In the chapter, ‘It’s Hard Even on the Good Days’, Richard Harris moves from the general idea of reproducibility to the biases and flaws occurring in the labs that cause it and the failures they have lead to. He also brought in a lot more perspectives from different scientists and researchers, as well as examples of relevant experiments.
An experiment Harris included in the chapter that surprised me was the discovery of the enzyme telomerase. It sparked an interest, so I researched the enzyme afterwards and found its potential uses to be exciting. In a general view, I learned that each time cells reproduce through mitosis, a bit of DNA gets lost, so our DNA strands have telomere caps at their ends that get decreased first, saving time before the actual genetic material of the strand gets affected, which is essentially what aging is. Telomerase is the enzyme that adds on more telomeres, saving you more time, which is why it is seen as a potential ‘anti-aging drug’.
One of the great perspectives Harris brought into his book was from Carol Greider, who discovered telomerase. I really admired the unique process she uses which Harris includes: “‘Rather than say, ‘Look, let’s find every piece of evidence we can to show that this is a new enzyme,’ instead we did the opposite,’ Greider told me. ‘We said, ‘How can we disprove our own hypothesis?’ She started to look for something else responsible for rebuilding the DNA at the chromosome tips. She was essentially trying to figure out whether she was fooling herself.” (pg. 34) It is this type of mindset that needs to be brought to more studies in the biomedical field to solve the lack of care and rigor it is experiencing.
This ‘fooling oneself’ in experiments is very difficult to avoid due to biases and false interpretations of data. Harris includes written quotes from Martin Schwartz at Yale University that describe how in an experiment, “the scientist asks the question and then interprets the answer,” (pg. 32) rather than asking the question and listening for an answer. The scientist has a specific outcome they are hoping for to prove their hypothesis, but they can’t let that get in the way of how they interpret the results. Schwartz describes a strategy called non-attachment by saying, “We all have hopes, desires and ambitions. Non-attachment means acknowledging them, accepting them and then not inserting them into a process that at some level has nothing to do with you.” (pg. 32) Surprisingly, there are 235 forms of bias, according to John Ioannidis and David Chavalarias. Whether those biases stem from hopes of a specific outcome or a fear of failure, the way they affect results can cause experiments to lose their reproducibility. There are many people in the field though, that believe these failures are constantly leading to bigger and better findings, after all, you always learn from your mistakes.