My dad likes to send me newspaper clippings. I’m a fan of his snail-mail tendencies. It means that, instead of a bunch of solicitations from strangers for my time and money, my mailbox is normally dominated by interesting tidbits about a random collection of topics.

The latest inspection of my mailbox produced articles on sleep rhythms, Ebola vaccine and Canadians. I particularly enjoyed the article on Canadians. It struck me as pertinent not just to Canadians, but to anyone who is part of a larger group. Be it, a member of a city, a university or a research lab.

I think the article is best summarized by its concluding paragraph (replace “the Canadian” with “our group’s” and “countries” with “groups”):

“ Gratitude, whether to God or our ancestors or the luck of the draw, requires a certain alertness to reality. It is not available to those who lack curiosity. To feel grateful we need perspective. We need to know something about the Canadian past and even more about the misery now endured by many other countries. Wisdom and peace (said the ancient Greek philosopher Epictetus) comes to someone who “does not grieve for the things not acquired but rejoices for those possessed.” “

(Excerpt from article by Robert Fulford, written for the National Post.)

Of course …… we should also always strive to make things better.

A conversation I had the other day on the news of a new hominid species, Homo naledi, led to a comment that the species had small brains. Can brain size tell us anything about a species? Or can our fondness for our favorite organ mislead us into thinking that its size matters?

It’s tempting to think that a bigger brain is better. I think of brains sort of like I think of wallets. The bigger they are, the more valuable material I can shove in. But in actuality it never works that way: bigger wallets don’t have more money, they just end up with more receipt paper, candy wrappers and membership cards.

Similarly, bigger brains don’t seem to correlate with intelligence. Neanderthals had bigger brains than modern humans, suggesting that we evolved from cavemen to current intelligence levels despite shrinking brain size. If we compare across species, humans also have smaller brains than other members of the animal kingdom, like whales and elephants (we have almost 200,000,000 less brain cells than an average elephant). If we scale brain size by unit body mass, modern humans still get beat by ants, the tree shrew and small birds, having the same brain-to-body-mass ratio as a mouse. Even within our species, there’s inconsistent evidence on whether bigger brained people are any smarter than smaller brained people.

How do we explain differences between human intelligence and the intelligence of other animals if we can’t find a physical feature that puts us at the top of the list in brain measurements? By using Jensen’s encephalization quotient. The encephalization quotient, or EQ, compares brain size to expected brain size for similarly sized species. Here humans win out but I find the justification for this metric confusing. Why should brain size increase with body size? The metric also seems to depend on which species are we using to fit a line between body size and brain size. Using animals with more massive bodies, which could be reflecting adaptations for movement rather than adaptations for behavioral strategies/intelligence, changes the regression line. Depending on which species are selected for the line fit, we could reach a different outcome in the species with the highest EQ. For example, if we used only primates or only flightless animals with higher body masses would our brain size residual be more similar to other animals? The EQ also seems meaningless when we compare between species: are pigs less intelligent than horses? Intelligence is a hard thing to measure, and seems too complex to compare across species.

So if brain size has little to do with intelligence, what can brain size tell us?

Brain size correlates well with body size, head circumference and height. Big brains = big heads.

Traveling internationally is good for the brain. I’m not sure which synapses are “sparking” differently, but I’ve been in Canada since last Wednesday and I’m pretty sure I think different up north than I do down south. Simple things are not simple anymore and I devote thinking time to things like speed limits and temperatures and how metric-illiterate I am. I also have to look at money very closely, wondering which size and color coin is which amount. I wait for my change in the grocery store but never get it because the country “rounds” the tab — nobody gets pennies back. The end result is that when I’m forced to think about little things I ordinarily wouldn’t pay attention to, I also start thinking about work things in a way that I wouldn’t ordinarily do.

I’m being hosted by Bill Nelson‘s lab at Queen’s University as part of a research exchange program. Bill is a biologist/mathematician who also crosses into the field-work world to look at Daphnia populations in local lakes.

Week one: I was thinking in math. Something I would ordinarily not consider myself to be doing. And when I inevitably had to email Bill after running into troubles, I received in return one of the best email responses ever written: a picture of a hand written math solution.

The simple translated email was: “You’re using an incorrect equation. Use this one instead.”

I would love if more emails were hand written. I miss seeing what hand writing looks like.

Week two: I worked in a boat. I’ve never worked in a boat before.

Field work in a boat: sampling gear laid out on the bench as we anchor in at the first field site.

Bill samples water for Daphnia from six lakes. The only way to get to sampling locations is via rowing.

I learned science while learning how to row. The rowing learning curve was a bit steeper than expected. Sitting between the oars with Bill in the back and Shelley sitting in the bow, I swerved too far left, distracted by loons, then overcorrected right, swerving back and forth before we got to our buoy-marked location in the deepest part of the lake.

Loons. I must be in Canada.

From there it was more non-stop learning: new biology jargon, new facts about the layers in water bodies and new terms describing aquatic species and communities.

Tomorrow, week two of learning continues! This time off-boat.

I spend a lot of time thinking about stochasticity (i.e. randomness) — what causes it, when is it important, and how does it impact data?  So I was really interested in a recent tv episode that discussed some of the different theories of what stochasticity is.  One that I thought was particularly interesting was the theory that stochasticity is an illusion.

Before I go on, a disclaimer.  I am a biologist.  I know very little about quantum physics.  Everything beyond this sentence should be viewed with a lot of skepticism.

To summarize in a way that is almost certainly oversimplifying (and wrong), many particles in our universe exist in multiple states at once.  When these particles are observed, they must “choose” a single state, which results in a single outcome.  If they had “chosen” a different state, it could have resulted in a different outcome.  The theory presented in this show that fascinated me was that no decision ever actually gets made, but instead, the universe splits at each decision such that every outcome occurs, but only one in each parallel universe.  So to the observer, it looks like stochasticity exists, but in actuality it doesn’t.  In practice, this results in infinite (or effectively infinite) parallel universes.

My problem with this theory is that by my reasoning it seems like it must be either useless, or wrong.  If multiple universes existed, but it is impossible to travel or communicate between them, then the theory is useless, because it has no impact on my reality, and it never could.  On the other hand, if it were possible to travel or communicate across these universes, and there are infinite of them, then there must be universes where people developed the technology to travel to other universes.  And in these universes where they developed the ability to travel, in a further subset of these universes, the people must have thought that it would be a good idea to spread their technology to other universes.  In still a further subset, the people from some of these universes that shared the travel technology must have thought that it would be a good idea to recruit other universes to help them spread the technology further.  This would create a multiplicative effect such that the technology would be spread to all universes.  So the fact that we don’t currently have the technology to travel between universes suggests that if there were infinite other universes, it must be impossible to travel between them.

Admittedly, my math might be wrong –I find it hard to think in infinites.  Alternatively, one might suggest that there hasn’t been enough time yet for the technology to spread, and that I should just be patient.  But that seems highly unlikely.  If there were infinite universes, sentient beings would have evolved and developed this travel ability on at least some of them long ago — long enough ago to spread it I would imagine.  A more interesting alternative to me is that there are infinite universes, and people trying to spread this technology, but there are also universes that don’t want the travel technology to get out, and so they travel from universe to universe destroying the people who are trying to spread the technology.

I’m currently in Cote d’Ivoire practicing my patient waiting skills. To pass the time, I started reading this book on how to conduct field trials for public health interventions. I’m currently on Chapter 11: Randomization, Blinding, and Coding. In addition to being a useful reference, it’s turning out to be a surprisingly interesting read.

Part of what I’ve learned so far is the real nuts and bolts of designing a field trial. For example, how to calculate trial size, how to stratify treatment arms, various methods for randomizing people or groups. I now know how to code individuals and their relationships in a polygamous household for census purposes.

There is also a section on ethical considerations, where I learned that it’s considered unethical to provide a standard of care that cannot be maintained after the end of the trial. This is something that seemed perfectly reasonable after I read it, but I probably wouldn’t have thought about it otherwise.

A lot of the blinding discussion is like this as well. I know blinding is important, and I know double blinding is the gold standard, but I haven’t really thought a lot about why it matters or how exactly to do it. For example there’s a lot of emphasis on making sure the placebo and treatment are as similar looking as possible (obviously this isn’t always possible, for example with interventions that are behavioral or structural). I wouldn’t think it matters so much, as long as nobody knew which pill was the active one. But apparently, different colored placebo and treatment pills can lead to problems, even if the study participants don’t know which color is which, just because one color is perceived to be more effective.

Blinding is not necessarily possible even when the treatment and placebo are identical looking pills. When people received ivermectin (an anti-helminthic drug) in a study testing the drug for use against river blindness, people were able to guess that they received the anti-helminthic because they started to pass non-target worms in their poop.

I’m looking forward to Chapter 12: Outcome Measures and Case Definition, which I’m sure I will have plenty of time to read in the upcoming week.

A few weeks ago I was hiking in Velebit National Park, Croatia. My sister and I had roadtripped there in a cheap $10/day rental car from the capital city of Zagreb to climb peaks, trail run and get muddy  (a trail runner’s favorite thing to do). We drove up to the National Park visitor center to get a trail map and were given a map similar to this one. In red are areas with suspected land mines.

I’d never been given a land-mine map in prep for hiking before. Most U.S. maps have warnings for more benign things like a dry spring or a sink hole. Here it seemed a bit more important to not venture off-trail.

The land mines in Croatia are relics of the Yugoslav wars that took place from 1991 – 1995. Twenty years later, land mines are still a danger to civilians and tourists in regions that, on the surface, appear to be recovered.

Who would expect a land mine in a place that looks like this?

The Croatian plan for land mine removal involves training honey bees to smell out mines.  In many parts of Afghanistan, they use dogs. In Cambodia and Mozambique, they use giant rats (how giant? these rats are over 3 ft in length from nose-tip to tail-tip). I’ve seen trained dogs and trained rats but I had never heard of a trained insect. Can insects be trained?

Insects, apparently, can be trained and have been for a variety of purposes. Mosquitoes have been trained to change landing preferences when certain lands were paired with electric shock. Cockroaches have been trained to “carry” backpacks for search and rescue missions. Wasps have been trained to detect a variety of drugs and pathogens. Maybe it’s not surprising then that bees can sniff out mines.

It seems like scientists are getting good at training insects to find and do things. Now maybe we can work on the reverse: can we train mosquitoes to not find me?

Sometimes completely random questions pop into my head.  Yesterday my completely random question was, why has it been common throughout history that inheritances go to first born male children (if that is in fact true across most cultures)?  Actually, it wasn’t a completely random question, the seed of the idea was planted when I was talking to Jo about “little r” for mosquito populations.  I had never really thought about it before, but the strategy of bequeathing wealth to an eldest male could make sense from an evolutionary point of view.  I’m sure many people with evolutionary backgrounds have thought about this before (and probably studied it in substantial detail).  Boiled down, there are two patterns that need to be explained, 1) choosing to leave resources to male over female children, and 2) choosing to leave resources to elder over younger children.

I know that the first choice has been discussed in animal populations to explain biased sex ratios within families.  When one sex has more variable realized fitness than the other, high resource parents should try to have the more variable sex because their offspring will have enough resources to develop into high quality individuals that can be highly competitive for mates.  Conversely, low resource parents should try to have the less variable sex.  Extending this theory to resource investment among siblings, parents should biasedly invest resources into the siblings that are of the more variable sex.  In human populations, male reproductive fitness is (or at least historically was) more variable than female reproductive success, and so from an evolutionary point of view, parents should have been more willing to leave their inheritances to males than females.  Fitness in modern society is governed by very different factors from that in the past, and so whether this conclusion still follows today is unclear.

The logic for the second choice was a little less obvious to me, until I started thinking about fitness in terms of “little r”.  For anyone unfamiliar with my use of the term “little r”, I am referring to the intrinsic rate of growth of a population (e.g. dN/dt = rN).  Number of offspring births is obviously important to this value, but perhaps less obvious is that the timing of these births is also very important in a growing population.  An individual who has three births spread out over 20 years, is much less fit than an individual who has three births spread out over 10 years, because the latter individual has a shorter generation time.  First born children on average are more important to fitness than latter born children, and so evolutionary theory should favor leaving inheritances to elder over young children.  Add to that the fact that younger children have more risk of dying before reaching reproductive age, and the effect only gets stronger.

I wonder if there are any other species that have inheritance-like events.  I would be super interested in learning whether this logic holds up for other species.

If you’re pressed for time, just read my title.

I was thinking about Google Scholar and what it means to be able to “click” and find an article from 1944 in less than a minute (or request it through ILL in as much time and have it the next day).

As an undergrad, it was part of my job in the lab to get these old research articles for the graduate student I worked with. This involved physically going to the library (at least at this point the catalogue was digitally searchable so I knew where to look!) and getting out a book containing a compilation of several months of journal volumes. Then, I actually opened real pages, and would stand at the photocopier making photocopies of these pages, turning them one by one in the volume, pressing it down to make sure the text in the crease of the book was not too distorted. Then, I would take the photocopies back to the lab, and sit in this great old leather office chair, highlighting relevant pieces of information for the grad student.

Prior to my beginning graduate school, there was the timely advent of Google Scholar. (In beta in 2004, useable in 2007 to find some papers, and from there it has grown to the beast it is today).

I now will rarely print unless there’s a table or figure I want to spend more time with, or need to make extensive notes. I often highlight and take notes using Papers.

Today, I found a citation of interest in an article I was reading, highlighted the text on the computer screen using the trackpad, copied the title into Google Scholar and 15 seconds later was reading it online.

I have a few thoughts about this, some germane our recent pub meeting about how articles are found and cited.

First, not every article Google Scholar finds is relevant, and it finds a LOT, so effective Google searching is a new skill unto itself.

Second, a lot of the articles that are found, are also interesting, making it easy to find tons of other cool stuff, and get really distracted in the process. I have termed this “going down the rabbit hole” and need to stop myself from following some interesting line of thought oftentimes to avoid too many detours.

Third, finding where you’ve read what you’ve read becomes even more difficult.

Fourth, organizing this stuff is a problem all its own. I’d love to hear how you all cope, particularly you PIs who must have thousands and thousands of articles you’ve read at this point! I use keywords the file name in addition to saving articles consistently by lead author last name and date, and some description of the title.

Fifth, does any of this save time doing research that’s already been done? With the push to publish (or perish) there are an increasing number of articles coming out daily and it feels a bit overwhelming to sort out the good science from the chaff.

I’d like to hear your thoughts about whether this level of access has made us any smarter or better informed than before.

This morning I received another cheerful e-mail from Monica Arismendi reminding me that it’s my turn to blog. But I have to admit that I’m not feeling particularly inspired at the moment, perhaps another casualty of the summer doldrums.

So instead, I just wanted to take a page from Lauren Cator’s book and express my appreciation for the work that Monica does. When I was responsible for the CIDD seminars, Monica played an important role in making sure everything ran smoothly. Monica also helps me with the reimbursements for my trips to Africa. I’ve given her receipts that are hand-written in Swahili, for money that was spent in shillings, and she has somehow managed to make magic happen in the Employee Reimbursement System. And she does it all with a smile :o)

Thanks Monica!

I’d like to file the one trillionth complaint against the US medical system for being non-transparent, expensive and idiotic. I’m healthy and young but with a recent unlucky proclivity of finding myself in urgent care facilities. Once with four breaks in the palm of my left hand and once with the characteristic rash and muscle aches of lyme disease. Once in America, and once in the United Kingdom. I’m taking it as an opportunity for a comparative analysis of US vs. UK healthcare systems.

Being treated for lyme disease and being treated for a broken hand starts the same: you wait an hour for 15 minutes with a healthcare provider who then gives the same advice as you’d get from Ask Jeeves, the only difference is Jeeves can’t write prescriptions. In America you pay $254.50 for this (after insurance), which on the itemized bill is a fraction of the total cost for an “Encounter with Mr. X, PA” ($580, insurance pays $325.50). If you add the X-rays (applicable for a broken hand, but not lyme) you will pay an additional $135, of which insurance covers none, despite the fact that the insurance plan costs $3,054/yr. In the UK, as an American tourist, you pay $0, with or without X-rays, with or without drug treatment and with seeing a real doctor rather than a nurse or PA.

In America, the price of getting an X-ray varies wildly. The cost in New York is different than in Pennsylvania, which is different than in California. If you look at Nerdwallet’s listing of out-of-pocket costs for X-rays across the states, you can get an X-ray for $15 at Brookdale University Hospital and Medical Center in Brooklyn, NY while the same X-ray costs $898 if you were to get it at Radiology Outpatient Imaging Services in Mountain View, CA. In the UK, X-rays cost the same if you were to get them in Edinburgh, London or Brighton, $0. Even if you decided to pay for private care not sponsored by their government healthcare system, the variance in prices would be much lower than in the US: the median price is 101 pounds, with the lowest price 75 pounds and the highest 120.

With 2/3 of all US bankruptcies a result of exorbitant medical costs, here’s an alternative to paying US healthcare bills: the next time you break a hand, get sick or need a surgery, buy a plane ticket to London and pay the affordable private rates available in a system free from insurance companies. If you leave on Friday, your plane ticket costs less than the State College medical bills for a broken hand ($538 vs. $580).

What if a vaccine made it so any vector that bit you died? You’d be a walking bednet, or better, and it would cut down on the need for other interventions.

I’ll admit it, I’m on the pan-vector vaccine bandwagon. I am also currently obsessed with the role of cows in malaria transmission. (Which is a weird thing to say, since cows don’t get or transmit malaria. They are essentially big undefended bags of blood = mosquito food).

Vector vaccines would be an awesome tool to add to the arsenal against vector transmitted parasites, but they have issues. The likelihood that a single vaccine would work against all vectors is like expecting a single vaccine to work against all parasites. There are plenty of other problems too, like figuring out how to amp up the immune system without causing an allergic reaction in the host, or giving any parasites that the vector is carrying a leg up, making potential infections much worse. Check out the latest Trends in Parasitology review (with a great title) by the fantastic Mary Ann McDowell.

Another great vector biologist, Brian Foy, ivermectin specialist, and his group put out this article on a channel (AgGluCl) they’ve found in mosquitoes from which an antibody insecticide/vaccine can be made. The antibodies an animal (rabbit was injected with surface proteins from the channel in their experiments) makes against these proteins kills mosquitoes. The journal picked up on the headliner future potential of this work in this piece, from which I’ve plucked the paragraph below.

“Having shown that antibodies targeted to AgGluCl in blood meals can be effective insecticides, Meyers and Foy are keen to find out if antibody-laced blood meals are equally deadly in real life. ‘The next step… is to immunize cattle against the AgGluCl antigen and directly feed A. gambiae on the immunized cattle in the lab’, explains Meyers. And if the strategy proves successful, Meyers envisages a large scale cattle immunisation program as part of a combined attack on the parasite. ‘Cattle are a major blood meal source for multiple malaria vectors,’ he says, explaining that any malaria-harbouring mosquito that consumed blood carrying the toxic antibodies during the malaria parasite’s incubation period would die, disrupting transmission of the disease and offering hope of a malaria-free future for generations to come.”

This only reinforces my stance that the solution to the problem of malaria lies with cows and vectors. I’d love to hear what you all think!

(Title inspired by Andrew’s recently suggested reading).

I spent much of my day working on a case report I am doing with Dr Bob. It concerns a patient who died from overwhelming evolution. This is my first ever n=1 paper. That number is in shocking contrast to our recently accepted MDV paper, led by Dave, which involved 287 billion subjects. Is that a record in ecology and evolutionary biology?

Even if you work on the number of stars in the Milky Way, or the number of galaxies in the Universe, and however you define a billion, 287 billion is a very big number.

But when I Google ‘How big is 287 billion?’, I see it is in dollars what Republicans committed to add to the American deficit last year. So it must be a very small number, right?

How often do we look at our data and, wowed by its beauty, fail to translate beautiful results into an equally beautiful data visualization? In science, I think the answer is very often. Read any online journal article and you’ll stare at a static raster image, that looks about the same as if you were reading a paper copy, only on a screen. Static images, often pixelated under zoom, not interactive, not attractive.

Why can’t we have more data look like the data in Hans Rosling’s TED talk? Why can’t we make data like this? Or make data fun? And interactive?

We can, we just don’t. One alternative to static pictures summarizing our data (think of the bargraphs, boxplots and lineplots we see in most journals) is using something called D3 interactive data visualization. D3 stands for data driven documents and is a JavaScript library (d3.js) written by Mike Bostock. Bostock is largely known for his work at the New York Times as an editor for the graphics department doing cool stuff like this, and even cooler stuff in his free time.

My recent preoccupation with following the work of Bostock and reading Marcel‘s book, Nature, in Code, has made me wonder if and when we’ll start seeing better data visualizations in science. The technology to create interactive data visualizations is available, easy to learn and largely open source. I’m not a techie by any stretch of a stretchy imagination, and within a week I could learn the basics of JavaScript, get the d3.js library up and running and write my own programs to visualize life table data.

One benefit to using d3 in science is transparency. When the data is bound to the figure, any user can see where the patterns the figure is showing are coming from. Many journals are starting to require data to be placed in a data repository such as dryad, but what about the alternative: the data enters the manuscript directly through d3 figures? It seems bizarre that the current system of publishing does not emphasize, and rarely requires, publishing the raw data — isn’t that the most important part?

I’m hoping that the future of online journal articles veers away from looking like paper photocopies on a static screen. Imagine how much more fun reading online journal articles will be when we have dynamic documents that respond to user questions, allow us to look at subsets and explore data in different ways and at a faster pace than looking at a raster image generated from a dataset we can’t see. When will Nature and Science hire the Mike Bostock for our field?

I was curious about the article Jo mentioned at the pub about something I’m sure we’d all never thought about, but apparently are curious to find out.

Dogs do apparently poop facing magnetic north (or south, alining with the magnetic N/S axis). At the face (or butt?) of it, this kind of science seems frivolous, but the researchers did at least two things well:

1) made observations cheaply and came out with decent science

2) caught media/popular interest

Like most ecologists, I love talking about a good trade-off. Survival-reproduction, virulence-transmission, rate-efficiency, generalist-specialist. We’re not the only ones. Myrmecologists talk about their dominance-discovery, the physicists, about force-velocity (P=Fv), and consumers curse the trade-offs between cost and performance. The more we look for trade-offs the more we find — but why are we always looking?

A week ago I was sitting in Andrew’s office and we were talking about trade-offs like good biologists, when Andrew said something to me that I’ve been hoping was true for the good part of the last year: we shouldn’t always expect trade-offs. “Cars are expensive. Houses are expensive. We should see a trade-off between nice cars and expensive houses. But the fact is, we don’t.” We see the opposite: people with expensive cars, have expensive houses.  People with cheap cars, live in cheap apartments.

Trade-offs are trendy. In some cases, I think we look for trade-offs for good reason.  In others, I wonder if our focus on always looking for trade-offs has masked our abilities to see interesting counter-examples. Agonistic pleitropy (as opposed to antagonistic)? Synergies? Fast-and-efficient instead of fast-and-inefficient (rate-yield trade-off)?

Jeremy Fox wrote a recent blog for Oikos making a point for why trade-offs should be expected in ecology and evolution. Both Fox and Rowe (Rowe wrote this article that inspired Fox’s post), assumed that the two traits trying to be maximized are on opposing axes (one trait is on the x axis and one on the y axis) so if you randomly fired a shotgun at their graph of y vs. x, the closer the shot was to high x values, the further the shot would be from high y values. What confuses me is why we assume they are on opposing axes? Maybe two traits are two lines on top of each other (falling on the same axis) or are two squiggly lines that interlace and share peaks at some points, and have opposing peaks at other times.

Why do I think alternatives to the x and y axes ideas are possible? Because we see things like balancing selection (if a trade-off coming from one trait is frequency dependent maybe there are squiggles in our trait lines?), evolutionary spandrels (if there’s no mutational decay maybe maintenance costs don’t exist?), and “jack-masters” (what trade-off?).

Trade-offs everywhere and very little talk of alternatives makes me wonder if it’s nature or a human looking problem. I think I could be convinced of both but I’m reminded of something one of my favorite college professors used to say at the end of class: “The more we look, the more we find.” He would pause to put his notes down for a dramatic effect (which wore off by mid-April), and then we’d all look at the board and his wry smile. In my head he was saying: Hey, life is interesting. But remember this interesting life is subject to sampling bias.

I read today that Chipotle has phased out the last GMO ingredients so that they are now 100% GMO free.  Too bad, I really liked Chipotle and I’m really going to miss eating it.

I see a lot of parallels between anti-vaccine and anti-GMO advocates.  It is quite the luxury to live in a place where food is plentiful and disease is rare.