ArticleIntegrative biology : quantitative biosciences from nano to macro2013
On being the right size: scaling effects in designing a human-on-a-chip.
Article in Integrative biology : quantitative biosciences from nano to macro, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 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
67 citing papers in PubMed, 133 citations in OpenAlex.
- Passage-Dependent Size Distributions of Human-Derived Cells: Implications for Metabolic Assays.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026Article
- Pillar arrays as tunable interfacial barriers for microphysiological systems.Communications engineering · 2025Article
- A 3D-printed multi-compartment organ-on-chip platform with a tubing-free pump models communication with the lymph node.Lab on a chip · 2025Article
- Tissue chips as headway model and incitement technology.Synthetic and systems biotechnology · 2025Review
- Targeted Cancer Therapy-on-A-Chip.Advanced healthcare materials · 2024Review
- Liver-on-chips for drug discovery and development.Materials today. Bio · 2024Review
- Mammalian Cell-Growth Monitoring Based on an Impedimetric Sensor and Image Processing within a Microfluidic Platform.Sensors (Basel, Switzerland) · 2023Article
- 3D engineered tissue models for studying human-specific infectious viral diseases.Bioactive materials · 2023Review
- Predictive Design and Analysis of Drug Transport by Multiscale Computational Models Under Uncertainty.Pharmaceutical research · 2023Review
- Joint-on-chip platforms: entering a new era of in vitro models for arthritis.Nature reviews. Rheumatology · 2022Review
- Studying metabolism with multi-organ chips: new tools for disease modelling, pharmacokinetics and pharmacodynamics.Open biology · 2022Review
- 2021 update on thyroid-associated ophthalmopathy.Journal of endocrinological investigation · 2022Review
- Scaling of joint mass and metabolism fluctuations in in silico cell-laden spheroids.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Patient-Specific Organoid and Organ-on-a-Chip: 3D Cell-Culture Meets 3D Printing and Numerical Simulation.Advanced biology · 2021Review
- Microphysiological systems: What it takes for community adoption.Experimental biology and medicine (Maywood, N.J.) · 2021Review
- Towards an Insulin Resistant Adipose Model on a Chip.Cellular and molecular bioengineering · 2021Article
- Studying Adipose Tissue in the Breast Tumor Microenvironment In Vitro: Progress and Opportunities.Tissue engineering and regenerative medicine · 2020Review
- Fat-On-A-Chip Models for Research and Discovery in Obesity and Its Metabolic Comorbidities.Tissue engineering. Part B, Reviews · 2020Review
- Fattening chips: hypertrophy, feeding, and fasting of human white adipocytesLab on a chip · 2020Article
- Microphysiological Systems: Design, Fabrication, and Applications.ACS biomaterials science & engineering · 2020Article
7 more citing papers are in PubMed but not listed here.
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 at 2 institutions in 2 countries.
Funding
Abstract
Developing a human-on-a-chip by connecting multiple model organ systems would provide an intermediate screen for therapeutic efficacy and toxic side effects of drugs prior to conducting expensive clinical trials. However, correctly designing individual organs and scaling them relative to each other to make a functional microscale human analog is challenging, and a generalized approach has yet to be identified. In this work, we demonstrate the importance of rational design of both the individual organ and its relationship with other organs, using a simple two-compartment system simulating insulin-dependent glucose uptake in adipose tissues. We demonstrate that inter-organ scaling laws depend on both the number of cells and the spatial arrangement of those cells within the microfabricated construct. We then propose a simple and novel inter-organ 'metabolically supported functional scaling' approach predicated on maintaining in vivo cellular basal metabolic rates by limiting resources available to cells on the chip. This approach leverages findings from allometric scaling models in mammals that limited resources in vivo prompt cells to behave differently than in resource-rich in vitro cultures. Although applying scaling laws directly to tissues can result in systems that would be quite challenging to implement, engineering workarounds may be used to circumvent these scaling issues. Specific workarounds discussed include the limited oxygen carrying capacity of cell culture media when used as a blood substitute and the ability to engineer non-physiological structures to augment organ function, to create the transport-accessible, yet resource-limited environment necessary for cells to mimic in vivo functionality. Furthermore, designing the structure of individual tissues in each organ compartment may be a useful strategy to bypass scaling concerns at the inter-organ level.
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.