Passive Clearing Kit

New to tissue clearing?

Try the most versatile passive clearing method there is with our simple and reliable kit that includes everything you need! The bundle includes all the ready-made solutions to preserve, clear, and index-match your samples with ease for 3-D imaging and analysis. The Passive Clearing Kit does not require the use of specialized tissue processing equipment such as the SmartClear II Pro or SmartLabel

We offer two different kit sizes:

  • 250 mL Kit: 250 mL SHIELD, 250 mL Passive Clearing Buffer, 250 mL EasyIndex. Capacity to process 8 or more mouse brains.
  • 500 mL Kit: 500 mL SHIELD, 500 mL Passive Clearing Buffer, 500 mL EasyIndex. Capacity to process 16 or more mouse brains.

Our reagents preserve fluorescent proteins, reduce autofluorescence, and optimally prepare samples for immunostaining and imaging. Download the protocol to learn more about passive tissue processing best practices.

Once you have some experience with passive clearing, drastically increase your clearing speed and sample throughput by upgrading to electrophoretic clearing with SmartClear II Pro. To learn more about the benefits of active clearing and active labeling using LifeCanvas products, refer to our blog.

Related blog posts

Cleared lung tissue allowing visualization of the collagen structure and matrix of lung tissue at 20x magnification. Bharat et al., 2021.

How 3D tissue clearing benefits COVID-19 research

Over 190 million people have now been infected with the novel coronavirus SARS-CoV-2 in the ongoing coronavirus disease (COVID-19) pandemic with a total number of deaths passing 4.1 million worldwide. Multiple organs are affected by COVID-19, however, the lungs are the main site of disease.

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Mouse brain viral expression

Recent publications leverage 3D histology to provide new insights into neuronal circuitry

The goal of histology has long been to interrogate complex structures in whole tissue samples. Over centuries, slicing of samples for traditional two-dimensional histology has been indispensable in understanding the structure and morphology of multiple tissue types. However, this approach is limited to yielding images in thin tissue sections, is time-consuming and is error-prone due to tissue distortion and information loss.

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