water exposure, perhaps lasting millions of years, when they were still part of larger asteroids.
This difference in water exposure history, and other characteristics, may mean that the parent bodies of these asteroids formed at different times or in different regions of the solar system before relocating to the main belt.
Compare, contrast
Donaldjohanson is thought to be made from rocky remnants of a larger, carbon- and water-rich asteroid that collided with another object in the main asteroid belt. Bennu and Ryugu are thought to have formed in the same way and in the same region.
But Donaldjohanson is different. At 155 million years old, it is much younger than Bennu and Ryugu, which formed 1 to 2 billion years ago. Donaldjohanson also has remained in the asteroid belt since birth, while its wandering cousins migrated into orbits around the Sun that bring them close to Earth’s orbit about once a year (which made them perfect close targets for sample return missions).
During its April 20, 2025, encounter with the main-belt asteroid Donaldjohanson, NASA’s Lucy spacecraft discovered evidence for iron-rich clays on the surface using its infrared spectrometer. These clays, which are similar to those found in carbon-rich meteorites such as QUE 97990, indicate that water was briefly present in the asteroid during the distant past.
NASA/Goddard/SwRI/Dan Gallagher
“It’s helpful for scientists to compare Donaldjohanson with asteroids like Bennu and Ryugu, which are seemingly similar asteroids, because every subtle difference is another clue to our origin story,” said Simone Marchi, Lucy deputy principal investigator and lead author of the study at the Boulder, Colorado, office of the Southwest Research Institute.
“Once we start learning more about the Trojans, a completely different population of space rocks with very different histories, our understanding of solar system formation is destined to be challenged,” said Marchi.
Named after a fossilized skeleton of a human ancestor discovered in Ethiopia in 1974, NASA’s Lucy will be the first mission to explore Jupiter’s Trojan asteroids, a population of well-preserved space rocks that formed early in our solar system’s history and could help scientists understand how the planets formed and moved around before settling in their current configuration.
Lucy’s principal investigator is based out of the Boulder, Colorado, branch of Southwest Research Institute, headquartered in San Antonio. NASA’s Goddard Space Flight Center in Greenbelt, Maryland, provides overall mission management, systems engineering, and safety and mission assurance. Lockheed Martin Space in Littleton, Colorado, built the spacecraft. Lucy is the 13th mission in NASA’s Discovery Program. NASA’s Marshall Space Flight Center in Huntsville, Alabama, manages the Discovery Program for the agency’s Science Mission Directorate in Washington.
For more information on NASA’s Lucy mission, visit:
Zooming through the main asteroid belt toward one of the Jupiter Trojan asteroid groups, the Lucy spacecraft collected the first close-up images and other data at Donaldjohanson on April 20, 2025, as it passed 650 miles away from the asteroid. The data revealed that, instead of spinning simply around one axis like most other asteroids and planets, Donaldjohanson has a more complicated two-axis rotation. Scientists also saw Donaldjohanson’s peanut shape and the craters and ridges on its surface.
Even small asteroids lead complex lives. During its flyby of the asteroid Donaldjohanson last year, NASA’s Lucy spacecraft revealed the asteroid to be a wobbly, peanut-shaped body that has undergone a lot of activity in its relatively short history. Formed as fragments coalesced after a violent collision 155 million years ago, the asteroid was transformed by the small but inexorable force of the Sun’s radiation, all while retaining signs of the brief presence of liquid water in its distant past.
Zooming through the main asteroid belt toward one of the Jupiter Trojan asteroid groups, the Lucy spacecraft collected the first close-up images and other data at Donaldjohanson on April 20, 2025, as it passed 650 miles away from the asteroid. The data revealed that, instead of spinning simply around one axis like most other asteroids and planets, Donaldjohanson has a more complicated two-axis rotation. Scientists also saw Donaldjohanson’s peanut shape and the craters and ridges on its surface.
A timelapse video made from images taken by NASA’s Lucy spacecraft as it approached the asteroid Donaldjohanson on April 20, 2025. The L’LORRI (Lucy Long Range Reconnaissance Imager) instrument, the spacecraft’s high-resolution black-and-white imager, collected these images over two hours as the spacecraft rapidly closed in on the asteroid from an initial separation of more than 58,000 miles (93,000 km), until the spacecraft passed a mere 650 miles (1000 km) from the 5-mile- (8 km-) wide asteroid.
NASA/Goddard/SwRI/JHU-APL
Lucy’s encounter with the asteroid was planned as a dress rehearsal for the spacecraft and mission team before its primary asteroid encounters, which begin with Lucy’s flyby of the Trojan asteroid Eurybates on Aug. 12, 2027. The instruments performed as expected, and, as a bonus, scientists got a rare opportunity to study a previously unexplored asteroid up close and to compare it to two asteroids with similar compositions but different histories: Bennu, the target of NASA’s OSIRIS-REx sample-return mission, and Ryugu, the site of JAXA’s (Japan Aerospace Exploration Agency) Hayabusa2 sample-return mission.
With Earth-based telescopes, observers saw fluctuations in the light Donaldjohanson reflects, regular patterns of peaks and valleys, typical of an elongated object rotating once every 10.5 Earth days. But Lucy’s data revealed another pattern: Donaldjohanson appears to be rotating like a wobbly top. Paper authors reported that the asteroid rotates end-over-end once every 10.5 Earth days, and wobbles back and forth around its long axis once every 26.5 days.
The asteroid Donaldjohanson is shown slowly rotating in a tumbling, non-principal axis motion, with its angular momentum vector and rotation axes indicated. The surface is colored by gravity slope, which measures the angle between the local surface and the direction of gravity. Higher values (warmer colors) indicate steeper terrain relative to the local gravitational pull. Regions with limited stereo image coverage have been masked out where the shape model is less well constrained.
Kel Elkins/NASA’s Science Visualization Studio/DLR
Peanut shape
While the Earth-based observations hinted at Donaldjohanson’s elongated shape, the Lucy flyby revealed a “bilobate” structure: two lobes connected by a neck, like a peanut. These lobes are likely two fragments from an asteroid collision that gently came together afterward by their mutual gravity.
Donaldjohanson likely rotated at least 10 times faster when it formed, having slowed to its current rate in the last 20 to 60 million years, the team estimates. As it slowed, the balance between the centrifugal force pushing things apart and gravity pulling things together changed and loose rocky material slid down slopes creating the worn-down appearance of many craters, as the flyby images showed.
The paper’s authors say that the asteroid’s slowing rotation is likely caused by a subtle consequence of solar heating known as the YORP effect. Each part of the asteroid’s Sun-warmed surface radiates heat away as infrared light, and that radiation imparts a tiny recoil force to the surface. Because the asteroid’s shape isn’t symmetric, this results in a net torque, or twist, that can change the asteroid’s rotation. Thus, YORP can slow asteroid spins down or speed them up, as in the case of Bennu (once every four hours) and Ryugu (once about every seven hours), which both likely used to rotate much slower than they do today.
Fleeting water
As it passed by Donaldjohanson at 30,000 mph, Lucy recorded the signatures of iron-rich clay minerals on the surface. These clays must have formed in the distant past with the help of liquid water. However, the exposure must have been brief, Lucy scientists concluded, because iron in clays tends to be replaced with other elements, such as magnesium, as water lingers.
Indeed, scientists saw magnesium-rich clays at Bennu and Ryugu, which suggested prolonged water exposure, perhaps lasting millions of years, when they were still part of larger asteroids.
This difference in water exposure history, and other characteristics, may mean that the parent bodies of these asteroids formed at different times or in different regions of the solar system before relocating to the main belt.
Compare, contrast
Donaldjohanson is thought to be made from rocky remnants of a larger, carbon- and water-rich asteroid that collided with another object in the main asteroid belt. Bennu and Ryugu are thought to have formed in the same way and in the same region.
But Donaldjohanson is different. At 155 million years old, it is much younger than Bennu and Ryugu, which formed 1 to 2 billion years ago. Donaldjohanson also has remained in the asteroid belt since birth, while its wandering cousins migrated into orbits around the Sun that bring them close to Earth’s orbit about once a year (which made them perfect close targets for sample return missions).
During its April 20, 2025, encounter with the main-belt asteroid Donaldjohanson, NASA’s Lucy spacecraft discovered evidence for iron-rich clays on the surface using its infrared spectrometer. These clays, which are similar to those found in carbon-rich meteorites such as QUE 97990, indicate that water was briefly present in the asteroid during the distant past.
NASA/Goddard/SwRI/Dan Gallagher
“It’s helpful for scientists to compare Donaldjohanson with asteroids like Bennu and Ryugu, which are seemingly similar asteroids, because every subtle difference is another clue to our origin story,” said Simone Marchi, Lucy deputy principal investigator and lead author of the study at the Boulder, Colorado, office of the Southwest Research Institute.
“Once we start learning more about the Trojans, a completely different population of space rocks with very different histories, our understanding of solar system formation is destined to be challenged,” said Marchi.
Named after a fossilized skeleton of a human ancestor discovered in Ethiopia in 1974, NASA’s Lucy will be the first mission to explore Jupiter’s Trojan asteroids, a population of well-preserved space rocks that formed early in our solar system’s history and could help scientists understand how the planets formed and moved around before settling in their current configuration.
Lucy’s principal investigator is based out of the Boulder, Colorado, branch of Southwest Research Institute, headquartered in San Antonio. NASA’s Goddard Space Flight Center in Greenbelt, Maryland, provides overall mission management, systems engineering, and safety and mission assurance. Lockheed Martin Space in Littleton, Colorado, built the spacecraft. Lucy is the 13th mission in NASA’s Discovery Program. NASA’s Marshall Space Flight Center in Huntsville, Alabama, manages the Discovery Program for the agency’s Science Mission Directorate in Washington.
For more information on NASA’s Lucy mission, visit:
Zooming through the main asteroid belt toward one of the Jupiter Trojan asteroid groups, the Lucy spacecraft collected the first close-up images and other data at Donaldjohanson on April 20, 2025, as it passed 650 miles away from the asteroid. The data revealed that, instead of spinning simply around one axis like most other asteroids and planets, Donaldjohanson has a more complicated two-axis rotation. Scientists also saw Donaldjohanson’s peanut shape and the craters and ridges on its surface.
In a groundbreaking advancement that could revolutionize cancer prognosis and treatment, a team of researchers led by Liu, X., Dai, F., and Dai, J., has unveiled a sophisticated multimodal multitask deep learning system for grading management in non-small cell lung cancer (NSCLC). Published recently in Nature Communications, this innovative approach integrates diverse data modalities through an advanced artificial intelligence framework, demonstrating unprecedented accuracy and efficiency in tumor grading and patient stratification—key factors in tailoring personalized therapies and improving patient outcomes.
Non-small cell lung cancer remains one of the leading causes of cancer-related mortality worldwide, largely due to its heterogeneity and the challenge of precise tumor grading. Traditional grading methods rely heavily on histopathological analysis, which, while indispensable, faces limitations in capturing the complex biological and morphological variations across patients. This novel multimodal multitask network leverages deep learning’s capacity to extract nuanced features across multiple data types, including histology images, radiographic scans, and molecular profiles, effectively capturing the multidimensional nature of the disease.
The core innovation of this system lies in its multitask learning architecture, which simultaneously addresses multiple clinical endpoints—tumor grading, staging, and survival prediction—within a unified model. This approach contrasts with previous single-task models that focus on one predictive target, often neglecting the interdependencies among clinically significant tasks. By jointly optimizing these objectives, the model enhances its robustness and clinical utility, improving prognostic accuracy and enabling more informed decision-making.
From a technical perspective, the deep learning model employs convolutional neural networks (CNNs) tailored to each data modality. For imaging data, sophisticated CNN architectures with residual connections enable hierarchical feature extraction, while genomic and proteomic data are processed via fully connected layers, integrated through fusion mechanisms within the network. Crucially, the system employs attention mechanisms that dynamically weigh contributions from each data source, ensuring that the most relevant features guide the tumor grading process. This multimodal fusion enhances interpretability, as clinicians can trace back which data aspects influence the model’s predictions.
The training dataset comprises an extensive cohort of NSCLC patients, encompassing thousands of digitized histopathology slides, CT images, and matched molecular data. The researchers implemented rigorous preprocessing pipelines to normalize and augment the data, addressing variability inherent in clinical datasets. Importantly, domain adaptation techniques were employed to mitigate batch effects and imaging protocol heterogeneity, ensuring the model’s generalizability across different clinical settings and patient populations.
Performance metrics reported in the study underscore the system’s superiority over conventional grading methods and previous AI models. With an area under the receiver operating characteristic curve (AUC-ROC) exceeding 0.90 for tumor grading tasks, the model exhibits remarkable sensitivity and specificity. Notably, survival prediction tasks achieved similarly high accuracy, enabling stratification of patients into risk categories with potential to guide treatment intensification or de-escalation.
In addition to diagnostic accuracy, the system’s design emphasizes clinical workflow integration. The researchers developed an interactive platform allowing pathologists and oncologists to visualize model outputs alongside raw data, fostering collaborative interpretation. This interface incorporates uncertainty quantification and confidence scores, aiding clinicians in evaluating prediction reliability and assimilating AI-driven insights with clinical judgment.
The researchers also addressed ethical and regulatory considerations critical for clinical deployment. Data privacy was preserved through federated learning techniques during model training, circumventing the need for centralized data storage and enabling multi-institutional collaboration without compromising patient confidentiality. Moreover, the model’s transparent architecture and interpretability features facilitate compliance with emerging AI governance frameworks and regulatory approvals.
Beyond the immediate clinical implications, this study exemplifies the transformative potential of deep learning for precision medicine. By capturing tumor heterogeneity through multimodal data fusion, it paves the way for dynamic tumor characterization that adapts to evolving cancer biology over time, potentially informing adaptive therapy paradigms. Furthermore, the model’s multitask structure could be extended to other malignancies or complex diseases characterized by multifactorial phenotypes.
The authors highlight several avenues for future research, including prospective clinical trials to assess real-world efficacy and impact on treatment outcomes. Plans to incorporate longitudinal patient data hold promise for modeling disease progression and therapy resistance. Additionally, incorporating emerging data modalities such as circulating tumor DNA and spatial transcriptomics could further refine the grading system’s sensitivity and specificity.
In summary, this landmark study ushers in a new era of AI-driven oncology, where deep learning models not only automate grading but also synthesize heterogeneous clinical data to empower personalized management in NSCLC. By bridging computational innovation and clinical applicability, it stands to significantly enhance diagnostic precision, treatment planning, and ultimately patient survival in a notoriously challenging cancer type.
As research continues to unravel the complexities of NSCLC, such sophisticated AI frameworks represent vital tools in the quest to deliver more effective, individualized care. The collaborative effort showcased by Liu, Dai, and colleagues sets a compelling precedent for harnessing multimodal data integration and multitask deep learning to tackle other pressing challenges in oncology and beyond.
Subject of Research: Multimodal multitask deep learning for tumor grading and management in non-small cell lung cancer
Article Title: Multimodal multitask deep learning for grading management system in non-small cell lung cancer
Article References: Liu, X., Dai, F., Dai, J. et al. Multimodal multitask deep learning for grading management system in non-small cell lung cancer. Nat Commun (2026). https://doi.org/10.1038/s41467-026-74474-2
Ebola Virus Finds Sanctuary in the Brain: Breaking Ground with Human Cerebral Organoids
In a landmark study published in Nature Microbiology, researchers from the Icahn School of Medicine at Mount Sinai and the Bernhard Nocht Institute for Tropical Medicine (BNITM) have uncovered how the deadly Ebola virus can persist and replicate stealthily within the human central nervous system. By leveraging cutting-edge cerebral organoid models—three-dimensional brain-like structures derived from human pluripotent stem cells—the team has shed light on the viral mechanisms that allow long-term survival, raising critical implications for treatment and prevention strategies of Ebola virus disease (EVD).
It has long been a harrowing clinical observation that survivors of acute Ebola infections sometimes suffer relapses or develop inflammatory syndromes months or even years after recovery. This enduring threat is attributed to the virus’s ability to hide out in “immune-privileged” regions of the body—such as the central nervous system (CNS)—where the immune surveillance is deliberately restrained to protect vulnerable tissue from damaging inflammation. This latest research elucidates the ways Ebola virus exploits this sanctuary and endures prison-like conditions inside cerebral tissue without fully succumbing to immune clearance.
The team engineered cerebral organoids by coaxing human induced pluripotent stem cells (iPSCs) into forming spherical, differentiated structures composed of multiple neural cell types: neurons, astrocytes, and microglia alike. These organoids mimic the cellular environment of the human brain closely enough to serve as a viable model to explore viral persistence with unprecedented resolution and relevance. Unlike traditional animal models, these human-derived organoids enable direct examination of host-virus interactions in a context that recapitulates human neuroanatomy and immunology.
Longitudinal infection experiments revealed that Ebola virus and related filoviruses—including Sudan, Reston, and Marburg viruses—could sustain active replication within these cerebral organoids for up to 120 days. More intriguingly, Ebola virus infected not just neurons but also astrocytes and microglia, the brain’s resident immune cells. The virus exhibited two spreading modalities: direct cell-to-cell contact transmission as well as classical budding from host cells. This productive persistence clearly places the virus in an infectious, replicative state rather than a latent or inactive one.
Despite the robust production of pro-inflammatory cytokines by infected organoids, the innate immune responses orchestrated within this model failed to clear the infection entirely. The study observed an upregulation of immune and inflammatory markers at later stages, mirroring clinical presentations seen in Ebola virus disease survivors who develop delayed meningoencephalitis and other inflammatory sequelae. The data affirm that persistent filovirus infection in immune-privileged tissues contributes to localized inflammation, fostering neurological disease conditions even after primary viremia subsides.
At the molecular level, whole-genome sequencing of viral populations recovered from persistently infected organoids uncovered the presence of defective viral genomes (DVGs) and a spectrum of mutations emerging during chronic replication. DVGs are truncated or mutated forms of viral genomes known to modulate replication dynamics and immune evasion in other viral families. These defective genomes may allow the Ebola virus to dampen replication while maintaining a foothold inside host tissue, facilitating long-term survival without triggering overwhelming immune destruction.
Several mutations identified in the viral sequences corresponded to variants previously reported to attenuate replication in natural infections, while others were novel and uncharacterized. This emerging mutational landscape hints at an ongoing evolutionary arms race as the virus adapts to the CNS environment and immune pressures. Such adaptations could be critical determinants in the capacity of Ebola virus to establish persistent reservoirs and cause relapses.
This cerebral organoid model’s faithful recapitulation of human Ebola virus infection patterns underscores its utility as a powerful platform for mechanistic studies of viral persistence. Unlike animal models, which often fail to mimic intricate human neural immunology adequately, organoids offer a nearer-to-human experimental system. This breakthrough has potential ramifications for testing and optimizing targeted antiviral therapies aimed specifically at reservoirs residing in immune-privileged compartments.
Moreover, cerebral organoids provide an ethically favorable and scalable alternative to animal experiments, fostering more humane and potentially faster progress in infectious disease research. This innovation aligns with global efforts to reduce animal use in biomedical studies and to increase translational fidelity to human conditions.
Looking ahead, the research team emphasizes expanding their investigations to include other lesser-studied filoviruses such as Taï Forest, Bombali, and Bundibugyo viruses. Comprehensive deciphering of host–virus dynamics in such a model may unravel universal persistence mechanisms across filovirus species, informing cross-cutting therapeutic strategies. Crucially, this work also lays groundwork for exploring how viral persistence in the CNS intersects with immune modulation, neuroinflammation, and long-term neurological sequelae in EVD survivors.
Persistent Ebola infection in the brain highlights a formidable challenge for public health, given the potential for virus reactivation or even transmission from immune-privileged sanctuaries. This study delivers a compelling window into that hidden battleground, leveraging state-of-the-art human cellular models to confront a deadly pathogen’s stealth strategies. Unlocking the biology of Ebola’s cerebral persistence may ultimately pave the way for interventions that not only save lives during acute infection but also circumvent post-recovery complications and community outbreaks.
As our understanding deepens, harnessing cerebral organoids as investigative tools promises to revolutionize the study of neurotropic viral infections. The Mount Sinai and BNITM collaboration exemplifies how multidisciplinary, translational research can illuminate the dark corners of viral pathogenesis and guide clinical innovation for diseases once deemed intractable.
Subject of Research: Animals (via human-derived cerebral organoids)
Article Title: Host–virus determinants of Ebola virus persistence in a human cerebral organoid model
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