Evidence map›Paper›PMID 38057475›Full record

ReviewNature reviews. Rheumatology2024

Profiling joint tissues at single-cell resolution: advances and insights.

Akshay Pandey, Nidhi Bhutani

Open access · greenAbstract readReview
In one paragraph

Review in Nature reviews. Rheumatology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
3.2field-weighted citation impact, top 8% 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

24 citing papers in PubMed, 21 citations in OpenAlex.

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  17. Spatial transcriptomic applications in orthopedics.Connective tissue research · 2025
    Review
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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

2 authors at 2 institutions in 1 country.

Akshay PandeyDepartment of Orthopaedic Surgery, School of Medicine, Stanford University, Stanford, CA, USA.
Nidhi BhutaniDepartment of Orthopaedic Surgery, School of Medicine, Stanford University, Stanford, CA, USA. nbhutani@stanford.edu.ORCID http://orcid.org/0000-0002-7494-5870
Stanford Medicine · USStanford University · US

Funding

Establishing a Single-Cell Proteomic Atlas for Normal and Osteoarthritic Articular CartilageR01AR077530 · NIAMS · STANFORD UNIVERSITY · PI BHUTANI, NIDHI · 2021 to 2025
$2.6M
NIAMS NIH HHS R01 AR077530
6 · The paper itself

Abstract

Advances in the profiling of human joint tissues at single-cell resolution have provided unique insights into the organization and function of these tissues in health and disease. Data generated by various single-cell technologies, including single-cell RNA sequencing and cytometry by time-of-flight, have identified the distinct subpopulations that constitute these tissues. These timely studies have provided the building blocks for the construction of single-cell atlases of joint tissues including cartilage, bone and synovium, leading to the identification of developmental trajectories, deciphering of crosstalk between cells and discovery of rare populations such as stem and progenitor cells. In addition, these studies have revealed unique pathogenetic populations that are potential therapeutic targets. The use of these approaches in synovial tissues has helped to identify how distinct cell subpopulations can orchestrate disease initiation and progression and be responsible for distinct pathological outcomes. Additionally, repair of tissues such as cartilage and meniscus remains an unmet medical need, and single-cell methodologies can be invaluable in providing a blueprint for both effective tissue-engineering strategies and therapeutic interventions for chronic joint diseases such as osteoarthritis and rheumatoid arthritis.

Indexed as

Arthritis, RheumatoidMeniscusOsteoarthritisHumansSynovial MembraneTissue Engineering

Identifiers

PMID38057475
PMCPMC11674069
OpenAlexW4389381361

What OpenQuestion holds

Textmetadata
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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.