Evidence map›Paper›PMID 40589273›Full record

ArticleAdvanced healthcare materials2025

Kidney Stone Dissolution By Tetherless, Enzyme-Loaded, Soft Magnetic Miniature Robots.

Afarin Khabbazian, Lauren Kwong, Aaron Lewis, Erica Liu, Noura Abdelrazec, Anna C Bakenecker, Nil Fontanals, Guillem Lopez, Samuel Sánchez, Juan Manuel Lopez and 6 more

Abstract read
In one paragraph

Article in Advanced healthcare materials, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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 registry

The 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 literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Afarin KhabbazianDepartment of Mechanical Engineering, University of Waterloo, Waterloo, N2L 3G1, Canada.
Lauren KwongMedical Microrobotics Lab, Department of Systems Design Engineering, University of Waterloo, Waterloo, N2L 3G1, Canada.
Aaron LewisMedical Microrobotics Lab, Department of Systems Design Engineering, University of Waterloo, Waterloo, N2L 3G1, Canada.ORCID https://orcid.org/0009-0000-9338-7854
Erica LiuMedical Microrobotics Lab, Department of Systems Design Engineering, University of Waterloo, Waterloo, N2L 3G1, Canada.
Noura AbdelrazecMedical Microrobotics Lab, Department of Systems Design Engineering, University of Waterloo, Waterloo, N2L 3G1, Canada.
Anna C BakeneckerInstitute for Bioengineering of Catalonia, Barcelona, 08028, Spain.
Nil FontanalsInstitute for Bioengineering of Catalonia, Barcelona, 08028, Spain.
Guillem LopezInstitute for Bioengineering of Catalonia, Barcelona, 08028, Spain.
Samuel SánchezInstitute for Bioengineering of Catalonia, Barcelona, 08028, Spain.
Juan Manuel LopezDepartment of Urology, University of Barcelona Clinic Hospital, Barcelona, 08036, Spain.
Brian CarrilloFarcas Lab, Department of Surgery, Division of Urology, St. Michael's Hospital, University of Toronto, Toronto, M5B 1W8, Canada.
Monica FarcasFarcas Lab, Department of Surgery, Division of Urology, St. Michael's Hospital, University of Toronto, Toronto, M5B 1W8, Canada.
Chris KallweitSchlegel Research Institute for Aging and Department of Electrical and Computer Engineering, University of Waterloo, Ontario, N2J0E2, Canada.
Alfred C H YuSchlegel Research Institute for Aging and Department of Electrical and Computer Engineering, University of Waterloo, Ontario, N2J0E2, Canada.
Mir Behrad KhameseeDepartment of Mechanical Engineering, University of Waterloo, Waterloo, N2L 3G1, Canada.
Veronika MagdanzMedical Microrobotics Lab, Department of Systems Design Engineering, University of Waterloo, Waterloo, N2L 3G1, Canada.ORCID https://orcid.org/0000-0001-7522-033X

Funding

Graham Seed Fund'la Caixa' Foundation LCF/BQ/PI21/11830003Natural Sciences and Engineering Research Council of Canada Discovery grant
6 · The paper itself

Abstract

Kidney stones are some of the most common urinary diseases, affecting 12% of the population. The high prevalence and recurrence of this disease urges the development of more targeted and effective treatment with lower side effects and less invasiveness avoiding recurrence and prolonged drug administration. Particularly for recurring stone formers, the current methods of persistent drug treatment and repetitive surgeries for stone removal are unsatisfying solutions that bring a huge burden to the patients and healthcare systems. For these reasons, a delivery strategy that provides drug administration at the disease site through active, wireless transport is urgently needed to improve urinary tract disease treatment. A wireless treatment of kidney stones is proposed with the help of flexible, magnetically steered, enzymatically active robots. These robots are designed to navigate in the urinary tract and locally dissolve the stones by action of embedded urease. The robots are made of millimeter-sized, gelatin-based polymer strips with embedded micromagnets and encapsulated urease which constantly converts urea to increase urinary pH. This study demonstrates enhanced stone dissolution and the robots' magnetic navigation through the different parts of a 3D printed human urinary tract model. A clinical ultrasound system allows real-time localization of the robots. This research proposes a less invasive and more targeted strategy for medical interventions in the urinary tract with potential to circumvent surgery in case of uric acid kidney stones, which is relevant especially in the light of high prevalence and recurrence of kidney stones.

Indexed as

Kidney CalculiRoboticsUreaseHumansMagneticsModels, AnatomicPrinting, Three-DimensionalUltrasonographyUrinary TractWireless TechnologyUreaseenzymatickidney stonesmagneticmicrorobotsrenal stonessoft robots

Identifiers

PMID40589273
PMCPMC12417750

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.