My Blog Has Moved!

For anyone who's still showing up around these parts, I wanted to let you know that, as I said I would, I've begun blogging regularly again... Just not here. For a variety of reasons, some explained here, I've decided to start up a new blog on a completely new hosting service. So point your browsers to carloartieri.com if you're inclined to keep following my musings!

Which Doctors?

Sorry for the lack of posts lately, but I've been oscillating between busy and sick - sometimes lurking in the quantum paradox of both. Case in point: I've been quite ill for the past week, suffering from sinus pain, congestion, the sniffles, and horrible phlegmy sneezes. It didn't seem like I was going to recover on my own, so I decided to set up an appointment with my doctor.

Now I'm a bit cautious regarding my doctor. She seems like a nice elderly woman, but there's a disturbing amount of woo being peddled in her waiting room. For instance, she's an advocate of laser acupuncture, which, umm... seems like some sort of Austin Powers-style combination of technology and Traditional Chinese Medicine. (Traditional Chinese Laser Acupuncture is both anachronistic AND oxymoronic). However, she's never actually pushed any of this woo on me until now.

During my latest appointment, she diagnosed me as having an ear infection, and proceeded to prescribe an antibiotic and a decongestant. All well and good, I thought. Unfortunately, before she could write out those prescriptions and send me on my way, I foolishly decided to inquire about some pain I've been having in my wrists. I spent almost the entire summer working on a computational study, you see, and thus I probably over-worked my poor hands typing. She told me that there were drugs that could help me with this, but that she thought that we should try something that she'd recently learned about - something that could cure all¹ of my problems.

My doctor told me that she'd learned of an energy technique that would allow her to determine what combination of medication would best help me. She then called in her secretary and they both huddled over me making pseudo-mystical movements. The doctor then touched my watch and ring in turn with one hand, while the other hand was held in the air with thumb and forefinger clenched. She proceeded to mumble some words while her secretary repeatedly attempted to pry her fingers apart. After a minute or so of this, she proceeded to tell me that neither my watch, nor my ring were 'negative', and thus they were not impeding my body's healing energies. "Umm... good?" I replied.

She then proceeded in the same manner, this time touching various herbal remedies against my body while chanting various doses, and frequencies: touching one bottle to my arm followed by "Mmmmm... One tablet before meals. no Mmmmm... One tablet after meals. Aha!", for example. All the while, her secretary was prying her fingers apart over and over.

Finally, it was determined(?) that I should take one pill each of StemEnhance and StemFlo, which, according to their producer's website:

StemEnhance is the very first product on the market from the product category called "stem cell enhancers" - products that support your natural stem cell physiology. It consists of a patented natural concentrate of an edible aquatic botanical known as Aphanizomenon flos-aquae (AFA) that includes Mobilin™.

Right. But is any of this scientifically studied?

Yes. Several clinical studies have been conducted on the product, in addition to several in-vitro trials.

Ah, well good to know. Actually, my doctor gave me several photocopied pages about the stuff that claim that proof of its efficacy was published in the New England Journal of Medicine. Unfortunately I guess I'll have to sift through its entire archives to find out WHICH article demonstrates this. Oh, also my doctor gave me a trial sample of the pills as well as a card indicating that she is Executive Director of STEMTech, the company that makes both of the amazing natural products she prescribed. I'm not sure if that's relevant to this story.

Ungh, I think I need to find another doctor²...


¹Well according to the information sheet I received, I'd estimate that this thing can cure pretty much any problem you can name. Wait... Irritable Bowel Syndrome isn't on the list, but Autism is. Great, now the kooks don't have to worry about vaccines anymore.

² Unfortunately, this isn't a trivial task. It means that I have to look for another doctor who is on my insurance program who is accepting patients and is in close vicinity to my home or work. Guess I'd better get looking...

Book Club: The Structure of Scientific Revolutions...

I've always been under the impression that Thomas Khun's The Structure of Scientific Revolutions (TSSR; 1962; University of Chicago Press) was a controversial book. For those unaware, this is the book wherein the author argued that science 'progressed' through 'paradigm shifts' - that is to say that most legitimate science takes place within a given accepted paradigm (e.g., the Earth is the center of the universe), until the weight of observations leads to a crisis (e.g., astronomical observations disagree with expectations), which results in a series of alternative paradigms being proposed until one is eventually accepted (e.g., heliocentrism). The cycle then begins anew.

Using this paraphrased formulation of Kuhn's model, I don't think anyone would have a problem with it, and for the first 120 pages of a ~200 page book, neither did I. It's what happens towards the end of the book that I think many people have taken issue with, including myself.

To begin with the author has a very nebulous application of his concept of paradigms¹. Paradigms are defined at least 22 different ways within the book (I didn't count, it's discussed in the postscript), which makes it difficult to nail down what a paradigm shift actually is. A paradigm isn't strictly the current framework of our understanding of a topic (models, laws, constants, forlmulae, etc.), it also has a behavioral component. Scientists raised within a given paradigm do not switch to a new one easily - if ever - and thus a current false paradigm will accrue large numbers of ad hoc/post hoc elements to explain away all of its inconsistencies.

Kuhn essentially argues that paradigm shifts do not equal progress. Towards the end, the book falls over the edge of relativism, where it becomes clear that since there will inevitably be a paradigm shift again, there's no way to know that this paradigm will be better than the last. The only way that TSSR is able to get away with such an argument is by very cursorily panning Popper's doctrine of falsifiability - something that I must admit did not sit right with me. I need to elaborate on this point in order to make this clear:

According to Popper, no scientific theory is ever 'proven', rather the strength of a theory relies on its ability to resist falsification. Every time a prediction made by the theory is verified, we become a bit more confident in its validity - though it could ultimately turn out to be false in the end. Thus the relative 'value' of a scientific theory lies in its ability to make predictions. A theory that makes no predictions is unfalsifiable, and thus useless. Theories that make more predictions, if those are then verified, are more valuable than those that make fewer predictions, because they necessarily explain more about the nature of reality.

Now, there's a cagey aspect to Popper's doctrine that has to do with what happens to a scientific theory when its predictions are falsified. The theory is supposed to be rejected, but in practice it's often not necessary to reject the entire theory, but rather re-evaluate the components that fail to agree with observation. This is where Kuhn dismisses Popper's doctrine because, according to him, one can always propose ad hoc adjustments to a theory until it falls in line with observation. Thus paradigms cannot truly be evaluated on their ability to make predictions.

If we could interpret Kuhn's paradigms in a Popperian framework, we could argue that the progress of science generally leads to theories that explain more of the universe and thus make more predictions. Thus, any new paradigm would have many more observations to account for, and thus the likelihood of new major paradigm shifts decreases with time, which can be interpreted as 'progress'. Kuhn however, argues (if I understand correctly) that because any theory can be made to fit observations with sufficient ad and post hoc tweaking, we cannot really be sure that there's actually any progress being made.

It's actually quite difficult to read a book with this sort of defeatist(?), relativistic philosophy because it seems to ignore the practical observation that what we think we know about the universe in modern times actually allows us to do more things than we could in the past. It's sometimes frustrating to see Kuhn pick particular examples to bolster his points. Lack of progress, for instance is illustrated by explaining that Pliny's epicycles and Copernicus' heliocentrism made the same predictions. Is this really the norm?

Overall, I think that Kuhn's concept (vague as it is) of paradigms is incredibly useful in understanding the history of science. However, I think that he goes quite far in interpreting the consequences of his paradigms when it comes to the progress of science. Taken at face value, we're told a lot of odd things such as people operating within a given paradigm cannot communicate with those operating within another, that new paradigms aren't necessarily based on evidence, or that progress is illusory, etc. TSSR is an immensely interesting book, but it veers into very controversial lines of reasoning when it reaches its more 'psychological' claims.

I don't know if anyone's doing this, but I think it would be very useful to get the perspective of scientists who lived through paradigm changes, in order to see if some of Kuhn's behavioral hypotheses are valid. Thinking about past paradigm shifts is interesting, but understanding more current ones, if they're occurring, may be more informative.


¹This is something that Kuhn himself admits in the postscript to the book, published 7 years after the 1st edition. He doesn't think it changes the veracity of his model, however.

Bikin' Hardcore!

I've discovered a new love: that of cycling. I'd actually been planning to buy a bike for the past six years or so, and now that I've gone out and done it, I'm chiding myself for not having 'pulled the trigger' sooner. Biking is awesome. The reason for my reluctance was, of course, financial: Biking for 'realz' requires the initial investment in a bike, plus several necessary accessories that quickly add up. It's more than worth it.

I now bike 11.5 km (~7.5 mi) to work every day using a local commuter trail. Amazingly, it takes me about 40 mins, which is often faster than taking public transit (and is always faster than taking public transit on weekends due to all of the track maintenance work). Also, biking > 20 km per day has really gone a long way to assisting 'Operation Iron-Carlo', or my attempt to be in the best shape I've ever been in by the time I'm 30. I'm actually making better-than-expected progress on this front, so I have no doubt that I will succeed.

To that end, today a friend and I went on an epic almost 50K bike ride all the way from Rockville MD to Capitol Hill in DC.

Here's a rough sketch of the route we took. There are more efficient routes to get from Rockville to DC, but they're not as nice and scenic.

The commuter trails for this trip are beautiful and a great ride. All told, it took about 3.5 hours - mostly because we weren't speeding along at breakneck pace. Instead we took it easy, and chatted about science-fiction novels most of the way. Who would've thought that you could mix geekyness and exercise? I'm sure that I'll have the chance to check out many more of the excellent bike trails they've got in this area... As long as I don't get anymore flat tires.

Feeling the Burn...

This was a pretty rough summer for me on many fronts: some personal, some professional. The latter had a lot to do with my effort to juggle a fairly time-consuming research project, while trying to manage an ever-shifting 'side-project' that lacked a clear objective and continued to metamorphose as the weeks went by. Sadly, I ended up writing 25 pages of a manuscript that will not see the light of publication in its current form¹.

I worked really hard on that side-project, so much so that I essentially abandoned my 'main' research for ~2 months. That's really not a lot of wasted time in the grand scheme of things. I suppose I've wasted more time in the past, but that was 4 years ago now and I've become quite used to being extremely organized about effort.

This brings us to the title of my post - I feel like I experienced a minor burn-out. I can tell that my general love of science, which is to say the amount of time I spend actively immersing myself in scientific culture outside of the work I'm required to do, dropped a bit during this season. I stopped reading science books, stopped following science blogs, stopped talking about science outside the lab, etc. As I'm sure I've said many times on the blog, this isn't very conducive to being in the sciences: research is a difficult job to pursue if you're not regularly thinking about possible ways to expand your work. It's also a heck of a lot of work to not enjoy, if you catch my drift.

I can feel some of my enthusiasm returning though. This is partially seasonal: Autumn is by far my favorite time of the year, and I'm looking forward to such niceties as colorful leaves, pumpkin pies, and not sweating to death every single day (the ice-water that flows through my Canadian veins isn't built for the heat here). However, the major part of my changing attitude is probably getting back to my main project. This is what I came here to do, and what I what I wrote-up for my funding proposal: It's what I actually wanted to work on. Oh, it's also helping that I'm reading science books again - Thomas Kuhn's The Structure of Scientific Revolutions will be a book club post soon!

Hopefully I'll come around soon. Hey, if everything becomes rosy again and I get a few hours of free time, maybe I'll continue blogging about that crazy alien book again. Who knows?


¹All is not lost, however, as I learned a lot of useful information/techniques in preparing said manuscript, and large sections of it will be cannibalized for a forthcoming study.

The Bleeding Edge...

Prior to my postdoc, I've never done research using 'bleeding edge' technology, which the Wikipedia defined as:

Bleeding edge technology refers to technology that is so new that the user is required to risk unreliability, and possibly greater expense, in order to use it.

While every project requires some degree of methods development, pretty much everything I've done before used well established protocols and procedures. This is no longer the case.

One of the techniques of which I've been making extensive use is RNA-seq, or short-read sequencing of RNA. The gist of this technique is that you extract RNA from a cell fragment it into small pieces and then convert it to DNA. You then generate millions of short reads (~75-100 bp nowadays) off of this DNA using flow-cell based sequencers (see the link I provided to RNA-seq for details) and map (align) these reads to the genome of the organism with which you're working. The read 'density' (or number of reads mapping to any given region of the genome) is correlated with abundance of the RNA in the original pool, and thus you get a digital read out of the abundance of all of the transcripts in the cell. In principle this technology has many benefits over traditional methods of transcriptome profiling, such as allowing isoform detection, and is widely expected to eventually replace microarrays.

While this is all fine and dandy, the more I use RNA-seq, the more concerned I become about it. A lot of people have jumped on this bandwagon and there hasn't been a lot of work done to investigate potential biases and caveats associated with the instruments required to generate these data. Here's a couple of examples: The relationship between number of reads mapping to a given gene/exon and its expression level only holds if reads are randomly distributed with respect to what's being sequenced - there shouldn't be sequences that are preferentially sequenced or underrepresented. Unfortunately, this does seem to be the case - either during fragmentation or sequencing library preparation, biases are introduced making certain sequences more or less common than would be expected by chance. It appears that this does not have a large effect on expression estimates of highly expressed genes, but genes with low expression, or short coding sequences show more variability than they should.

A much more significant problem is that many papers seem to have assumed that RNA-seq is somehow beyond the need to 'normalize' data (that is control for systematic biases). It isn't (see Srivastava and Chen 2010, for example). A slew of recent papers have shown that there are biases associated with short read data, especially when the cells/tissues/organisms being compared have radically different expression profiles. Normalization is required, but rarely applied. Oh, and I haven't even gotten into the serious problem of lack of replicates in many of these studies.

These are just some of the issues RNA-seq users face. Now, you may be asking yourself why I'm telling you this; I assure you it's not a rant. My bigger point is this: Our lab has been spending an inordinate amount of time investigating the very real biases that these issues may be creating in our data. However, at the same time, other groups are using the tools available, limited as some may be, and publishing work under the assumption that such biases are not 'show stoppers'. Whether they are or not is difficult to say at this point, but we're pretty much at the mercy of labs with a much better grasp of statistics to come up with solutions as to how to properly normalize and handle these data.

To what extent is it reasonable to use the tools available and assume that they're 'good enough'? Science is always progressing/refining its products, so is it okay to use particular methods, even if you suspect that they're producing uncontrolled biases? I think that the vast majority of what's being done in the field is quality (as far as we know what quality is) but the use of such new technology is somewhat worrisome.

Thoughts?

Paying the Piper...

It's an interesting fact that when you're young, you really tend to think about the consequences of all of the loans you end up taking out in order to pay for post-secondary education (at least if you're growing up in North America, that is). Once the student loans get up into the 5 digits, what's another ten grand here or there? This is further compounded because the loans sit completely in the back of your mind for years and years, providing much needed cash seemingly without consequence.

Unfortunately school ends, and everyone must eventually 'pay the piper'.

In the folk legend, the Pied Piper of Hamelin takes care of the city's rat problem by playing his magic flute and causing the vermin to jump into the nearby river. When the city refuses to pay him for his deed, he retaliates by using his magic flute to ensorcel the city's children and march them out of town, after which they are never seen again. Thus the origin of the idiom, 'Time to pay the Piper'. Image cred.

All told, I'm roughly $25,000 in debt - not that bad if you consider that I spent 10 years in University. Now that I'm a postdoc, I've begun having to pay it back - as expected, I should add. This is the point where one realizes that say, $1,000 is actually a lot of money. Put into more concrete terms, if I wanted to pay back $1000 in one year, that would be ~$83.34 per month, a not insubstantial amount of dough, when one considers that that's essentially an extra cell phone bill.

I know what you're thinking: This is all obvious. Unfortunately, I don't really think that it is, at least to many people. Paying ~$300/month for 5 years is fairly typical of someone coming out of university in North America. That's a pretty big chunk of change when you're living on a postdoc's salary. Many Europeans, for example, come out of post-secondary education without any tuition-based debt, which is pretty amazing.

As scientists, not only do we experience arrested development by spending a decade (or more in school), but we're further cramped by living in relative squalor for the first few years in the work-force (assuming that most people consider a postdoc being actually in the work-force...)! Oh well, them's the breaks, I guess. Someday I'll have the dough to do all of those wonderful things I've always wanted to do. Bah, who am I kidding?!?