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….
In a recent conversation with my PI and our collaborator we talked about a potentially very interesting experiment that would involve a pretty lengthy behavioral experiment followed by slice electrophysiology. It would mean that a certain person would have to come in every single day (so both days on the weekend) for months. Collaborator:”Yeah that’s what it’s like to be a post-doc”. I said that that certain person was not going to be me, and that I wasn’t going to do those experiments unless I was promised help.
This is not the first time that I refuse to do an experiment because it means that I will be in the lab for an endless number of days, and the last time this happened I didn’t even have BlueEyes yet. I don’t think this sets me back; I just only do those ridiculous experiments when I feel that it is really worth it.
Bottom line is that we are going to put those experiments in the grant that we’re writing, and when push comes to shove we’ll see who is going to be running them… I just already made sure that that won’t be me entirely.
Recently, I’ve been thinking a lot about fraud in science. First of all because there is a lot of it, and because a significant amount comes from my home country
… But also, because I can partly understand what drives people to commit fraud in science. I recently wrote about the experiment for the paper that is almost done
and how getting data consistent with previous results is going to increase the chance of getting this paper in a high impact journal a lot. And we all need many/high impact papers in order to get grants… The experiment is still not done, so I don’t know yet what the results are, but it is kind of ridiculous if you think about it that the same amount of work will yield a different impact factor paper depending on the results.
And then recently I read this blog post
from NeuroSkeptic that in animal research only about 50% of the results get published in academia and only about 10% in industry. So 50-90% of the data just disappear into a drawer!
And what about all the times you read that only a certain percentage of animals learned a certain task, or a certain population of cells responded in a certain way. What happened to the rest?
Recently, I heard a story from a grad student in a different electrophysiology lab who had problems replicating results from a post-doc who had been in the lab. He thought he was doing the exact same things and couldn’t understand what the problem was, until the PI told him that this post-doc had very strict criteria for including cells. They had to be within a certain range of membrane potential, input resistance and variability of EPSP amplitude, but the weird thing is HE DIDN’T DESCRIBE THIS IN HIS PAPER. So it seemed like every cell he patched had showed the same response, whereas in reality the data in the paper were only from a small subset of cells. And from the grad student’s experiments it seemed like many cells did not show the reported response… In this case, when it comes to the health of the cell this makes some sense, but the bad thing is that the PI didn’t seem to know how many cells were omitted from the analysis according to these criteria. Perhaps the post-doc had never even shown these data to the PI, because he would only show the ‘good’ data. I don’t know that the latter is true, but it got me thinking about all the experiments that have been done, but that we never hear about.
But I think there is also an issue at the lab-level, because what if people just use half of the data in their publication? Is the PI responsible to see ALL the data that are produced in the lab? Do we need a different system where it is also encouraged to publish more ‘boring’ research? What are your thoughts?
Today at Scientopia, I’m writing about how the experiments that I’m currently doing should fit previous data in order to go into a paper. Is this ethical and how can we prevent bias in such cases?