Category Archives: The Life Scientific

Weeble wobbles

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Today marks the two month anniversary of my arrival in State College and the beginning of my postdoc in Matt and Andrew’s group. Not surprisingly, I’ve spent a lot of the past two months thinking about career transitions.

One thing I’ve come to realize is that moving to a new lab is a bit like being a Weeble. If you’re not familiar, a Weeble is an egg shaped toy with a weight in the bottom. When you push a Weeble, it swings around wildly until the heavy bottom brings it back to a stable and upright position. Likewise, when you transition between labs, some wobbling is to be expected but hopefully you too will eventually stabilize, thanks to your heavy bottom (or solid foundation, if you prefer).

Obviously career transitions are not unique to science, as most people switch jobs at some point in their lives. But in science, such changes are notably frequent and largely regarded as necessary. For example, I’ve worked in four labs thus far and my current position is, again, temporary. Even in a permanent position, turnover in a lab is so constant that you are still effectively changing labs every few years.

These transitions are so engrained in the scientific culture that staying on in a lab can be viewed as bad for your career. I’ve heard multiple times the advice that, when you do your postdoc, you should change at least two of three things: the institution, the study system, or the question. Presumably, the idea behind this advice is that broadening your experiences also broadens your thinking. Unfortunately, it also takes you out of a lab where you’ve spent a significant amount of time developing your skills and research projects, and sets you wobbling off into a new lab.

Likewise from the PI’s perspective, you put time and money into somebody only to send them away as soon as you start getting a return on your investment. As Mark Cohen wrote earlier this year in a letter to Science, “can you imagine a private-sector environment that demands of its best workers that they find jobs at other companies, rather than nurturing them towards the success of the business overall?” This observation makes me wonder if the frequent turnover in academic science plays a role in driving scientists out of universities and into the private sector.

All of this is not to say that I am unhappy in my new postdoc position. Despite the immediate cost to my productivity, I made the move because I anticipate a net positive in the longer term. However, I do think that it’s worth discussing the trade-off that comes with moving labs, and questioning whether the current emphasis on change really is best for many mentors and mentees, and for science in general.

Mastering the Art of Gametocyte Induction

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Everything seems harder the first time you do it. 

If you’ve made bread, or, for you scientists, designed PCR primers, think about the first time you did it. On the face of it these processes are simple, and share the same formula; you have a recipe, you follow it, you get the desired product. End of story. Yet, acquiring new skills often doesn’t feel simple.

I usually have some apprehension the very first time I try something – will the bread really rise like it’s supposed to? – and experience relief, satisfaction, and the sense that I’ve experienced some small miracle when ingredients have been turned into a loaf of bread, bands on a gel, etc. But the magic wears off. Later, looking back, it’s hard to remember what the big deal was.

So what makes learning new skills seem difficult?

At least two things – feel free to add more:

1) How intrinsically hard it is. Let’s face it, some things are just hard (e.g. requiring many steps, background knowledge, complex movements – see “expertise“, etc).  This is related to the learning curve, or the difficulty of the new skill. Not much skill necessary to boil an egg, and quite a bit to design working PCR primers. For simpler skills, learning happens in huge leaps early on, followed by smaller gains as there is less left to know, whereas for harder tasks the climb up the curve is just one long slow haul.

2) Level of familiarity, i.e. transferrable skills. If you apply previous experiences new skills seem much easier: PCR aids learning quantitative PCR. And, we actually do get better and faster with practice; this looks a lot like improving efficiency along an experience curve to me.

Right now I’m learning how to grow Plasmodium falciparum parasites in culture.

I’ve been told this is really straightforward, and the basic steps for growing an asexual culture seem to be – plus they are relatively hardy little buggers. But I’m interested in the life stage that can infect mosquitoes – the gametocytes. These are the sexual stage, the prima donna parasites, finicky about temperature changes, whether they get human or animal sera, fresh or less-than fresh RBCs, you name it. Unfortunately, even the people that do this for a living have told me gametocyte induction is really hard.

Why?  Well, as best I can tell it’s a combination of slightly technical challenges (sneeze in your culture and it’s all over), and the need for experience to know exactly when to do each step. The parasites are only convinced to become gametocytes by being stressed. Without stress, the asexuals would happily keep on growing, and might never make any gametocytes. In practice, this means that after I get the parasites growing I’m then stressing them to the point where some inevitably die, more have a near-death experience, but not stressing them so much that the whole flask of parasites kicks the bucket. (I find the parasites aren’t the only ones a little stressed by this particular step). Afterwards I make every effort to placate them with a cushy environment, the freshest red blood cells available, and try to make amends (all while selectively killing the other non-gametocyte-producing stages with heparin). After several days only gametocytes are in the culture. This is way more involved than any bread I’ve ever baked.

Feeling about as comfortable as Julia at a too-small stove...

But, as Julia Child said, “Anyone can cook in the French manner anywhere, with the right instruction” (Mastering the Art of French Cooking, introduction). [Translation – “Even Jessi can learn gametocyte induction techniques with the right instruction”].  And fortunately I have the written instruction of many other scientists that have tried this. Much more importantly I have the expert instruction of the members of the Cui lab. In particular, Feng’s advice and patient explanations continue to be invaluable in this process.

Having mentorship in learning complex techniques is vital, and nothing beats actually seeing the process through when first figuring it out. It has allowed me to jump along the experience curve to become more efficient much faster than I ever would have been able to without this type of help. With luck, and enough observation and practice, I’ll be bringing this skill to the Read/Thomas group sometime soon. I’m planning to use the same equipment and tools since familiarity makes the learning process easier, and reduces room for errors due to picking the wrong types of flasks and so on.

When an expert isn’t available there are often alternatives – perhaps this explains in part the popularity of cooking shows, or youtube instructional videos. Scientists are cluing into this – just check out the Journal of Visualized Experiments.

This week my parasites are on their way to becoming beautiful gametocytes. In fact, the precocious ones made their appearance this afternoon! They should continue to develop, barring any hurricane-related interruptions to their care. I’ll keep you posted.

Success or failure?

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Lauren asserted at a lab meeting a few weeks back that we (Matt and I) don’t talk enough about our failures. What was she thinking? Of course we don’t. We’re blokes. But three times, NIH refused to fund Lauren’s work, even though her idea is excellent, her preliminary data good, her track record excellent, and Matt and I threw our best grantsmanship at the problem. We fund her work anyway, and Lauren now has some great results. Hopefully, a story of success despite the system. But Lauren’s point was that as mentors, we need to equip our people with the right expectations.

It turned out Matt and I had no idea what rejection rates to train people to expect. The national statistics are not much help because many people write bad grants. What you want are the numbers for people who are competitive. Matt and I had no idea how well even we were doing, so we dug up the data for a subsequent lab meeting. The numbers dropped out like this.

We submitted our first US grant in May 2008. Forty two (yes, 42) grant applications later, our success rate per application is 48%. This includes grants we did together, as well as our individual efforts, or grants one of us did with other collaborators. If we break it down by project, and ask what proportion of projects we eventually got funded, the rate is 78%. That includes things we flogged away at repeatedly (worst cases: success on the seventh go, success on the fourth attempt). The proportion of grants that got funded first time was 31%. The proportion of eventually-funded grants that got funded first time was 63%. We abandoned only two of the submitted proposals as having no future or being too low priority. The remaining 95% of applications led to external funding eventually or we continue to fund them internally because we believe in them. Total cash raised? Somewhere between $27-$28 million, of which the share coming to Penn State is about $11 million.

Is that a record of success or failure? Hard to say. We now have a large well-funded group filled with smart people I like a lot. That feels good.

From the expectations point of view, there seem to be three lessons.  First, even senior people with much experience get rejected a lot. In this game, you need to develop the ability to absorb rejection. Second, raising money requires huge effort. A Gates Grand Challenge Exploration grant takes just a few days to put together if you know what you want to do. An NIH R01 application, especially one with complex partnerships, might take 6-8 weeks to put together the first time, but only once it is clear in your head. An R01 re-submission takes perhaps 1-2 weeks if it was in good shape the first time round. Putting all that together, Matt and I estimate that over the last four years, we have each spent at least a day a week raising money.

The third important lesson I realized only after the lab meeting. According to the post-docs I talked with, the most sobering insight was prompted by Matt’s comment that the whole process never stops. And it doesn’t. It is professional combat sport: highly competitive and very bruising if you do not have the right mindset. But in sport, it’s unusual to compete at the highest level for more than a decade. In science, winning means you get the chance to keep competing with the world’s best — for thirty years or more.

Scientists to be jailed for failing to predict earthquake

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Yesterday, seven Italian scientists were convicted of manslaughter and sentenced to six years in jail for, as many headlines asserted, failing to predict an earthquake that killed just over 300 people in L’Aquila, Italy in April 2009.

The formal details of the case are a bit more nuanced than the sound bites suggest, but that ultimate outcome is still disturbing, as a scientist. An “unidentified woman on Sky television” thought it was “just a tiny bit of justice so that it doesn’t happen again” (NY Times). I found it upsetting, that individuals would feel comforted by dumping the burden of the deaths of hundreds of people on someone for not pinpointing a natural disaster, and ridiculous that they would think this would somehow get negligent scientists back on their game. What do people think that scientists can/should do?

These scientists populated the country’s National Commission for the Forecast and Prevention of Major Risks. Given that the scientific consensus on the possibility of earthquake prediction seems to be something like “certainly not within a timeframe very useful for informing short term evacuations,” what did these scientists say they could do?

There are many interesting discussion points surrounding this case, beyond just the fundamental, scientific question about the extent to which different aspects of the world and life are predictable; my mind swirls with them. But I guess I’ll ask this mini-blogosphere directly if you think that this conclusion is a worrying precedent? Do you think it is likely to help or hurt more people, and, if so, how?

Other articles: 1, 2

A proposition for recognition by the Olympic Movement

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A lady with hair suspiciously like mine, running

Science should be recognized as a sport.

The parallels are undeniable. I accept that ‘The Loneliness of the Long-Haul Lab Worker’ doesn’t quite have the same ring to it but the repetition; the solitary hours spent at the bench or before the screen; all motivated by one goal – surely not unlike weights workouts; miles pounded.

This isn’t an original thought by any means, indeed it doesn’t take much to realize that members of the two fields are united by similar personality traits. Yesterday, Becky joked that scientists could be contained under the ‘masochist’ umbrella. Isn’t this also a term regularly applied to athletes and what our friends will say when we line up on Sunday to run fifty miles of hilly road at the Tussey MountainbackTM? What unites these activities is the quest for highs – unchartered ground, the answer, the win.

Of course with massive highs come lows. The first time I ran an experiment to test a novel ecologically-rooted theory of drug resistance management, all the signs of success were there. Yet, after analysis, the results revealed only failure. Blame fell on ‘Stochasticity’, scientists’ chance. But this morning, I sat down with ‘Coach’ (alright, the metaphor’s gone too far but did I just find a sufficiently annoying nickname for Andrew?!) after round two and showed him that this time we’d performed, the work had paid off.

There was a long silence.

“Blimey”, he said.

Gold.

The point of it.

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The mentoring issue Matt Thomas and I worry about most is writing. To produce papers that have impact, and to be successful in the brutal competition that is the modern grant system — in other words, to have a career in science — you just have to be able to communicate effectively. No matter how brilliant you are, no matter how fantastic your data or how earth-shattering your new idea, if you can’t sell it, you might as well not exist.

Yet good writing is one of the hardest skills to acquire. It is relatively straight forward to learn the latest lab techniques, and even statistics, reasoning, experimental design and knowledge of the literature. It’s even relatively easy to have good ideas. But writing well is hard. I have a theory that’s because scientists don’t practice telling stories, so when it comes time to write, they have no natural narrative or rhetorical skills. Rightly focussed on trying to get the science correct, trainee scientists can not tell the story in an elegant or simple way.

I think it helps to practice writing in a context which does not define a career. Hence this blog. My hope is that freed of the necessary discipline of writing a scientific paper, our people can practice engaging writing. A good thing about this blog is the potential audience: my mum, others in the group, academic colleagues, competitors – and future employers. Hopefully, the challenge of that diversity will enforce a professional discipline but also allow a bit of individualized spirit. It’s an experiment. Let’s see.

Meanwhile, here we all are on my 50th Birthday in September. Courtney was on holiday. Penny is on computer from England. Apart from Matt, a good looking bunch I reckon. Certainly a lot of brain power and energy. And for the PSU police, those bottles of bubbly on the table are non-alcoholic.