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Record W4407948708 · doi:10.1126/scitranslmed.adq1975

An electroadhesive hydrogel interface prolongs porcine gastrointestinal mucosal theranostics

2025· article· en· W4407948708 on OpenAlex
Binbin Ying, Kewang Nan, Qing Zhu, Tom Khuu, Hana Ro, Sophia Qin, Shubing Wang, Karen Jiang, Yonglin Chen, Guangyu Bao, J. A. Jenkins, Andrew Pettinari, Johannes Kuosmanen, Keiko Ishida, Niora Fabian, Aaron Lopes, Flavia Codreanu, Joshua Morimoto, Jason Li, Alison Hayward, Róbert Langer, Giovanni Traverso

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 Translational Medicine · 2025
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicAdvanced Drug Delivery Systems
Canadian institutionsMcGill University
Fundersnot available
KeywordsSelf-healing hydrogelsAdhesionBiomedical engineeringGLUEGastrointestinal tractNanotechnologyBiophysicsChemistryMaterials scienceMedicineBiologyBiochemistryPolymer chemistry

Abstract

fetched live from OpenAlex

Establishing a robust and intimate mucosal interface that allows medical devices to remain within lumen-confined organs for extended periods has valuable applications, particularly for gastrointestinal theranostics. Here, we report the development of an electroadhesive hydrogel interface for robust and prolonged mucosal retention after electrical activation (e-GLUE). The e-GLUE device is composed of cationic polymers interpenetrated within a tough hydrogel matrix. An e-GLUE electrode design eliminated the need for invasive submucosal placement of ground electrodes for electrical stimulation during endoscopic delivery. With an electrical stimulation treatment of about 1 minute, the cationic polymers diffuse and interact with polyanionic proteins that have a relatively slow cellular turnover rate in the deep mucosal tissue. This mucosal adhesion mechanism increased the adhesion energy of hydrogels on the mucosa by up to 30-fold and enabled in vivo gastric retention of e-GLUE devices in a pig stomach for up to 30 days. The adhesion strength was modulated by polycationic chain length, electrical stimulation time, gel thickness, cross-linking density, voltage amplitude, polycation concentration, and perimeter-to-area ratio of the electrode assembly. In porcine studies, e-GLUE demonstrated rapid mucosal adhesion in the presence of luminal fluid and mucus exposure. In proof-of-concept studies, we demonstrated e-GLUE applications for mucosal hemostasis, sustained local delivery of therapeutics, and intimate biosensing in the gastrointestinal tract, which is an ongoing clinical challenge for commercially available alternatives, such as endoclips and mucoadhesive. The e-GLUE platform could enable theranostic applications across a range of digestive diseases, including recurrent gastrointestinal bleeding and inflammatory bowel disease.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.592
Threshold uncertainty score0.821

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.059
GPT teacher head0.465
Teacher spread0.406 · 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