Evidence map›Paper›PMID 37760908›Full record

ReviewBiomedicines2023

Signaling Mechanisms of Stem Cell Therapy for Intervertebral Disc Degeneration.

Xiaotian Du, Kejiong Liang, Shili Ding, Haifei Shi

Open access · goldAbstract readReview
In one paragraph

Review in Biomedicines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. 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

4 authors at 1 institution in 1 country.

Xiaotian DuDepartment of Orthopedic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.
Kejiong LiangDepartment of Orthopedic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.
Shili DingDepartment of Orthopedic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.
Haifei ShiDepartment of Orthopedic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.ORCID 0000-0001-8159-4610
First Affiliated Hospital Zhejiang University · CN

Funding

Health Science and Technology Program of Zhejiang Province 2021KY163National Natural Science Foundation of China 82272465Zhejiang Provincial Natural Science Foundation LY20H060008
6 · The paper itself

Abstract

Low back pain is the leading cause of disability worldwide. Intervertebral disc degeneration (IDD) is the primary clinical risk factor for low back pain and the pathological cause of disc herniation, spinal stenosis, and spinal deformity. A possible approach to improve the clinical practice of IDD-related diseases is to incorporate biomarkers in diagnosis, therapeutic intervention, and prognosis prediction. IDD pathology is still unclear. Regarding molecular mechanisms, cellular signaling pathways constitute a complex network of signaling pathways that coordinate cell survival, proliferation, differentiation, and metabolism. Recently, stem cells have shown great potential in clinical applications for IDD. In this review, the roles of multiple signaling pathways and related stem cell treatment in IDD are summarized and described. This review seeks to investigate the mechanisms and potential therapeutic effects of stem cells in IDD and identify new therapeutic treatments for IDD-related disorders.

Indexed as

intervertebral discsignaling pathwaystem cell treatmenttissue degeneration

Identifiers

PMID37760908
PMCPMC10525468
OpenAlexW4386485131

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.