The Futile Cycle

I enjoy cooking; I think in general, a lot of people who like chemistry and biology also really like cooking. Maybe it’s because they like working with their hands.

Anyway, I saw this post, where they suggest heavily salting a steak before grilling in order to make it taste better. Sounds like a good idea; maybe I’ll try it next time.

Then they have a really weird argument about why the salting works. They claim that salt first sucks some water out of the steak (ok, no argument there). Then, the salt supposedly dissolves a bit and moves back into the steak (which they mistakenly call “osmosis”; really, the first step is osmosis). Ok, not beyond the stretch of imagination; I’m not an expert in surface and fluid chemistry. This higher ionic concentration in the steak then denatures (they say “relaxes”) the proteins in the steak, and “relaxed” proteins are more tender and juicy. (Of course, denaturing proteins is not really the same as relaxing them, for the same reason that stretching a Slinky toy out straight doesn’t relax the toy.)

Sorry, not buying it. Denaturing proteins doesn’t make things tender and juicy; in fact, it tends to do the opposite. Consider egg white; it’s pretty much pure protein. It’s goopy. Cooking it makes the proteins denatured, which unravels them from their mostly globular state, making little networks out of them. Hence, uncooked egg white = liquid, cooked egg white = solid. Cooking proteins and denaturing them tends to make them form more fibers and solidify meat. Hence, a well-done steak is stiffer and harder than a rare steak, because more of the protein is denatured.

So what makes steak nice and juicy? Well, the concept might seem gross, but it’s your saliva. More saliva = more juicy. Salty things are juicier because they make you salivate more. Ever try eating an unsalted saltine cracker without water? Compare that to a salted saltine cracker. The latter is much easier to get down without getting thirsty. So your saliva is probably the biggest component of the “juicy” or “dry” taste.

The salting of the meat doesn’t make it juicy because it denatures the protein (or make it “relaxed”). It makes the meat taste better because the meat becomes saltier, and salty tastes good. It’s the same reason chargrilling steak tends to make it taste juicier, because for a lot of people, chargrilled things make them salivate more. And rare meat has more fat (and I presume more salty blood and fluids) left in the steak, which tends to make people salivate, too.

This knowledge becomes instantly useful in a school cafeteria. Every once in a while, my school would serve “pepper steak”, which was usually dry as a bone, and it felt like I was eating leather. I always salted both sides of the steak liberally, and though it’s no substitute for a properly seasoned and grilled steak, it did make the meat substantially more palatable.

Yesterday was the first day of orientation for the department, and today, I leave for a departmental retreat, wherein the first-year students get bashed over the head with tons of talks, plenty of poster sessions, free food, drinks, and lots of interaction with the professors, post-docs, and older graduate students.

During the retreat, I’ll also be thinking about this post from “GTD in Academia”, especially the comment about developing a toolkit. (It reminds me very much of the part of Surely You’re Joking, Mr. Feynman, where Feynman talks about his mathematical toolbox and differentiation under the integral sign.) The post focuses on ecology, but of course the advice is more general than that.

Develop a toolkit. You’re going to know how to design experiments and analyze data and think broadly and synthetically about ecology. But you should also develop a toolkit to distinguish yourself from all of the other ecologists who can do those things. Your toolkit might include modeling or null model analyses or genetic techniques or specialized statistics. Just make sure you have one, and make sure everyone knows what it is. MK–make yourself unique and indispensable part of the group.

So I keep wondering, what kind of toolbox can I develop? Even as I try to find a topic that I’m interested in during the retreat, and lab rotation choices, I’ll be thinking hard about that.

All of the professors that I’ve admired have their own little niche that they create with their unique expertise, their esoteric collection of abilities. Howard Berg, for example, is really good at machine-work, and so he was able to hand-make the parts needed for a 3D E. coli chemotaxis tracking microscope, which led to his great theoretical contributions to that field. David Evans is spectacularly good at dissecting molecules down to their basic, synthetically manageable parts, to make clever insights about reaction mechanisms via molecular orbital theory, and visualize asymmetric induction at a very sophisticated level in his head, allowing him to manage the beautiful, almost pedagogic syntheses of really complicated molecules. Martin Nowak is really good at paring away the complexity of a problem to get at the underlying mathematical structure and model, in order to gain very deep, and yet strangely simple and beautiful insight. They’re not expertises in the sense that they’re one-trick ponies; it’s more that they have some sort of edge on the competition that just allows them to break through and do the work better and faster.

I need to find my own toolbox to really succeed and do well. But what? I’m decent at math, programming, physics, chemistry, and biology, but not a big deal on any of it. No subject really scares me, though; I know I can learn more of anything if need be, so I have some help there. But what’ll be my edge? Finding that will be my goal this year. Jack-of-all-trades, master-of-none is not the way to succeed in grad school, I think. Still, until I find that straight-flush, lots of jacks aren’t that bad either…

“Most species show ubiquitous heritable variation in [gene] expression, whereas the malarial parasite Plasmodium falciparum shows remarkably little.” — MV Rockman and L. Krulgyak (2006), Nat Rev Genet, 7, 862-72

I think bugs are simultaneously hideous, disgusting, but incredibly cool. Just read about this symbiotic-ish wasp virus.

For some reason, many people who’ve bought iPhones early on are complaining now that Apple issued a $200 price cut. These people may sound like whiners, but really, it’s because what they’re buying is not just a phone they really like, but the prestige of being able to shell out $600 for a phone. It’s the brand, the exclusivity, the signaling, that they’re buying. Sure, the iPhone is more functional and much better made than most other phones, but several hundred dollars worth? It’s hard to say; individual preferences and weights strongly come into play there. For most people, I’d say it isn’t worth it, in the same way that the “hand-made quality” and “attention to detail” in an Aston Martin just isn’t worth the cost to most people.

So, that’s why consumers are complaining. The theory doesn’t make them any less whiney and pathetic, but it does explain why there’s so much backlash, and Apple does need to realize that it’s not just competing as a technology company, but as a fashion company, one in which price plays a large role in social prestige and branding.

For the first week of grad school, I have a bit of free time, not having yet joined a lab, so in between walking around and talking to people, I’ve been filling in various gaps in my education. For example, I never really learned statistics — not formally, anyway, my knowledge of genetics and genomics is purely incidental, and my study of computer science and artificial intelligence essentially froze after learning about perceptrons and Hopfield networks in high school.

So, I’ve been reading. A lot. I’ve finally learned the notation and vocab that geneticists commonly use, so that I don’t have to keep googling words as I read papers. It still takes me a half-second to recall stuff (and I still find it strange that the names of many genes are of the mutant phenotype), but it’s definitely sped up my reading of the literature (or at least, the abstract and figure captions).

Statistics is really difficult for me to retain. The problem is, I really like concepts more than details, and I’ve always enjoyed probability theory more than the nitty gritty details of statistics. Unfortunately, everything in science at some point or another needs it, so I learn it begrudgingly, though sometimes learning the details feels like trying to grab a handful of loose sand. Z-test? One-tailed, two-tailed?

Computational biology, on the other hand, I can retain a bit more, perhaps because I’m concentrating on theory and concepts; I definitely can’t remember all the nuances of the various implementations and side-add-ons to the original theory. It’s hard, though, to find good descriptions of basic concepts and theory on the web, rather than implementation. (For BLAST, I eventually resorted to a book; I love O’Reilly, I really do). I’m learning about Bayesian networks from a tutorial I found on “Computational Biology News”, while with singular value decomposition and principal value analysis, I’m learning from a hodge-podge of different sources to try and connect everything together.

One thing I always love is hearing stories about how a field progresses; there’s of course the fascination with the early 20th century breakthroughs in physics, and the astounding mid-century breakthroughs in molecular biology, but such stories happen all the time (if not as spectacularly), and I enjoy listening to them.

I found an interesting article in Current Biology which was essentially a story about the discovery of a new class of photoreceptor in the mammalian eye (i.e. not a rod or a cone). It’s not really my field, and obviously the authors cleaned up the story to make the whole investigation seem much more linear and rational than it probably was, but regardless, the recounting of the discovery of these new opsin proteins was a pleasure to read. Key experiments, the conclusions drawn, all the different sub-fields and methods, and the paradigm shifting story that wove all those things together made the article really quite fascinating.

I am now moved in to my new room in graduate school. Classes have yet to start, but the weather is nice, the rooms are spacious, and the campus is very beautiful. It’s a bit weird to settle into a new campus this fall instead of returning to the old undergraduate campus, but I’m very excited about what’s to come. I’m also nervous that I’ve gotten soft during the summer, so I’m currently reviewing a bit of genetics, but in the meantime, I stumbled upon this interesting article on treating HIV by raising its mutation rate.

This is an interesting idea, since one would normally think that raising mutation rates on an organism would just increase the opportunities for it to become more virulent, more resistant, etc. But HIV is a pretty high-mutation rate virus already (any specific one letter mutation will arise more than 20,000 times per day); by the estimate of Martin Nowak, it’s mutation rate is currently the highest possible rate that allows for efficient adaptation and natural selection, in that if the mutation rate were lower, the virus would not adapt as quickly to adverse conditions (e.g. drugs), and if the mutation rate were higher, the virus would mutate so much that it would find it difficult to maintain any beneficial mutations. It’s at the cusp, the so-called “error threshold” (which is roughly the reciprocal of the genome length). So, by raising the mutation rate of HIV even higher, one could tip HIV over the error threshold and make the HIV quasi-species unstable enough to hamper its spread.

I only wonder, however, what kind of cancerous havoc it might raise in the human body. The drug doesn’t look flat enough to incorporate into anything but the most error-prone of DNA polymerases (e.g. HIV reverse transcriptase), but still, clinical study might show high rates of skin cancer and congenital defects for fetuses. The lack of a double bond on the major groove side of the nucleoside should prevent too many cycloadducts from forming with UV light, but then again, I’m no expert in heterocycle photochemistry, seeing as almost all the heterocycle-forming reactions I’ve ever tried to do ended with awful black tar on the bottom of my tiny flask.