Evidence map›Paper›PMID 40213438›Full record

ArticleSmall science2024

Multi-Organ Microphysiological Systems Targeting Specific Organs for Recapitulating Disease Phenotypes via Organ Crosstalk.

Joeng Ju Kim, Mihyeon Bae, Dong-Woo Cho

Abstract read
In one paragraph

Article in Small science, 2024. 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
–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

6 citing papers in PubMed.

  1. 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

3 authors.

Joeng Ju KimDepartment of Mechanical Engineering Pohang University of Science and Technology (POSTECH) Pohang Kyungbuk 37673 Republic of Korea.
Mihyeon BaeDepartment of Mechanical Engineering Pohang University of Science and Technology (POSTECH) Pohang Kyungbuk 37673 Republic of Korea.
Dong-Woo ChoDepartment of Mechanical Engineering Pohang University of Science and Technology (POSTECH) Pohang Kyungbuk 37673 Republic of Korea.ORCID https://orcid.org/0000-0001-5869-4330

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Various systemic metabolic diseases arise from prolonged crosstalk across multiple organs, triggering serious impairments in various physiological systems. These diseases are intricate systemic pathologies characterized by complex mechanisms and an unclear etiology, making the treatment challenging. Efforts have been made to develop in vitro models to understand these diseases and devise new treatments. However, there are limitations in reconstructing the causal relationships between diseases and interorgan crosstalk, including the tissue-specific microenvironment. Alternatively, multi-organ microphysiological systems (MOMPS) present new possibilities for capturing the complexity of systemic metabolic diseases by replicating human microphysiology and simulating diverse interorgan crosstalk. Controlled interactions and scalable representations of biological complexity in MOMPS offer a more accurate portrayal of organ interactions, enabling the identification of novel relationships between organ crosstalk, metabolism, and immunity. This, in turn, can yield valuable insights into disease mechanisms and drug development research and enhance the efficiency of preclinical studies. In this review, the examples and technical capabilities of MOMPS pathological modeling for various diseases are discussed, leveraging state-of-the-art biofabrication technology of MOMPS. It evaluates the current opportunities and challenges in this field.

Indexed as

biofabricationsbiomaterialsdisease in vitro modelsmulti‐organ microphysiological systemsorgans on‐a‐chip

Identifiers

PMID40213438
PMCPMC11935247

What OpenQuestion holds

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Registered trials

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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.