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Record W4389985519 · doi:10.1101/2023.12.19.572448

Electroadhesive hydrogel interface for prolonged mucosal theranostics

2023· preprint· en· W4389985519 on OpenAlexafffund
Binbin Ying, Kewang Nan, Qing Zhu, Tom Khuu, Hana Ro, Sophia Qin, Shubing Wang, Karen Jiang, Yonglin Chen, Guangyu Bao, Andrew Pettinari, Johannes Kuosmanen, Keiko Ishida, Niora Fabian, Aaron Lopes, Jason Li, Alison Hayward, Róbert Langer, Giovanni Traverso

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicAdvanced Drug Delivery Systems
Canadian institutionsMcGill University
FundersNovo NordiskNatural Sciences and Engineering Research Council of CanadaEidgenössische Technische Hochschule ZürichNatural Science Foundation of NingboKoch Institute for Integrative Cancer Research, Massachusetts Institute of Technology
KeywordsMucusIn vivoSelf-healing hydrogelsGastrointestinal tractAdhesionMedicineChemistryBiologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract 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 (GI) theranostics. Here, we report the development of e-GLUE , an e lectroadhesive hydro g e l interface for robust and prolonged m u cosal r e tention following electrical activation. Notably, this novel mucosal adhesion mechanism can increase the adhesion energy of hydrogels on the mucosa by up to 30-fold and enable in vivo GI retention of e-GLUE devices for up to 30 days. Strong mucosal adhesion occurs within one minute of electrical activation, despite the presence of luminal fluid, mucus exposure, and organ motility, thereby ensuring compatibility with complex in vivo environments. In swine studies, we demonstrate the utility of e-GLUE for mucosal hemostasis, sustained local delivery of therapeutics, and intimate biosensing in the GI tract. This system can enable improved treatments for various health conditions, including gastrointestinal bleeding, inflammatory bowel disease, and diagnostic applications in the GI tract and beyond.

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.

How this classification was reachedexpand

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
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 score0.132
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.078
GPT teacher head0.366
Teacher spread0.288 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes2
Has abstractyes

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