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Bernoulli's Principle: Applications

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Design Example: Application of Archimedes' Principle

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Related Experiment Video

Updated: Feb 10, 2026

Fragmenting Bulk Hydrogels and Processing into Granular Hydrogels for Biomedical Applications

Fragmenting Bulk Hydrogels and Processing into Granular Hydrogels for Biomedical Applications

Published on: May 17, 2022

Hydrogel-Tissue Chemistry: Principles and Applications.

Viviana Gradinaru¹, Jennifer Treweek¹, Kristin Overton²

¹Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California 91125, USA;

Annual Review of Biophysics

|May 25, 2018

Summary

New hydrogel-tissue chemistry enables high-resolution data retrieval from animal systems. This approach preserves cellular and molecular information, advancing neuroscience and biological research.

Keywords:

CLARITY HTC clearing hydrogel-tissue hydrogels metareactant

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Last Updated: Feb 10, 2026

Fragmenting Bulk Hydrogels and Processing into Granular Hydrogels for Biomedical Applications

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Published on: May 17, 2022

The Synthesis of RGD-functionalized Hydrogels as a Tool for Therapeutic Applications

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Processing of Human Cardiac Tissue Toward Extracellular Matrix Self-assembling Hydrogel for In Vitro and In Vivo Applications

Processing of Human Cardiac Tissue Toward Extracellular Matrix Self-assembling Hydrogel for In Vitro and In Vivo Applications

Published on: December 4, 2017

Area of Science:

Biotechnology
Neuroscience
Systems Biology

Background:

Advancements in experimental techniques allow for detailed analysis of multicellular systems.
Hydrogel-tissue chemistry is emerging as a key process for preserving biological information.

Purpose of the Study:

To describe a novel experimental approach for high-resolution, high-content information retrieval from intact metazoan systems.
To highlight the utility of this approach in neuroscience for understanding sensation, cognition, and action.

Main Methods:

Utilizing hydrogel-tissue chemistry to create new chemical and physical forms.
Developing methods for retaining and retrieving phenotypic information, including gene expression and cellular activity.
Preserving spatial information such as three-dimensional positioning and neural connectivity.

Main Results:

Successful collection of rich datasets at single-cell resolution.
Demonstration of preserving crucial phenotypic information and interrelationships between cells and molecules.
Application in neuroscience revealing fundamental cellular and chemical representations of neural processes.

Conclusions:

The described approach enables unprecedented data retrieval from complex biological systems.
Reimagining metazoans as 'metareactants' drives innovation in biology and medicine.
This methodology is poised to significantly advance our understanding of biological functions at multiple scales.