Should Biologists be Guided by Beauty?

Lingulodinium polyedrum is a unicellular marine organism which belongs to the dinoflagellate group of algae. Its genome is among the largest found in any species on this planet, estimated to contain around 165 billion DNA base pairs – roughly fifty times larger than the size of the human genome. Encased in magnificent polyhedral shells, these bioluminescent algae became important organisms to study biological rhythms. Each Lingulodinium polyedrum cell contains not one but at least two internal clocks which keep track of time by oscillating at a frequency of approximately 24 hours. Algae maintained in continuous light for weeks continue to emit a bluish-green glow at what they perceive as night-time and swim up to the water surface during day-time hours – despite the absence of any external time cues. When I began studying how nutrients affect the circadian rhythms of these algae as a student at the University of Munich, I marveled at the intricacy and beauty of these complex time-keeping mechanisms that had evolved over hundreds of millions of years.

Lingulodinium polyedrum (scanning electron micrograph)
Lingulodinium polyedrum (scanning electron micrograph) – Credit: FWC Fish and Wildlife Research Institute (via Flickr)


I was prompted to revisit the role of Beauty in biology while reading a masterpiece of scientific writing, “Dreams of a Final Theory” by the Nobel laureate Steven Weinberg in which he describes how the search for Beauty has guided him and many fellow theoretical physicists to search for an ultimate theory of the fundamental forces of nature. Weinberg explains that it is quite difficult to precisely define what constitutes Beauty in physics but a physicist would nevertheless recognize it when she sees it.Over the course of a quarter of a century, I have worked in a variety of biological fields, from these initial experiments in marine algae to how stem cells help build human blood vessels and how mitochondria in a cell fragment and reconnect as cells divide. Each project required its own set of research methods and techniques, each project came with its own failures and successes. But with each project, my sense of awe for the beauty of nature has grown. Evolution has bestowed this planet with such an amazing diversity of life-forms and biological mechanisms, allowing organisms to cope with the unique challenges that they face in their respective habitats. But it is only recently that I have become aware of the fact that my sense of biological beauty was a post hoc phenomenon: Beauty was what I perceived after reviewing the experimental findings; I was not guided by a quest for beauty while designing experiments. In fact, I would have been worried that such an approach might bias the design and interpretation of experiments. Might a desire for seeing Beauty in cell biology lead one to consciously or subconsciously discard results that might seem too messy?

One such key characteristic of a beautiful scientific theory is the simplicity of the underlying concepts. According to Weinberg, Einstein’s theory of gravitation is described in fourteen equations whereas Newton’s theory can be expressed in three. Despite the appearance of greater complexity in Einstein’s theory, Weinberg finds it more beautiful than Newton’s theory because the Einsteinian approach rests on one elegant central principle – the equivalence of gravitation and inertia. Weinberg’s second characteristic for beautiful scientific theories is their inevitability. Every major aspect of the theory seems so perfect that it cannot be tweaked or improved on. Any attempt to significantly modify Einstein’s theory of general relativity would lead to undermining its fundamental concepts, just like any attempts to move around parts of Raphael’s Holy Family would weaken the whole painting.

Can similar principles be applied to biology? I realized that when I give examples of beauty in biology, I focus on the complexity and diversity of life, not its simplicity or inevitability. Perhaps this is due to the fact that Weinberg was describing the search of fundamental laws of physics, laws which would explain the basis of all matter and energy – our universe. As cell biologists, we work several orders of magnitude removed from these fundamental laws. Our building blocks are organic molecules such as proteins and sugars. We find little evidence of inevitability in the molecular pathways we study – cells have an extraordinary ability to adapt. Mutations in genes or derangement in molecular signaling can often be compensated by alternate cellular pathways.

This also points to a fundamental difference in our approaches to the world. Physicists searching for the fundamental laws of nature balance the development of fundamental theories whereas biology in its current form has primarily become an experimental discipline. The latest technological developments in DNA and RNA sequencing, genome editing, optogenetics and high resolution imaging are allowing us to amass unimaginable quantities of experimental data. In fact, the development of technologies often drives the design of experiments. The availability of a genetically engineered mouse model that allows us to track the fate of individual cells that express fluorescent proteins, for example, will give rise to numerous experiments to study cell fate in various disease models and organs. Much of the current biomedical research funding focuses on studying organisms that provide technical convenience such as genetically engineered mice or fulfill a societal goal such as curing human disease.

Uncovering fundamental concepts in biology requires comparative studies across biology and substantial investments in research involving a plethora of other species. In 1990, the National Institutes of Health (NIH – the primary government funding source for biomedical research in the United States) designated a handful of species as model organisms to study human disease, including mice, rats, zebrafish and fruit flies. A recent analysis of the species studied in scientific publications showed that in 1960, roughly half the papers studied what would subsequently be classified as model organisms whereas the other half of papers studied additional species. By 2010, over 80% of the scientific papers were now being published on model organisms and only 20% were devoted to other species, thus marking a significant dwindling of broader research goals in biology. More importantly, even among the model organisms, there has been a clear culling of research priorities with a disproportionately large growth in funding and publications for studies using mice. Thousands of scientific papers are published every month on the cell signaling pathways and molecular biology in mouse and human cells whereas only a minuscule fraction of research resources are devoted to studying signaling pathways in algae.

The question of whether or not biologists should be guided by conceptual Beauty leads us to the even more pressing question of whether we need to broaden biological research. If we want to mirror the dizzying success of fundamental physics during the past century and similarly advance fundamental biology, then we need substantially step-up investments in fundamental biological research that is not constrained by medical goals.



Dietrich, M. R., Ankeny, R. A., & Chen, P. M. (2014). Publication trends in model organism research. Genetics, 198(3), 787-794.

Weinberg, S. (1992). Dreams of a final theory. Vintage.

Note: An earlier version of this article was first published on the 3Quarksdaily blog.

Dietrich, M., Ankeny, R., & Chen, P. (2014). Publication Trends in Model Organism Research Genetics, 198 (3), 787-794 DOI: 10.1534/genetics.114.169714


Weinberg, Steven (1992). Dreams of a Final Theory Vintage Books

The Dire State of Science in the Muslim World

Universities and the scientific infrastructures in Muslim-majority countries need to undergo radical reforms if they want to avoid falling by the wayside in a world characterized by major scientific and technological innovations. This is the conclusion reached by Nidhal Guessoum and Athar Osama in their recent commentary “Institutions: Revive universities of the Muslim world“, published in the scientific journal Nature. The physics and astronomy professor Guessoum (American University of Sharjah, United Arab Emirates) and Osama, who is the founder of the Muslim World Science Initiative, use the commentary to summarize the key findings of the report “Science at Universities of the Muslim World” (PDF), which was released in October 2015 by a task force of policymakers, academic vice-chancellors, deans, professors and science communicators. This report is one of the most comprehensive analyses of the state of scientific education and research in the 57 countries with a Muslim-majority population, which are members of the Organisation of Islamic Cooperation (OIC).

Map of Saudi Arabia in electronic circuits via Shutterstock (copyright drical)
Map of Saudi Arabia using electronic circuits via Shutterstock (copyright drical)

Here are some of the key findings:

1.    Lower scientific productivity in the Muslim world: The 57 Muslim-majority countries constitute 25% of the world’s population, yet they only generate 6% of the world’s scientific publications and 1.6% of the world’s patents.

2.    Lower scientific impact of papers published in the OIC countries: Not only are Muslim-majority countries severely under-represented in terms of the numbers of publications, the papers which do get published are cited far less than the papers stemming from non-Muslim countries. One illustrative example is that of Iran and Switzerland. In the 2014 SCImago ranking of publications by country, Iran was the highest-ranked Muslim-majority country with nearly 40,000 publications, just slightly ahead of Switzerland with 38,000 publications – even though Iran’s population of 77 million is nearly ten times larger than that of Switzerland. However, the average Swiss publication was more than twice as likely to garner a citation by scientific colleagues than an Iranian publication, thus indicating that the actual scientific impact of research in Switzerland was far greater than that of Iran.

To correct for economic differences between countries that may account for the quality or impact of the scientific work, the analysis also compared selected OIC countries to matched non-Muslim countries with similar per capita Gross Domestic Product (GDP) values (PDF). The per capita GDP in 2010 was $10,136 for Turkey, $8,754 for Malaysia and only $7,390 for South Africa. However, South Africa still outperformed both Turkey and Malaysia in terms of average citations per scientific paper in the years 2006-2015 (Turkey: 5.6; Malaysia: 5.0; South Africa: 9.7).

3.    Muslim-majority countries make minimal investments in research and development: The world average for investing in research and development is roughly 1.8% of the GDP. Advanced developed countries invest up to 2-3 percent of their GDP, whereas the average for the OIC countries is only 0.5%, less than a third of the world average! One could perhaps understand why poverty-stricken Muslim countries such as Pakistan do not have the funds to invest in research because their more immediate concerns are to provide basic necessities to the population. However, one of the most dismaying findings of the report is the dismally low rate of research investments made by the members of the Gulf Cooperation Council (GCC, the economic union of six oil-rich gulf countries Saudi Arabia, Kuwait, Bahrain, Oman, United Arab Emirates and Qatar with a mean per capita GDP of over $30,000 which is comparable to that of the European Union). Saudi Arabia and Kuwait, for example, invest less than 0.1% of their GDP in research and development, far lower than the OIC average of 0.5%.

So how does one go about fixing this dire state of science in the Muslim world? Some fixes are rather obvious, such as increasing the investment in scientific research and education, especially in the OIC countries which have the financial means and are currently lagging far behind in terms of how much funds are made available to improve the scientific infrastructures. Guessoum and Athar also highlight the importance of introducing key metrics to assess scientific productivity and the quality of science education. It is not easy to objectively measure scientific and educational impact, and one can argue about the significance or reliability of any given metric. But without any metrics, it will become very difficult for OIC universities to identify problems and weaknesses, build new research and educational programs and reward excellence in research and teaching. There is also a need for reforming the curriculum so that it shifts its focus from lecture-based teaching, which is so prevalent in OIC universities, to inquiry-based teaching in which students learn science hands-on by experimentally testing hypotheses and are encouraged to ask questions.

In addition to these commonsense suggestions, the task force also put forward a rather intriguing proposition to strengthen scientific research and education: place a stronger emphasis on basic liberal arts in science education. I could not agree more because I strongly believe that exposing science students to the arts and humanities plays a key role in fostering the creativity and curiosity required for scientific excellence. Science is a multi-disciplinary enterprise, and scientists can benefit greatly from studying philosophy, history or literature. A course in philosophy, for example, can teach science students to question their basic assumptions about reality and objectivity, encourage them to examine their own biases, challenge authority and understand the importance of doubt and uncertainty, all of which will likely help them become critical thinkers and better scientists.

However, the specific examples provided by Guessoum and Athar do not necessarily indicate a support for this kind of a broad liberal arts education. They mention the example of the newly founded private Habib University in Karachi which mandates that all science and engineering students also take classes in the humanities, including a two semester course in “hikma” or “traditional wisdom”. Upon reviewing the details of this philosophy course on the university’s website, it seems that the course is a history of Islamic philosophy focused on antiquity and pre-modern texts which date back to the “Golden Age” of Islam. The task force also specifically applauds an online course developed by Ahmed Djebbar. He is an emeritus science historian at the University of Lille in France, which attempts to stimulate scientific curiosity in young pre-university students by relating scientific concepts to great discoveries from the Islamic “Golden Age”. My concern is that this is a rather Islamocentric form of liberal arts education. Do students who have spent all their lives growing up in a Muslim society really need to revel in the glories of a bygone era in order to get excited about science? Does the Habib University philosophy course focus on Islamic philosophy because the university feels that students should be more aware of their cultural heritage or are there concerns that exposing students to non-Islamic ideas could cause problems with students, parents, university administrators or other members of society who could perceive this as an attack on Islamic values? If the true purpose of liberal arts education is to expand the minds of students by exposing them to new ideas, wouldn’t it make more sense to focus on non-Islamic philosophy? It is definitely not a good idea to coddle Muslim students by adulating the “Golden Age” of Islam or using kid gloves when discussing philosophy in order to avoid offending them.

This leads us to a question that is not directly addressed by Guessoum and Osama: How “liberal” is a liberal arts education in countries with governments and societies that curtail the free expression of ideas? The Saudi blogger Raif Badawi was sentenced to 1,000 lashes and 10 years in prison because of his liberal views that were perceived as an attack on religion. Faculty members at universities in Saudi Arabia who teach liberal arts courses are probably very aware of these occupational hazards. At first glance, professors who teach in the sciences may not seem to be as susceptible to the wrath of religious zealots and authoritarian governments. However, the above-mentioned interdisciplinary nature of science could easily spell trouble for free-thinking professors or students. Comments about evolutionary biology, the ethics of genome editing or discussing research on sexuality could all be construed as a violation of societal and religious norms.

The 2010 study Faculty perceptions of academic freedom at a GCC university surveyed professors at an anonymous GCC university (most likely Qatar University since roughly 25% of the faculty members were Qatari nationals and the authors of the study were based in Qatar) regarding their views of academic freedom. The vast majority of faculty members (Arab and non-Arab) felt that academic freedom was important to them and that their university upheld academic freedom. However, in interviews with individual faculty members, the researchers found that the professors were engaging in self-censorship in order to avoid untoward repercussions. Here are some examples of the comments from the faculty at this GCC University:

“I am fully aware of our culture. So, when I suggest any topic in class, I don’t need external censorship except mine.”

“Yes. I avoid subjects that are culturally inappropriate.”

“Yes, all the time. I avoid all references to Israel or the Jewish people despite their contributions to world culture. I also avoid any kind of questioning of their religious tradition. I do this out of respect.”

This latter comment is especially painful for me because one of my heroes who inspired me to become a cell biologist was the Italian Jewish scientist Rita Levi-Montalcini. She revolutionized our understanding of how cells communicate with each other using growth factors. She was also forced to secretly conduct her experiments in her bedroom because the Fascists banned all “non-Aryans” from going to the university laboratory. Would faculty members who teach the discovery of growth factors at this GCC University downplay the role of the Nobel laureate Levi-Montalcini because she was Jewish? We do not know how prevalent this form of self-censorship is in other OIC countries because the research on academic freedom in Muslim-majority countries is understandably scant. Few faculty members would be willing to voice their concerns about government or university censorship and admitting to self-censorship is also not easy.

The task force report on science in the universities of Muslim-majority countries is an important first step towards reforming scientific research and education in the Muslim world. Increasing investments in research and development, using and appropriately acting on carefully selected metrics as well as introducing a core liberal arts curriculum for science students will probably all significantly improve the dire state of science in the Muslim world. However, the reform of the research and education programs needs to also include discussions about the importance of academic freedom. If Muslim societies are serious about nurturing scientific innovation, then they will need to also ensure that scientists, educators and students will be provided with the intellectual freedom that is the cornerstone of scientific creativity.


Guessoum, N., & Osama, A. (2015). Institutions: Revive universities of the Muslim world. Nature, 526(7575), 634-6.

Romanowski, M. H., & Nasser, R. (2010). Faculty perceptions of academic freedom at a GCC university. Prospects, 40(4), 481-497.



 Note: An earlier version of this article was first published on the 3Quarksdaily blog.


Guessoum N, & Osama A (2015). Institutions: Revive universities of the Muslim world. Nature, 526 (7575), 634-6 PMID: 26511563



Romanowski, M., & Nasser, R. (2010). Faculty perceptions of academic freedom at a GCC university PROSPECTS, 40 (4), 481-497 DOI: 10.1007/s11125-010-9166-2

Murder Your Darling Hypotheses But Do Not Bury Them

“Whenever you feel an impulse to perpetrate a piece of exceptionally fine writing, obey it—whole-heartedly—and delete it before sending your manuscript to press. Murder your darlings.”

Sir Arthur Quiller-Couch (1863–1944). On the Art of Writing. 1916


Murder your darlings. The British writer Sir Arthur Quiller Crouch shared this piece of writerly wisdom when he gave his inaugural lecture series at Cambridge, asking writers to consider deleting words, phrases or even paragraphs that are especially dear to them. The minute writers fall in love with what they write, they are bound to lose their objectivity and may not be able to judge how their choice of words will be perceived by the reader. But writers aren’t the only ones who can fall prey to the Pygmalion syndrome. Scientists often find themselves in a similar situation when they develop “pet” or “darling” hypotheses.

Hypothesis via Shutterstock
Hypothesis via Shutterstock

How do scientists decide when it is time to murder their darling hypotheses? The simple answer is that scientists ought to give up scientific hypotheses once the experimental data is unable to support them, no matter how “darling” they are. However, the problem with scientific hypotheses is that they aren’t just generated based on subjective whims. A scientific hypothesis is usually put forward after analyzing substantial amounts of experimental data. The better a hypothesis is at explaining the existing data, the more “darling” it becomes. Therefore, scientists are reluctant to discard a hypothesis because of just one piece of experimental data that contradicts it.

In addition to experimental data, a number of additional factors can also play a major role in determining whether scientists will either discard or uphold their darling scientific hypotheses. Some scientific careers are built on specific scientific hypotheses which set apart certain scientists from competing rival groups. Research grants, which are essential to the survival of a scientific laboratory by providing salary funds for the senior researchers as well as the junior trainees and research staff, are written in a hypothesis-focused manner, outlining experiments that will lead to the acceptance or rejection of selected scientific hypotheses. Well written research grants always consider the possibility that the core hypothesis may be rejected based on the future experimental data. But if the hypothesis has to be rejected then the scientist has to explain the discrepancies between the preferred hypothesis that is now falling in disrepute and all the preliminary data that had led her to formulate the initial hypothesis. Such discrepancies could endanger the renewal of the grant funding and the future of the laboratory. Last but not least, it is very difficult to publish a scholarly paper describing a rejected scientific hypothesis without providing an in-depth mechanistic explanation for why the hypothesis was wrong and proposing alternate hypotheses.

For example, it is quite reasonable for a cell biologist to formulate the hypothesis that protein A improves the survival of neurons by activating pathway X based on prior scientific studies which have shown that protein A is an activator of pathway X in neurons and other studies which prove that pathway X improves cell survival in skin cells. If the data supports the hypothesis, publishing this result is fairly straightforward because it conforms to the general expectations. However, if the data does not support this hypothesis then the scientist has to explain why. Is it because protein A did not activate pathway X in her experiments? Is it because in pathway X functions differently in neurons than in skin cells? Is it because neurons and skin cells have a different threshold for survival? Experimental results that do not conform to the predictions have the potential to uncover exciting new scientific mechanisms but chasing down these alternate explanations requires a lot of time and resources which are becoming increasingly scarce. Therefore, it shouldn’t come as a surprise that some scientists may consciously or subconsciously ignore selected pieces of experimental data which contradict their darling hypotheses.

Let us move from these hypothetical situations to the real world of laboratories. There is surprisingly little data on how and when scientists reject hypotheses, but John Fugelsang and Kevin Dunbar at Dartmouth conducted a rather unique study “Theory and data interactions of the scientific mind: Evidence from the molecular and the cognitive laboratory” in 2004 in which they researched researchers. They sat in at scientific laboratory meetings of three renowned molecular biology laboratories at carefully recorded how scientists presented their laboratory data and how they would handle results which contradicted their predictions based on their hypotheses and models.

In their final analysis, Fugelsang and Dunbar included 417 scientific results that were presented at the meetings of which roughly half (223 out of 417) were not consistent with the predictions. Only 12% of these inconsistencies lead to change of the scientific model (and thus a revision of hypotheses). In the vast majority of the cases, the laboratories decided to follow up the studies by repeating and modifying the experimental protocols, thinking that the fault did not lie with the hypotheses but instead with the manner how the experiment was conducted. In the follow up experiments, 84 of the inconsistent findings could be replicated and this in turn resulted in a gradual modification of the underlying models and hypotheses in the majority of the cases. However, even when the inconsistent results were replicated, only 61% of the models were revised which means that 39% of the cases did not lead to any significant changes.

The study did not provide much information on the long-term fate of the hypotheses and models and we obviously cannot generalize the results of three molecular biology laboratory meetings at one university to the whole scientific enterprise. Also, Fugelsang and Dunbar’s study did not have a large enough sample size to clearly identify the reasons why some scientists were willing to revise their models and others weren’t. Was it because of varying complexity of experiments and models? Was it because of the approach of the individuals who conducted the experiments or the laboratory heads? I wish there were more studies like this because it would help us understand the scientific process better and maybe improve the quality of scientific research if we learned how different scientists handle inconsistent results.

In my own experience, I have also struggled with results which defied my scientific hypotheses. In 2002, we found that stem cells in human fat tissue could help grow new blood vessels. Yes, you could obtain fat from a liposuction performed by a plastic surgeon and inject these fat-derived stem cells into animal models of low blood flow in the legs. Within a week or two, the injected cells helped restore the blood flow to near normal levels! The simplest hypothesis was that the stem cells converted into endothelial cells, the cell type which forms the lining of blood vessels. However, after several months of experiments, I found no consistent evidence of fat-derived stem cells transforming into endothelial cells. We ended up publishing a paper which proposed an alternative explanation that the stem cells were releasing growth factors that helped grow blood vessels. But this explanation was not as satisfying as I had hoped. It did not account for the fact that the stem cells had aligned themselves alongside blood vessel structures and behaved like blood vessel cells.

Even though I “murdered” my darling hypothesis of fat –derived stem cells converting into blood vessel endothelial cells at the time, I did not “bury” the hypothesis. It kept ruminating in the back of my mind until roughly one decade later when we were again studying how stem cells were improving blood vessel growth. The difference was that this time, I had access to a live-imaging confocal laser microscope which allowed us to take images of cells labeled with red and green fluorescent dyes over long periods of time. Below, you can see a video of human bone marrow mesenchymal stem cells (labeled green) and human endothelial cells (labeled red) observed with the microscope overnight. The short movie compresses images obtained throughout the night and shows that the stem cells indeed do not convert into endothelial cells. Instead, they form a scaffold and guide the endothelial cells (red) by allowing them to move alongside the green scaffold and thus construct their network. This work was published in 2013 in the Journal of Molecular and Cellular Cardiology, roughly a decade after I had been forced to give up on the initial hypothesis. Back in 2002, I had assumed that the stem cells were turning into blood vessel endothelial cells because they aligned themselves in blood vessel like structures. I had never considered the possibility that they were scaffold for the endothelial cells.

This and other similar experiences have lead me to reformulate the “murder your darlings” commandment to “murder your darling hypotheses but do not bury them”. Instead of repeatedly trying to defend scientific hypotheses that cannot be supported by emerging experimental data, it is better to give up on them. But this does not mean that we should forget and bury those initial hypotheses. With newer technologies, resources or collaborations, we may find ways to explain inconsistent results years later that were not previously available to us. This is why I regularly peruse my cemetery of dead hypotheses on my hard drive to see if there are ways of perhaps resurrecting them, not in their original form but in a modification that I am now able to test.



Fugelsang, J., Stein, C., Green, A., & Dunbar, K. (2004). Theory and Data Interactions of the Scientific Mind: Evidence From the Molecular and the Cognitive Laboratory. Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale, 58 (2), 86-95 DOI: 10.1037/h0085799


Note: An earlier version of this article first appeared on 3Quarksdaily.

Literature and Philosophy in the Laboratory Meeting

Research institutions in the life sciences engage in two types of regular scientific meet-ups: scientific seminars and lab meetings. The structure of scientific seminars is fairly standard. Speakers give Powerpoint presentations (typically 45 to 55 minutes long) which provide the necessary scientific background, summarize their group’s recent published scientific work and then (hopefully) present newer, unpublished data. Lab meetings are a rather different affair. The purpose of a lab meeting is to share the scientific work-in-progress with one’s peers within a research group and also to update the laboratory heads. Lab meetings are usually less formal than seminars, and all members of a research group are encouraged to critique the presented scientific data and work-in-progress. There is no need to provide much background information because the audience of peers is already well-acquainted with the subject and it is not uncommon to show raw, unprocessed data and images in order to solicit constructive criticism and guidance from lab members and mentors on how to interpret the data. This enables peer review in real-time, so that, hopefully, major errors and flaws can be averted and newer ideas incorporated into the ongoing experiments.


During the past two decades that I have actively participated in biological, psychological and medical research, I have observed very different styles of lab meetings. Some involve brief 5-10 minute updates from each group member; others develop a rotation system in which one lab member has to present the progress of their ongoing work in a seminar-like, polished format with publication-quality images. Some labs have two hour meetings twice a week, other labs meet only every two weeks for an hour. Some groups bring snacks or coffee to lab meetings, others spend a lot of time discussing logistics such as obtaining and sharing biological reagents or establishing timelines for submitting manuscripts and grants. During the first decade of my work as a researcher, I was a trainee and followed the format of whatever group I belonged to. During the past decade, I have been heading my own research group and it has become my responsibility to structure our lab meetings. I do not know which format works best, so I approach lab meetings like our experiments. Developing a good lab meeting structure is a work-in-progress which requires continuous exploration and testing of new approaches. During the current academic year, I decided to try out a new twist: incorporating literature and philosophy into the weekly lab meetings.

My research group studies stem cells and tissue engineeringcellular metabolism in cancer cells and stem cells and the inflammation of blood vessels. Most of our work focuses on identifying molecular and cellular pathways in cells, and we then test our findings in animal models. Over the years, I have noticed that the increasing complexity of the molecular and cellular signaling pathways and the technologies we employ makes it easy to forget the “big picture” of why we are even conducting the experiments. Determining whether protein A is required for phenomenon X and whether protein B is a necessary co-activator which acts in concert with protein A becomes such a central focus of our work that we may not always remember what it is that compels us to study phenomenon X in the first place. Some of our research has direct medical relevance, but at other times we primarily want to unravel the awe-inspiring complexity of cellular processes. But the question of whether our work is establishing a definitive cause-effect relationship or whether we are uncovering yet another mechanism within an intricate web of causes and effects sometimes falls by the wayside. When asked to explain the purpose or goals of our research, we have become so used to directing a laser pointer onto a slide of a cellular model that it becomes challenging to explain the nature of our work without visual aids.

This fall, I introduced a new component into our weekly lab meetings. After our usual round-up of new experimental data and progress, I suggested that each week one lab member should give a brief 15 minute overview about a book they had recently finished or were still reading. The overview was meant to be a “teaser” without spoilers, explaining why they had started reading the book, what they liked about it, and whether they would recommend it to others. One major condition was to speak about the book without any Powerpoint slides! But there weren’t any major restrictions when it came to the book; it could be fiction or non-fiction and published in any language of the world (but ideally also available in an English translation). If lab members were interested and wanted to talk more about the book, then we would continue to discuss it, otherwise we would disband and return to our usual work. If nobody in my lab wanted to talk about a book then I would give an impromptu mini-talk (without Powerpoint) about a topic relating to the philosophy or culture of science. I use the term “culture of science” broadly to encompass topics such as the peer review process and post-publication peer review, the question of reproducibility of scientific findings, retractions of scientific papers, science communication and science policy – topics which have not been traditionally considered philosophy of science issues but still relate to the process of scientific discovery and the dissemination of scientific findings.

One member of our group introduced us to “For Whom the Bell Tolls” by Ernest Hemingway. He had also recently lived in Spain as a postdoctoral research fellow and shared some of his own personal experiences about how his Spanish friends and colleagues talked about the Spanish Civil War. At another lab meeting, we heard about “Sycamore Row” by John Grisham and the ensuring discussion revolved around race relations in Mississippi. I spoke about “A Tale for a Time Being” by Ruth Ozeki and the difficulties that the book’s protagonist faced as an outsider when her family returned to Japan after living in Silicon Valley. I think that the book which got nearly everyone in the group talking was “Far From the Tree: Parents, Children and the Search for Identity” by Andrew Solomon. The book describes how families grapple with profound physical or cognitive differences between parents and children. The PhD student who discussed the book focused on the “Deafness” chapter of this nearly 1000-page tome but she also placed it in the broader context of parenting, love and the stigma of disability. We stayed in the conference room long after the planned 15 minutes, talking about being “disabled” or being “differently abled” and the challenges that parents and children face.

On the weeks where nobody had a book they wanted to present, we used the time to touch on the cultural and philosophical aspects of science such as Thomas Kuhn’s concept of paradigm shifts in “The Structure of Scientific Revolutions“, Karl Popper’s principles of falsifiability of scientific statements, the challenge of reproducibility of scientific results in stem cell biology and cancer research, or the emergence of Pubpeer as a post-publication peer review website. Some of the lab members had heard of Thomas Kuhn’s or Karl Popper’s ideas before, but by coupling it to a lab meeting, we were able to illustrate these ideas using our own work. A lot of 20th century philosophy of science arose from ideas rooted in physics. When undergraduate or graduate students take courses on philosophy of science, it isn’t always easy for them to apply these abstract principles to their own lab work, especially if they pursue a research career in the life sciences. Thomas Kuhn saw Newtonian and Einsteinian theories as distinct paradigms, but what constitutes a paradigm shift in stem cell biology? Is the ability to generate induced pluripotent stem cells from mature adult cells a paradigm shift or “just” a technological advance?

It is difficult for me to know whether the members of my research group enjoy or benefit from these humanities blurbs at the end of our lab meetings. Perhaps they are just tolerating them as eccentricities of the management and maybe they will tire of them. I personally find these sessions valuable because I believe they help ground us in reality. They remind us that it is important to think and read outside of the box. As scientists, we all read numerous scientific articles every week just to stay up-to-date in our area(s) of expertise, but that does not exempt us from also thinking and reading about important issues facing society and the world we live in. I do not know whether discussing literature and philosophy makes us better scientists but I hope that it makes us better people.


Note: An earlier version of this article was first published on the 3Quarksdaily blog.

Thomas Kuhn (2012). The Structure of Scientific Revolutions University of Chicago Press DOI: 10.7208/chicago/9780226458106.001.0001

How Does Your Facebook News Feed Affect You?

Researchers at Facebook, Inc., the University of California, San Francisco (UCSF) and Cornell University teamed up to study whether manipulating the News Feeds of Facebook users would affect the emotional content of the users’ status updates or postings. They recently published their findings in the PNAS paper “Experimental evidence of massive-scale emotional contagion through social networks”  and suggest that they have found evidence of an “emotional contagion”, i.e. the idea that emotions can spread via Facebook.


The size of the study is quite impressive: The researchers analyzed the postings of 689,003 Facebook users (randomly selected based on their user ID) during the week of January 11-18, 2012! This probably makes it the largest study of its kind in which social media feeds of individual users were manipulated. Other large-scale social media research studies have relied on observing correlations but have not used actual interventions on such a massive scale. The users’ postings (over three million of them) were directly analyzed by a software which evaluated the emotional content of each posting. The researchers did not see the actual postings of the Facebook users, which is why they felt that their research was covered by Facebook’s Data Use Policy and did not require individual informed consent. This means that the individual Facebook users were probably unaware of the fact that their News Feeds were manipulated and that their postings were being analyzed for emotional content.


The researchers selectively removed items with either “positive” or “negative” emotional content from the News Feeds of individual users. The emotional content of News Feed items was categorized using the LIWC software, which defines words such as “ugly” or “hurt” as negative and “nice” or “”sweet” as positive. Each emotional post had a 10%-90% chance (assigned based on their User ID) of being removed from the News Feed. Since removal of News Feed items could have a non-specific, general effect on users being exposed to lesser updates, the researchers also ensured that they studied control groups in whom the same number of News Feed items were randomly removed, independent of their emotional content.


Importantly, 22.4% of posts contained “negative” words, whereas 46.8% of posts contained “positive” words, suggesting that there is roughly a 2:1 ratio of “positive” to “negative” posts on Facebook. This bias towards positivity is compatible with prior research which has shown that sharing of “negative” emotions via Facebook is not always welcome. The difference in total number of “positive” and “negative” posts forced the researchers to use two distinct control groups. For example, users for whom 20% of News Feed posts containing “positive” content were removed required a control group in which 20% of 46.8% (i.e., 9.36%) of News Feed items were randomly removed (regardless of the emotional content). On the other hand, users for whom 20% of News Feed items containing “negative” content were removed had to be matched with control groups in which 20% of 22.4% (i.e., 4.48%) of posts were randomly removed. The researchers only manipulated the News Feeds but did not remove any posts from the timeline or “wall” of any Facebook user.


The tweaking of the users’ News Feeds had a statistically significant impact on what the users posted. Removing “positive” items from the News Feed decreased the “positive” word usage in the users’ own postings from roughly 5.25% to 5.1%. Similarly, removal of “negative” News Feed items resulted in a reduction of “negative” word usage in the posts of the negativity-deprived users.The overall effects were statistically significant but still minuscule (changes of merely 0.05% to 0.15% in the various groups). However, one has to bear in mind that the interventions were also rather subtle: Some of the positivity- or negativity-deprived subjects only had 10% of their positive News Feed items removed. Perhaps the results would have been more impressive if the researchers had focused on severe deprivation of “positivity” or “negativity” (i.e. 90% or even 100% removal of “negative”/”positive” items).


The study shows that emotions expressed by others on Facebook can indeed influence our own emotions. However, in light of the small effect size, it is probably premature to call the observed effect a “massive-scale emotional contagion”, as the title of the PNAS paper claims. The study also raises important questions about the ethics of conducting such large-scale analysis of postings without informing individual users and obtaining their individual consent. The fact that the researchers relied on the general Facebook Data Use Policy as sufficient permission to conduct this research (manipulating News Feeds and analyzing emotional content) should serve as a reminder that when we sign up for “free” accounts with Facebook or other social media platforms, we give corporate social media providers access to highly personal data.
Kramer, A., Guillory, J., & Hancock, J. (2014). Experimental evidence of massive-scale emotional contagion through social networks Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.1320040111

To Err Is Human, To Study Errors Is Science

The family of cholesterol lowering drugs known as ‘statins’ are among the most widely prescribed medications for patients with cardiovascular disease. Large-scale clinical studies have repeatedly shown that statins can significantly lower cholesterol levels and the risk of future heart attacks, especially in patients who have already been diagnosed with cardiovascular disease. A more contentious issue is the use of statins in individuals who have no history of heart attacks, strokes or blockages in their blood vessels. Instead of waiting for the first major manifestation of cardiovascular disease, should one start statin therapy early on to prevent cardiovascular disease?

If statins were free of charge and had no side effects whatsoever, the answer would be rather straightforward: Go ahead and use them as soon as possible. However, like all medications, statins come at a price. There is the financial cost to the patient or their insurance to pay for the medications, and there is a health cost to the patients who experience potential side effects. The Guideline Panel of the American College of Cardiology (ACC) and the American Heart Association (AHA) therefore recently recommended that the preventive use of statins in individuals without known cardiovascular disease should be based on personalized risk calculations. If the risk of developing disease within the next 10 years is greater than 7.5%, then the benefits of statin therapy outweigh its risks and the treatment should be initiated. The panel also indicated that if the 10-year risk of cardiovascular disease is greater than 5%, then physicians should consider prescribing statins, but should bear in mind that the scientific evidence for this recommendation was not as strong as that for higher-risk individuals.


Oops button - via Shutterstock
Oops button – via Shutterstock

Using statins in low risk patients

The recommendation that individuals with comparatively low risk of developing future cardiovascular disease (10-year risk lower than 10%) would benefit from statins was met skepticism by some medical experts. In October 2013, the British Medical Journal (BMJ) published a paper by John Abramson, a lecturer at Harvard Medical School, and his colleagues which re-evaluated the data from a prior study on statin benefits in patients with less than 10% cardiovascular disease risk over 10 years. Abramson and colleagues concluded that the statin benefits were over-stated and that statin therapy should not be expanded to include this group of individuals. To further bolster their case, Abramson and colleagues also cited a 2013 study by Huabing Zhang and colleagues in the Annals of Internal Medicine which (according to Abramson et al.) had reported that 18 % of patients discontinued statins due to side effects. Abramson even highlighted the finding from the Zhang study by including it as one of four bullet points summarizing the key take-home messages of his article.

The problem with this characterization of the Zhang study is that it ignored all the caveats that Zhang and colleagues had mentioned when discussing their findings. The Zhang study was based on the retrospective review of patient charts and did not establish a true cause-and-effect relationship between the discontinuation of the statins and actual side effects of statins. Patients may stop taking medications for many reasons, but this does not necessarily mean that it is due to side effects from the medication. According to the Zhang paper, 17.4% of patients in their observational retrospective study had reported a “statin related incident” and of those only 59% had stopped the medication. The fraction of patients discontinuing statins due to suspected side effects was at most 9-10% instead of the 18% cited by Abramson. But as Zhang pointed out, their study did not include a placebo control group. Trials with placebo groups document similar rates of “side effects” in patients taking statins and those taking placebos, suggesting that only a small minority of perceived side effects are truly caused by the chemical compounds in statin drugs.


Admitting errors is only the first step

Whether 18%, 9% or a far smaller proportion of patients experience significant medication side effects is no small matter because the analysis could affect millions of patients currently being treated with statins. A gross overestimation of statin side effects could prompt physicians to prematurely discontinue medications that have been shown to significantly reduce the risk of heart attacks in a wide range of patients. On the other hand, severely underestimating statin side effects could result in the discounting of important symptoms and the suffering of patients. Abramson’s misinterpretation of statin side effect data was pointed out by readers of the BMJ soon after the article published, and it prompted an inquiry by the journal. After re-evaluating the data and discussing the issue with Abramson and colleagues, the journal issued a correction in which it clarified the misrepresentation of the Zhang paper.

Fiona Godlee, the editor-in-chief of the BMJ also wrote an editorial explaining the decision to issue a correction regarding the question of side effects and that there was not sufficient cause to retract the whole paper since the other points made by Abramson and colleagues – the lack of benefit in low risk patients – might still hold true. Instead, Godlee recognized the inherent bias of a journal’s editor when it comes to deciding on whether or not to retract a paper. Every retraction of a peer reviewed scholarly paper is somewhat of an embarrassment to the authors of the paper as well as the journal because it suggests that the peer review process failed to identify one or more major flaws. In a commendable move, the journal appointed a multidisciplinary review panel which includes leading cardiovascular epidemiologists. This panel will review the Abramson paper as well as another BMJ paper which had also cited the inaccurately high frequency of statin side effects, investigate the peer review process that failed to identify the erroneous claims and provide recommendations regarding the ultimate fate of the papers.


Reviewing peer review

Why didn’t the peer reviewers who evaluated Abramson’s article catch the error prior to its publication? We can only speculate as to why such a major error was not identified by the peer reviewers. One has to bear in mind that “peer review” for academic research journals is just that – a review. In most cases, peer reviewers do not have access to the original data and cannot check the veracity or replicability of analyses and experiments. For most journals, peer review is conducted on a voluntary (unpaid) basis by two to four expert reviewers who routinely spend multiple hours analyzing the appropriateness of the experimental design, methods, presentation of results and conclusions of a submitted manuscript. The reviewers operate under the assumption that the authors of the manuscript are professional and honest in terms of how they present the data and describe their scientific methodology.

In the case of Abramson and colleagues, the correction issued by the BMJ refers not to Abramson’s own analysis but to the misreading of another group’s research. Biomedical research papers often cite 30 or 40 studies, and it is unrealistic to expect that peer reviewers read all the cited papers and ensure that they are being properly cited and interpreted. If this were the expectation, few peer reviewers would agree to serve as volunteer reviewers since they would have hardly any time left to conduct their own research. However, in this particular case, most peer reviewers familiar with statins and the controversies surrounding their side effects should have expressed concerns regarding the extraordinarily high figure of 18% cited by Abramson and colleagues. Hopefully, the review panel will identify the reasons for the failure of BMJ’s peer review system and point out ways to improve it.


To err is human, to study errors is science

All researchers make mistakes, simply because they are human. It is impossible to eliminate all errors in any endeavor that involves humans, but we can construct safeguards that help us reduce the occurrence and magnitude of our errors. Overt fraud and misconduct are rare causes of errors in research, but their effects on any given research field can be devastating. One of the most notorious occurrences of research fraud is the case of the Dutch psychologist Diederik Stapel who published numerous papers based on blatant fabrication of data – showing ‘results’ of experiments on non-existent study subjects. The field of cell therapy in cardiovascular disease recently experienced a major setback when a university review of studies headed by the German cardiologist Bodo Strauer found evidence of scientific misconduct. The significant discrepancies and irregularities in Strauer’s studies have now lead to wide-ranging skepticism about the efficacy of using bone marrow cell infusions to treat heart disease.


It is difficult to obtain precise numbers to quantify the actual extent of severe research misconduct and fraud since it may go undetected. Even when such cases are brought to the attention of the academic leadership, the involved committees and administrators may decide to keep their findings confidential and not disclose them to the public. However, most researchers working in academic research environments would probably agree that these are rare occurrences. A far more likely source of errors in research is the cognitive bias of the researchers. Researchers who believe in certain hypotheses and ideas are prone to interpreting data in a manner most likely to support their preconceived notions. For example, it is likely that a researcher opposed to statin usage will interpret data on side effects of statins differently than a researcher who supports statin usage. While Abramson may have been biased in the interpretation of the data generated by Zhang and colleagues, the field of cardiovascular regeneration is currently grappling in what appears to be a case of biased interpretation of one’s own data. An institutional review by Harvard Medical School and Brigham and Women’s Hospital recently determined that the work of Piero Anversa, one of the world’s most widely cited stem cell researchers, was significantly compromised and warranted a retraction. His group had reported that the adult human heart exhibited an amazing regenerative potential, suggesting that roughly every 8 to 9 years the adult human heart replaces its entire collective of beating heart cells (a 7% – 19% yearly turnover of beating heart cells). These findings were in sharp contrast to a prior study which had found only a minimal turnover of beating heart cells (1% or less per year) in adult humans. Anversa’s finding was also at odds with the observations of clinical cardiologists who rarely observe a near-miraculous recovery of heart function in patients with severe heart disease. One possible explanation for the huge discrepancy between the prior research and Anversa’s studies was that Anversa and his colleagues had not taken into account the possibility of contaminations that could have falsely elevated the cell regeneration counts.


Improving the quality of research: peer review and more

Despite the fact that researchers are prone to make errors due to inherent biases does not mean we should simply throw our hands up in the air, say “Mistakes happen!” and let matters rest. High quality science is characterized by its willingness to correct itself, and this includes improving methods to detect and correct scientific errors early on so that we can limit their detrimental impact. The realization that lack of reproducibility of peer-reviewed scientific papers is becoming a major problem for many areas of research such as psychology, stem cell research and cancer biology has prompted calls for better ways to track reproducibility and errors in science.

One important new paradigm that is being discussed to improve the quality of scholar papers is the role of post-publication peer evaluation. Instead of viewing the publication of a peer-reviewed research paper as an endpoint, post publication peer evaluation invites fellow scientists to continue commenting on the quality and accuracy of the published research even after its publication and to engage the authors in this process. Traditional peer review relies on just a handful of reviewers who decide about the fate of a manuscript, but post publication peer evaluation opens up the debate to hundreds or even thousands of readers which may be able to detect errors that could not be identified by the small number of traditional peer reviewers prior to publication. It is also becoming apparent that science journalists and science writers can play an important role in the post-publication evaluation of published research papers by investigating and communicating research flaws identified in research papers. In addition to helping dismantle the Science Mystique, critical science journalism can help ensure that corrections, retractions or other major concerns about the validity of scientific findings are communicated to a broad non-specialist audience.

In addition to these ongoing efforts to reduce errors in science by improving the evaluation of scientific papers, it may also be useful to consider new pro-active initiatives which focus on how researchers perform and design experiments. As the head of a research group at an American university, I have to take mandatory courses (in some cases on an annual basis) informing me about laboratory hazards, ethics of animal experimentation or the ethics of how to conduct human studies. However, there are no mandatory courses helping us identify our own research biases or how to minimize their impact on the interpretation of our data. There is an underlying assumption that if you are no longer a trainee, you probably know how to perform and interpret scientific experiments. I would argue that it does not hurt to remind scientists regularly – no matter how junior or senior- that they can become victims of their biases. We have to learn to continuously re-evaluate how we conduct science and to be humble enough to listen to our colleagues, especially when they disagree with us.


Note: A shorter version of this article was first published at The Conversation with excellent editorial input provided by Jo Adetunji.
Abramson, J., Rosenberg, H., Jewell, N., & Wright, J. (2013). Should people at low risk of cardiovascular disease take a statin? BMJ, 347 (oct22 3) DOI: 10.1136/bmj.f6123

New Study Shows Surgical Checklists In Operating Rooms Are Less Effective Than Assumed

The patient has verified his or her identity, the surgical site, the type of procedure, and his or her consent. Check.

The surgical site is marked on a patient if such marking is appropriate for the procedure. Check.

The probe measuring blood oxygen content has been placed on the patient and is functioning. Check.

All members of the surgical and anesthesia team are aware of whether the patient has a known allergy? Check.

Surgeon – via Shutterstock

These were the first items on a nineteen-point World Health Organization (WHO) surgical safety checklist from an international research study to evaluate the impact of routinely using checklists in operating rooms. The research involved over 7,500 patients undergoing surgery in eight hospitals (Toronto, Canada; New Delhi, India; Amman, Jordan; Auckland, New Zealand; Manila, Philippines; Ifakara, Tanzania; London, England; and Seattle, WA) and was published in the New England Journal of Medicine in 2009.

Some of the items on the checklist were already part of standard care at many of the enrolled hospitals, such as the use of oxygen monitoring probes. Other items, such as ensuring that there was a contingency plan for major blood loss prior to each surgical procedure, were not part of routine surgical practice. The impact of checklist implementation was quite impressive, showing that this simple safety measure nearly halved the rate of death in surgical patients from 1.6% to 0.8%.  The infection rate at the site of the surgical procedure also decreased from 6.2% in the months preceding the checklist introduction to a mere 3.4%.

Checklists as a Panacea?

The remarkable results of the 2009 study were met with widespread enthusiasm. This low-cost measure could be easily implemented in hospitals all over the world and could potentially lead to major improvements in patient outcomes. It also made intuitive sense that encouraging communication between surgical team members via checklists would reduce complications after surgery.

A few weeks after the study’s publication, the National Patient Safety Agency (NPSA) in the United Kingdom issued a patient safety alert, requiring National Health Service (NHS) organizations to use the WHO Surgical Safety Checklist for all patients undergoing surgical procedures. In 2010, Canada followed suit and also introduced regulations requiring the use of surgical safety checklists. However, the data for the efficacy of such lists had only been obtained in observational research studies conducted in selected hospitals. Would widespread mandatory implementation of such a system in “real world” community hospitals also lead to similar benefits?

A recently published study in the New England Journal of Medicine lead by Dr. David Urbach at the University of Toronto has now reviewed the surgery outcomes of hospitals in Ontario, Canada, comparing the rate of surgical complications during three-month periods before and after the implementation of the now mandatory checklists.  Nearly all the hospitals reported that they were adhering to the checklist requirements and the vast majority used either a checklist developed by the Canadian Patient Safety Institute, which is even more comprehensive than the WHO checklist or other similar checklists. After analyzing the results of more than 200,000 procedures at 101 hospitals, Urbach and colleagues found no significant change in the rate of death after surgery after the introduction of the checklists (0.71% versus 0.65% – not statistically significant). Even the overall complication rates or the infection rates in the Ontario hospitals did not change significantly after surgical teams were required to complete the checklists.


Check the Checklist


The discrepancy in the results between the two studies is striking. How can one study demonstrate such a profound benefit of introducing checklists while a second study shows no significant impact at all? The differences between the two studies may hold some important clues. The 2009 study had a pre-checklist death rate of 1.6%, which is more than double the pre-checklist death rate in the more recent Ontario study. This may reflect the nature and complexity of the surgeries surveyed in the first study and also the socioeconomic differences. A substantial proportion of the patients in the international study were enrolled in low-income or middle-income countries. The introduction of a checklist may have been of much greater benefit to patients and hospitals that were already struggling with higher complication rates.

Furthermore, as the accompanying editorial by Dr. Lucian Leape in the New England Journal of Medicine points out, assessment of checklist implementation in the recent study by Urbach and colleagues was based on a retrospective analysis of self-reports by surgical teams and hospitals. Items may have been marked as “checked” in an effort to rush through the list and start the surgical procedures without the necessary diligence and time required to carefully go through every single item on the checklist. In the 2009 WHO study, on the other hand, surgical teams were aware of the fact that they were actively participating in a research study and the participating surgeons may have therefore been more motivated to meticulously implement all the steps on a checklist.

One of the key benefits of checklists is that they introduce a systematic and standardized approach to patient care and improve communication between team members. It is possible that the awareness of surgical teams in the Ontario hospitals in regards to patient safety and the need for systematic communication was already raised to higher level even before the introduction of the mandatory checklists so that this mandate may have had less of an impact.


Looking Forward

The study by Urbach and colleagues does not prove that safety checklists are without benefit. It highlights that there is little scientific data supporting the use of mandatory checklists. Since the study could not obtain any data on how well the checklists were implemented in each hospital, it is possible that checklists are more effective when team members buy into their value and do not just view it as another piece of mandatory and bureaucratic paperwork.

Instead of mandating checklists, authorities should consider the benefits of allowing surgical teams to develop their own measures that improve patient safety and team communication. The safety measures will likely contain some form of physical or verbal checklists. By encouraging surgical teams to get involved in the development process and tailor the checklists according to the needs of individual patients, surgical teams and hospitals, they may be far more motivated to truly implement them.

Optimizing such tailored checklists, understanding why some studies indicate benefits of checklists whereas others do not and re-evaluating the efficacy of checklists in the non-academic setting will all require a substantial amount of future research before one can draw definitive conclusions about the efficacy of checklists. Regulatory agencies in Canada and the United Kingdom should reconsider their current mandates. Perhaps an even more important lesson to be learned is that health regulatory agencies should not rush to enforce new mandates based on limited scientific data.

Urbach DR, Govindarajan A, Saskin R, Wilton AS, & Baxter NN (2014). Introduction of surgical safety checklists in Ontario, Canada. The New England Journal of Medicine, 370 (11), 1029-38 PMID: 24620866