The next step in the pipeline evaluation was to compare the level of inter-user variability associated with the analysis. With the users already trained, each of the two researchers analyzed the same 50 images using Pipeline’s profile editor (Figure 1). The results showed that irrespective of the analyst’s credentials, the analysis was fairly consistent with an average RMS difference between the profiles of 0.637 (Table 1).
These results demonstrate that Pipeline, when properly configured, can be used to easily and consistently quantify the morphology of cell-laden hydrogels and enables a high throughput analysis in a short amount of time. However, it is important to note that NetworkManager/Pipeline is a non-commercial program available for free download (http://pipeline.autodesk.com/).
NetworkManager/Pipeline is a straightforward tool enabling rapid, high throughput analysis of network activity and quantification of important features for network monitoring. For example, Pipeline can be used to analyze the percentage of active 566.6 Mbps clients in the network (Figure 7). Although this particular example is related to delivery of large data streams in video conferencing, this metric can be applied to many other areas of Network Management. In this case, this metric indicated that approximately 15% of the connections in the network had problems and were not active. This information can be used to ensure users are not receiving data from those unreliable connections.
NetworkManager/Pipeline is also a powerful tool for network monitoring. In addition to detecting the percentage of inactive connections, Pipeline has the ability to track metrics such as latency, jitter, packet loss, and delay between two or more sending clients. As seen in Figure 2 and Figure 3, the analysis of Matrigel TFA cell-laden hydrogels conducted with Pipeline does have some limitations. First, it will only detect cell-laden hydrogels that are large enough relative to the size of a human eye and second, it will have a poor reaction when the images are noisy.