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4 months is a long time to go without any posts here. After making my big decision of picking a lab, I took sometime off and spent a good one month at home. Just about the time I got back, Philly welcomed me with an earthquake on the same day I landed and an Irene that very weekend :| Within 3 days of settling down, I was back to grad school and most importantly it was my first day in the lab – my lab for the next few years :)

With teaching alongside coursework and preparing for quals, applying for fellowships and deciding upon my thesis work while doing some preliminary experiments has been a little too much to take in one go. These last few months it felt like I had time for nothing but work. And just when I thought it was getting better, the semester is almost coming to an end with quals in December which is again nerve wracking and also my head telling me – damn it, already 2 months in lab with no data! Its amazing how slowly things move in science when things around us just zoom past by.

With those updates, my take on teaching so far: to put it simply, I’m really enjoying it. I’m glad I took up a lab course where we are supposed to teach 2 lab sessions every week which is 3 hour long each. I have about 15-16 students in each section which is a good number – you can actually get to know them and any day easier to teach small classes. I was a little nervous in my first session but figured these kids might be as nervous as they are all freshmen at Penn. Except for the weekly grading of their lab reports and assignments and the midterm grading which is even worse (as we do it for the entire class which is about 230 students), it is fun. It does take up a lot of time but now that I think about it, its actually good that we have to do this in our 2^nd year of grad school and be done with it when we anyway have too many things going on and when its not so easy to get a good amount of research work done.

iGEM is back this year – I could not go last year but I think I’ll be going this year. The team from IIT Madras seems to be doing well so far and the fact that they had to do a selection at the regional level probably means that the teams competing in the world championship are all pretty good ones. That reminds me – its sad that Penn doesn’t have an undergrad team representing at iGEM. What is it? An Ivy League?! Maybe I could talk about this at some point with my students and atleast make them aware that something as cool as iGEM exists. I’m excited about seeing some cool stuff at MIT over the weekend. I’ll definitely have a post here on that one.

Thermal capture and all the other blah

A lot of exciting things have been happening over the last few weeks (which also included a short vacation to the west coast) which kept me busy. Its time to blog about all the awesome stuff thatI came across before my mind tries to erase bits and pieces of them. So here it goes.

This post is about a study that came out this year in June and unlike most other research articles we all read, this is about teaching in the laboratory. First of all, I never heard of this journal (Adv. Physiol. Educ) before and it’s sad that most of us miss out on some really good stuff just by virtue of not knowing that some of these journals even exist. This study was born out of a Physiology course for graduate students taken by Prof. Luke Janssen at McMaster University, Canada.

Here at Penn, a small set of us meet up every Monday and we call it the Nano club and talk about recent papers in the motors field. I was pleasantly surprised when this one was listed in the spreadsheet of new papers that we circulate amongst ourselves. The revelation that molecular motors are stuff with kinetic energy and they move things around efficiently and generate force had a deep impression on me when I first learnt it. What we were taught in undergrad was these smart motors convert chemical energy of ATP hydrolysis to kinetic energy. That’s reasonable, not too hard to break your head over. Professors like to keep things simple in undergrad courses I guess. When I went about reading more about motors I realized that there is another way that scientists like to think about as well which is the Brownian ratchet model. To put it in a simple sentence – the motors can make use of their inherent random fluctuations and vibrations (present in all directions) in a way way that these motions occur only in the required direction and hence doing useful work. This is also called thermal capture. How are these vibrations filtered in one direction and negated in the other? This never made sense to me, or rather it was so hard to grasp this concept.

This study addresses just that! I could connect to the introduction of this paper where the authors talk about how this is not very easy to explain to students. They describe ways and methods to demonstrate this concept in a lab setting with things that we use almost everyday. One of their simplest models used a cell phone in the vibration mode with paper clips. Have the phone vibrate on the table and it vibrates in all directions. Have 2 long paper clips attached to it in a way that each time the phone vibrates, (due to the way the clips are attached) – one of which acts as a ratchet so the vibrations make it to move only in the direction of the paperclip* .

With this model, the students were asked to come up with other such models and some of them came up with very interesting ones which also demonstrated some fundamental things like how small changes in the setup could lead to huge changes like say, two motors very similar to each other but one moves towards the + end and the other towards the – end. They also have a very nice one for how DNA polymerase moves along a track adding nucleotides.

I strongly recommend you take a look at this if you’re even remotely interested in molecular motors and even if you’re not, just to take a peek at the elegance of such a teaching method and style.

*I wrote to Luke asking if I could use his pictures here and though as much as he appreciated my idea of having a post dedicated to their study, his mail made me realize its not the authors but the journal which has the copyright once its published. Its funny how once your study gets published in a journal, the ownership now becomes that of the journal.

Time for a giant leap

It’s that time again when I have to take an important decision – choosing my thesis advisor/lab. Its funny that each time I have to make an important decision, I feel like I just cannot afford to make a wrong choice here. Though in the past, I have made some wrong choices at times, I could work my way through them and it never felt like all things would come to an end. However, choosing an advisor is a totally different issue on all levels. If I went wrong here, things could be brutal and all that I had to do to come this far could just come crashing down.

The more I think about it, the more I realize that this is one decision which will decide so many other things in my career in science. This is my 3^rd and last rotation and though I am glad I was able to eliminate one of the three pretty easily, choosing between the two remaining still seems a daunting task. These days almost every day ends with me adding more and more things in the pros and cons lists in my head and thinking so hard to the extent that I’m really drained out of energy. However, it did give me a good chance to think about what are the things that I really need - to be able to do some good and important science.

Freedom – I join a lab, I pick a problem a statement that I find really interesting and try to answer it in the best way possible. I realized it’s very important for me that I am the person designing my research with my advisor and not have somebody else do it for me where I just end up doing what someone else proposed. It should be like my story, my very first story in science :)

Support – More than half the things you do tend to not work in biology. Then begins the troubleshooting and I should mention that though the joy of discovering what went wrong and fixing it and getting working assays is truly satisfying, it does take time to nail down the culprit. It is this time when you probably need the most support from your peers in the lab and your advisor – when things refuse to work. You need people who could throw at you many more possibilities why the assay is not working and through all this, your advisor giving you a helping hand.

People – I have come to believe that it’s a huge resource to have a set of motivated people around you to bounce ideas off. I’ve been a part of several labs in the past and I’ve seen lab meetings where people just listen to the speaker’s work, ask a few questions and leave and meetings where the others in the lab actually make a good effort to see how the speaker’s project can be made better – what would be another cool thing that can be done at this point, what would that one big idea be to claim your hypothesis convincingly. The synergy is amazing – everybody trying to make each other’s project better and better. Oh well, I am glad I was able to sample such labs as well.

There could be several other things that someone else in my stage could come up with but I figured to me the most important things would be the freedom and the support; maybe I could compromise for the 3^rd factor but definitely not the first two. Another few weeks and I’d have this choice made. And that would mark my first success in grad school :)

Blogger glitches

What do you do when you realize that one of your recent posts that did have comments shows 0 comments? What do you do when you notice that one of your posts is missing and better still, what do you do when you realize all your blog posts have disappeared.

I’ve experienced the first scenario and (fingers crossed) hopefully will not see the other cases in my blog. Based on whatever little research I did following this event, turns out Blogger always had such issues and the blogger help forum is inundated with such queries which happen on a regular basis. I wouldn’t be too surprised if this is the case with platforms other than blogger as well.

That reminds me – sometime in February the gmail blog had a post about a gmail issue where 0.02% of gmail users found their gmail empty when logged in. I was completely taken aback reading this and 0.02% is quite a bit given the large number of gmail users. I’m sure none of us can imagine something like that happen to our accounts – can clearly see how crazy it would drive us given that we depend on it so much; the moment you log out of it, you want to log back.

Now coming back to the current issue about content on blog disappearing. It is reported that this could happen when the user tries to change the url, export it to another domain and other things that I don’t completely understand. In my case, no changes were done at all. Though it was frustrating in the beginning, I’ve decided to have a copy of all the posts that I put up and will put up. After all, you don’t want to spend time and energy to do something you really like and see it vanish into thin air someday unable to retrieve it from anywhere.

For all the bloggers out there – I am prepared to deal with this if it happens again and at a larger magnitude. Are you? It’s time you are.

Data analysis – the good and the bad

Last 2 weeks in April were crazy for me with finals and term paper submissions and assignments and trying to wind up experiments. As far as research was concerned (my 2^nd rotation in an awesome lab), I was able to stick to the plan I made - did all the experiments that I had to and was left with data analysis in the last few days. Yes, the other side of things. Getting experiments to work is just the first half of the story; trying to make (any) sense of the data you get out of experiments is the other half.

It was only after I plunged into this other half, did I realize how much of data I generated that it felt close to impossible to analyse all of it before my big day – when I’d be presenting in the lab meeting. I was beginning to wonder which is the tougher one that makes you go crazy – the experiments or the data analysis. It really tires you out. Though I got through everything and even got some interesting results, I still don’t have an answer to that question (which I think is a profound one).

But I did learn a couple of things about this whole process of studying data. The most important thing being - never leave this task to the end. Never. The best way to go about it is to start getting a hang of how the data looks as and when you have some of it ready. In my case, each time I did an experiment I took a good number of movies so I could have a good number of data points but once I started analysing the movies, I realized that they were not enough. I needed so many more movies. This happens when you are studying motors in invitro assays (which was what I was studying). There were also some data sets where I felt I’d be better off with a longer movie, maybe slower/faster frame rate and such things. Its always good to know what are the things you need to work on before you do the experiment again at a later point.

Another important aspect – honesty. Since I sort of knew what kind of a trend or pattern I should see in the parameters that I was studying across several different experiments, each time I got to a point where I was able to compare these cases, my mind would try to work its way and make sure I was seeing exactly the expected trend. I found it slightly hard in the beginning to do a completely unbiased analysis. But I got around this by telling myself that what people have seen in the past need not be true at all and maybe I’d see something novel (well, I know this is not true in most cases but you get what I mean, atleast it motivated me to do a blindfold analysis). Its very important to be completely honest with yourself and be able to communicate to others how exactly you went about analysing your data. That way me giving a talk in the lab meeting was good – I realized each person has a different style of looking at his/her data and even representing it. I think that’s one of the things that has to be given a good thought – what is the one best way to represent your data that will definitely make people think and not just listen.

All said, I’m glad I learnt these small things early on. Also, just so you know my talk went very well and the rotation was extremely satisfying :)

PS: About the title - I don't think there's an ugly side to data analysis, is there?

‘Live and learn’: H.M

Ever wondered how scientists came to show that hippocampus in the brain plays an important role in the formation of memories. The best way to show this with 100% confidence is probably do some studies on a person who has his hippocampus removed, right. H.M was one such person who took the field by storm. He’s probably one of the most famous neuroscience patients and has been invaluable to the advancement of the field.

When he was about 27 years old (1953), he underwent an operation to get rid of his frequent seizures. Though the seizures reduced, the operation changed his life completely as he had a memory loss and could not form new memories as well. He couldn’t remember who he spoke to that morning or what he had for lunch that day. During that time it was widely believed that the ability to form memories and retain them was a function that was distributed all over the brain. Through several studies on H.M, Dr. Scoville and Dr. Milner could show that memory can be distinct from other cognitive abilities.

I recently got a chance to attend a seminar by Dr. Suzanne Corkin from MIT who was once a student of Dr. Milner. Corkin (and her lab) studied him for four decades until his death in 2008. I didn’t even know that a person H.M existed until my friend told me about this talk.

Corkin and her students gave several tests to H.M over all the years that they studied him and were able to learn an insurmountable amount about the brain and learning and memory. She told us about how declarative memory could be episodic (event based) or semantic (fact based). Citing her examples – recollecting your dinner time last night would be episodic, you know the capital of France being Paris as a fact but you probably don’t remember when was the first time you ever came to know of it, that’s semantic. Turned out that though H.M had no episodic memory he was still ok with semantic – he could tell things about WWII, which country the US was fighting, so on and so forth. This is just one example and several such interesting things were deduced by experimenting with H.M. After his death, MRI scans of his brain were taken and his brain has been sliced and is now at UCSD.

It was an engaging seminar and at the same time overwhelming that one person who contributed so much to the field (who probably didn’t even know how phenomenal this was for the field) is now no more. Corkin mentioned she is writing a book on H.M and said he was like a family member to her and her lab. She said he was a person with a good sense of humor and he used to say ‘you should live and learn; I’m, living and you’re learning’. When I later asked Corkin about the emotional bonding between them, she said ‘we did as much as we could but that can’t replace what he lost. We celebrated Christmas together and he thought I was his friend from high school’.

Given how closely she worked with H.M and got to know him, I think her book will be a page turner – both scientifically and otherwise. Looking forward to it.

The Essence of Shape

As kids we all learn that various cell types have different shapes and sizes. But how many times have you actually thought a little bit more about it. I think the very first time I thought of this aspect was when we were explained in undergrad what happens in sickle cell anaemia – red blood cells are crescent shaped rather than disc like and hence deliver lower oxygen levels to tissues. And after that it was only during my senior year and now in grad school that I am beginning to grasp the complexity involved in this concept called shape and how vital it is.

Cell division is a fundamental process in which cell shape plays a huge role – imagine how complex a task it actually is for the cell to calculate the location of its central plane (if the division is symmetric of course) and be able to divide into two. I got a chance to read this interesting paper published in Cell this February that came out of the Chang lab at Columbia University. They put sea urchin eggs in microfabricated chambers of different shapes with volume of each being the same as that of the egg. In ways I don’t completely understand the egg now takes up this shape of the chamber – rectangle, ellipse and triangle. They then saw the plane of division in each of these cases and observed the positioning of the nucleus which ultimately is the deciding factor for how a cell divides. They show by experiments and by a very elegant mathematical model that the microtubules ‘sense’ this cell geometry and orient the nucleus along the axis of cell division accordingly by exerting forces on it.

If that didn’t make any sense at all, how about this – a protein X in some organism Y localizes to only to membranes that are convex; all it needs is this geometric cue rather than some cell specific cues. Yes, this was shown to be the case for a spore forming protein in bacteria by Richard Losick’s group at Harvard, published in Science sometime back. They purified the protein and when incubated with different kinds of vesicles in vitro, the protein localized to the smallest vesicle, which is the most convex one.

That’s cool stuff out there.