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Record W4414628942 · doi:10.1186/s12951-025-03707-1

Dimensional control of DNA nanostructures enhances cellular uptake and guides tissue-regenerative responses

2025· article· en· W4414628942 on OpenAlexaff
Xinyue Tang, Tingting Zhai, Tian‐Cheng Li, Yu Jin, Cheng Zhu, Luyao Qu, Y. Li, Yudong Wang, Hongzhou Gu, Bing Fang

Bibliographic record

VenueJournal of Nanobiotechnology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsMcMaster University
FundersProgram of Shanghai Academic Research LeaderNational Key Research and Development Program of ChinaSchool of Medicine, Shanghai Jiao Tong UniversityNational Natural Science Foundation of ChinaShanghai Jiao Tong UniversityNational Research Foundation
KeywordsMulticellular organismRegenerative medicineDrug deliveryCellDNAElectroporationCell growthDNA nanotechnologyEndocytosis

Abstract

fetched live from OpenAlex

Precise regulation of cellular functions is fundamental for advancing tissue regeneration and drug delivery systems. Structural DNA nanotechnology enables the design of well-defined nanostructures, emerging as a promising platform in these biomedical applications. However, a clear understanding of how the dimensional properties of DNA nanostructures affect cellular uptake and biological responses remains limited. In this study, we constructed three distinct DNA nanostructures: a one-dimensional six-helix bundle (6HB), a two-dimensional three-point star, and a three-dimensional tetrahedron. We systematically evaluated their endocytic efficiency in five representative cell types: endothelial cells, dermal fibroblasts, myoblasts, chondrocytes, and osteoblasts. Among them, the 6HB exhibited the highest cellular uptake, with minimal variability across cell types in both 2D petri dish cultures and 3D multicellular spheroid invasion models. Moreover, DNA nanostructures were found to enhance cell proliferation in fibroblasts and chondrocytes, support chondrocyte phenotype maintenance, and, in the case of the 6HB, promote myoblast differentiation. These findings provide new insights into structure-function relationships in DNA nanomaterials and offer guidance for optimizing DNA-based platforms for drug delivery and regenerative medicine.

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 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 score0.015
Threshold uncertainty score0.480

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 head0.005
GPT teacher head0.266
Teacher spread0.261 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2025
Admission routes1
Has abstractyes

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