Evidence map›Paper›PMID 40352349›Full record

ReviewFrontiers in bioengineering and biotechnology2025

Tendon regeneration deserves better: focused review on

Damla Aykora, Burak Taşçı, Muhammed Zahid Şahin, Ibrahim Tekeoğlu, Metehan Uzun, Victoria Sarafian, Denitsa Docheva

Abstract readReview
In one paragraph

Review in Frontiers in bioengineering and biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Review
  6. Article
  7. Review
  8. Article
  9. Tendon mechanobiology in the context of tendon biofabrication.Frontiers in bioengineering and biotechnology · 2025
    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

7 authors.

Damla AykoraHealth Services Vocational School, Department of Medical Services and Techniques, First and Emergency Aid, Bitlis Eren University, Bitlis, Türkiye.
Burak TaşçıVocational School of Technical Sciences, Fırat University, Elazığ, Türkiye.
Muhammed Zahid ŞahinFaculty of Medicine, Department of Physical Medicine and Rehabilitation, Sakarya University Training and Research Hospital, Sakarya University, Sakarya, Türkiye.
Ibrahim TekeoğluFaculty of Medicine, Department of Internal Medicine, Department of Physical Medicine and Rehabilitation, Kütahya Health Sciences University, Kütahya, Türkiye.
Metehan UzunHealth Services Vocational School, Department of Medical Services and Techniques, First and Emergency Aid, Bitlis Eren University, Bitlis, Türkiye.
Victoria SarafianDepartment of Medical Biology, Medical University-Plovdiv, Plovdiv, Bulgaria.
Denitsa DochevaDepartment of Musculoskeletal Tissue Regeneration, Orthopaedic Hospital König-Ludwig-Haus, Julius-Maximilians-University Würzburg, Wuerzburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tendon regeneration has been one of the most challenging issues in orthopedics. Despite various surgical techniques and rehabilitation methods, tendon tears or ruptures cannot wholly regenerate and gain the load-bearing capacity the tendon tissue had before the injury. The enhancement of tendon regeneration mostly requires grafting or an artificial tendon-like tissue to replace the damaged tendon. Tendon tissue engineering offers promising regenerative effects with numerous techniques in the additive manufacturing context. 3D bioprinting is a widely used additive manufacturing method to produce tendon-like artificial tissues based on biocompatible substitutes. There are multiple techniques and bio-inks for fabricating innovative scaffolds for tendon applications. Nevertheless, there are still many drawbacks to overcome for the successful regeneration of injured tendon tissue. The most important target is to catch the highest similarity to the tissue requirements such as anisotropy, porosity, viscoelasticity, mechanical strength, and cell-compatible constructs. To achieve the best-designed artificial tendon-like structure, novel AI-based systems in the field of 3D bioprinting may unveil excellent final products to re-establish tendon integrity and functionality. AI-driven optimization can enhance bio-ink selection, scaffold architecture, and printing parameters, ensuring better alignment with the biomechanical properties of native tendons. Furthermore, AI algorithms facilitate real-time process monitoring and adaptive adjustments, improving reproducibility and precision in scaffold fabrication. Thus,

Indexed as

AI systemsanimal modelsbiomaterialsscaffoldstendon regenerationtendon rupturethree-dimensional (3D) bioprintingtissue engineering

Identifiers

PMID40352349
PMCPMC12062838

What Socratic 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 Socratic graph.