Yesterday Nature published an editorial about the fact that addiction is a disease and not a choice. This is a very pervasive idea that even persists in my graduate school IACUC for example. There both I and other addiction researchers had to explain over and over that addiction is not a lifestyle choice, but rather a chronic disease. Even though the first use of alcohol, cigarettes or other drugs can be considered a choice, the continued use and especially relapse following abstinence is not. It is a chronic brain disorder that kills people and that we need to study in both animal models and people in order to find better treatment.
So I shared this piece on Facebook and on my personal twitter. I thought about doing this because wasn’t I supposed to #boycottNature after everything that happened over the past couple weeks/months/years? I think it is very important that Nature gets the message that they need to show that they take steps to be inclusive and treat everybody the same. It doesn’t feel right to say on twitter that I will boycott Nature but do something else in my real person identity. So I will share here that I decided I won’t boycott Nature. Not only because boycotting Nature publishing group means boycotting some of the journals that I tend to publish in and review for, but most importantly because I think it is more important to try to speak up rather than to silently boycott. Just like not going to Sochi won’t magically make gay rights happen in Russia, boycotting Nature won’t increase the amount of women authors, reviewers and other voices in the journal.
With a very hesitant hand I hit the Publish button….
Time always seems limited, whether you’re a parent in the lab or not. So how do you best spend that limited time: with writing grants or papers or doing experiments? Obviously you have to do experiments to get data. You need data to put into papers to have publications in order to look good for your grants. Or you need to do experiments to get preliminary data for your grants. But how do you prioritize what to do first?
I spend most of the second half of last year writing grants, thinking that I would need money to have a job in the homecountry. Actually, I got a job on somebody else’s money, because all 3 of the fellowship applications that I wrote were rejected. This makes me wonder whether I should have spent my time doing more experiments instead of writing those proposals. But had I not written those proposals, then the one that I submitted recently would probably not have been as good as it was (at least I thought it was good…).
How do you go about this? When does writing take precedence over doing experiments? As a post-doc what are your priorities? And as a PI where do you think your post-doc’s priorities should lie?
Yesterday, Scicurious wrote a very honest post
about how she thought that she didn’t have enough ideas to write grants and stay in academic science. This is something that I hear around me every now and then (mostly from women). I have given this some thought before
: how brilliant do your ideas have to be? Because I think that is what people mean when they say they don’t have enough ideas: that they don’t have enough brilliant ideas. But honestly, I think that the percentage of brilliant ideas in science is maybe 1-2% of all the science that is done. I think that the bulk of science is to repeat something with a slight modification to come up with something ‘new’. For example instead of looking at the dopamine system in behavior A, you now study the opioid system and you have another grant proposal. Of course nobody admits that this is how they come up with new experiments, but I have a sneaking suspicion that most PIs will have a variation of the machine below in their office somewhere.
|The optogenetics experiment generator: pick your opsin, roll the bingo wheel for brain region A, spin the wheel of fortune for brain region B and roll the dice for your behavior of choice. This generator can be modified for experiments in any field of life science and beyond.
My graduate advisor did not like desktop computers. Ze was under the impression that people don’t really care for their desktop computers and they quickly get filled up with crap and then become slow. The lab only had desktop computers that were designated for things like the qPCR machine. So we all needed to have laptops. I think this is nice, because then you automatically have a computer if you need to work from home. However, my graduate advisor only paid for 150 euros a year (~$180) towards the purchase of a laptop (and mind you, this came from someone who hirself used laptops like lab notebooks: when one was full, ze would just buy a new one). Considering a graduate project in my homecountry takes 4 years that meant that you got $720 for a laptop (unless you worked on your own laptop for a year, and only then needed a new one, then you only got 3 years worth of money…). Given that I worked in a lab where we did a lot of “big data” type stuff, it basically meant that if you wanted to be able to still process data in your fourth year, you needed a laptop that was more expensive then what our graduate advisor would pay for.
Currently, I am in a lab where most people have desktop computers but some (including me) prefer get a laptop instead. I like to have all my stuff in one place and be able to work from more than one spot without having to remember to put my files on a hard drive or in a dropbox. My current PI paid for my laptop, and for some (but not all) people’s laptops in the lab. The rule was that if you got your own fellowship, you could get a laptop (however, as you might know I did not get a fellowship, but did get a laptop). But after nearly 3.5 years of daily use (to work in the lab and at home but also to watch TV at home) my laptop broke. I don’t have a fellowship yet to pay my own new laptop, and since I will only be in the lab for 5 more months, I decided that I didn’t want to ask my PI for another new laptop. So now I am working on a laptop that I paid for myself. And I know of more labs where people are required to bring a laptop to do work, but have to pay for those themselves. And I understand money is tight and all that, but if lab equipment and consumables are so much more costly than computers, why don’t some PIs equip the people in their lab with decent computers?
Without going into too much detail about the state that our lab is in due to the economy and sequestration, there is a great lack in motivation in some people in the lab. This is not new, as I have written about this before, but it does make me wonder what PIs do to motivate people in their lab. How do you make sure people stay enthusiastic about doing experiments and if they’re not, how do you try to help them? Personally, I find that it helps to associate with people that are working hard and are trying to be productive rather than to hang with the people that seem to have given up hope to get experiments done and papers written. But other than that, when I am in the position to mentor someone (like an undergrad, summer student or tech) I find it hard to find a balance between giving someone the freedom to schedule their experiments and plan their time for them for example. How do you go about motivating the people in your lab? Or do you feel that’s not necessary as people should come with enough intrinsic motivation?
I’m in my fourth year as a post-doc (well technically I’mnot a post-doc anymore, but it does feel that way) and yesterday I submitted my first first-author paper as a post-doc. Is that a little late? Perhaps, but in my defense: I had to learn slice electrophysiology first, and then I got sucked into a bunch of collaborative projects (one can argue about how smart that is, but it did leave me with 2 published (2nd author) papers and at least one (shared 1stauthor) paper in the making).
What I want to tell you about is how this paper came into the world. It started when the collaborator I consulted about my main project asked me to do a control experiment. That control experiment showed something interesting to me, and even though the collaborator was not super interested, I pursued this and got a bunch of rather interesting data. Then I got an invitation to submit a paper to an okay, but not very high-impact journal. I figured that this could be a fast and relatively easy way to get a first author paper out, where I could show the world the things that I can do. So I did some slice electrophysiology to make my side project a bit more interesting and when I sent this to the collaborator he was pretty enthusiastic about it. Without really realizing it (because, shame on me, I wasn’t aware enough of the literature) I had discovered something new and interesting! So something tiny, that no one was really enthusiastic about at first, turned into something cool!
And my main project? That turned out to be way too ambitious and technically challenging (read: impossible). And thanks to my mentor’s “hands-off” mentoring style and my own stubbornness, I realized this only this year… It was a good lesson in project design, that I hope I will be able to use in the future.
When you watch classical ballet, you see dancers that appear to be flying through the air. You see women who seem to weight only 2 pounds, as the men can easily lift them up. You don’t see sweat, you don’t see hard work, and you don’t see feet that hurt. If you’ve ever attempted doing classical ballet, you know that it takes every inch of your strength to jump up, and then it probably looks only 1% as gracious as on stage.
I often think about this when I see someone present their science. It looks like they happily walked into the lab, thought of their hypothesis first, then did one Western blot, one immuno staining, and one behavioral experiment, and took the data to make beautiful figures. When I was an undergrad I honestly thought that the experiments you saw in a paper were the only experiments that people had done. Ha! Was I wrong! In reality, scientists sometimes just play around in the lab, do some experiments, and then think about how to streamline it into a paper. And my first experience in the lab was 6 months of doing a zillion Western blots, just to get a publication quality figure, which we then called a “representative” example.