Evidence map›Paper›PMID 42194271›Full record

ReviewBioengineering (Basel, Switzerland)2026

Bone Tissue Engineering: Scaffold Design Principles, Biomaterial Advances, and Strategies for Functional Regeneration and Clinical Translation.

Naznin Sultana

Abstract readReview
In one paragraph

Review in Bioengineering (Basel, Switzerland), 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. Article
  2. Review
  3. Review
  4. Review
  5. Review
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

1 author.

Naznin SultanaTexas Undergraduate Medical Academy, School of Public and Allied Health, Prairie View A&M University, Texas A&M University System, Prairie View, TX 77446, USA.ORCID 0000-0001-6036-7865

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bone is a hierarchically organized composite material with unique mechanical properties and an intrinsic regenerative capacity that conventional repair strategies, including autografts, allografts, xenografts, and metallic or ceramic implants, fail to fully replicate due to donor scarcity, immunogenicity, mechanical mismatch, and poor long-term integration. Bone tissue engineering (TE) offers a biologically informed alternative by integrating osteoconductive scaffolds, osteogenic progenitor cells, and osteoinductive signaling molecules into a unified regenerative framework. Unlike existing reviews that evaluate these components in isolation, this review provides a mechanistically integrated analysis that repositions scaffold design as a biologically instructive platform whose topography, stiffness, porosity, and surface chemistry collectively govern cell adhesion, mechanotransduction, osteogenic differentiation, and extracellular matrix remodeling. Critically, it moves beyond cataloging materials and fabrication approaches to evaluate how specific scaffold features drive biological outcomes and to identify frequently understated limitations, including polymer-ceramic degradation kinetics and the inadequacy of small-animal models for clinical translation. By synthesizing advances in biomaterials, additive manufacturing, and smart scaffold technologies within this integrative framework, this review provides researchers and clinicians with a structured framework for evaluating emerging strategies and prioritizing future directions in functional bone regeneration.

Indexed as

bone graft substitutesbone tissue engineeringosteoconductionregenerative medicinescaffold design

Identifiers

PMID42194271
PMCPMC13203364

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.