Evidence map›Paper›PMID 41910374›Full record

ArticleAdvanced materials (Deerfield Beach, Fla.)2026

AI-Guided 4D Printing of Carnivorous Plants-Inspired Microneedles for Accelerated Wound Healing.

Hyun Lee, Moon-Jo Kim, DongEung Kim, Chan Ho Moon, Seojoon Bang, Hyeong Seok Kang, Ju Yeong Gwon, Jong Hwa Seo, Junhyub Jeon, Junhyuk Son and 12 more

Abstract read
In one paragraph

Article in Advanced materials (Deerfield Beach, Fla.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Hyun LeeResearch Institute of Intelligent Manufacturing & Materials Technology, Korea Institute of Industrial Technology, Incheon, Republic of Korea.
Moon-Jo KimResearch Institute of Intelligent Manufacturing & Materials Technology, Korea Institute of Industrial Technology, Incheon, Republic of Korea.
DongEung KimResearch Institute of Intelligent Manufacturing & Materials Technology, Korea Institute of Industrial Technology, Incheon, Republic of Korea.
Chan Ho MoonDivision of Materials Science and Engineering, Hanyang University, Seoul, Republic of Korea.
Seojoon BangDivision of Materials Science and Engineering, Hanyang University, Seoul, Republic of Korea.
Hyeong Seok KangDivision of Materials Science and Engineering, Hanyang University, Seoul, Republic of Korea.
Ju Yeong GwonDepartment of Bioengineering, Hanyang University, Seoul, Republic of Korea.
Jong Hwa SeoDivision of Materials Science and Engineering, Hanyang University, Seoul, Republic of Korea.
Junhyub JeonResearch Institute of Intelligent Manufacturing & Materials Technology, Korea Institute of Industrial Technology, Incheon, Republic of Korea.
Junhyuk SonResearch Institute of Intelligent Manufacturing & Materials Technology, Korea Institute of Industrial Technology, Incheon, Republic of Korea.
Munwon LimResearch Institute of Intelligent Manufacturing & Materials Technology, Korea Institute of Industrial Technology, Incheon, Republic of Korea.
Minho KangDepartment of Biotechnology, The Catholic University of Korea, Bucheon, Republic of Korea.
Dong Yun LeeDepartment of Bioengineering, Hanyang University, Seoul, Republic of Korea.
Donghyun LimDepartment of Bioengineering, Hanyang University, Seoul, Republic of Korea.
Jung-Hoon ParkDepartment of Convergence Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Gi Doo ChaDepartment of Systems Biotechnology, Chung-Ang University, Anseong-si, Gyeonggi-do, Republic of Korea.
Soo-Hong LeeDepartment of Biomedical Engineering, Dongguk University, Seoul, Republic of Korea.
Tae-Sik JangSchool of Biomedical Convergence Engineering, Pusan National University, Yangsan, Republic of Korea.
Kisuk YangDivision of Bioengineering, College of Life Sciences and Bioengineering, Incheon National University, Incheon, Republic of Korea.
Yunho JeongDepartment of Organic and Nano Engineering, Human-Tech Convergence Program, Hanyang University, Seoul, Republic of Korea.
Youngho EomDepartment of Organic and Nano Engineering, Human-Tech Convergence Program, Hanyang University, Seoul, Republic of Korea.
Hyun-Do JungDivision of Materials Science and Engineering, Hanyang University, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0001-8632-7431

Funding

Korea Institute of Industrial Technology (KITECH) KITECHEH-26-0002Korea Institute of Industrial Technology (KITECH) KITECH UR-25-0112Korea Institute of Industrial Technology (KITECH) KITECHUR-26-0018Korea Institute of Marine Science and Technology promotion RS-2024-00405273Korean Fund for Regenerative Medicine (KFRM) KFRM 24A0105L1Korea Planning & Evaluation Institute of Industrial Technology (KEIT) and the Ministry of Trade, Industry & Energy (MOTIE) of the Republic of Korea RS-2024-00410959National Research Foundation of Korea RS-2024-00405381National Research Foundation of Korea RS-2025-00513935
6 · The paper itself

Abstract

Artificial intelligence (AI) integrated with bioinspired design enables the development of materials that adapt and dynamically respond to biological cues. In this study, a Drosera capensis-inspired thermo-responsive microneedle (MN) platform was developed, integrating motion, surface, and functional mimicry through AI-guided 4D printing. Shape memory polymers (SMPs) composed of tert-butyl acrylate (tBA) and 1,6-hexanediol diacrylate (HDDA) were designed to exhibit reversible shape recovery upon thermal stimulation. The complex shape-memory behavior was quantitatively modeled using multiple machine learning (ML) algorithms, including support vector regression (SVR), extreme gradient boosting (XGB), and Gaussian process regression (GPR). Among them, GPR demonstrated superior predictive accuracy (R

Indexed as

Artificial IntelligenceBiomimetic MaterialsNeedlesPrinting, Three-DimensionalWound HealingAnimalsDNAMicroneedle Drug DeliveryPolymersDNAPolymers4D printingadhesive DNAartificial intelligencebiomimicrychronic wound healing

Identifiers

PMID41910374
PMCPMC13361166

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.