Novelty in science – real necessity or distracting obsession?

File 20171219 5004 1ecssnn.jpg?ixlib=rb 1.1
It may take time for a tiny step forward to show its worth.
ellissharp/Shutterstock.com

Jalees Rehman, University of Illinois at Chicago

In a recent survey of over 1,500 scientists, more than 70 percent of them reported having been unable to reproduce other scientists’ findings at least once. Roughly half of the surveyed scientists ran into problems trying to reproduce their own results. No wonder people are talking about a “reproducibility crisis” in scientific research – an epidemic of studies that don’t hold up when run a second time.

Reproducibility of findings is a core foundation of science. If scientific results only hold true in some labs but not in others, then how can researchers feel confident about their discoveries? How can society put evidence-based policies into place if the evidence is unreliable?

Recognition of this “crisis” has prompted calls for reform. Researchers are feeling their way, experimenting with different practices meant to help distinguish solid science from irreproducible results. Some people are even starting to reevaluate how choices are made about what research actually gets tackled. Breaking innovative new ground is flashier than revisiting already published research. Does prioritizing novelty naturally lead to this point?

Incentivizing the wrong thing?

One solution to the reproducibility crisis could be simply to conduct lots of replication studies. For instance, the scientific journal eLife is participating in an initiative to validate and reproduce important recent findings in the field of cancer research. The first set of these “rerun” studies was recently released and yielded mixed results. The results of 2 out of 5 research studies were reproducible, one was not and two additional studies did not provide definitive answers.

There’s no need to restrict these sort of rerun studies to cancer research – reproducibility issues can be spotted across various fields of scientific research.

Researchers should be rewarded for carefully shoring up the foundations of the field.
Alexander Raths/Shutterstock.com

But there’s at least one major obstacle to investing time and effort in this endeavor: the quest for novelty. The prestige of an academic journal depends at least partly on how often the research articles it publishes are cited. Thus, research journals often want to publish novel scientific findings which are more likely to be cited, not necessarily the results of newly rerun older research.

A study of clinical trials published in medical journals found the most prestigious journals prefer publishing studies considered highly novel and not necessarily those that have the most solid numbers backing up the claims. Funding agencies such as the National Institutes of Health ask scientists who review research grant applications to provide an “innovation” score in order to prioritize funding for the most innovative work. And scientists of course notice these tendencies – one study found the use of positive words like “novel,” “amazing,” “innovative” and “unprecedented” in paper abstracts and titles increased almost ninefold between 1974 and 2014.

Genetics researcher Barak Cohen at Washington University in St. Louis recently published a commentary analyzing this growing push for novelty. He suggests that progress in science depends on a delicate balance between novelty and checking the work of other scientists. When rewards such as funding of grants or publication in prestigious journals emphasize novelty at the expense of testing previously published results, science risks developing cracks in its foundation.

Houses of brick, mansions of straw

Cancer researcher William Kaelin Jr., a recipient of the 2016 Albert Lasker Award for Basic Medical Research, recently argued for fewer “mansions of straw” and more “houses of brick” in scientific publications.

One of his main concerns is that scientific papers now inflate their claims in order to emphasize their novelty and the relevance of biomedical research for clinical applications. By exchanging depth of research for breadth of claims, researchers may be at risk of compromising the robustness of the work. By claiming excessive novelty and impact, researchers may undermine its actual significance because they may fail to provide solid evidence for each claim.

Kaelin even suggests that some of his own work from the 1990s, which transformed cell biology research by discovering how cells can sense oxygen, may have struggled to get published today.

Prestigious journals often now demand complete scientific stories, from basic molecular mechanisms to proving their relevance in various animal models. Unexplained results or unanswered questions are seen as weaknesses. Instead of publishing one exciting novel finding that is robust, and which could spawn a new direction of research conducted by other groups, researchers now spend years gathering a whole string of findings with broad claims about novelty and impact.

There should be more than one path to a valuable journal publication.
Mehaniq/Shutterstock.com

Balancing fresh findings and robustness

A challenge for editors and reviewers of scientific manuscripts is assessing the novelty and likely long-term impact of the work they’re assessing. The eventual importance of a new, unique scientific idea is sometimes difficult to recognize even by peers who are grounded in existing knowledge. Many basic research studies form the basis of future practical applications. One recent study found that of basic research articles that received at least one citation, 80 percent were eventually cited by a patent application. But it takes time for practical significance to come to light.

A collaborative team of economics researchers recently developed an unusual measure of scientific novelty by carefully studying the references of a paper. They ranked a scientific paper as more novel if it cited a diverse combination of journals. For example, a scientific article citing a botany journal, an economics journal and a physics journal would be considered very novel if no other article had cited this combination of varied references before.

This measure of novelty allowed them to identify papers which were more likely to be cited in the long run. But it took roughly four years for these novel papers to start showing their greater impact. One may disagree with this particular indicator of novelty, but the study makes an important point: It takes time to recognize the full impact of novel findings.

The ConversationRealizing how difficult it is to assess novelty should give funding agencies, journal editors and scientists pause. Progress in science depends on new discoveries and following unexplored paths – but solid, reproducible research requires an equal emphasis on the robustness of the work. By restoring the balance between demands and rewards for novelty and robustness, science will achieve even greater progress.

Jalees Rehman, Associate Professor of Medicine and Pharmacology, University of Illinois at Chicago

This article was originally published on The Conversation. Read the original article.

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.

 

References

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. 

 

 

ResearchBlogging.org

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.

References:

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.

 

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

 

ResearchBlogging.org

 

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

Funding Fever: Researchers Will Use Genome Editing to Increase Support for Science Among Politicians

“If we achieve what we are working on, I will have a job forever.”

“We have reason to believe that there is a single gene that distinguishes those people who give funding for scientific research and those who do not give. When we find that gene, we are going to be able to introduce it into individuals and change them so that now they are going to become donors.”

“The question that really motivates my research is how can I get people to give me more money, to give money to science.”

“By using the CRISPR/Cas9 technique, we are hoping to ensure that all future generations of politicians have the ‘Fund Science’ gene.”

Created for the American Association of Immunologists 2015 Annual Meeting

Written And Directed by Matt Klinman
Shot and Edited by Alec Cohen

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.

 

Reference:

ResearchBlogging.org

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.

STEM Education Promotes Critical Thinking and Creativity: A Response to Fareed Zakaria

Fareed Zakaria recently wrote an article in the Washington Post lamenting the loss of liberal arts education in the United States. However, instead of making a case for balanced education, which integrates various forms of creativity and critical thinking promoted by STEM (science, technology, engineering and mathematics) and by a liberal arts education, Zakaria misrepresents STEM education as primarily teaching technical skills and also throws in a few cliches about Asians. You can read my response to his article at 3Quarksdaily.

 

Fractal

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.

Books

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.

ResearchBlogging.org

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

How Often Do Books Mention Scientists and Researchers?

Here is a graphic showing the usage of the words “scientists”, “researchers”, “soldiers” in English-language books published in 1900-2008. The graphic was generated using the Google N-gram Viewer which scours all digitized books in the Google database for selected words and assesses the relative word usage frequencies.

Ngram

 

(You can click on the chart to see a screen shot or on this link for the N-gram Viewer)

It is depressing that soldiers are mentioned more frequently than scientists or researchers (even when the word frequencies of “scientists” and “researchers” are combined) in English-language books even though the numbers of researchers in the countries which produce most English-language books are comparable or higher than the number of soldiers.

Here are the numbers of researchers (data from the 2010 UNESCO Science report, numbers are reported for the year 2007, PDF) in selected English-language countries and the corresponding numbers of armed forces personnel (data from the World Bank, numbers reported for 2012):

United States: 1.4 million researchers vs. 1.5 million armed forces personnel
United Kingdom: 255,000 researchers vs. 169,000 armed forces personnel
Canada: 139,000 researchers vs. 66,000 armed forces personnel

I find it disturbing that our books – arguably one of our main cultural legacies – give a disproportionately greater space to discussing or describing the military than to our scientific and scholarly endeavors. But I am even more worried about the recent trends. The N-gram Viewer evaluates word usage up until 2008, and “soldiers” has been steadily increasing since the 1990s. The usage of “scientists” and “researchers” has reached a plateau and is now decreasing. I do not want to over-interpret the importance of relative word frequencies as indicators of society’s priorities, but the last two surges of “soldiers” usage occurred during the two World Wars and in 2008, “soldiers” was used as frequently as during the first years of World War II.

It is mind-boggling for us scientists that we have to struggle to get funding for research which has the potential to transform society by providing important new insights into the nature of our universe, life on this planet, our environment and health, whereas the military receives substantially higher amounts of government funding (at least in the USA) for its destructive goals. Perhaps one reason for this discrepancy is that voters hear, see and read much more about wars and soldiers than about science and research. Depictions of heroic soldiers fighting evil make it much easier for voters to go along with allocation of resources to the military. Most of my non-scientist friends can easily name books or movies about soldiers, but they would have a hard time coming up with books and movies about science and scientists. My take-home message from the N-gram Viewer results is that scientists have an obligation to reach out to the public and communicate the importance of science in an understandable manner if they want to avoid the marginalization of science.

Science and Poetry: #ScienceLanday #ScienceHaiku

In a recent essay for 3Quarksdaily, I describe my fascination with short poetic forms such as haiku and landays (short Afghani folk poems) and how these traditional Asian forms of poetry can serve as means to create English-language poems that relate to science and our lives as academic scientists.

217px-Basho's_Flowers,_66x60_by_Adam_Shaw

Example of science-related haiku:

 

Mitochondria

Grainy threads in cells,

powerhouses of life are

harbingers of death

 

Example of a landay:

 

Tenure Trek

Sirens of tenure captivate us,

chained to hallowed halls of academic freedom.

 

Please check out the essay, which includes additional haiku and landays. It also contains excerpts from a wonderful issue of Poetry Magazine about Afghani women and how they compose and share landays as a form of lyrical resistance, finding beautiful and cutting verses to describe their struggles and hardships.

I hope you will be inspired to compose your own haiku or landays related to science. It would be great if you could either include your compositions as comments at the end of this Scilogs post, or share them via Twitter using the hashtags #ScienceHaiku or #ScienceLanday. I intend to collect your science-related haiku and landays and publish them in an upcoming Scilogs blog post. Please make sure that you provide a reference at the end so that I know how to credit you, i.e your name, your Twitter-handle, etc.

Image Credit: Basho’s Flowers (by Adam Shaw via Wikimedia Commons)

 

Job Interviews Are Like Scientific Experiments

Most scientists are extremely meticulous when it comes to planning, performing and interpreting experiments. We spend many days reading up on the background literature to find out what aspects of the research is already established, and what research questions would be novel or meaningful. Once the nature and goals of the experiments are established, we generate an experimental plan and ensure that we have all the necessary equipment and supplies. While performing the experiments, we often run into unanticipated problems (“we just ran out of cell culture media”, “the cell number is half of what we had anticipated”, “the qPCR machine just broke down”) and have to quickly improvise to salvage as much of the experiment as possible. Once the experiments have been sufficiently replicated, scientists interpret the data and give rise to conclusions and novel hypotheses. One could presume that scientists would apply a similar degree of meticulous planning and execution in other situations at work that require organization skills, such as …..job interviews. Unfortunately, this is not necessarily true. I can speak from my own experience as an interview candidate in a variety of situations, as well as someone who has interviewed many graduate students, post-docs, research technicians and faculty candidates. When I look back at my career, I realize that I was not very well prepared for my job interviews and have had a “roll-of-the-dice attitude’, very different from my approach to my scientific experiments.

 

 

An interesting recent commentary in the journal Nature Immunology by Haseltine and Gould suggests that many scientists abandon the scientific process that they are so accustomed to when they are interviewing for jobs, and that this can be quite detrimental to a scientist’s job prospects. The article provides specific examples of how to approach a job interview in a “scientific” manner by applying principles and practices that we use for our scientific work to the interview process. This experiment-interview analogy can be quite useful as long as it is tailored according to the individual situation of a scientist applying for a job.

1. Background research

Before scientists perform experiments, they routinely use literature search engines such as PubMed or Web of Knowledge to find out what has been previously discovered and published. Job candidates should make use of these search engines to thoroughly research recent scientific publications from the laboratory or department in which they are interviewing. This gives the candidate a good overview of the topics of interest and productivity of their future employer, and it also allows the candidate to impress the interviewers with an in-depth and current knowledge of the area of research the interviewer is engaged in. Haseltine and Gould also make the excellent suggestion that candidates should not just rely on search engines of published scientific findings of a laboratory, but also make use of information available from grant funding agencies. The NIH (National Institutes of Health) grant search engine RePORTER, for example, is extremely useful for applicants seeking biomedical research positions in the academic world, because it gives detailed information about the grants of the future employer. It is always good to know how well-funded a future employer is, because one’s career prospects in biomedical research heavily depend on access to NIH funding. Furthermore, the proposal in the  RePORTER database include abstracts and aims of funded grants and will inform the candidate about ongoing and future research efforts, something which is not always easily discerned from published papers in the PubMed database. Lastly, many scientists and departments now have websites or blogs which should be carefully reviewed before the interview because they may also contain valuable information, such as the number of research groups in a department or whether the academic department is ensuring gender equality and adequate representation of minorities, especially for people in leadership positions.

2. Identify goals

Before we conduct experiments, we always clearly define the “read-outs”. Will we be measuring cell proliferation? Gene expression? Survival of experimental animals in response to an injury? Delineating the specific goals of an experiment allows us to ensure that the experiment is adequately powered (i.e. the proper sample size), uses the appropriate methods and that our expectations match the experimental design. For example, a “screening experiment” intended to identify a few potential cell survival signaling pathways will be conducted very differently than an experiment that definitively tests the impact a specific signal has on the cell survival.

Prior to a job interview, the candidate has to first perform an introspective analysis and clearly understand one’s own goals and expectations for the new job. Am I interested in this job because of the specific research area or because of the track record of the laboratory or department? Am I primarily interested in this job because it will provide me with an opportunity to acquire new scientific skills? Will this job prepare me for a career as an independent scientific investigator? Will the job ideally increase my chances of employment in the private sector such as a biotech company? We often only have vague notions about what we want for our future, and the time prior to a job interview is a good opportunity to narrow down and specify the short-term and long-term goals.

In addition to the introspective analysis that needs to be performed prior to the interview, the candidate needs to use the interview as an opportunity to identify the goals and expectations of the prospective employer and find out whether they match up with one’s own expectations identified during the introspective analysis.

3. Experimenting and Improvising

Experiments rarely work the first time, and even if they do, one still needs to repeat them multiple times under varying conditions to ensure their validity. The same is true for job interviews. Practice makes perfect, and it does not hurt to take advantage of multiple interview opportunities. It can also be useful to perform practice interviews with colleagues or friends, so that one gets into the habit of having a coherent answer to questions such as “Where do you see yourself in 5 years?” or “What do you see as your emerging scientific focus?”.

Improvisation is the key to successful experimentation. The best laid plans of mice and scientists often go awry, but one has to quickly adapt one’s experimental plan without compromising the scientific integrity of the data. Whether it involves running from lab to lab to chase down a missing chemical or changing the timeline of the experiment at the last minute, experimental scientists learn to become flexible while remaining rigorous. Similarly, job interviews require the same kind of flexibility. One may assume that everyone will stick to the pre-arranged itinerary regarding the prospective colleagues that a candidate will meet during the interview day, but it is not uncommon to have major last-minute changes to the itinerary. I have even seen cases where a candidate is asked to give an unplanned talk and therefore it is important to be prepared for such surprises.

4. Analyze and Interpret

Experiments always need to be analyzed and interpreted; experimental data without the proper context and interpretation can be quite meaningless. Similarly, analysis and interpretation is important for job interviews. Some of the analysis and interpretation can occur during the interview. Interviewers perusing the CV of an applicant may see the data (i.e. grades, the list of publications, abstracts that one has presented, awards, etc), but it can be very advantageous for an applicant to steer the interviewer towards one’s strengths. For example, if the applicant has published in three very different areas and appears “unfocused”, the applicant can preempt such a judgment by providing a narrative of why one worked in these seemingly different research areas.

Even after the interview, an applicant needs to sit down and analyze the “data” obtained from the interview experience. How did the interviewers respond to my career goals? Were they impressed or turned off by my research background? Which questions did I master and which ones were challenging? Were the people I met the colleagues that I could get along with? Is this really the best place in terms of helping me meet my scientific and career goals?

5. Conclusion

At the end of the interview, it is important to arrive at some sort of conclusion and a timeline for when a definitive decision can or will be made. Are there any questions that need to be resolved prior to arriving at a decision? In many cases it is also helpful for job candidates to follow-up on the subsequent day with a brief email, thanking the interviewer(s) for the opportunity to meet them. Including specific, unique points that came up during the interview will help ensure that the applicant makes a lasting impression and stick out from a large group of applicants. A generic “Thank you” is not as powerful as a “Thank you” coupled with, for example, expressing one’s excitement about the prospect of working on microbiome regulation of inflammation and proposing a few innovative experiments to address questions raised during the interview. Not only do such emails reinforce one’s interest, the responses of the interviewer(s) to an email can also help the applicant gauge the level of enthusiasm of the prospective employers.

These are just suggestions of how to approach a job interview in a logical and organized manner, something which every scientist ought to be accustomed to. The main take-home message is that the effort and time that goes into preparing for an interview is a worthwhile investment because it can have a major impact on the course of one’s scientific career.
ResearchBlogging.org

Haseltine, Derek, & Gould, James (2013). Job-search basics: a scientific approach to interviewing Nature Immunology, 14, 1199-1201 DOI: 10.1038/ni.2748