ReviewMicromachines2021
Diversity Models and Applications of 3D Breast Tumor-on-a-Chip.
Review in Micromachines, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Emerging Nano Bioinks in Bioprinting: Functional Materials, Engineering Strategies, and Biomedical Applications.Materials (Basel, Switzerland) · 2026Review
- Article
- Design strategy primer for organ-on-chips.Biomaterials translational · 2025Article
- Advancement in Cancer Vasculogenesis Modeling through 3D Bioprinting Technology.Biomimetics (Basel, Switzerland) · 2024Review
- Exploring the interaction between extracellular matrix components in a 3D organoid disease model to replicate the pathophysiology of breast cancer.Journal of experimental & clinical cancer research : CR · 2023Review
- Patient-derived tumor models and their distinctive applications in personalized drug therapy.Mechanobiology in medicine · 2023Review
- Three Dimensional Models of Endocrine Organs and Target Tissues Regulated by the Endocrine System.Cancers · 2023Review
- The Variety of 3D Breast Cancer Models for the Study of Tumor Physiology and Drug Screening.International journal of molecular sciences · 2023Review
- Recent Advances of Organ-on-a-Chip in Cancer Modeling Research.Biosensors · 2022Review
- Tissue clearing of human iPSC-derived organ-chips enables high resolution imaging and analysis.Lab on a chip · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Breast disease is one of the critical diseases that plague females, as is known, breast cancer has high mortality, despite significant pathophysiological progress during the past few years. Novel diagnostic and therapeutic approaches are needed to break the stalemate. An organ-on-chip approach is considered due to its ability to repeat the real conditions found in the body on microfluidic chips, offsetting the shortcomings of traditional 2D culture and animal tests. In recent years, the organ-on-chip approach has shown diversity, recreating the structure and functional units of the real organs/tissues. The applications were also developed rapidly from the laboratory to the industrialized market. This review focuses on breast tumor-on-a-chip approaches concerning the diversity models and applications. The models are summarized and categorized by typical biological reconstitution, considering the design and fabrication of the various breast models. The breast tumor-on-a-chip approach is a typical representative of organ chips, which are one of the precedents in the market. The applications are roughly divided into two categories: fundamental mechanism research and biological medicine. Finally, we discuss the prospect and deficiencies of the emerging technology. It has excellent prospects in all of the application fields, however there exist some deficiencies for promotion, such as the stability of the structure and function, and uniformity for quantity production.
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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.