ReviewAnnual review of biochemistry2017
Conceptual and Experimental Tools to Understand Spatial Effects and Transport Phenomena in Nonlinear Biochemical Networks Illustrated with Patchy Switching.
Review in Annual review of biochemistry, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled 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.
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
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Modeling Immunity In Vitro: Slices, Chips, and Engineered Tissues.Annual review of biomedical engineering · 2021Pooled it
- Mechanistic insights of smart biofilms in environmental bio-monitoring: from growth to detection.Microbial cell factories · 2026Review
- Cellular Adaptation to Mechanical Stress Emerges via Cell Shrinkage Triggered by Nonlinear Calcium Elevation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Towards spatially-organized organs-on-chip: Photopatterning cell-laden thiol-ene and methacryloyl hydrogels in a microfluidic device.Organs-on-a-chip · 2022Article
- LncRNA LINC00525 suppresses p21 expression via mRNA decay and triplex-mediated changes in chromatin structure in lung adenocarcinoma.Cancer communications (London, England) · 2021Article
- Acute Lymph Node Slices Are a Functional Model System to Study Immunity Ex Vivo.ACS pharmacology & translational science · 2021Article
- Spatially Resolved Analytical Chemistry in Intact, Living Tissues.Analytical chemistry · 2020Review
- User-defined local stimulation of live tissue through a movable microfluidic port.Lab on a chip · 2018Article
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
Many biochemical systems are spatially heterogeneous and exhibit nonlinear behaviors, such as state switching in response to small changes in the local concentration of diffusible molecules. Systems as varied as blood clotting, intracellular calcium signaling, and tissue inflammation are all heavily influenced by the balance of rates of reaction and mass transport phenomena including flow and diffusion. Transport of signaling molecules is also affected by geometry and chemoselective confinement via matrix binding. In this review, we use a phenomenon referred to as patchy switching to illustrate the interplay of nonlinearities, transport phenomena, and spatial effects. Patchy switching describes a change in the state of a network when the local concentration of a diffusible molecule surpasses a critical threshold. Using patchy switching as an example, we describe conceptual tools from nonlinear dynamics and chemical engineering that make testable predictions and provide a unifying description of the myriad possible experimental observations. We describe experimental microfluidic and biochemical tools emerging to test conceptual predictions by controlling transport phenomena and spatial distribution of diffusible signals, and we highlight the unmet need for in vivo tools.
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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.