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Record W4408345701 · doi:10.1126/sciadv.adr3356

Active microgel particle swarms for intrabronchial targeted delivery

2025· article· en· W4408345701 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScience Advances · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMicro and Nano Robotics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsImaging phantomBiomedical engineeringLungNanotechnologyMaterials scienceComputer scienceMedicineRadiology

Abstract

fetched live from OpenAlex

Intrabronchial delivery of therapeutic agents is critical to the treatment of respiratory diseases. Targeted delivery is demanded because of the off-target accumulation of drugs in normal lung tissues caused by inhalation and the limited motion dexterity of clinical bronchoscopes in tortuous bronchial trees. Herein, we developed microrobotic swarms consisting of magnetic hydrogel microparticles to achieve intrabronchial targeted delivery. Under programmed magnetic fields, the microgel particle swarms performed controllable locomotion and adaptative structure reconfiguration in tortuous and air-filled environments. The swarms were further integrated with imaging contrast agents for precise tracking under x-ray fluoroscopy and computed tomography imaging. Magnetic navigation of the swarms in an ex vivo lung phantom and in vivo delivery into deep branches of the bronchial trees were achieved. The on-demand reconfiguration of swarms for avoiding the microgel particles from entering nontarget bronchi and the precise delivery into tilted bronchi through climbing motion were validated.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score0.289

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.273
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it