The next time you are considering taking time off, remember that if Alexander Fleming hadn’t taken a two-week vacation he wouldn’t have discovered penicillin. When Fleming returned from his vacation, he realized he had forgotten to place his staphylococcus culture in the incubator, and had left it at room temperature. Under these less than ideal conditions, the plates became infested with various molds. Frustrated, he threw out the cultures and moved on. He later noticed that one mold was clearly causing a colony of staphylococcus to lyse, as the colony appeared transparent. He described this observation in a publication in 1929 which detailed his initial accidental finding and his attempts to isolate and characterize this unique mold. The scientific community didn’t pay much attention to his findings at the time. In fact, it wasn’t until 1940 that Howard Florey and Ernst Chain reignited interest in penicillin and produced it at scale to aid World War II soldiers.
Fleming’s 1929 publication contained four figures (half of which were of the infamous accidentally infected plate), four references, and was about 10 pages long. This was commonplace for groundbreaking papers back in the day. Consider Watson and Crick’s paper describing the structure of DNA. It was published in Nature in 1953 and consisted of only two figures summarized in two pages. Yamanaka published his Nobel winning discovery of induced pluripotent stem cells in 2006 in Cell. Excluding the supplementary figures, this paper contains seven detailed figures, described in 14 pages. With the explosive growth of scientific techniques and knowledge, science has become easier to do in many ways, but much harder to publish.
Stringency in publishing isn’t a bad thing. A higher standard for publishing increases the likelihood that the scientific findings are rigorous and reproducible. But what if your science is good, your methods are sound, and you’ve proven your hypothesis wrong? What if all of your data are negative?
A recent article in the Nature Career Column highlighted one researcher’s struggle to publish their failed experiment. While their work was ultimately published in Genome Biology, they were met with unexpected pushback due to the lack of positive results. The author, Devhang Metha, points out that there is a concerning preference to publish positive results. In fact, one study demonstrates that in 2007, 85% of papers highlighted positive findings. Anyone who’s ever worked in a lab knows that 85% of experiments do not yield positive results. Most of us come back from two weeks of vacation to find our culture infected, without the reward of discovering penicillin.
While there are millions of reasons to support the publication of negative data, many of which Devhang Metha beautifully laid out in their recent article, allowing graduate students and postdocs to publish their negative findings could not only strengthen their training but reduce the time to graduation, ultimately increasing retention rates. Decreasing the time to degree is imperative for universities and government funding agencies alike. Graduate school is a long, hard, and costly endeavor (even if graduate students aren’t paying the bill), and evidence shows that shorter time to degree results in higher retention rates. Usually, when asked how long it will take to complete a PhD in the sciences, the response is five years. However, in 2017, the NIH reported that among F31 NRSA recipients, the median time to degree was 6.2 years. The median age of PhD recipients was 30, and 38.6% of those graduates had definite plans for a postdoc, meaning they will likely spend an additional 5-6 years before they are able to start their independent career. By redefining a successful scientific study as one that includes methodically tested negative results and unanswered questions rather than only defining success by positive data, we can likely reduce the time to graduation.
In an ideal world, if a negative finding was impactful to its relevant field, respectable scientific journals would accept it. However, this may not always be the case. If you are struggling to publish due to the negative nature of your results, you can publish in several places. In 2015, PLOS One launched Missing Pieces, a collection of publications containing negative, null, or inconclusive results. These papers undergo the same stringent review process that any other would, without the bias toward positive data. Additionally, the advent of BioRxiv provides a new outlet for publishing negative data. Maybe you only followed a project yielding negative results for a short time, and don’t quite have a full story. BioRxiv may be a good place to communicate your negative findings in a more informal way. In the end, your negative result, even if it’s only one figure worth, is likely important to someone and may save another researcher time, money, effort, and (most importantly) heartache.
Having an outlet to communicate negative or inconclusive findings, as well as view these rigorous studies as successful, is imperative for the progression of scientific knowledge. An environment in which researchers are unable to publish negative data (which will affect their success in the scientific field) leads to the temptations of data manipulation and false reporting. This ultimately creates unrealistic expectations for dissertation projects, leaving some graduate students inevitably stuck. When a graduate student or postdoc feels that their only escape from quasi-adulthood is if their experiments render positive results, we are setting them up for issues like imposter syndrome. In fact, feeling stuck in graduate school is likely a major contributor to the mental health crisis many graduate students face today.
As scientists, we understand the importance of remaining unbiased. Let’s try and apply that to our own data and start reporting all of those scientific studies that resulted in inconclusive or negative results. This will not only reduce the amount of time and money spent on false leads but help to redefine success in scientific research, likely improving the mental health of researchers at all career levels. In the end, you never know where your data can lead you.
About the Author:
Natalya Ortolano is a PhD candidate in Vivian Gama’s laboratory at Vanderbilt University in Nashville, TN. The Gama lab seeks to identify the novel role of apoptotic proteins in stem cell maintenance and differentiation. Natalya’s project is focused on characterizing the function of an E3-ubiquitin ligase known as Cullin 9 in stem cell self-renewal and neural differentiation. Twitter: @NatOrtolano Email: email@example.com