Porcine skin gelatin
Porcine skin gelatin is a type of gelatin derived from the skin of pigs. It is a natural, protein-based material that is commonly used in various applications, including as a component in laboratory equipment and procedures.
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Market Availability & Pricing
Porcine skin gelatin is an officially listed product from Merck Group and available through their authorized distributors. The product is currently commercialized and pricing typically ranges from $50 to $200, depending on the quantity and specific variant.
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Get pricing insights and sourcing optionsSpelling variants (same manufacturer)
Similar products (other manufacturers)
The spelling variants listed below correspond to different ways the product may be referred to in scientific literature.
These variants have been automatically detected by our extraction engine, which groups similar formulations based on semantic similarity.
Product FAQ
107 protocols using «porcine skin gelatin»
Fabrication of Synthetic Posterior Lens Capsule
Visualizing FCV Infection in CrFK Cells
Inhibition ELISA for rSola l 7 Antibody Binding
Photocrosslinkable Chitosan-Based Hydrogel
3D Vascular Mapping and Pericyte Analysis
We utilized our previously described software pipeline to perform de-aberration, normalization, and imaging stitching steps for all STPT data collected for this study29 (link). Moreover, we used the same analytical tools to binarize the vessel signals and skeletonize for further analysis. This pipeline also performs cleaning/reconnecting of artifacts, traces the vessel diameter, and finally outputs the coordinates for each vessel segment and its connectivity. The distance to the nearest vasculature is calculated by probing all tissue space in the data and finding the average distance to its nearest vasculature surface. For every point being probed, we first take all the vasculature data within the +/− 100 µm cartesian coordinated cube and calculate the straight-line distance between the probe and each vascular data point inside the cube. Then we take the minimum of those distances as the distance to the nearest vasculature for that probing point. We performed our calculation at 10 µm isotropic voxel resolution probing, which provides enough data entry for each ROI that is at least 100 µm in size. For pericyte cell counting, we used previously developed Deep Learning Neural Network (DLNN) cell counting29 (link). This DLNN uses a per-cell multi-resolution-hybrid ResNet classification with potential cell locations to reduce computational time and resources without loss of quality. While aged mouse brains do have increased noise due to the accumulation of cellular debris, we validated that our DLNN pipeline performed at the same level as with young adult mice and did not incorporate cellular debris as potential cells.
Top 5 protocols citing «porcine skin gelatin»
Porcine Eye Biomechanics Characterization
Synthesis of Biofunctional Hydrogel Precursors
Synthesis and Characterization of GelMA
Measuring Cell Migration via Boyden Chambers
Establishment of In Vitro Blood-Brain Barrier Models
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