Evidence map›Paper›PMID 29511444›Full record

ArticleAmerican journal of translational research2018

Functional peptides for cartilage repair and regeneration.

Qisong Liu, Zhaofeng Jia, Li Duan, Jianyi Xiong, Daping Wang, Yue Ding

Abstract read
In one paragraph

Article in American journal of translational research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Therapeutic Peptides in Orthopaedics: Applications, Challenges, and Future Directions.Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews · 2026
    Review
  2. Frontiers in bioengineering and biotechnology · 2023
    Article
  3. Review
  4. 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

6 authors.

Qisong LiuDepartment of Orthopedic, Memorial Hospital of Sun Yat-sen UniversityGuangzhou 510120, Guangdong Province, China.
Zhaofeng JiaShenzhen Key Laboratory of Tissue Engineering, Shenzhen Second People's HospitalShenzhen 518035, Guangdong Province, China.
Li DuanShenzhen Key Laboratory of Tissue Engineering, Shenzhen Second People's HospitalShenzhen 518035, Guangdong Province, China.
Jianyi XiongShenzhen Key Laboratory of Tissue Engineering, Shenzhen Second People's HospitalShenzhen 518035, Guangdong Province, China.
Daping WangShenzhen Key Laboratory of Tissue Engineering, Shenzhen Second People's HospitalShenzhen 518035, Guangdong Province, China.
Yue DingDepartment of Orthopedic, Memorial Hospital of Sun Yat-sen UniversityGuangzhou 510120, Guangdong Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cartilage repair after degeneration or trauma continues to be a challenge both in the clinic and for scientific research due to the limited regenerative capacity of this tissue. Cartilage tissue engineering, involving a combination of cells, scaffolds, and growth factors, is increasingly used in cartilage regeneration. Due to their ease of synthesis, robustness, tunable size, availability of functional groups, and activity, peptides have emerged as the molecules with the most potential in drug development. A number of peptides have been engineered to regenerate cartilage by acting as scaffolds, functional molecules, or both. In this paper, we will summarize the application of peptides in cartilage tissue engineering and discuss additional possibilities for peptides in this field.

Indexed as

cartilage repaircartilage tissue engineeringmesenchy-mal stem cellsPeptidepeptide hydrogeltransforming growth factor-β

Identifiers

PMID29511444
PMCPMC5835815

What OpenQuestion holds

Textmetadata
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.