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Record W4288084761 · doi:10.1002/adhm.202201471

Interfacing Perforated Eardrums with Graphene‐Based Membranes for Broadband Hearing Recovery

2022· article· en· W4288084761 on OpenAlexaff
Chunyan Li, Zhiyuan Xiong, Lei Zhou, Weiluo Huang, Yu‐Shi He, Linpeng Li, Haibo Shi, Jiayu Lu, Jian Wang, Dan Li, Shankai Yin

Bibliographic record

VenueAdvanced Healthcare Materials · 2022
Typearticle
Languageen
FieldEngineering
TopicGraphene and Nanomaterials Applications
Canadian institutionsDalhousie University
FundersNational Natural Science Foundation of ChinaAustralian Research CouncilNatural Science Foundation of Shanghai
KeywordsEardrumMaterials scienceBroadbandPerforationBiomedical engineeringHearing lossAcousticsComputer scienceMedicineAudiologyTelecommunicationsPhysicsComposite material

Abstract

fetched live from OpenAlex

Eardrum perforation and associated hearing loss is a global health problem. Grafting perforated eardrum with autologous tissues in clinic can restore low-frequency hearing but often leaves poor recovery of high-frequency hearing. In this study, the potential of incorporating a thin multilayered graphene membrane (MGM) into the eardrum for broadband hearing recovery in rats is examined. The MGM shows good biocompatibility and biostability to promote the growth of eardrum cells in a regulated manner with little sign of tissue rejection and inflammatory response. After three weeks of implantation, the MGM is found to be encapsulated by a thin layer of newly grown tissue on both sides without a significant folded overgrowth that is often seen in natural healing. The perforation is well sealed, and broadband hearing recovery (1-32 kHz) is enabled and maintained for at least 2 months. Mechanical simulations show that the high elastic modulus of MGM and thin thickness of the reconstructed eardrum play a critical role in the recovery of high-frequency hearing. This work demonstrates the promise of the use of MGM as a functional graft for perforated eardrum to recover hearing in the broadband frequency region and suggests a new acoustics-related medical application for graphene-related 2D materials.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.078
Threshold uncertainty score1.000

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 head0.017
GPT teacher head0.245
Teacher spread0.227 · 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

Citations10
Published2022
Admission routes1
Has abstractyes

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