A Slightly More Specific Update: Control and Data

Recently working at the lab has been quite busy for me including one time where I stayed till 7 PM to finish which gave me several topics to think about that will be divided into multiple blog posts. This post will primarily be concerned with data gathering.

First, a quick overview of my specific project: growth kinetics. Stem cells are used for a variety of experiments since people believe in their potential for treatments and medical advancements. However, these cells have to be cultivated and grown for experimentation. By putting them in flasks and adding media (essentially food for the cells), the cells multiply and we have the cells for experimentation. My project is aimed at seeing if there's a way of increasing growth kinetics which could help yield more cells. To test this requires data, which as noted in my prior blog post is the end result of experimenting.

Also, while I couldn't find a photo online of the comic, I took a picture of it with my phone (which has since died on itself):

I've just begun gathering data and have nothing to compare it to yet, but this leads to a topic on control groups.

Control groups are essentially the litmus test for comparison. Starting most vaguely, if a certain treatment ends up with a significantly different result than the control group, there probably is something special to the treatment. An example of this would be placebos versus actual medicine or sham treatments versus the actual operation. In the case of placebos, the control test is whether or not the perceived cure actually is the mechanism that solves problems or if simply the idea of a cure is sufficient. With placebos like sugar pills, the experiment sets to test if the cure is actually "the cure". Control groups are essential because without control groups, any extrapolation is impossible. Like with my data, since I haven't begun working on the control groups, I lack a meaningful comparison and can't derive meaning from my results.

Leading on from this, experiment design has come up often as a topic in the lab. Experiments should be designed around a certain hypothesis with specific aims and from that, extrapolation becomes possible whether the hypothesis is disproved or not. However more specifically control groups must always be a part of the experiment for the data to matter. In some extreme cases, forgetting the control group can cost people months depending on the project such as with live animals in which case they need to go back and gather data on the control group.

On a note more on blogging, I think I'll continue being slightly dissociative with my blog posts in terms of personalizing it. I'd rather have my personal experiences be grounds for reflection rather than something to be taken as face value so I'll generally lead with an experience and then add reflection to it. The possible exception will be lab meetings which if they present a topic that I feel confident to write a blog on, it will likely be more personal rather than reflective since I think most of the scientific process can be thought about during experimentation and that the end result is something more relatable. Also in the interest of keeping blog posts consistent in structure and substance I will be keeping to one major idea per blog post and then reflections on blogging at most which might result in multiple posts per day.