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Merck

VIV401004

SynVivo SynRAM 3D Inflammation model starter kit, microvascular network configuration, includes pneumatic priming device

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About This Item

UNSPSCコード:
60104506
NACRES:
NA.84

包装

case of 1 ea

メーカー/製品名

SynVivo 401004

保管温度

room temp

詳細

10 - SMN2 C001 SynRAM 50 μm gap, 3 μm height pillar barrier chips, 100 ft Tygon Tubing, 25 pack - Slide Clamps, 50 pack - 1 mL Syringe with Luer-Lok Tip, 50 pack - 24 Gauge Needle x 0.5 in long, SynVivo Pneumatic Primer, 2 - Five Stopcock Manifold 4-Way all FLL

The SynRAM 3D Inflammation Model from SynVivo has been developed to study the entire inflammation pathway in a realistic and dynamic environment. By recreating a histological slice of co-cultured tissue and/or tumor cells with a lumen of endothelial cells, the SynVivo platform delivers a physiologically realistic model including flow and shear in a platform and enables real-time tracking of rolling, adhesion and migration processes. This model has been successfully validated against in vivo studies showing excellent correlation with rolling velocities, adhesion patterns and migratory processes (Lamberti et al 2014, Soroush et al 2016).

The SynRAM 3D inflammation model provides a realistic testing environment including:

  • Physiological shear stress within a microvascular environment
  • In vivo like vascular morphology with fully enclosed lumen
  • Co-culture capability for cell-cell interactions
  • Quantitative real-time rolling, adhesion, and migration data from a single experiment

SynRAM′s innovative design overcomes the current limitations inherent in flow chambers or Transwell chamber based assays. Current flow chamber designs are oversimplified, lack the scale and geometry of the microenvironment and cannot model transmigration. Similarly, Transwell chambers do not account for fluid shear and size/topology observed in vivo, the end point measurements of migration are not reproducible and do not provide real-time visualization.

SynVivo′s proprietary chip designs range from complex in vivo derived microvascular networks (obtained from digitized images) to produce realistic cellular makeup and vascular morphology resulting in varying shear and flow conditions, to simplified idealized networks designed to reproduce the cellular makeup and constant shear and flow conditions.

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