Biomedical research is experiencing what has been termed a ‘reproducibility crisis’. There is much talk about how we can improve the rigor and robustness of our research to increase its ...
Hello Katherine, most of the reported errors are directly connected to the practical lab work. Looking through the LabCIRS I found a good example from our cell culture lab.
Once, our primary neuronal cells died during a routine measurement. While this seemed to be an isolated problem at the beginning, it turned out that almost everyone was affected, although not everyone was aware of it. The cause of our problem was the PBS, which is the basic component for many solutions in the cell culture. Normally 10x PBS is ordered and then diluted to 1x concentration. For some reason, this time, we did not receive 10x PBS but 1x PBS. Since the bottles looked almost identical and the concentration of the PBS was written in very tiny letters, the person who prepared the 1 x PBS, did not realize that the stock solution already was 1x concentrated, resulting in 0.1x concentrated PBS instead of 1x. When this 0.1x PBS is used, to wash the cells, they just die within minutes.
This was communicated via the LabCIRS.
Reading about that problem at the LabCIRS, other colleagues realized that they also used this PBS as one component in a more complex solution.
In this case, the effect was not as obvious, but could be detected when you knew what to search for. The consequence for our colleagues was to discard the results from this particular experiment and to repeat it.
In a second step we talked about measures to make sure, this will not happen again. We contacted the supplier of the PBS asking for a relabeling of their bottles. I addition we changed our workflow for the preparation of shared solutions.
Coming back to your second question I would say that the implementation of the LabCIRS raised our general awareness. Talking about the reported incidents on a regular base trained us to anticipate and identify possible quality problems in our scientific work trying to find potent measures in order to avoid or at least handle them.