Evidence map›Paper›PMID 40583370›Full record

ReviewAdvanced healthcare materials2025

Microphysiological Systems for Comorbidity Studies: Chronic Kidney Disease and Osteoarthritis.

Mingying Han, Weiping Lin, Yuanxiong Cao, Patricia Murray, Bettina Wilm, Stephen J McWilliam, Jude Curran, Ruoxiao Xie

Abstract readReview
In one paragraph

Review in Advanced healthcare materials, 2025. 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. Review
  2. Review
  3. Article
  4. 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.

Mingying HanDepartment of Materials, Design and Manufacturing Engineering, School of Engineering, University of Liverpool, Liverpool, L69, UK.ORCID https://orcid.org/0000-0002-5251-2337
Weiping LinCentre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation, CAS Ltd., Fifth Affiliated Hospital of Guangzhou Medical University, China.ORCID https://orcid.org/0000-0002-8772-3919
Yuanxiong CaoDepartment of Physiology, Anatomy and Genetics, Kavli Institute for Nanoscience Discovery, University of Oxford, Oxford, OX1 3QU, UK.
Patricia MurrayDepartment of Women's and Children's Health, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, L69, UK.
Bettina WilmDepartment of Women's and Children's Health, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, L69, UK.
Stephen J McWilliamDepartment of Women's and Children's Health, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, L69, UK.
Jude CurranDepartment of Materials, Design and Manufacturing Engineering, School of Engineering, University of Liverpool, Liverpool, L69, UK.
Ruoxiao XieDepartment of Materials, Design and Manufacturing Engineering, School of Engineering, University of Liverpool, Liverpool, L69, UK.ORCID https://orcid.org/0009-0000-1000-8960

Funding

China Scholarship CouncilHong Kong SAR Research Grants Council 14108720Hong Kong SAR Research Grants Council C7030-18GRoyal Society RGS∖R2∖242300
6 · The paper itself

Abstract

The global increase in chronic diseases and comorbidities due to aging populations is placing significant strain on healthcare systems. Chronic kidney disease (CKD) and osteoarthritis (OA) are among the most prevalent conditions in the elderly, with complex interconnections driven by shared risk factors such as systemic inflammation and metabolic dysregulation. Despite the critical need to understand these interactions, traditional animal models often fail to adequately capture the multidirectional crosstalk between human comorbid conditions, limiting insights into their mechanisms and complicating translational research. Advancements in microphysiological systems (MPS), which also known as organ-on-a-chip (OoC) technologies, offer a promising alternative for studying comorbidities, such as CKD-OA. MPS, which integrate human cells within biomimetic, bioengineered platforms, replicate the structural and functional properties of human tissues with unparalleled physiological relevance. This review explores the transformative potential of MPS technology in comorbidity research, focusing on CKD-OA as a case study. Kidney-on-a-chip and joint-on-a-chip models and their applications in CKD and OA modeling are summarized and discussed. Furthermore, multi-organ-on-a-chip systems are = discussed for their potential to model comorbidities = and support the development of safer and more effective disease treatment strategies. This review underscores the potential of MPS to revolutionize comorbidity research and pave the way for personalized therapies.

Indexed as

Lab-On-A-Chip DevicesOsteoarthritisRenal Insufficiency, ChronicAnimalsComorbidityHumansMicrophysiological Systemschronic kidney diseasecomorbiditymicrophysiological systemmulti‐organ‐on‐a‐chiporgan‐on‐a‐chiposteoarthritis

Identifiers

PMID40583370
PMCPMC12683232

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.