In one paragraphArticle in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registryThe trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
18 authors.
Hohyun LeeWoodruf School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States.ORCID 0000-0002-7939-6751 Victor MenezesWoodruf School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States.ORCID 0009-0009-8377-0054 Shiqin ZengSchool of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States.ORCID 0000-0002-9798-5576 Chulyong KimWoodruf School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States.ORCID 0009-0000-7550-0980 Cynthia M BasemanSchool of Interactive Computing, Georgia Institute of Technology, Atlanta, Georgia, United States.ORCID 0009-0004-8507-438X Jae Hyun KimWoodruf School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States.ORCID 0009-0004-9603-9002 Samhita PadmanabhanCoulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, United States.ORCID 0000-0003-0780-7248 Pranav PremdasSchool of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States.ORCID 0000-0002-8451-0467 Naima DjeddarInstitute of Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia, United States.
Anton BryksinInstitute of Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia, United States.ORCID 0000-0003-3302-8248 Nikhil PandeyDepartment of Neurosurgery, University of Maryland School of Medicine, Baltimore, Maryland, United States.ORCID 0000-0002-6560-6893 Pavlos AnastasiadisDepartment of Neurosurgery, University of Maryland School of Medicine, Baltimore, Maryland, United States.ORCID 0000-0002-0230-7925 Anthony J KimDepartment of Neurosurgery, University of Maryland School of Medicine, Baltimore, Maryland, United States.ORCID 0000-0002-8385-417X Tobey J MacDonaldAflac Cancer & Blood Disorders Center, Department of Pediatrics, Emory University School of Medicine, Atlanta, Georgia, United States.ORCID 0000-0003-4918-1300 Chetan BettegowdaDepartment of Neurosurgery, John Hopkins University School of Medicine, Baltimore, Maryland, United States.ORCID 0000-0001-9991-7123 Graeme F WoodworthDepartment of Neurosurgery, University of Maryland School of Medicine, Baltimore, Maryland, United States.ORCID 0000-0001-9663-0768 Felix J HerrmannSchool of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States.ORCID 0000-0003-1180-2167 Costas ArvanitisWoodruf School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States.ORCID 0000-0002-7737-1446 Funding
"Transcranial FUS therapy with closed-loop US image guidance and circulating tumor DNAR37CA239039 · NCI · GEORGIA INSTITUTE OF TECHNOLOGY · PI Konstantinos-Costas Arvanitis · 2020 to 2026
$3.3MNCI NIH HHS R37 CA239039
6 · The paper itselfAbstract
The blood-brain barrier (BBB) renders the delivery of nanomedicine in the brain ineffective and the detection of circulating disease-related DNA from the brain unreliable. Here, we show that the acoustic emission content of focused ultrasound-controlled microbubble dynamics (MB-FUS) incorporates precursor signals that allow large-data models to predict sonication regimens for safe and effective BBB opening. Crucially, closed-loop MB-FUS controller augmented by machine learning (ML-CL) expands the treatment window (4-fold), as compared to conventional controllers, by persistently and proactively maximizing the BBB permeability while preventing tissue damage. By successfully scaling up from mice to rats and from healthy to diseased brains (glioma), ML-CL rendered the BBB permeable to large nanoparticles and markedly improved the release and detection of tumor DNA in plasma. Together, our findings reveal the potential of data-driven feedback to support the development of next-generation AI-powered ultrasound systems for safe, robust, and efficient nanotheranostic targeting of brain diseases.
Identifiers
PMID40654633
PMCPMC12247749
What OpenQuestion holds
Textmetadata
LicenceCC BY
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