ReviewCirculation research2023
Microfluidic Organ-Chips and Stem Cell Models in the Fight Against COVID-19.
Review in Circulation research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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.
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.
Who cites it
13 citing papers in PubMed, 21 citations in OpenAlex.
- Shear cytokine crosstalk is a determinant of SARS-CoV-2-induced endothelial pathophysiology and thrombosis in human vessel chips.Journal of thrombosis and haemostasis : JTH · 2026Article
- Review
- Organ-on-a-Chip Technology and Global Multi-Omics: Current Applications and Future Directions.MedComm · 2026Review
- AI-driven drug reposition for pathogens: a new paradigm in pandemic preparedness.Frontiers in chemistry · 2026Review
- Current knowledge on the host-pathogen interactions of henipaviruses and novel platforms to enable further characterisation.EBioMedicine · 2026Review
- Article
- Decoding long COVID-associated cardiovascular dysfunction: Mechanisms, models, and new approach methodologies.Journal of molecular and cellular cardiology · 2025Review
- Machine learning-assisted point-of-care diagnostics for cardiovascular healthcare.Bioengineering & translational medicine · 2025Review
- Article
- Evaluation of Pm2.5 Influence on Human Lung Cancer Cells Using a Microfluidic Platform.International journal of medical sciences · 2024Article
- Complex in vitro Model: A Transformative Model in Drug Development and Precision Medicine.Clinical and translational science · 2023Review
- Alternatives to animal models to study bacterial infections.Folia microbiologica · 2023Review
- COVID-19 and the Cardiovascular System:Circulation research · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 3 countries.
Funding
Abstract
SARS-CoV-2, the virus underlying COVID-19, has now been recognized to cause multiorgan disease with a systemic effect on the host. To effectively combat SARS-CoV-2 and the subsequent development of COVID-19, it is critical to detect, monitor, and model viral pathogenesis. In this review, we discuss recent advancements in microfluidics, organ-on-a-chip, and human stem cell-derived models to study SARS-CoV-2 infection in the physiological organ microenvironment, together with their limitations. Microfluidic-based detection methods have greatly enhanced the rapidity, accessibility, and sensitivity of viral detection from patient samples. Engineered organ-on-a-chip models that recapitulate in vivo physiology have been developed for many organ systems to study viral pathology. Human stem cell-derived models have been utilized not only to model viral tropism and pathogenesis in a physiologically relevant context but also to screen for effective therapeutic compounds. The combination of all these platforms, along with future advancements, may aid to identify potential targets and develop novel strategies to counteract COVID-19 pathogenesis.
Indexed as
Identifiers
What Socratic holds
Registered trials
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.