Shedding Light on Dark Energy

Dark energy and the nature of the universe are two of the most exciting discoveries of the past couple decades, but can be some of the most difficult concepts for non-physicists to grasp. More often than not, dark energy is just a futuristic-sounding prop in a science fiction novel. But while it may make for a fantastical plot tool, the real discoveries in dark energy are even more exciting. I’m going to do my best to explain a bit of the history of dark energy and some of the experimental evidence that helps to constrain the theory.

The History of Dark Energy

The original concept of dark energy was proposed by Einstein in his field equations in the 1910s, which essentially describe the behavior of matter due to gravity. A good analogy for Einstein’s Theory of General Relativity is a linen sheet, stretched tight – this represents the universe. Let’s scatter a few marbles across the sheet. Each will create a small dimple in the sheet. These represent mass in the universe – galaxies. Now we can observe the effect of gravity: each marble is going to start to roll towards nearby marbles due to each other’s dimples, as gravity causes massive bodies to attract to each other. This is the problem Einstein encountered: the universe couldn’t remain the same size if gravity were the only force to act on massive objects. To keep the size of the universe static, Einstein needed a repulsive force to counteract gravity, and essentially added a “fudge factor” to his field equations, which he called the “cosmological constant.” This constant would be a property of space itself.

When Hubble discovered that the universe was expanding in 1928, Einstein quickly abandoned the idea of a cosmological constant, purportedly calling it his “greatest blunder.” An expanding universe is no longer static, and therefore Einstein didn’t need a force to counteract the contraction due to gravity. Essentially, the expansion of the universe wouldn’t contradict his theory, provided that the expansion was slowing from gravitational pull.

However, in 1998, it was discovered that the expansion of the universe was accelerating. This no longer agreed with a model that only included gravity – the cosmological constant would have to be reintroduced. This accelerating expansion is the first piece of modern evidence that points towards the existence of dark energy.

Type Ia Supernovae

In 1998, Type Ia supernovae provided the first indication of the accelerating expansion of the universe. The explosions of these particular supernovae occur consistently enough that they can be used as a basis for a brightness measurement, referred to as a “standard candle.” Astronomers measure the amount of light received from a particular supernova, and, by tracking the supernova over several days, can estimate how much light the supernova emits at its source. This provides a measurement of how far away the supernova is. Then, by looking at the colors the supernova emits, astronomers can determine how quickly the star is moving away from Earth, using the Doppler shift, or “redshift” (the change in frequency as a result of velocity). Since it takes time for light from these supernovae to reach Earth, light from more distant supernovae was emitted longer ago, and similarly, light from closer supernovae was emitted more recently. Distant supernovae can thus give a measure of the expansion of the universe via their redshifts, and this is where the accelerating expansion was observed: closer supernovae are receding far faster than distant supernovae.

The model of the universe mentioned earlier dictates that there are four parameters that govern cosmology: matter (or mass), the radiation (or light), the cosmological constant (or dark energy), and curvature (or the shape of the universe). We can think of these as “fractions” of what make up the universe, as they add up to 1. (However, the curvature can be positive or negative.) So, if we don’t know anything about dark energy, we should still be able to make measurements of the other parameters and figure out whether or not the dark energy fraction is zero, i.e. if it actually exists.

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Results of the Supernova Cosmology Project and BOOMERanG, the cosmic microwave background experiment. Numbers represent fractions, so 0.5 on the dark energy axis would indicate 50% of the universe is dark energy. Source: Supernova Cosmology Project, Lawrence Berkeley Laboratory.

These supernova measurements provide information about the mass dark energy fractions, shown on the right. It doesn’t provide an exact answer for each, but instead gives an estimate, shown as the yellow oval to the right. This shows that the values for dark energy fraction and mass fraction fall somewhere inside that oval. Supernova data largely point towards the existence of dark energy, but not definitively. The oval is bisected by the red “flat universe” line, along which the true value would lie if there universe were shown to be flat. Thus, determining the shape of the universe is a key step towards determining the existence of dark energy.

Cosmic Microwave Background

The second experiment we’ll look at is the observation of the cosmic microwave background, which is the residual light left in the universe from the Big Bang. This corresponds to a temperature of 2.7 Kelvins (-455 °F), and gives a direct measure of the radiation fraction, which turns out to be the minute value of 0.01%. It also allows astronomers to determine the curvature of the universe.

The notion of curvature is difficult to visualize. Our linen sheet from earlier describes a flat universe. A closed universe would be a world contained along the surface of a spherical shell, and an open universe is a saddle-like shape.

Representation of closed, open, and flat geometries. Source: NASA, Wilkinson Microwave Anisotropy Probe.

Representation of closed, open, and flat geometries. Source: NASA, Wilkinson Microwave Anisotropy Probe.

The temperature of the cosmic microwave background is remarkably consistent, but small part-per-million fluctuations in it (called “anisotropies”) can be observed, which come from sound waves in the very early universe, just after the Big Bang. Astronomers know what pitch these sound waves should be, so by measuring the residual waves in the sky, they can tell whether or not the observed angle is from a flat or a curved universe. An experiment called BOOMERanG collected data in a balloon above Antarctica, and found that the Universe is flat, and so there is zero curvature. Going back to the graph earlier, the combination of supernova and BOOMERanG data puts the dark energy and mass fractions somewhere inside the green wedge. We’ll need one more experiment to precisely determine what the fractions are.

Baryon Acoustic Oscillations

Returning to the model mentioned at the beginning, we now have values for the radiation fraction and the curvature, and a relationship between the mass and the dark energy fractions. The final piece of our puzzle comes from baryon acoustic oscillations, which are the peaks and troughs in the concentrations of galaxies found in the universe. Essentially, the size of these oscillations gives a number for the mass fraction of the universe, which turns out to be roughly 30% of the universe. Now that we have the mass fraction, we can figure out the dark energy fraction directly.

Putting It All Together

Combination of Type Ia supernova (SNe), cosmic microwave background (CMB) and baryon acoustic oscillation (BAO) data. The combination of the three experiments confines the dark energy and mass fractions of the universe to a very narrow range. Source: Supernova Cosmology Project, Lawrence Berkeley Laboratory.

Combination of Type Ia supernova (SNe), cosmic microwave background (CMB) and baryon acoustic oscillation (BAO) data. The combination of the three experiments confines the dark energy and mass fractions of the universe to a very narrow range. Source: Supernova Cosmology Project, Lawrence Berkeley Laboratory.

Merging the three different experimental data sets, the true story of dark energy surfaces – a whopping 70% of the universe is made up of dark energy. Of the 30% that is mass, it turns out that only 4% is ordinary matter, the stuff we think of being in the universe (stars, planets, interstellar dust, etc.) while the other 26% is dark matter (different from dark energy).

So What?

There’s strong evidence that dark energy exists, and experiments based on different physics come together to support each other. In fact, dark energy comprises most of the universe. However, the nature of dark energy is still unknown – all our evidence is indirect (hence the moniker “dark”). Even though it makes up so much of the Universe, its tendency to “push back” means that it has a very low density (10-26 kg/m3). Theories about the nature of dark energy abound, but, until there is a way to experimentally challenge each, the true identity of dark energy will remain a mystery.


bioDan is a physics Ph.D. student at University of Colorado Boulder and is a graduate research assistant at the National Institute of Standards and Technology. His research involves the development of infrared lasers for the detection of atmospheric greenhouse gases. You can reach him at daniel.maser AT colorado.edu.

References / Further Reading

  1. A. G. Riess et al., Astronomical Journal 116, 1009 (1998).
  2. S. Perlmutter et al., Astrophysical Journal 517, 565 (1999).
  3. B. Schwarzschild, Physics Today 60, 21+ (2007).
  4. B. Schwartzschild, Physics Today 54, 17 (2001).
  5. P. J. E. Peebles and B. Ratra, Reviews of Modern Physics 75, 559 (2003).
  6. P. de Bernardis et al., Nature 404, 955 (2000).
  7. D. J. Eisenstein, New Astronomy Reviews 49, 360 (2005).
  8. S. Perlmutter, Physics Today 56, 53 (2003).
  9. J. B. Hartle, Gravity: An Introduction to Einstein’s General Relativity (Addison-Wesley, 2003).
  10. W. Hu, N. Sugiyama, and J. Silk, Nature 386, 37 (1997).
  11. L. Miao, L. Xiao-Dong, W. Shuang, and W. Yi, Communications in Theoretical Physics 56, 525 (2011).
  12. J. A. Frieman, M. S. Turner, and D. Huterer, Annual Review of Astronomy and Astrophysics 46, 385 (2008).
  13. M. Kowalski et al., Astrophysical Journal 686, 749 (2008).
  14. J. E. Lidsey, Temperature fluctuations in the cosmic microwave background, (2003).
  15. Planck Collaboration, P. Ade et al., Astronomy & Astrophysics (2013), arXiv:1303.5076.
  16. Planck Collaboration, P. Ade et al., (2013), arXiv:1303.5075.
  17. H.-J. Seo and D. J. Eisenstein, The Astrophysical Journal 598, 720 (2003).
    S. W. Allen, A. E. Evrard, and A. B. Mantz, Annual Review of Astronomy and Astrophysics 49, 409 (2011).

Category: Physics, The Student Blog | 5 Comments

What we could learn from industry

You have probably heard a lot of articlesblog posts, tweets, and facebook rants lately about the abysmal state of the job market for aspiring academics.  You’ve probably heard stories (the Berkeley Science Review even ran one last semester) about the shifting reality for graduate students, and about the needed focus on non-academic careers for graduate education.

I’m not here to debate any of this, but there’s plenty of material out there if you’re curious.  However, there’s a really important point in this discussion that almost never gets voiced: learning about the non-academic world is not only about getting a non-academic job, it also makes us better scientists. 

Now, I can see you all rushing to your keyboards to rise up in protest, so let me make this clear: I’m not saying that academia should be a “business” in some sense, and I understand the importance of keeping conflicts of interest out of science (though last time I checked the simple desire to publish can be, itself, a conflict of interest).  What I’m saying is that we have a lot to learn from the non-academic world, about how to interact with our peers, how to work together as teams, how to manage projects, and how to communicate with others.

In my most cynical moments, I view “business” as a relatively simple game: how can the right collection of people make as much money as humanly possible?  This may sound like a critique, but it’s not. It is just a goal (in reality probably only one of many). And guess what businesses are really good at doing?  Making money, and accomplishing that goal.  They’re clearly doing something right, so what is it that we can learn from them?

Let’s take a moment and think about what being part of a successful business generally entails: you need to get a group of people together with a wide range of expertise and experience.  You must define a common goal, and make a plan to accomplish that goal.  Moreover, you need to split up chunks of that plan and assign each of them to people in your group, making sure to pair the right job with the right person.  In so doing, each individual contributes their own skills to the project, and they learn a lot in doing so.  At the end of the day, the team achieves their goal, and everyone shares in the riches gained.

To me, this sounds a lot like a science lab.  Labs tend to be focused on a single “theme” of scientific question (e.g., “we study visual processing in zebrafish”).  They’ve got a bunch of graduate students and post-docs, all of whom bring something unique to the table, and each of which is involved in asking a different question related to the “big picture”.  Finally, you’ve got the PI at the top, pulling the strings and making sure the machine runs smoothly (ideally anyway).

The only problem is that even though the task that academics and businesses must accomplish is quite similar, they take very different approaches to solving it.  The business world has a tendency to emphasize interpersonal relationships and “teamwork” as attributes that it admires.  It gives credit to those who can work with groups, and who learn to share the load and the glory.

“Piled Higher and Deeper” by Jorge Cham
www.phdcomics.com

Academia, on the other hand, runs on a sort of “wheel and spoke” model in which each graduate student is expected to be the sole lead in “their project”.  Post-docs may have a few people working underneath them, but it’s rare to find a lab that truly distributes the workload.  And why should they?  Academic publishing incentives encourage the outdated picture of a lone genius toiling away in the lab until the wee hours of the morning.  How many of you remember the last names of all those middle authors?

Another lesson we could all learn from the business world is communication.  What’s the single most important thing that you can do after discovering something amazing about the world?  Tell people about it.  Unfortunately, many academics seem to have an aversion to speaking in “layperson’s” terms, and do little more than pay it lip-service in trying to tailor their writing and speaking to be understandable by the average person.

In the non-academic world, communication skills are one of the most important abilities that anyone can have.  You must be able to make other people understand what you’re talking about, whether this means presenting to others on your team, potential partners, or even your boss(es).  Businesses understand that image and presentation are incredibly powerful tools in persuasion, and academia would do well to take a lesson from this.

To this point, many researchers say “but our job isn’t to speak to the average person, it’s to speak with other scientists who take an inherently objective approach to everything!”  Perhaps they’re right (that’s a point we can debate another time), but at the risk of insulting our fellow academics, there’s a good chance that those fancy experts in the audience are just as swayed by a well-crafted presentation, and that they probably have no idea what you’re talking about.

In reality, scientists are humans just like everybody else.  They don’t have super-human intelligence or the attention spans of an owl, and just like everybody else they respond to material that is clearly presented, well prepared, and above all interesting.  If you’ve ever said to yourself “well, this slide is full of jargon, but the audience is pretty well-versed in this field so it’s OK”, then you should stop right there and read journal abstracts until your eyes bleed.  Then, rewrite your presentation with the goal of not inflicting the same kind of pain on your audience.

So, do I think academia should be run like a business? No. We study far more interesting problems that (for better or worse) most companies are never going to be interested in.  That said, we have a duty to do the best possible work with the resources that we have.  To me, that means looking towards other industries, learning about what they do well, and incorporating this wisdom into our own scientific culture.  I dream of a world in which scientists are viewed like entrepreneurs: masters of many trades, steeped in charisma, making connections where none existed before and forging a path into the unknown.

Author’s Note: Some people have excellently pointed out that my use of “average people” comes across as condescending.  I want to reiterate that by “average”, I do not mean inferior or less intelligent in any way at all.  By “average”, I simply mean people with less specialized, domain knowledge than someone with scientific training in a particular field might have.


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Chris studies cognitive and computational neuroscience, attempting to link higher-level theories of the mind with information processing in the brain. He’s also an avid science communicator – check out his posts on the Berkeley Science Review and follow him on Twitter at @choldgraf

Category: The Student Blog | 1 Comment

Not So Ordinary: A Tale of Unsung Science Heroes

Of the 638 Nobel laureates in the sciences (physics, chemistry, medicine, and economics), how many names do you recognize? Einstein, Pierre and Marie Curie, and perhaps Pavlov? Most scientists—even Nobel laureates—do not become household names. However, these “ordinary” scientists are no less brilliant, hard-working, or interesting than the “extraordinary” ones.

Gino Segrè’s 2011 book, Ordinary Geniuses, is the biography of two such “ordinary” figures, Max Delbrück and George “Geo” Gamow, whose contributions to their respective fields of genomics and cosmology were anything but ordinary. Delbrück and his team discovered the mechanism of gene replication, for which they were awarded the Nobel Prize in Physiology or Medicine in 1969, and Gamow and his team were early proponents of the then-controversial Big Bang theory, which provided a theoretical framework that could explain how hydrogen and helium were formed in the baby universe.

Max Delbrück and his team discovered the mechanism of gene replication.

Max Delbrück and his team discovered the mechanism of gene replication. Image sources: left, right.

Gamow and his team were early proponents of the Big Bang theory.

Gamow and his team were early proponents of the Big Bang theory. Image sources: left [in public domain due to expired copyright], right.

Ordinary Geniuses follows Delbrück and Gamow from their humble beginnings as unknown but promising students to their emergence as pioneers in biology and physics. They both began as students in physics, and became friends while studying at the Niels Bohr Institute for Theoretical Physics in Copenhagen. Sometimes, late at night, Gamow would barge into Delbrück’s room, turn on the lights, and announce his latest idea on physics, which they would then discuss over beer and sausages. However, though Gamow’s career was taking off with his work on radioactive decay, Delbrück was not so successful. Bohr convinced Delbrück that the “next big question” would be in the life sciences, and so he began making a transition to biology.

When the two met again as established scientists decades later—this time in the United States—Delbrück had become a giant in genetics research. Gamow’s interest also shifted to biology around that time, and he even started the RNA Tie Club, a scientific “gentlemen’s club” dedicated to discovering how DNA instructs the body to create proteins. With Delbrück’s and Gamow’s careers established, the book concludes by summarizing modern perspectives on genomics and cosmology.

Segrè weaves together Delbrück’s and Gamow’s stories, alternating between them every chapter or two. The descriptions of scientific theories and discoveries are interesting, and can be readily understood by the curious layperson. As a biography, however, the book shines in its descriptions of these two fascinating figures. Here are some of my favourite parts:

1) Young Delbrück as he sought a research specialty.

As a graduate student struggling to carve out my own niche in science, it heartened me to know that even a Nobel laureate once felt lost and confused in his youth. In his own words, “I had not felt that I was doing well in astronomy and I did not feel that I was doing well in physics; and I was just hoping that something would happen that I was doing well and was willing to carry on with.” Even after he switched to biology, it took several years before he established a name and a lab for himself. I enjoyed reading about how his persistence and trust in his instincts led him to pioneer a field.

2) Gamow as a jovial, kind man with an unmatched joie de vivre.

Whereas I would have been somewhat afraid to meet Delbrück—he was known to have a sharp tongue as well as a sharp mind, frequently declaring seminars to be the worst that he had ever heard—Gamow comes across as far more approachable. A prankster, a joker, and an accomplished artist, he adorned his letters to colleagues with hilarious illustrations. “[a] discussion of the virus that attacks tobacco plants might be accompanied by a drawing of a happy smoker flicking cigarette ashes, and the question of what can be accommodated into the spacing between the bases on a DNA molecule sidetracks Geo [Gamow] into contemplating what fits into the open mouth of a tiger.” A picture of the latter is provided on page 218.

Gino Segrè is a particle physicist with an interest in astrophysics. He has previously written two books, Faust in Copenhagen and A Matter of Degrees.

Gino Segrè is a particle physicist with an interest in astrophysics. He has previously written two books, Faust in Copenhagen and A Matter of Degrees. Image source.

3) The “Copenhagen spirit.”

Bohr created a welcoming and stimulating environment at the Institute for Theoretical Physics. Several of the scientists were permanent members of the institute, but others stayed for a few months at a time. They lived and worked together, united by their interest in physics. The stay at Copenhagen clearly affected Delbrück and Gamow; they later tried to re-create the Copenhagen spirit at the Cold Spring Harbor Laboratory, and at the George Washington University Theoretical Physics Conference. I loved the idea of being surrounded by friendly, like-minded individuals focused on the same topic, and found myself becoming quite envious of the Copenhagen spirit.

What does it mean to be an extraordinary scientist? Despite the title of the book, I got the sense that drawing a distinction between the ordinary and the extraordinary may be misguided. The ordinary geniuses of Segrè’s book are anything but ordinary—they are accomplished, brilliant people in the modern history of science. Ordinary Geniuses entertains and educates, and is highly recommended.

 
 
 

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Photo by Karen Meberg

Minjung (“MJ”) is a PhD student at the New York University Department of Psychology, Cognition and Perception Program. She studies the visual perception of light and colour, with a keen interest in material perception (e.g., what makes glowing objects appear to glow?). 

To read more about MJ’s work, please go to her academic site.

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Fruitless remains ever-fruitful: a genetic story of love and aggression

This article is being cross-listed on The Berkeley Science Review. Check out some other really interesting pieces there!

One of the most exciting prospects of biological inquiry lies in its potential to explain the peculiarities of our own lives. Human behavior provides some of the most spectacular examples of the output of a fundamentally biological system, the brain, but despite decades of remarkable research spanning the scale of neurotransmitters, to brain hemispheres, to interactions on the internet, we struggle to firmly explain the biological (and environmental) underpinnings of any given human behavior.

Luckily, some of our behaviors aren’t exclusive to our species. Chimpanzees seem to mourn the death of family members. Ants are capable of organizing into social hierarchies that eerily resemble human social structures.  Even the lowly fruit fly, Drosophila melanogaster, goes through bouts of light and heavy sleep that resemble human sleep cycles. All these examples suggest that the biology of behavior might be conserved in the same way that many genes are conserved from fly to human, and hint that perhaps the same genes control similar behaviors in wildly different organisms – a hint that tantalizes scientists to this day.

Thomas Hunt Morgan, the Nobel-prize-winning biologist who popularized the use of the fruit fly, D. melanogaster, as the model organism of choice for modern genetics.

Thomas Hunt Morgan, the Nobel-prize-winning biologist who popularized the use of the fruit fly, D. melanogaster, as the model organism of choice for modern genetics.
Source: Wikipedia

A century ago, when the fruit fly was popularized as a model organism by the lab of Thomas Morgan, these similarities were fairly well-appreciated, but tools for manipulating fly genetics and observing fly behavior were lacking.  Fifty years later, researchers were better-prepared to manipulate the fruit fly genome, thanks to advances made in prior decades with mutating the fly genome with x-rays. In 1963, a researcher at Yale named Kulbir Gill used this technology to create mutant flies that lacked the typical behavioral program ensuring male pursuit of female partners for reproduction. These mutant male flies courted male and female partners equally, and utterly failed to reproduce. Gill dubbed this mutation ‘fruity,’ a less-than-appropriate pun on the fruit fly and its mating strategy, but limited his observations to a short note in a fly journal, declining to investigate further.

In 1977, the geneticist Jeffrey Hall dug up Gill’s fruity line, and again observed a failure of male flies to properly court and reproduce with female flies. Hall renamed the mutation fruitless, acknowledging Gill’s original name while tactfully shifting its implication onto these flies’ futile attempts at reproduction. With Hall’s resurrection of the fruitless fly line, scientists now had an animal model that could provide insight into how genes influence male behavior – an insight with the potential to explain the root of differences in the behavior of men and women.

We now know that the original fruitless flies possessed a mutation in the fruitless gene, which disrupts the production of the male-specific protein FruM. FruM is expressed in neurons that exist in the male, but not female, fly brain, and some of these neurons are responsible for orchestrating the male courtship ritual. When scientists engineered female flies to express FruM, these female flies began to behave like courting males, despite their lack of the very neurons that guide male courtship. All this raises some of the biggest questions in biology. If sexual orientation and courtship can be influenced by a single gene in flies, might these traits be controlled by a gene, or genes, in humans? If differential gene expression in female versus male flies leads to behavioral differences, does a similar scenario explain behavioral differences across the human sexes? And lastly, how does the introduction of a male protein into a female brain allow that female brain to carry out a male behavior, when the male neural circuitry is not present?

FruM, and the male neurons possessing FruM, obviously deserved further study, as biological mediators of male behavior. Over the course of his career, Hall himself managed to define the FruM neurons responsible for male courtship, but these neurons represented but a fraction of the total of two thousand FruM neurons, suggesting that FruM might control other male-specific behaviors in the fly. High on the list of observable sexually-dimorphic behaviors in the fly is aggression: though both male and female flies are capable of exhibiting aggression, males are measurably more aggressive than females. This is also true for most mammalian species, including humans. Men are broadly more violent than women, and while the causes of human violence are likely more complex than any violence observed in a fly vial, it is tempting to speculate on how biology, and genetics, might be influencing this behavioral sexual dimorphism, just like how FruM neurons enable male flies to perform their courtship song.

Perhaps unsurprisingly, aggression was formally linked to fruitless by the lab of Barry Dickson at Harvard in 2006, with a study that was able to swap male and female modes of aggressive fighting by replacing the fruitless variant of one gender with the fruitless variant from the opposite gender. However, despite the efforts of dozens of additional labs, the identity of the FruM neurons that drove male-specific aggression remained unknown. Furthermore, even though both courtship and aggression in flies seemed to depend on fruitless, this gene was nowhere to be found in higher organisms, including humans. Fruitless, fifty years out, was still puzzling the best of the science community – could further study actually bring us closer to understanding divergent behavior between the sexes?

A male flies prepares to lunge at a second male fly, a stereotypically aggressive behavior that can be detected by automated software developed in David Anderson's lab.  Source

A male fly prepares to lunge at a second male fly, a stereotypically aggressive behavior that can be detected by automated software developed in David Anderson’s lab. Source: Anderson Lab

Though fruitless retained mystery, the fly field did not rest. Just how did FruM impart aggression in male flies? Researchers at Caltech, led by David Anderson, had spent over a decade developing automated tools for monitoring a variety of fly behaviors, so they undertook a modern version of Gill’s original observational study: manipulate fly genetics systematically, and document the consequences for fly behavior. Other groups had shown the importance of particular hormones, also known as neuropeptides, in fruitless-mediated courtship, which led Anderson’s group to speculate that an unknown neuropeptide could be responsible for male fly aggression.

Harnessing genetic tools for screening many mutant flies at once, the Anderson group created forty fly lines in which small groups of neurons could be activated by heat, depending on which one of twenty neuropeptides they expressed, hypothesizing that some of these lines would display increased aggression. Of these forty lines, two stood out as having increased aggression (for flies, this includes stereotyped lunging and boxing behavior). Both of these lines contained neurons that produced the neuropeptide tachykinin (Tk), also known as Substance P in mammals – a promising early observation for connecting aggression across species. When the researchers obtained high-quality images of these neurons within the fly brain, they noticed that they visually resembled FruM neurons identified in other studies. Digging deeper, lo and behold, this handful of neurons actually expressed FruM, corroborating the earlier work of Dickson’s lab, but refining the aggression-responsible group from two thousand FruM neurons to just four Tk/FruM neurons.

Visualization of Tk/FruM neurons (green), responsible for aggressive behavior, in the male fly brain (left, yellow arrows); for comparison, the female fly brain (right) lacks these neurons.  Source

Visualization of Tk/FruM neurons, responsible for aggressive behavior, in the male fly brain (left, yellow arrows); for comparison, the female fly brain (right) lacks these neurons. Asahina et al., 2014. Source: Caltech

The hunt was on. Anderson’s team characterized how Tk neurons sparked aggression, and found that overexpressing Tk itself, while simultaneously activating the Tk neurons, ramped up aggressive behavior to the point of driving flies to attack inanimate objects (in this case, a fly-sized magnet). Despite also expressing FruM, activating these neurons had no effect on courtship, indicating their specific role in increasing ‘aggressive arousal,’ or the likelihood of engaging in aggressive behavior. These neurons were only observed in males, as expected for FruM neurons, potentially explaining female flies’ low levels of observed aggression. And perhaps most intriguingly, the neuropeptide Tk itself was driving aggression, presenting the first molecular link between aggression in flies and mammals.

With a gene and a neuropeptide pinned down as the factors responsible for male aggression in flies, the Anderson lab, and indeed the entire field studying aggression, now has a new lead on the genetic basis of gender differences in aggression. Will we soon understand why men and women demonstrate different levels and kinds of aggressive behavior? Maybe not for some time. But a similar, aggression-related molecule is present in the mammalian brain, and the fruit fly’s behavior provides the foundation for further study into how sexual dimorphism occurs in higher organisms.The fruitless gene, over forty years since its inception as fruity, continues to bear intellectual fruit, as the grandfather of behavior-regulating genes known to be expressed in a sex-based fashion. Good science takes time, some fumbles with inappropriate names, and some gambles, but the modest fruit fly has yet again proven it is not to be underestimated. Especially when it is up for a fight.

Category: The Student Blog | 1 Comment

My path to graduate school: medicine vs. research

After leaving the California Institute of Technology with a BS degree in biology, I took a relaxed summer in preparation for what is going to be the next 5, 6, or maybe even 7 years of my life – graduate school.

The first step to tackling graduate school starts well before you step through the front doors. It starts in your undergraduate years when you find your passion. For me, that passion was in the sciences. Aided by my parents’ urging towards a career in science, I participated in local science fairs and started research in the latter years of high school at the National Cancer Institute. There, I truly had my first taste of biological research. However, I didn’t expect that I would ever end up in graduate school.

National Cancer Institute at Frederick, MD.

National Cancer Institute at Frederick, MD. Source.

Despite only having experience in research, I never considered it as a career choice. Biology was something that I excelled at, and I knew that I was interested in helping people through medicine. These dreams motivated me to want to become a doctor from a young age. I wanted to make a difference in the lives of as many as I could touch. I was so focused on that path that I never considered any others– blinded to other careers, especially those not in science. To understand how a career in medicine would be, I chose to do an internship at the Huntington Memorial Hospital in Pasadena.

Huntington Memorial Hospital in Pasadena, CA.

Huntington Memorial Hospital in Pasadena, CA. Source.

For 6 weeks, I arrived at 7:00AM to doctors checking on patients and reading charts. I rotated through different wards including pediatrics, neurosurgery, and pathology. I remember that, on several occasions, I had to stand for 6 or more hours watching surgeries. The doctors told me that they had done the same surgery several times that week for many weeks in the month and many months in the year. But, of course, not all the rotations were so repetitive. My experiences in internal medicine were probably most interesting because I was able to meet different patients every day and see doctors’ diagnoses and treatments. However, what I found after the 6 weeks was most telling about the outlook of my future – I wanted to be a scientist.

For the last 3 weeks of my internship, most of my thoughts led to returning to the laboratory bench. I realized that leading up to this point in my life, I was being trained to be a scientist, yet I was so blinded by the goals set by my parents and myself. I realized I yearned for the creativity that comes with research and the flexibility to take projects in whichever direction was most interesting. The natural curiosity I had about the world around me was repressed by, from what I thought, the monotonous routine of being a medical doctor. Even more telling was the fact that I was at one of the world’s leading research institutions. It’s almost as if my actions knew what I was meant to do, but my mind had yet to accept.

As a young student in middle school and high school, I lacked the wisdom to understand that I should question my motives for wanting to be a medical doctor. Equally or even more important than using medicine to treat patients is to discover those medicines, and that is almost exclusively the job of the scientists. It took me several years to realize that researchers could be as helpful to people as a medical doctor.

Now that I’m in graduate school, I’m glad to be where I am. I go to work every day wondering how to take my science to the next level and think about biology in ways that I had never before. Every day seems like a new problem to tackle, and I appreciate that about research. I realized that being a medical doctor was not something that matched my interests, although it can certainly be the right career for those looking for patient contact and a direct impact on patients’ lives.

DSC04096

Marvin is a PhD candidate at Stanford University in Immunology. He was an editor-in-chief at the Caltech Undergraduate Research Journal. See it at curj.caltech.edu. Follow on twitter @Marvzipan. gee.marvin@gmail.com

Category: The Student Blog | 10 Comments

A Science Junkie’s Guide to Art

Some of the best things in the world exist at intersections between disciplines. My favorites emerge from the union of art and science. It is at the heart of this intersection that artists and scientists come together in order to make explanations of our world all the more rich through art.

Artistic depictions of constellations help us understand positions of stars over time. (CC)

Artistic depictions of constellations bring us closer to understanding our universe by making the night sky more relatable and navigable. (CC)

Take for example constellations. Through my childhood, I was fascinated with the universe. Instead of bedtime stories, I would ask, “Daddy, tell me about space!” He taught me many things about black holes and moons and life cycles of stars, but more than anything I remember the constellations. We lived in a rural canyon with clear night skies. Moonless nights meant more stars than you could ever hope to count — and indeed more stars than my young mind could recognize without help.

Fortunately, help was close. I had a poster of ‘Constellations of the Northern Hemisphere’ tacked to my bedroom ceiling (complete with glow-in-the-dark stars). With the light on, I could see every character’s name and a portrait overlaying the corresponding stars. With the light off, hundreds of small points glowed back at me, and in the dark I would try to remember the patterns and strange names.

Egyptian hieroglyphs from between 1500 and 1609 BCE represented agricultural growing seasons. (Wikimedia Commons)

Egyptian hieroglyphs from between 1500 and 1609 BCE represented agricultural growing seasons.
(Wikimedia Commons)

Science illustration itself has a long tradition, reaching back millennia from celestial pictograms to agricultural records of the seasons. If you will be in New York before October, the American Museum of Natural History is running an exhibit with 400 years of scientific illustration. If you won’t be in traveling through the Big Apple anytime soon, the AMNH has published a companion book (with a bonus century!) of rare science illustrations from their collection.

It is easy enough to buy a poster, or visit a museum for your science art fix. For some, however, passive viewing is not enough. Last September while hiking near San Francisco, I met a woman with an integrated DNA-circuit board design etched into her back. Literally etched. “Why scars? Why that design?” I asked. “I wanted something other than an ink tattoo. The design is a combination of my interests in bio and tech.” She works at Kaiser improving healthcare technologies.

Still curious, I asked her about the scarification process. “You have to go to an expert and have it done professionally,” she told me seriously. Her scars were made on the East Coast by peeling back several layers of skin, and then scraping away the underlying flesh. The top layer is folded back into place, and after several weeks of healing, delicate white scars begin to form. “Some of the details are beginning to fade,” she added. Eventually, over many years, the curves of the double helix and circuit nodes will sink back into her skin. It is poetic, in a sense, that the regenerative properties of her body will reclaim the homage made to them.

Tattoos themed in science are becoming increasingly popular. (CC)

Tattoos themed in science are becoming increasingly popular. (CC)

 While scarification is perhaps more rare, the world of science tattoos is alive and well. In 2007, well-known science writer Carl Zimmer began compiling images and stories behind various tattoos science enthusiasts have accumulated over the years. The results were splendid and zany enough to fill an entire book, Science Ink, which boasts the best by discipline.

“Art” is an all-encompassing term that embraces many media. So far I have focused on the illustration sides of science. There are several other artistic science scenes, and one of my favorites is sound. You can make any math geek’s day by sending them this catchy a cappella love song laden with higher-order math puns. On the programming side, computer music and audio tech continue to mature, giving us gems like the Re: Sound Bottle and sine wave water.

Bathsheba Grossman's 3D-printed sculptures tie algorithms with aesthetics to create math-inspired art. (CC)

Bathsheba Grossman’s 3D-printed sculptures tie algorithms with aesthetics to create math-inspired art. (CC)

Another venue for science art is in sculpture. Take for example the recent collaboration between MIT and Disney to create awesome character models using multi-material 3D printing. And have you ever seen a cube walk on its own? Cubli is here to cure you of that ‘not yet’.

Science art is also creeping into the digital world. Where once artists relied on paper and pigments, we now have digital cameras and high-resolution touch screens to aid discovery. For example, my favorite author, Simon Winchester, recently collaborated with skull collector Alan Dudley and photographer Nick Mann to produce an iPad app named Skulls. The application harnesses recent developments in 3D visualization and user interactivity, as well as traditional text and narration, to explore new bounds of science education through art.

The Amoeba Network, by Maki Naro, is an example of comic art as an explanatory platform for science (shared with permission from sci-ence.org).

The Amoeba Network, by Maki Naro, is an example of comic art as an explanatory platform for science.
(Shared with permission from sci-ence.org.)

Scientific webcomics are on the rise, as well. There are, of course, the wonderful standards like XKCD, PhD Comics, and The Oatmeal. Fortunately, many of these comics are actually comical. One of my personal favorite artist/authors is Maki Naro. He recently moved from his popular blog, Sci-ənce, to the Popular Science blog, Boxplot, where he continues to operate “at the intersection of art and science in an attempt to act as a mediator between the two.”

It seems this mediation drives many scientists who later turn their creative efforts to the arts. Scientific American illustrator, Jen Christiansen, just wrote about the pull between the disciplines, and how she instead decided to merge art and science. The same seems to be true of trained neuroscientist Greg Dunn, who opted to replace his pipette with the paintbrush, and has carved a corner in many hearts with his shimmery, beautiful, Ramon y Cajal-reminiscent paintings of brain.

The intricate patterns in kolams, traditional Indian chalk drawings, are helping scientists better understand protein folding. (CC)

The intricate patterns in kolams, traditional Indian chalk drawings, are helping scientists better understand protein folding. (CC)

Those who practice science art bridge worlds that are cerebral and theoretical with those that are aesthetic and tactile. We rely on artists to imagine distant worlds for us, or to reanimate scenes that have long since faded back into the soil. Art can help us understand the scientific beauty of a flower (with a little help from that fine man, Mr. Feynman), or even help improve our science.

I have an astronomy artist to thank for one of the great joys in my childhood. Because of that constellation poster, I now recognize Cetus the Whale, the galaxy in Andromeda’s armpit, and how to spell Cassiopeia. I consider this a triumph for science art in educating a young girl who was curious about the cosmos.

Jahlela is a recent graduate of the  cognitive neuroscience program at the  University of California, Berkeley. She is an avid photographer, sings constantly, and loves all things science. Follow her  @jahlela or on tumblr

jahlela AT berkeley.edu

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Happy New Year from the Student Blog!

Image via CC BY 3.0 license

Image via CC BY 3.0 license

Happy New Year! As we say hello to 2014, I want to take a chance to look at some of the fantastic work that from the Student Blog in 2013.

We had a look at diverse opinions about science education. There were passionate calls for making research part of the undergraduate experience: see Rachel Cotton’s advocacy for undergraduate research and Sean Lim explanation of what a student seeks from a research mentor. Deepshikha Mishra rounded-up new opportunities for life science in India. Rebecca Marton encouraged students to stay in STEM, and urged other STEM students to do the same. Jeremy Borniger argued that a gap year was the best choice he made before going to graduate school and Anna Goldstein assured us that it is possible to switch research groups – and live to tell the tale!

Several posts highlighted key debates in the science community. Jane Hu looked at the plight of women in science, and why women may not be staying. Michael Selep discussed the difference between translational research and basic science, and found them not to be that different at all. Tyler Shimko entered the climate change debate, discussing how his scientific background made him an effective activist and encouraging others to get involved.

Science communication itself entered the conversation when Jahlela Hasle wrote about the time a poorly written science article made her cry,  and Chris Holdgraf sparked conversation when his observations about being ‘right’ in science included the controversial mantra “Never hesitate to sacrifice truth for understanding.”

The Student Blog also featured some fabulous science writing. Alex Padron gave us insight on the history of science with his post on Alexis St. Martin’s fistula, Katrina Magno looked at the ways scientists are studying black holes, and Prashant Bhat showed how a beautiful bloom could also prove deadly. And Minjung Kim’s review of Brilliant Blunders showed that it’s okay to mess up time and again.

We also had some excellent commentary about the importance of Open Access. David Carroll and Joe McArthur shared progress on the OA Button, an exciting web tool that launched last November. Sara Lindenfeld advocated using Open Access science to educate the public about climate science. Angelica Tavella detailed the Open Access Initiative at UC Berkeley and how she got involved in the Open Access movement, and high school student Jack Andraka gave a passionate argument for tearing down paywalls to help connect young people to science and inspire a new generation of scientists.

Marvin Gee expressed the opinion of many when he resolutely asserted that research is not a job, but a lifestyle.

On a personal note, it’s been an amazing experience working with all these wonderful bloggers over the last few months. There will be more great stuff in 2014, so I encourage you to add “Read the Student Blog regularly” to your list of New Year’s Resolutions.

So stay tuned! The first official Student Blog post of 2014 will launch this week!

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The Infinite Classroom: An Ode to Student-Led Classes in Science

Science education in schools has a flaw: Large lectures are by definition impersonal, and they often leave out the larger context of the material. You can ask a calculus student “Why, exactly, did you just learn that double integral?” to see what I mean. Students go to lecture, memorize the material, regurgitate during the test, and then promptly forget it. Lather, rinse, repeat.

This seems like a regrettable state of affairs. Retention of information is highest when the relevance of what we are learning is transparent and accessible. My experience with student-led classes is not comprehensive, but I am convinced the model is perfect for cultivating true understanding.

Paul Broca

Paul Broca, the French neuroanatomist who first discovered first functional specialization in the brain. The region he identified, now called Broca’s Area, is critical for speech production. (Wikimedia Commons)

A Class on How to Read Science

 As a budding Cognitive Science major, I heard of a class with a peculiar name straight out of an abnormal psychology textbook: BROCA. The ‘Berkeley Review of Cognitive science Articles’ is one of many student-led classes offered at UC Berkeley, and while I never took the class, I had the honor of teaching it this fall.

Three years ago, BROCA’s founders identified a hole in the undergrad CogSci curriculum. For students interested in pursuing research experience and careers, there were no dedicated research methods or statistics classes. As such, students were entering research positions without the skills they needed.

The solution was simple: Start a class with weekly guest speakers who discuss an exciting research paper in cognitive science.  BROCA was born into this model, and by taking the class, students are exposed to not just the written reports of science, but also the personal stories of the scientists creating the reports.

If you are considering starting a similar class for your school, don’t be afraid to reach out. Our speakers have included professors, PhD candidates, research assistants, and even former researchers who have gone on to work in industry.

Importantly, the students are not simply listening to yet another lecture. During the week leading up to each class, students read the assigned paper, prepare responses, and formulate questions. Before the speaker arrives, the facilitators help begin the discussion by covering the basics, then open the floor for debate and inquiry. As needed, we also  design crash courses in many of the topics — how to compare brain imaging techniques or the differences between various animal models.

Another benefit of small classes is versatility. I interviewed several facilitators in other science-themed classes, and though they all shared that theme, the range of topics is impressive. Here is a sampling:

BSJ

The Berkeley Scientific Journal, an undergraduate publication for original research and interviews. (Image by Hadrien Picq)

A Class on How to Write Science

We all consume science writing at some point in our lives — in newspapers, radio programs, documentaries, textbooks, magazines. The writers have to come from somewhere, and the Berkeley Scientific Journal (founded in 1996) is an undergraduate publication that gives students not only a start, but also gives them university credit.

BSJ offers a platform where students can interact with discoveries in a field in a way that is distinct from reading a textbook or lecture notes. For those without experience in research labs, becoming part of an interview team is the perfect introduction to laboratory sciences. I became involved this semester as an author, editor, and photographer. Incidentally, the BSJ’s editor-in-chief, Prashant Bhat, is also a PLoS student blogger.

A Class on how to Integrate Science

The trend for student-taught classes is not exclusive to Berkeley. Just down the coast in Santa Cruz, the Brain Mind & Consciousness class is the first undergrad-taught science class in years. The class and epynomous BMC Society were c0-founded by Andrew Kornfeld, a student of psychology and neuroscience. For 3.5 hours every week, he and several co-facilitators taught students everything from nuclear physics to brain chemistry to drug policy to how patterns in nature are preserved across many scales of observation.

BMC

The Brain Mind & Consciousness Society teaches UC Santa Cruz’s only science-based class taught by undergraduates.
(Image by Andrew Kornfeld)

The most important feature of the class is contextualization of each level of detail. If the students learned the chemical structure of caffeine, it was going to be in the context of how its structure relates to adenosine, and how caffeine’s blocking of adenosine receptors will affect one’s conscious experience.

Another advantage of small classes is flexibility. Last spring, as the Supreme Court reviewed a case on gene patenting, the class was debating the ethics of genetic ownership while overlooking Monterey Bay.

Teaching a class of course comes with its challenges. Kornfeld spoke of his trepidation about speaking for a solid hour and a half. After the first class, he quickly realized discussion-based class was far more important than one that was lecture-based. Another worry for any instructor is information accuracy. Questions will come up in your class that you won’t know how to answer. This is an opportunity to put the question to your class to discuss.

A Class that is not a Class, but Ought to Be

“My school doesn’t offer student-led class opportunities.” There are alternatives to an official academic space that can do the trick. For example, a few years ago a small group of students at Portland State University began a weekly event called ‘Tea with TED’. The premise: bring students together in order to “develop more complex insights about a world that transcends disciplines.”

TWT

Tea with TED examines the crossroads of art + science, education + technology, culture + industry, language + empathy, literature + psychology, and more. (Image by Stephen F.)

During the first 20-30 minutes, students watch a TED talk or two together, and use the remaining time to discuss the talk. The beauty of TED is its fundamental design for wide audiences. For example, if you know nothing about mycelia, start your Tea with TED by watching Paul Stamets’ talk, ‘6 Ways Mushrooms Can Save the World’. The ensuing discussion could range from using mushrooms as alternate fuel sources to ecosystem creation to terraforming other planets. Ideas not easily conveyed with words bleed onto  butcher paper-covered tables — all of this over tea, of course.

TWT’s founder, Stephen F., describes the result as “a colorful, healthful, and intellectual atmosphere that feels like a book club hacked by RSAnimate.” While not technically a class, the Thursday meetings frequently drew 20-30 people. It sounds like the perfect complement to single-subject classes, which can feel detached from life beyond the classroom.

As we move through our years in college, with hope we have collected enough experience in our major to return the pedagogic favor and begin teaching our own classes. Teaching BROCA was the highlight of my week, and I look forward to seeing the next generation of classes in science.

Jahlela is a senior undergraduate student studying cognitive neuroscience and music at the University of California, Berkeley. She is an avid photographer, sings constantly, and loves all things science. Follow her  @jahlela or on tumblr

jahlela AT berkeley.edu

Category: The Student Blog | Tagged , , | 1 Comment

We need to check our work: Rethinking replication and publishing

The most exciting phrase to hear in science, the one that heralds the most discoveries, is not “Eureka!” (I found it!) but “That’s funny…”
― Isaac Asimov

A popular theoretical framework in my field, developmental psychology, compares children to scientists. Alison Gopnik first championed the view that children, like scientists, have theories about the world, and test and revise those theories through their everyday behavior. “A theory, in science or in everyday life, doesn’t just describe one particular way the world happens to be at the moment,” Gopnik wrote in a 2005 Slate article. “Instead, having a theory tells you about the ways the world could have been in the past or might be in the future.”

Children have been observed experimenting by repeating the same intervention many times – for instance, in many of Gopnik’s studies, children place blocks on a “magical machine” to determine which ones make the machine light up and play music. It seems from these repetitions that children want to be sure what they’re observing isn’t a one-off fluke, but a real causal effect in the world. Children study the results of their interventions, and revise their theories if there’s a new result that contradicts their previous theory. This is, in theory, what scientists do to test our theories as well — except it seems that preschoolers have bested us in the process of repeating interventions to check our work.

Replicating a study seems easy enough, but the time and effort involved in replicating even your own work can be quite costly. In most STEM circles, a research group that finds a significant result would be crazy not to publish it as quickly as possible, lest someone else beats them to the punch. Additionally, there is no incentive to replicate, since journals typically seek out new results for publication. In theory, this is a good thing – we want original findings to make progress in science – but publishing norms have taken this to an extreme. A 2007 study by Daniele Fanelli found that 86% of publications are positive results (up 22% from 1990).

The disincentives for replicating are usually enough for researchers to steer clear of it, but the few who try are in for more hurdles. In order to replicate a study, one needs to know how the original study was done. As journal articles are skewing shorter, methods sections may provide less information, giving the reader only a basic idea of a study’s procedure. In many studies, effects could be due in part to small details, like the exact wording an experimenter uses, or even the color of the walls of the testing room. To probe the strength of an effect, we need to play with these variables to see how they affect the results. In the discussion surrounding the replicability of psychologist John Bargh’s studies, fellow psychologist Daniel Kahneman likened the small details in experiments to “the direction of a theatre performance,” and suggested that perhaps the reason why Bargh’s studies weren’t replicating were because Bargh just “has a knack that not all of us have”.

“The conduct of subtle experiments has much in common with the direction of a theatre performance,” said Daniel Kahneman. If these subtle details are what are driving effects, that’s all the more reason to be thorough in reporting our procedures.

Researchers are humans, and we’re subject to the same biases as everyone else, despite our meticulous training in objectivity. There are many points in the process of publishing a study where human bias can lead to a portrait of the world that is less than accurate. For instance, when psychologists Stéphane Doyen and colleagues tried to replicate John Bargh’s famous result that priming participants with “old” words led to slower walking, they found that the experimenters’ unconscious bias in timing participants’ walking speed could have exaggerated the original findings.

More meticulous reporting of procedures and results will encourage researchers to be more critical of their own work, and will create opportunities for collaboration. In casual conversations with other researchers, I’ve often heard things like, “If only I knew how they did that!” or “I wonder if the researchers looked at X in their results…” The availability of detailed procedures and raw data would allow new life for results, and will allow researchers to do replications or extensions quickly, rather than spending time figuring out the exact procedure that led the original researchers to find an effect.

Replications are also important to safeguard against human fallacy. We hope that our current peer-review process will weed out studies in which experimenter bias or poor study design explain the results, but reviewers, like researchers, are human and subject to biases. One glaring bias is the fact that some journals are not double-blind! We scientists pride ourselves on objectivity and recognition of merit, but it’s hard to say how scientists’ reputation (or lack thereof) influences their publication acceptance rate at journals that reveal the authors’ identities.

Reviewers may also fail to spot errors in research. The Economist reported several studies that indicate reviewers are less familiar with stats and less meticulous than one would hope. Anyone who has served as a peer reviewer can tell you – it is a thankless job. Most reviewers are not paid or recognized in any way for their time and effort, besides the right to add an additional line in the “professional service” section of their CV.

Besides their dedication to the furthering of science, reviewers have little incentive to thoroughly vet the papers they’re assigned to review, especially when this volunteer assignment is competing with other job duties, like research, teaching, and grant-writing. Sometimes, reviewers are assigned to comment on papers that are outside their expertise, which makes them even less motivated or qualified to provide good feedback on manuscripts. A colleague of mine recently waited six months to hear back from the third reviewer of his paper, only to receive an email from that reviewer in which he admitted that he did not feel qualified to comment on the paper because the research was outside his expertise.

Often, reviewers are overworked academics with little incentive to give thoughtful feedback.

Though traditional journals are doing their part to adapt to the shortcomings of the current publishing system, alternative open-source and web-based publishing groups are poised to help address many of these issues with new technologies. For one, replications may be more like to be accepted by and easier to execute in non-traditional journals. Many of these journals or publishing services (PLOS, PeerJ, the Winnower) publish based on the soundness of a study’s methods and conclusions, rather than its perceived impact on its field, which encourages high-quality rather than flashy work. Also, without the word-limit and space constraints that come with printed journals, non-traditional journals could allow researchers to upload detailed procedure instructions, raw data, or even video clips of their procedure.

New publishing systems could also improve the speed of science communications. Cover letters to reviewers were probably useful when correspondence about manuscripts was limited to sending mail through the postal service, but they are now just a relic of an old system. Rather than specifying that you changed a sentence on page 34, paragraph 3, perhaps one day authors and reviewers will be able to submit digital documents highlighting changes, comments, and suggestions, rather than writing formal letters to one another; this would cut down on the amount of time wasted on formatting correspondence between authors and reviewers. Online journal PeerJ allows registered users to comment on papers, creating a community in which feedback can be given instantaneously and less formally.

Online publishing and review also opens up the possibility of more feedback. Why stop at the standard three reviewers? Allowing qualified, registered users to comment on or review articles may also present the incentive for higher-quality feedback. Comments, for better or for worse, could be made public, allowing academics to be recognized for thoughtful feedback. PeerJ, for instance, incentivizes high quality comments by awarding points to users who have written a comment nominated as “insightful” by other users.

Surely, there are other cultural changes that need to occur in the science world before we adopt new publishing systems – for instance, as Berkeley cell biologist and Nobel Prize winner Randy Schekman suggested in an op-ed last week, placing less importance on journals’ impact factors. And even after we adopt new publishing systems, they will not be a panacea for all issues in science world. Still, these recurring discussions about the importance of replication and the need for alternative publishing systems suggest that the time is ripe to refine our scientific values and to rethink the system we have in place to uphold those values.

jane huJane Hu is a PhD candidate in the psychology department at University of California, Berkeley. Her research focuses on social cognition and learning in preschoolers. She is also an editor of the Berkeley Science Review. Follow her on Twitter @jane_c_hu, and check out her science blog: metacogs.tumblr.com

 

 

For more about replicability & replication projects:

Check out these open-source publishing and collaborative tools:

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An Ode to Patch Clamping

I’ve been a graduate student in bioengineering for quite a while now—let’s call it “more than five years”—but I harbor a far more embarrassing secret (for a bio-centric program) than that. I’ve only known how to pipette for four of them. When I entered graduate school my lab experience had been limited to computer work: mostly data analysis in Matlab. I had never actually gathered my own data. Perhaps I should’ve directly mentioned this in my application, though at times computational work is all one does to complete a PhD in bioengineering (the field is diverse).

AllYourBugAreBelongToMeThere were many times as an undergrad that I was so frustrated troubleshooting code in Matlab I actually yelled at whatever living thing was inside the computer and obviously out to get me. But I eventually figured out how to massage the computer into doing what I wanted. And that particular problem was solved.

As a grad student I’ve come to know the pains of experimental work with actual living things. One particular technique deserves the utmost reverence: patch clamping.

Less widely practiced than computer programming, patch clamping is one of the most transformative techniques in neuroscience. It’s a delicate process in which you, the experimenter, first bring the tip of a microscopic glass pipette down to a cell membrane ever-so-gently under a microscope. You then physically apply suction with your own mouth on the other end of the pipette, which is archaically connected though a long rubbery tube. By applying suction you draw the cell membrane so close to the pipette tip that it adheres and forms a seal on the rim of the glass. Then with more powerful suction, you break open the bit of membrane that’s stuck to the pipette opening, all while the cell is still alive.

A microscopic glass pipette (in blue) patched onto a neuron in the hippocampus, a region of the brain that processes memory.

A tiny glass pipette (blue) patched onto a neuron in the hippocampus, a region of the brain that processes memory.

When this happens, you suddenly have all kinds of access to the inside of a cell (in my case, a neuron). The liquid contents in your pipette diffuse into the cytoplasm, and the small electrical signals generated by ion channels in the cell membrane are detectable by an electrode that sits further up in the pipette (a cell membrane usually filters these signals such that they are undetectable from the outside). You are now part of the living neuron and can inject current or perfuse drugs into the 15 um (on average) space that generates action potentials, integrates synaptic signals, produces proteins and transcribes DNA.

Patch clamping is a powerful technique that has no alternative.

But it takes a special kind of person to perform such a technique regularly. When one troubleshoots a computer program, there is complete control of the system (even if it doesn’t feel that way). Bugs in code, once solved, are solved permanently. They possess no quantum phenomenon like randomly changing or disappearing. Bugs occur in experimental protocols as well, except that they are much less well defined. Patch-clamp bugs require a personality with the highest tolerance for frustration I’ve ever encountered. They reappear with very few hints to a reason. It’s a maniacal game.

There are obvious parameters to fiddle with when patch clamping. I can count them on both hands, but beyond that, there are an unknown number of parameters that govern the cell about to be patched. Humans made computers, so we know exactly how every part works, down to the transistor. But humans did not make cells, and we don’t know nearly enough about how they work.

When something common goes wrong during a patch clamp experiment—the cell membrane won’t seal onto the pipette, or the cell dies as soon as you break into the cytoplasm, or the patch fails too soon to measure what you wanted—there’s no quick or permanent fix. One can tweak the shape of the pipette to be more amenable to sealing, one can mix up new internal solution (the liquid that goes inside the pipette), one can grow or harvest new cells, trying to be extra careful so as not to hurt them. Any number of these solutions might fix the problem, and each one takes anywhere from an hour to days to try.

A computer program contained in a stack of punched cards, waiting to be inserted into a machine that can read them. You can see edits in red marking where the programmer has made changes from the last iteration.

A computer program contained in a stack of punched cards. The red markings depict where changes have been made from the last iteration through a central computer.

If you converge on something that works, you patch a bunch of cells that day and celebrate! But when you come back next day, the same problem happens. Or a different problem happens, and the cycle starts again. Perhaps this was the frustration early programmers experienced when they had to wait in line to try out revised code on punched cards in a centralized computing center. I applaud them for sticking it out!

Patch clamping can be incredibly frustrating. In my lab we joke about making sacrificial offerings to the “patch clamp Gods.” The technique is often likened to black magic, but when done by someone with utmost patience, it is a powerful art form. To be able to peer at and control the electrochemical signals that govern neurological processes within single cells was revolutionary over three decades ago and has advanced neuroscience at an incredible rate. We now know that ion channels (the pores in cell membranes that control flow of various chemicals in or out) open in a probabilistic manner. We can study how neurotransmitters like serotonin modulate internal electrical signals, and how a neuron decides whether to fire an action potential (i.e. communicate with other neurons), given the small electrical currents induced when a single synapse relays a message to that neuron.

Patch clamping can be excruciating, but like computer programming it opens up an entire scientific realm that is inaccessible any other way*. I commend those who stick with the technique and accept the frustration in exchange for the rewards it offers.

 

*Though as they improve, optical techniques might one day replace patch clamping.

Category: The Student Blog | 3 Comments