Evidence map›Paper›PMID 38311627›Full record

ReviewBone research2024

Spatial analysis of the osteoarthritis microenvironment: techniques, insights, and applications.

Xiwei Fan, Antonia Rujia Sun, Reuben S E Young, Isaac O Afara, Brett R Hamilton, Louis Jun Ye Ong, Ross Crawford, Indira Prasadam

Open access · goldAbstract readReview
In one paragraph

Review in Bone research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 1 pooled it
21.6field-weighted citation impact, top 1% 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

44 citing papers in PubMed, 1 synthesis or guideline pooled it, 46 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Review
  6. Review
  7. Article
  8. Review
  9. Review
  10. Review
  11. Review
  12. Article
  13. Transcriptomics in the Study of Bone and Cartilage.Current osteoporosis reports · 2026
    Review
  14. Article
  15. Review
  16. Article
  17. Review
  18. Review
  19. Article
  20. 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

8 authors at 2 institutions in 2 countries.

Xiwei FanCentre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia.
Antonia Rujia SunCentre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia.
Reuben S E YoungCentral Analytical Research Facility, Queensland University of Technology, Brisbane, QLD, Australia.
Isaac O AfaraDepartment of Technical Physics, University of Eastern Finland, Kuopio, Finland.ORCID 0000-0001-7114-0439
Brett R HamiltonCentre for Microscopy and Microanalysis, University of Queensland, Brisbane, QLD, Australia.
Louis Jun Ye OngCentre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia.
Ross CrawfordCentre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia.
Indira PrasadamCentre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia. i.prasadam@qut.edu.au.
Queensland University of Technology · AUThe University of Queensland · AU

Funding

Academy of Finland (Suomen Akatemia) 315820Department of Health | National Health and Medical Research Council (NHMRC) APP1176298Jane ja Aatos Erkon Säätiö (Jane and Aatos Erkko Foundation) 190001
6 · The paper itself

Abstract

Osteoarthritis (OA) is a debilitating degenerative disease affecting multiple joint tissues, including cartilage, bone, synovium, and adipose tissues. OA presents diverse clinical phenotypes and distinct molecular endotypes, including inflammatory, metabolic, mechanical, genetic, and synovial variants. Consequently, innovative technologies are needed to support the development of effective diagnostic and precision therapeutic approaches. Traditional analysis of bulk OA tissue extracts has limitations due to technical constraints, causing challenges in the differentiation between various physiological and pathological phenotypes in joint tissues. This issue has led to standardization difficulties and hindered the success of clinical trials. Gaining insights into the spatial variations of the cellular and molecular structures in OA tissues, encompassing DNA, RNA, metabolites, and proteins, as well as their chemical properties, elemental composition, and mechanical attributes, can contribute to a more comprehensive understanding of the disease subtypes. Spatially resolved biology enables biologists to investigate cells within the context of their tissue microenvironment, providing a more holistic view of cellular function. Recent advances in innovative spatial biology techniques now allow intact tissue sections to be examined using various -omics lenses, such as genomics, transcriptomics, proteomics, and metabolomics, with spatial data. This fusion of approaches provides researchers with critical insights into the molecular composition and functions of the cells and tissues at precise spatial coordinates. Furthermore, advanced imaging techniques, including high-resolution microscopy, hyperspectral imaging, and mass spectrometry imaging, enable the visualization and analysis of the spatial distribution of biomolecules, cells, and tissues. Linking these molecular imaging outputs to conventional tissue histology can facilitate a more comprehensive characterization of disease phenotypes. This review summarizes the recent advancements in the molecular imaging modalities and methodologies for in-depth spatial analysis. It explores their applications, challenges, and potential opportunities in the field of OA. Additionally, this review provides a perspective on the potential research directions for these contemporary approaches that can meet the requirements of clinical diagnoses and the establishment of therapeutic targets for OA.

Indexed as

OsteoarthritisHumansMetabolomicsPhenotypeProteomicsSynovial Membrane

Identifiers

PMID38311627
PMCPMC10838951
OpenAlexW4391521761

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.