Evidence map›Paper›PMID 38111377›Full record

ArticleSmall methods2024

Nested Biofabrication: Matryoshka-Inspired Intra-Embedded Bioprinting.

Mecit Altan Alioglu, Yasar Ozer Yilmaz, Yogendra Pratap Singh, Momoka Nagamine, Nazmiye Celik, Myoung Hwan Kim, Vaibhav Pal, Deepak Gupta, Ibrahim T Ozbolat

Open access · hybridAbstract read
In one paragraph

Article in Small methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.4field-weighted citation impact, top 20% of its field
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

10 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Deposition Volume Compensation for Enhanced Shape Fidelity in Nested Printing.Journal of manufacturing science and engineering · 2025
    Article
  5. 3D Printing of Air.Research square · 2025
    Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 1 institution in 2 countries.

Mecit Altan AliogluThe Huck Institutes of the Life Sciences, Penn State University, University Park, PA, 16802, USA.
Yasar Ozer YilmazThe Huck Institutes of the Life Sciences, Penn State University, University Park, PA, 16802, USA.
Yogendra Pratap SinghThe Huck Institutes of the Life Sciences, Penn State University, University Park, PA, 16802, USA.
Momoka NagamineThe Huck Institutes of the Life Sciences, Penn State University, University Park, PA, 16802, USA.
Nazmiye CelikThe Huck Institutes of the Life Sciences, Penn State University, University Park, PA, 16802, USA.
Myoung Hwan KimThe Huck Institutes of the Life Sciences, Penn State University, University Park, PA, 16802, USA.
Vaibhav PalThe Huck Institutes of the Life Sciences, Penn State University, University Park, PA, 16802, USA.
Deepak GuptaThe Huck Institutes of the Life Sciences, Penn State University, University Park, PA, 16802, USA.
Ibrahim T OzbolatThe Huck Institutes of the Life Sciences, Penn State University, University Park, PA, 16802, USA.ORCID 0000-0001-8328-4528
Pennsylvania State University · US

Funding

Technology Development Project - Increasing the complexity of ex vivo human airway models for studying immune response to viral infectionU19AI142733 · NIAID · JACKSON LABORATORY · PI Anna Karolina Palucka · 2019 to 2026
$23.1M
Intraoperative bioprinting of composite tissues with zonal stratification for craniomaxillofacial reconstructionR01DE028614 · NIDCR · PENNSYLVANIA STATE UNIVERSITY, THE · PI OZBOLAT, IBRAHIM · 2020 to 2024
$2.8M
High-throughput Spheroid Bioprinting Technology for Scalable Fabrication of TissuesR01EB034566 · NIBIB · PENNSYLVANIA STATE UNIVERSITY, THE · PI Ibrahim Ozbolat · 2023 to 2026
$2.2M
Directorate for Engineering 1914885Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases U19AI142733NIAID NIH HHS U19 AI142733NIBIB NIH HHS R01 EB034566NIBIB NIH HHS R01EB034566NIDCR NIH HHS R01 DE028614NIDCR NIH HHS R01DE028614TUBITAK 121C359
6 · The paper itself

Abstract

Engineering functional tissues and organs remains a fundamental pursuit in bio-fabrication. However, the accurate constitution of complex shapes and internal anatomical features of specific organs, including their intricate blood vessels and nerves, remains a significant challenge. Inspired by the Matryoshka doll, here a new method called "Intra-Embedded Bioprinting (IEB)" is introduced building upon existing embedded bioprinting methods. a xanthan gum-based material is used which served a dual role as both a bioprintable ink and a support bath, due to its unique shear-thinning and self-healing properties. IEB's capabilities in organ modeling, creating a miniaturized replica of a pancreas using a photocrosslinkable silicone composite is demonstrated. Further, a head phantom and a Matryoshka doll are 3D printed, exemplifying IEB's capability to manufacture intricate, nested structures. Toward the use case of IEB and employing an innovative coupling strategy between extrusion-based and aspiration-assisted bioprinting, a breast tumor model that included a central channel mimicking a blood vessel, with tumor spheroids bioprinted in proximity is developed. Validation using a clinically-available chemotherapeutic drug illustrated its efficacy in reducing the tumor volume via perfusion over time. This method opens a new way of bioprinting enabling the creation of complex-shaped organs with internal anatomical features.

Indexed as

BioprintingPrinting, Three-DimensionalTissue EngineeringBreast NeoplasmsFemaleHumansPancreasPolysaccharides, BacterialSpheroids, CellularTissue ScaffoldsPolysaccharides, Bacterialxanthan gumbioprintingcancer‐on‐a‐chipintra‐embedded bioprintingorgan modeling

Identifiers

PMID38111377
PMCPMC11187694
OpenAlexW4389938685

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.