ReviewNano convergence2024
Integration of nanobiosensors into organ-on-chip systems for monitoring viral infections.
Review in Nano convergence, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- AI-driven text mining of the female reproductive system: enabling multiscale biomedical modeling and personalized medicine.Nano convergence · 2026Review
- Biosensor applications in organ-on-a-chip platforms and disease modeling.Frontiers in bioengineering and biotechnology · 2026Review
- Current knowledge on the host-pathogen interactions of henipaviruses and novel platforms to enable further characterisation.EBioMedicine · 2026Review
- Engineering an immune-integrated lung-on-a-chip to reveal TOX-RAGE axis-driven fibrosis and RAGE blockade as a therapeutic strategy.Nano convergence · 2025Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
The integration of nanobiosensors into organ-on-chip (OoC) models offers a promising advancement in the study of viral infections and therapeutic development. Conventional research methods for studying viral infection, such as two-dimensional cell cultures and animal models, face challenges in replicating the complex and dynamic nature of human tissues. In contrast, OoC systems provide more accurate, physiologically relevant models for investigating viral infections, disease mechanisms, and host responses. Nanobiosensors, with their miniaturized designs and enhanced sensitivity, enable real-time, continuous, in situ monitoring of key biomarkers, such as cytokines and proteins within these systems. This review highlights the need for integrating nanobiosensors into OoC systems to advance virological research and improve therapeutic outcomes. Although there is extensive literature on biosensors for viral infection detection and OoC models for replicating infections, real integration of biosensors into OoCs for continuous monitoring remains unachieved. We discuss the advantages of nanobiosensor integration for real-time tracking of critical biomarkers within OoC models, key biosensor technologies, and current OoC systems relevant to viral infection studies. Additionally, we address the main technical challenges and propose solutions for successful integration. This review aims to guide the development of biosensor-integrated OoCs, paving the way for precise diagnostics and personalized treatments in virological research.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.