Field of Science Combined Feed

When is the logically impossible possible?

GamesWithWords — Thu, 02 Sep 2010 17:12:00 -0700

Child's Play has posted the latest in a series of provoking posts on language learning. There's much to recommend the post, and it's one of the better defenses of statistical approaches to language learning around on the Net. It would benefit from some corrections, though, and into the gap I humbly step...

The post sets up a classic dichotomy:

Does language “emerge” full-blown in children, guided by a hierarchy of inbuilt grammatical rules for sentence formation and comprehension? Or is language better described as a learned system of conventions — one that is grounded in statistical regularities that give the appearance of a rule-like architecture, but which belie a far more nuanced and intricate structure?

It's probably obvious from the wording which one they favor. It's also less obviously a false dichotomy. There probably was a very strong version of Nativism that at one point looked like their description of Option #1, but very little Nativist theory I've read from the last few decades looks anything like that. Syntactic Bootstrapping and Syntactic Bootstrapping are both much more nuanced (and interesting) theories.

Some Cheek!

Here's where the post gets cheeky:

For over half a century now, many scientists have believed that the second of these possibilities is a non starter. Why? No one’s quite sure — but it might be because Chomsky told them it was impossible.

Wow? You mean nobody really thought it through? That seems to be what Child's Play thinks, but it's a misrepresentation of history. There are a lot of very good reasons to favor Nativist positions (that is, ones with a great deal of built-in structure). As Child's Play discuss -- to their credit -- any language admits an infinite number of grammatical sentences, so any finite grammar will fail (they treat this as a straw-man argument, but I think historically that was once a serious theory). There are a number of other deep learning problems that face Empiricist theories (Pinker has an excellent paper on the subject from around 1980). There are deep regularities across languages -- such as linking rules -- that are crazy coincidences or reflect innate structure.

The big one, from my standpoint, is that any reasonable theory of language is going to have to have, in the adult state, a great deal of structure. That is, one wants to know why "John threw the ball AT Sally" means something different from "John threw the ball TO Sally." Or why "John gave Mary the book" and "John gave the book to Mary" mean subtly different things (if you don't see that, try substituting "the border" with "Mary"). A great deal of meaning is tied up in structure, and representing structure as statistical co-occurrences doesn't obviously do the job.

Unlike Child's Play, I'm not going to discount any possibility of the opposing theories to get the job done (though I'm pretty sure they can't). I'm simply pointing out that Nativism didn't emerge from a sustained period of collective mental alienation.

Logically Inconsistent

Here we get to the real impetus for this response, which is this extremely odd section towards the end:

We only get to this absurdist conclusion because Miller & Chomsky’s argument mistakes philosophical logic for science (which is, of course, exactly what intelligent design does). So what’s the difference between philosophical logic and science? Here’s the answer, in Einstein’s words, “No amount of experimentation can ever prove me right; a single experiment can prove me wrong.”

In context, this means something like "Just because our theories have been shown to be logically impossible doesn't mean they are impossible." I've seen similar arguments before, and all I can say each time is:

Huh?

That is, they clearly understand logic quite differently from me. If something is logically impossible, it is impossible. 2 + 2 = 100 is logically impossible, and no amount of experimenting is going to prove otherwise. The only way a logical proof can be wrong is if (a) your assumptions were wrong, or (b) your reasoning was faulty. For instance, the above math problem is actually correct if the answer is written in base 2.

In general, one usually runs across this type of argument when there is a logical argument against a researcher's pet theory, and said researcher can't find a flaw with the argument. They simply say, "I'm taking a logic holiday." I'd understand saying, "I'm not sure what the flaw in this argument is, though I'm pretty sure there is one." It wouldn't be convincing (or worth publishing), but I can see that. Simply saying, "I've decided not to believe in logic because I don't like what it's telling me" is quite another thing.

Science Online London

Akshat Rathi — Thu, 02 Sep 2010 17:56:00 -0700

I will be attending Science Online London or #solo10 on September 3-4 at the British Library. The conference theme is How is the web changing science?

This conference promises to be very different from the Science Communication Conference that happened in May. In the words of an attendee of Science Online 2008 & 2009, "It is a conference which is not just about science communicators."

As a matter of fact, the conference has already begun with many participants attending two simultaneous events that took place tonight one was the tour of diamond light source and the other was a pub crawl in London (hard choice!).

I attended the diamond light source tour for two reasons, one :I do small organic molecule crystallography in my department and some of our crystals do end up going to diamond and two: it is located much closer to Oxford than London. Much of what was talked about at a short presentation before the tour can be found here and then followed a tour of the site. As the synchrotron was off, we could go and look at it from the inside and I really enjoyed the tour.

As for the conference, what I am looking forward to?

Understanding the future of science journalism
How to connect the various scientific resources
The state of science blogging
How to run a successful social media campaign for science
How to get scientists to use Web 2.0 tools
#fringefriv10

And more than that meeting all the wonderful people coming to the conference, especially the mini-Lindau reunion. :)

The difference between being religous and being a believer

trees@hbase.com (Tom Rees) — Thu, 02 Sep 2010 14:51:00 -0700

One of the big news stories from last year was the revelation that Americans are leaving their churches and religious institutions in droves. They are becoming "unaffiliated", although there was a lot of debate over what that meant. Are Americans losing religion, or is it simply that they are disillusioned with what they're being offered?

A new analysis, using data collected over the last three decades by the General Social Survey, sheds some light on this - and also tells us more about just who is religious in the USA these days. Some of the answers are quite surprising.

First a little bit about how they framed the questions on religion in the General Social Survey - it's not straightforward. First, they asked "what is your religious preference". Those who said "none" were counted as unaffiliated and weren't asked any further questions. Those who gave a religious preference were then asked how often they attended religious services and how strong was their faith.

So the data on strength of faith and religious attendance relate only to the dwindling number of people who are affiliated. That's important to remember.

The new analysis (Kevin Flannelly and colleagues from the Spears Research Institute, New York) confirmed that religious affiliation has dropped off over the years of the survey (since 1972). Now, you might think that this happens because those who are lukewarm in their religion have dropped out. If that were so, then the average 'religious strength' of those left in would go up.

In fact, that hasn't happen. Even those still affiliated to a religious faith go to services less often than they used to. And people still in religion are no more fervent than the religious of 30 years ago.

But there are some interesting differences between the affiliated and the non affiliated. For example, the unaffiliated are, on average, better educated than the affiliated. Yet, among the affiliated, the better-educated actually have stronger faith and go to Church more often.

Perhaps that's because those educated people who remain in religion do so as an active choice.

It works the opposite way around for income. After adjusting for all the other factors, richer people are more likely to be affiliated. However, among the affiliated, wealth means weaker faith.

The last anomaly is children. Previous research suggests that religious people tend to have more children than the non-religious. And, indeed, this new research shows that the unaffiliated have fewer children than the affiliated. But, among the affiliated, those with stronger religious faith actually have fewer children those whose faith is weaker.

Now, the effect is tiny. However, it does suggest something interesting about the connection between religion and fertility. It suggests that families join (or remain in) a religion for the religious congregations - a social structure in which to raise their children - rather any particular religious zeal.

It's the classic demonstration of the difference between being religious and being believer.

Flannelly KJ, Galek K, Kytle J, & Silton NR (2010). Religion in America--1972-2006: religious affiliation, attendance, and strength of faith. Psychological reports, 106 (3), 875-90 PMID: 20712176

This article by Tom Rees was first published on Epiphenom. It is licensed under Creative Commons.

Stimulating quasi-erotic excitement through organic structure determination

noreply@blogger.com (Wavefunction) — Thu, 02 Sep 2010 10:57:00 -0700

Thanks to the graces of the intertubes I came across this rare and fascinating video of R B Woodward put up by some kind soul a couple of months ago. The novelty of the quintessential Bostonian accent, the cigarette and glass of scotch adorning the lectern and the man in blue are only eclipsed by his achievements and what he has to say. He especially saves the coup de grace for the end.

Woodward essentially sheds light on the remarkable developments in organic chemistry until then by providing contrasting examples from his own research. He emphasizes how times had changed between his own work and the state of the art in 1979. One can make similar comparisons right now. Woodward basically attributes the astonishing progress in organic chemistry in the last forty years to two factors- an intense infusion of theoretical concepts in their most general form (MO theory, quantum chemistry etc.), and the path-breaking developments in physical methods, including IR, UV and NMR spectroscopy and x-ray crystallography. He then provides famous examples from his own work to starkly emphasize the contrast.

The first example is from his synthesis of quinine. In this synthesis, one of the steps involved the elimination of a quaternary ammonium ion to form a double bond. The question was whether the double bond formed was a vinyl double bond or an ethylidene double bond; it was the vinyl that was desired. Nowadays, and even in 1979, a graduate student could settle this question in literally a matter of minutes, but at that point (circa 1945), Harvard did not even have the experimental facilities necessary to chemically investigate this fact. Woodward had to send the sample to the famous chemist Max Tischler at Merck. Tischler got back saying it was an ethylidene. This threw the chemists into a state of despondency for a few days, until Tischler called back to inform them that Merck had made a mistake and it was in fact the vinyl double bond. The tense drama during this situation seems almost comical in the light of modern structure determination methods.

The second example concerned Woodward’s astonishing decade-long synthesis of Vitamin B12. He expressed wonder how an NMR spectrometer had been able to obtain the natural abundance C13 spectrum of 1 mg of the synthetic finished product using 995,000 transient scans. This incredulity would sound almost laughable today. Capillary NMR and 1 GHZ machines have pushed the science and art of structure determination to limits, and doing a million scans on 1 mg of material is almost old hat.

The third example was a nice little anecdote. Woodward had a wager with Linus Pauling in the 1950s whether he could chemically determine the structure of the antibiotic terramycin faster than Pauling could do it with x-ray crystallography. Woodward won the wager, but also admitted that he would probably lose it today because x-ray crystallography had gotten so powerful. Today x-ray crystallography is already at the top of its game, and who knows what breakthroughs in structure determination would be possible with AFM and STM.

The last example cracked everyone up. Woodward talked about the structure determination of cantharidin, the active principle of the Spanish fly. Chemists had isolated up to 500 grams of cantharidin to find out its structure. “Just think of it, 500 grams of cantharidin”, says Woodward. “There are many people who would think it’s an absolute tragedy. Realize that that would be enough to keep the entire population of Spain in a state of quasi-erotic excitement for a period of a full year!”

What would be Woodward’s reaction if he were to suddenly materialize today in a poof of chemical pixie dust and survey the synthesis landscape? My humble guess is that he would not be too impressed. He would undoubtedly be excited by the development of the Sharpless and Grubbs methods and the great success of the palladium-catalyzed reactions (not to mention the general development of organometallic chemistry, in the founding of which he himself played a role). But beyond that, I doubt if he would notice any fundamental change in the science of organic synthesis compared to what he witnessed and orchestrated during his own lifetime. Sure, things have become more efficient, streamlined and automated, but those details, as impressive as they are, are really operational details.

My personal guess is that Woodward would be much more impressed by the application of organic synthesis to biology and materials science. But as for the science itself, it probably still stands very close to where Woodward left it thirty years ago, and the whiz-kid from Quincy would have little trouble bringing himself up to speed on it in no time at all.

Virginia's war on science and academic freedom

noreply@blogger.com (Steven Salzberg) — Thu, 02 Sep 2010 06:57:00 -0700

The attorney general of Virginia, Ken Cuccinelli, is waging a war on science. Earlier this week, a federal judge dismissed Cuccinelli's lawsuit against the University of Virginia, but Cuccinelli has already announced that he will appeal the decision. This battle threatens not just climate researchers, but any scientist working in the state of Virginia.

Cuccinelli is a disturbingly right-wing politician whose primary actions since taking office have all been designed, seemingly, for his own political gain. He doesn't seem to mind wasting the tax dollars of Virginia's citizens as long as he can get his own name in the headlines.

His current battle is against global warming. Back in May, he announced with great fanfare that he was suing the University of Virginia over the work of climate scientist Michael Mann, a professor at Pennsylvania State University. It appears that Mr. Cucinelli disagrees with Prof. Mann over his findings about global warming. Prof. Mann is one of the world's leading experts on global warming, and he co-authored the study that produced the "hockey stick graph" showing a dramatic increase in temperature in recent decades:

Source: 2001 IPCC Third Assessment Report

The conclusions that the Earth is warming up, and that humans are one of the main causes, are no longer controversial within the scientific community, especially after the UN's Intergovernmental Panel on Climate Change (the IPCC) issued its report a few years ago. Nonetheless, many global warming denialists, including Mr. Cucinelli, continue to dispute them.

But Cucinelli isn't just a global warming denialist. He's also the attorney general of Virginia, which gives him quite a bit of power within that state. He's not a scientist, but that didn't stop him from suing the University of Virginia. His legal "trick" - what allowed him to use his power to go after Prof. Mann - hinges on the fact that Prof. Mann formerly was a professor at UVA, and while working there, he received a small grant from the state to support his work. (Never mind that the vast majority of his funding came from the federal government.) This was enough for Cucinelli to sue UVA, claiming that Prof. Mann had committed fraud by misusing state funds.

Cucinelli demanded that the University release all documents related to Prof. Mann's work, including all emails, laboratory notes, and any other correspondence since 1999. (This was a classic "fishing expedition: he didn't say what he was looking for.) To its credit, UVA refused, citing academic freedom, and challenged Cucinelli in court. The judge who dismissed the case pointed out that Cucinelli's suit was so vague that it didn't even specify how it was that Prof. Mann committed fraud. Apparently Cucinelli was unable to come up with a single concrete example of fraud.

Academic freedom is often cited in defense of questionable behaviors, but this case goes to the very heart of what academic freedom is all about. University professors - scientists, economists, historians, all of us - should be free to pursue the evidence wherever it takes us, and to write about our findings without fear of retribution. Even if his lawsuit fails on appeal, Cucinelli's lawsuit threatens to cast a chill over research in Virginia. Will scientists at UVA or other state universities, perhaps concerned about lawsuits, word their findings more carefully in the future? Will they simply avoid research on controversial topics, even if those topics are important to society?

The Virginia attorney general's groundless lawsuit, based on his purely political views and ambitions, is clearly intended to intimidate academic scientists at Virginia universities. Prof. Mann himself called the case "criminal harrassment." This kind of political threat is reminiscent of the oppressive regimes of the Soviet Union, whose scientists only published findings that met with the approval of their political masters. Political threats are a recipe for bad science.

UVA is a great university, but I'm glad I don't work there right now. If I did, I'd probably be looking to move.

NGC 4666

Edward — Wed, 01 Sep 2010 09:21:00 -0700

Visible light image of the starburst galaxy NGC 4666 (center) and neighbouring galaxy NGC 4668 (lower left) from the ESO's La Silla Observatory in Chile.
Credit: ESO/J. Dietrich

Getting OMPs to the membrane - SGM series

Lab Rat — Tue, 31 Aug 2010 10:30:00 -0700

This is the first post of my SGM conference series: I'm going to try and write about seven topics from the Society for General Microbiology September conference over the course of two weeks. The first topic I'm looking at is Protein Folding and Misfolding which consisted of thirteen presentations covering various aspects of protein folding in bacteria, fungi and yeast. As a quick background: when proteins are synthesized they are constructed as long chains of amino-acids which then need to fold up into the correct shape.

This may not sound terribly interesting at first, but it proves problematic for proteins that are in awkward places, for example in the outer membrane of Gram negative bacteria. These outer membrane proteins (OMPs) not only have to fold up correctly inside the membrane but they have to actually get to the outer membrane In Gram negative bacteria, this means first getting through the inner membrane, then across the peptidoglycan layer between the membranes, and finally half way through the outer membrane in order to coil up correctly inside it.

Gram negative cell membrane

The type of proteins found inside the outer membrane are usually B-barrel proteins, so called because they contain lots of protein folds known as a B-sheets, which can wrap up to form a channel shape as shown in the example on the right. Each blue arrow is a single B-sheet and these fold specifically to form pore-like structures which in the case of porins make a little hole through the membrane.

Transport of B-barrel OMPs accross the inner membrane is achieved by synthesising them with a signal sequence attached to one end. This signal sequence is recognised by proteins on the inner membrane and ATP energy is used to pump the proteins accross the inner membrane and into the periplasm (the space between the two membranes). Once in the periplasm they bind to little chaperone proteins which carry them safely to the complex responsible for folding them correctly into the outer membrane, the rather awesomely named BAM complex.As an aside the chaperones do have to get the OMPs there fairly promptly as there are proteases that float around in the periplasmic space and degrade any proteins that don't get incorporated into the outer membrane quick enough.

One of the key proteins in the BAM complex is BamA as knocking it out results in a lot of unfolded OMPs in the periplasm (and probably a field day for the proteases). BamA consists of two major components, a B-barrel domain which anchors it into the outer membrane, and five "polypeptide transport-associated" domains, shortened to POTRA by someone who didn't like three-lettered acronyms. The POTRA domains do what they say, they are associated with the transport of proteins (polypeptides).

It's still a little uncertain quite how the BAM complex works but a couple of the presentations on the topic were convering it, including work done on changing the genes between different bacterial species. All Gram-negative bacteria have a BamA gene, however taking the BamA gene from one bacteria and putting it into another does not end happily unless it's done between two very close species. Closer research with chimeric proteins (i.e proteins that are half from one bacteria and half from another) shows that this only applies to the POTRA domains. The anchoring B-barrel can be switched between several different species, but the POTRA domain is very species specific.

Another interesting thing to address is how BamA gets itself into the outer membrane. One of the periplasmic chaperone proteins, Skp, is thought to be involved in this process, and it was found that when the outer membrane was negatively charged Skp is involved in inserting BamA into the membrane, whereas when the negative charge is removed Skp inhibits BamA folding and insertion. Negative charge is caused by an increase in the phosphatidylglycerol content in the membrane. I found that idea quite exciting as it implies that the bacteria can control where they want the BAM complex to go. The idea of membranes forming "lipid rafts" with certain components that organise where proteins are held is not a new one, and the BAM complex forming in specific places in order to create the correct outer membrane protein concentration is one that appeals to me.

They may just be single little cells with no true nucleus, but they are capible of a lot of control over their intracellular processes!

---
Knowles TJ, Scott-Tucker A, Overduin M, & Henderson IR (2009). Membrane protein architects: the role of the BAM complex in outer membrane protein assembly. Nature reviews. Microbiology, 7 (3), 206-14 PMID: 19182809

Johnson, A., & Jensen, R. (2004). Barreling through the membrane Nature Structural & Molecular Biology, 11 (2), 113-114 DOI: 10.1038/nsmb0204-113

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Is psychology a science, redux

GamesWithWords — Tue, 31 Aug 2010 02:45:00 -0700

Is psychology a science? I see this question asked a lot on message boards, and it's time to discuss it again here. I think the typical response by a researcher like myself is an annoyed "of course, you ignoramus." But a more subtle response is deserved, as the answer depends entirely on what you mean by "psychology" and what you mean by "science."

Two Psychologies

First, if by "psychology" you mean seeing clients (like in Good Will Hunting or Silence of the Lambs), then, no, it's probably not a science. But that's a bit like asking whether engineers or doctors are scientists. Scientists create knowledge. Client-visiting psychologists, doctors and engineers use knowledge. Of course, you could legitimately ask whether client-visiting psychologists base their interventions on good science. Many don't, but that's also true about some doctors and, I'd be willing to bet, engineers.

Helpfully, "engineering" and "physics" are given different names, while the research and application ends of psychology confusingly share the same name. (Yes, I'm aware that engineering is not hte application of physics writ broadly -- what's the application of string theory? -- and one can be a chemical engineer, etc. I actually think that makes the analogy to the two psychologies even more apt). It doesn't help that the only psychologists who show up in movies are the Good Will Hunting kind (though if paleoglaciologists get to save the world, I don't see why experimental psychologists don't!), but it does exist.

A friend of mine (a physicist) once claimed psychologists don't do experiments (he said this un-ironically over IM while I was killing time in a psychology research lab). My response now would be to invite him to participate in one of these experiments. Based on this Facebook group, I know I'm not the only one who has heard this.

Methods

There are also those, however, who are aware that psychologists do experiments, but deny that it's a true science. Some of this has to do with the belief that psychologists still use introspection (there are probably some somewhere, but I suspect there are also physicists who use voodoo dolls somewhere as well, along with mathematicians who play the lottery).

The more serious objection has to do with the statistics used in psychology. In the physical sciences, typically a reaction takes place or does not, or a neutrino is detected is not. There is some uncertainty given the precision of the tools being used, but on the whole the results are fairly straight-forward and the precision is pretty good (unless you study turbulence or something similar).

In psychology, however, the phenomena we study are noisy and the tools lack much precision. When studying a neutrino, you don't have to worry about whether it's hungry or sleepy or distracted. You don't have to worry about whether the neutrino you are studying is smarter than average, or maybe too tall for your testing booth, or maybe it's only participating in your experiment to get extra credit in class and isn't the least bit motivated. It does what it does according to fairly simple rules. Humans, on the other hand, are terrible test subjects. Psychology experiments require averaging over many, many observations in order to detect patterns within all that noise.

Science is about predictions. In theory, we'd like to predict what an individual person will do in a particular instance. In practice, we're largely in the business of predicting what the average person will do in an average instance. Obviously we'd like to make more specific predictions (and there are those who can and do), but they're still testable (and tested) predictions. The alternative is to declare much of human and animal behavior outside the realm of science.

Significant differences

There are some who are on board so far but get off the bus when it comes to how statistics are done in psychology. Usually an experiment consists of determining statistically whether a particular result was likely to have occurred by chance alone. Richard Feynman famously thought this was nuts (the thought experiment is that it's unlikely to see a license plate printed CPT 349, but you wouldn't want to conclude much from it).

That's missing the point. The notion of significant difference is really a measure of replicability. We're usually comparing a measurement across two populations. We may find population A is better than population B on some test. That could be because population A is underlyingly better at such tests. Alternatively, population A was lucky that day. A significant difference is essentially a prediction that if we test population A and population B again, we'll get the same results (better performance for population A). Ultimately, though, the statistical test is just a prediction (one that typically works pretty well) that the results will replicate. Ideally, all experiments would be replicated multiple times, but that's expensive and time-consuming, and -- to the extent that the statistical analysis was done correctly (a big if) -- largely unnecessary

So what do you think? Are the social sciences sciences? Comments are welcome.

Taxon of the Week: Protoperidinium grande

noreply@blogger.com (Christopher Taylor) — Mon, 30 Aug 2010 20:53:00 -0700

I can't really award anyone the prize for identifying yesterday's image; identifying it as a "dinoflagellate" doesn't really cut the mustard considering how many thousands of dinoflagellate species are known.

Protoperidinium grande. From Steidinger & Williams (1970).

Many references describe dinoflagellates as photosynthetic; this is wrong, in the same way as describing mosquitoes as feeding on blood is wrong. In terms of number of species, there are probably more non-photosynthetic than photosynthetic dinoflagellates. Protoperidinium is a genus of more than 200 species of mostly non-photosynthetic marine dinoflagellates, many of which possess a single apical horn and two antapical horns as seen in the photo above. Features distinguishing P. grande include the reticulate theca and the compressed cingular area (the cingulum is the groove around the midline; one of the dinoflagellate's two flagella wraps around the cingulum). Unlike some other Protoperidinium species, P. grande does not produce resting cysts; as a result, it is found only in warmer waters around the world. As non-photosynthetic heterotrophs, Protoperidinium species obtain their nutrition by feeding on other micro-organisms such as diatoms, cyanobacteria or other dinoflagellates. Rather than directly engulfing their prey in the way of an amoeba, Protoperidinium extend a large pseudopodial extension called a pallium from their theca's antapical pole to envelop it. The food organism is digested by the pallium, which is then withdrawn back into the dinoflagellate theca carrying a load of nutrients with it. This feeding behaviour was first 'discovered' in the late 1990s, but ironically it had actually been illustrated as long ago as 1895 with later researchers failing to recognise earlier records for what they were (Jacobson 1999*).

*Jacobson's comment on this re-discovery are worth repeating: "the brilliant, detailed observations of Kofoid and Swezy, Schütt, and Biecheler remain a humbling reminder to those of us working in a highly capitalized, high-tech environment that important work can arise from a simple light microscope, coupled with patience, luck and the appropriate search image".

Protoperidinium depressum feeding on diatoms. Figure from Jacobson (1999).

Until relatively recently, Protoperidinium species were included in the genus Peridinium along with a number of freshwater dinoflagellates. The taxonomy of Recent dinoflagellates* has traditionally been dominated by a small number of what might be termed 'super-genera' of hundreds of species that between them encompass the great majority of living taxa. It is probably not surprising that phylogenetic analyses have suggested that many of these super-genera are polyphyletic, but most of those analyses have tended to return very poorly supported results and attempts to subdivide the super-genera have not been entirely successful. The division of Peridinium is one of the more successful examples, based on ecology (Peridinium sensu stricto is freshwater, Protoperidinium is marine), fine details of the arrangement of plates in the theca (Peridinium has five plates around the cingulum; Protoperidinium has four) and the features of cysts produced in some species (Dale, 1978). Molecular analyses have supported the monophyly of Protoperidinium (Yamaguchi & Horiguchi, 2005). The division on ecological grounds has been a common pattern in studies on protists; molecular analyses of a number of other micro-eukaryotic groups such as myxozoans have also produced results that contradict traditional morphological classifications but correlate strongly with ecological features.

*The taxonomy of fossil dinoflagellates is an entirely separate pot of evil.

REFERENCES

Dale, B. 1978. Acritarchous cysts of Peridinium faeroense Paulsen: implications for dinoflagellate systematics. Palynology 2: 187-193.

Jacobson, D. M. 1999. A brief history of dinoflagellate feeding research. Journal of Eukaryotic Microbiology 46 (4): 376-381.

Steidinger, K. A., & J. Williams. 1970. Dinoflagellates. Memoirs of the Hourglass Cruises 2: 1-251.

Yamaguchi, A., & T. Horiguchi. 2005. Molecular phylogenetic study of the heterotrophic dinoflagellate genus Protoperidinium (Dinophyceae) inferred from small subunit rRNA gene sequences. Phycological Research 53 (1): 30-42.

Inside the Mathematician's Studio

Ben Allen — Mon, 30 Aug 2010 08:30:00 -0700

One of the aims of this blog is to give the general public a sense of what we applied mathematicians and other non-laboratory scientists actually do with our time. An earlier post addressed the content of what we do: the development and analysis of models. This post, on the other hand, will focus on process. Specifically, my process: how I actually do math. This post is a joint project with my partner Anna, whose beautiful sequence of illustrated text about the nature of the creative process appears on her site drawmedy.

Of course, there are many aspects of what I do. Activities such as reading through the literature, meeting with collaborators, and writing up results, don't require much explanation. I focus here on the parts of my job that makes me feel most like a mathematician: coming up with new ideas and developing them into mathematical arguments.

It starts with a problem. Most often I'm trying to prove some result of the form "In this model, under these conditions, this kind of behavior can arise". Sometimes these questions can be addressed using textbook-style sequences of steps, or even using programs like Mathematica. But such straightforward solutions don't interest me as a mathematician, and I like to leave this kind of work to other people. What really makes me come alive are the questions for which new mathematical approaches must be conceived.

This is an inherently creative process. There is no way of knowing at the outset what the solution may look like, or even whether a solution will be found. All you start with is your toolbox of mathematical techniques, and some hunches about which tools might work if applied correctly.

From this starting point, it's a process of trying approaches, failing, trying other approaches, asking questions, re-framing the problem, working out simple examples, and trying to make connections between different areas of my knowledge. This process plays out in pencil scratchings on my bound notebooks, two pages of which I've reproduced here:

These two (non-consecutive) pages show some of my musings on Prisoner's Dilemma games played on networks. On the first page I'm mainly working through some visual examples. You can also see some of the general questions these examples inspired. ("Maybe this is all about...")

The first half of the second page shows me asking questions (indicated by the Q:) and formulating hypotheses about how different models might be connected. I typically jot down my thoughts in real time as they occur to me, so that it almost feels like journalling. I tend to write in complete sentences, but sometimes a thought will end mid-sentence as something else occurs to me. I'll also go back and write in the margins (e.g. the circled questions at the top right of the second page) if I have an idea that connects to something I wrote earlier.

The second half of the second page shows some calculations as I test one of the hypotheses generated above. Note the circled line with the words "NOT TRUE" to the right. Mistakes and retractions are ubiquitous in my notebooks (as they probably are in the scratchwork of most mathematicians).

My favorite position for such notebook-scribblings is reclining in a couch or comfy chair, as Anna deftly illustrates:

I tend to get antsy when sitting upright for too long. In fact, I'm a big fan of changing scene in general. If I'm stuck in one room with no good ideas, I'm liable to go searching for another room to work in. Perhaps this helps me get a new perspective on what I'm doing, or maybe it just stops frustration from building up.

I should add that many of my best ideas actually come in the shower, or jogging, or in other situations where my brain has the time and space to chart its own course. Other mathematicians I've spoken to share this experience. If you've been focusing on a single problem for long enough, it can seep into your subconscious, which may continue to generate ideas even when you're doing other things. Back in college (when I was a pure mathematician) I even got to the point of solving homework problems in my sleep, though the sleep was not exactly what you'd call "restful".

I'll end with a call to other science bloggers and writers. The Paris Review, since the 1950's, has conducted a series of interviews with world's preeminent writers on their process: how they generate their ideas and shape them into finished pieces of writing. Collectively, these interviews have helped shape public perception of writing as an occupation, and illustrated the variety of methods that writers employ. In this age where science is increasingly misunderstood and distorted in the public eye, I think it would be powerful to have a similar series of documents illustrating the daily processes of scientists. So I'd encourage any science bloggers/writers reading this to consider expressing your own personal "scientific method" to the general public, and pass the word along!

Assessing computationally designed enzymes

noreply@blogger.com (Wavefunction) — Mon, 30 Aug 2010 14:38:00 -0700

One of the most promising recent developments in computational biochemistry is the development of potential capability to computationally design entirely new enzymes from scratch that can perform reactions inaccessible to naturally occurring proteins. Such enzymes can be of great utility as novel biofuels, synthetic reagents and new drugs. A particularly noteworthy set of publications in this regard was from David Baker’s and Ken Houk’s groups in Seattle and Los Angeles. In 2008, the groups designed an enzyme for performing a base-catalyzed Kemp elimination, a reaction which converts a benzisoxazole into a cyanophenoxide by proton abstraction.

A couple of months back, they again made news by designing a Diels-Alderase from scratch, an enzyme catalyzing the DA reaction whose natural counterpart does not exist. Although the catalytic rates they obtained were relatively modest compared to the best rates seen in nature, this is still an important and remarkable step forward.

The studies hinged on two tools- quantum mechanical design of a transition state for the enzymatic reaction, and buildup of the protein architecture around this ideal transition state using the program Rosetta. In the first step, a transition state for the reaction was surrounded by specific amino acid residues and optimized in an ideal geometry. This arrangement is called a “theozyme”, an ideal, minimal theoretical construct. In the second step, Rosetta was used to ‘embed’ this theozyme in a protein framework borrowed from existing protein structures in the PDB. Iterative cycles of optimization of the amino acids around the reactants led to several designs. Some of these designs turned out to be active, and crystal structures revealed the remarkable similarity between the computer and real-life counterparts. However, there was no easy way except actual testing to distinguish active and inactive designs beforehand (the inactive designs could not be crystallized since by definition they were probably too unstable to form crystals).

Now a new analysis nicely looks at the difference between the active and inactive designs obtained for the Kemp elimination. The authors first try to use static quantum chemistry calculations to resolve the difference between the two sets. Unfortunately this does not work very well since the energy difference between the sets are quite small, about 2 kcal/mol, and QM methods for such complex systems can often produce comparable errors.

However, enzymes are dynamic creatures, and it’s probably not too surprising that one has to resort to dynamical studies to discern the differences between active and inactive structures. To this end, the authors used 20 ns MD simulations. They compared the results with two designed Kemp eliminators (including one antibody) whose crystal structures are available. Firstly, they simply observed the mobility of the residues in the active sites and found out that in general, residues in the active designs don’t move around as much as those in the inactive ones, indicating stable packing. Then they looked at the hydrogen bonds holding the reactants together. In general, they found a tighter distribution of hydrogen bond angles in the active and crystallized structures compared to the inactive ones. This observation would be in keeping in line with the optimized hydrogen bonding networks in active sites. Lastly, they looked at accessibility of water in the active site. The base involved in the Kemp elimination is a carboxylate. Ideally, this carboxylate would not be solvated so that it is free to serve as a base. Indeed, analysis of water molecules surrounding this carboxylate indicated that while the carboxylates in the active, crystallized proteins are almost completely free of water molecules, the carboxylates in the inactive designs are typically surrounded by a couple of water molecules. This also again confirms the ‘looser’ packing in the inactive sites.

This is a nice study because it not only validates MD as a possible tool to distinguish and rank active and inactive designed enzymes, but it also provides insights into the basic physical features of optimized enzyme active sites. Compact packed side-chains, optimal hydrogen bonding geometries and relative inaccessibility of key residues to water is about what you would expect evolution to do when asked to come up with good enzyme designs.

Kiss, G., Röthlisberger, D., Baker, D., & Houk, K. (2010). Evaluation and ranking of enzyme designs Protein Science DOI: 10.1002/pro.462

Unfortunate change of plans

Lab Rat — Mon, 30 Aug 2010 07:12:00 -0700

So...anyone following me on Twitter probably saw me getting all excited when I signed up to go to the Society of General Microbiology conference a couple of months ago. The conference is next week, but unfortunately I won't be at it, which is a pity because I was all set to blog about it and everything.

There are two main reasons that I can't make it:

1-Time. I'm just finishing off my summer project and starting to need/get exciting results. Also I'm sorting out my wedding, trying to get a PhD organised, and heading off to another more work-related conference later this month. Taking four days off would be slightly overindulgent at this point.

2-Money. I do not have any. As an undergraduate SGM member I can't get a travel grant from them (graduates only) and as I've graduated the university isn't about to give me any money. So I have to pay to transport myself up there, and for somewhere to sleep for four nights. Train fares are expensive nowadays and even the cheapest B-and-B I had planned came to £180. Quite frankly if I had £180 I'd use it to clear my overdraft.

HOWEVER - all is not lost. As I registered for going to the conference (for free - the perks of being an undergraduate member) they sent me a PDF of the abstracts for each session. So, over the next two weeks I'm going to have a rather sad and nerdy little single-person conference of my own on my blog. I'm going to try and get a post up every other day (so seven posts over two weeks) covering one topic at the conference with each post.

I've got a choice of seventeen, but here are the topics I'll probably aim to cover as they're the ones I most wanted to see:

Metals and Microbes

Streptococci

Acid Stress

Microbial Death

New Insights into Secondary Metabolism

Extremophiles

Protein Folding and Misfolding

(and if I have time, Microbial Models of Human Diseases)

Before anyone starts feeling too sorry for me about missing this I should point out that a) I have another conference I'm going to this month b) that conference is fully funded and c) that conference is in Italy...

And there will be many more conferences in my life, I'm sure!

Riding off into the twilight...

noreply@blogger.com (Wavefunction) — Mon, 30 Aug 2010 05:13:00 -0700

In "The Twilight of the Bombs", the last volume of his breathtaking account of nuclear history, Richard Rhodes describes the post Cold War problems and hopes associated with nuclear weapons. The books bears many of Rhodes's trademarks- it is extremely well-researched and contains sharp portraits of the major players as well as fast-paced accounts of key events that make you feel as if you were there. Rhodes's abilities as a storyteller are still remarkable. This book is relatively slim and does not command the high-octane prose of Rhodes's masterpiece "The Making of the Atomic Bomb" but as usual, Rhodes's authoritative knowledge of nuclear matters provides many revelations and he has a novelist's eye for detail which keeps the reader hooked.

The book can roughly be divided into four parts. The first part concerns the first Gulf War and the dismantling of Iraq's nuclear infrastructure, the second part describes the race to secure nuclear material in the former Soviet republics after the fall of the Soviet Union, the third part briefly talks about South Africa's nuclear ambitions and and then in more detail about attempts to contain nuclear efforts by North Korea and the last part concerns the run-up to the second Gulf War and some final thoughts on the future of nuclear weapons. One striking omission in the book is Iran, and I think readers would have appreciated Rhodes's insightful thoughts on the Iranian nuclear problem.

The first part examines the troubling evidence in the 1980s that Saddam Hussein was trying to build a nuclear capability. Rogue Pakistani scientist A Q Khan had even tried to unsuccessfully sell Iraq a bomb design based on a Chinese weapon. At the same time that the US was providing aid and goodwill to Iraq to support it against Iran in the Iran-Iraq war, it was also unearthing evidence in the form of dual-use equipment shipments and intelligence analysis that Iraq was pursuing enriched uranium. Interestingly, the technology that Iraq was using turned out to be electromagnetic separation, a primitive technology that the US did not initially believe would be used; for nations pursuing nuclear capability, separating uranium isotopes by using centrifuges is much more efficient. Yet electromagnetic separation is exactly the kind of technology that a relatively primitive and cash-strapped economy would pursue. This is a good example of how biases can lead to false conclusions in spite of supporting evidence. Later, Rhodes has pulse-racing accounts of searches for enrichment technology in Iraq conducted by the weapons inspectors of the IAEA and the UN. Even after the inspectors discovered evidence of enrichment in the form of equipment used for electromagnetic separation, this was not yet conclusive evidence of weapons building. Probably the most exciting moment was when, deep down in a small room in a basement, the inspectors discovered a report that did provide such evidence in the form of clear and detailed descriptions of materials and design for an implosion bomb.

The second part of the book deals with the fragmentation of the Soviet Union and the spirited and at times desperate race to acquire nuclear weapons from the former Soviet republics of Ukraine, Belarus and Kazakhstan. There are many heroes in this story which stands as a model of bipartisan cooperation against a serious threat. Among these are David Kay, Hans Blix and Bob Gallucci who were nuclear inspectors and disarmament specialists. Probably the most prominent ones are the Democratic and Republican senators Sam Nunn and Richard Lugar who worked day and night to acquire funds from Congress to secure nuclear material and weapons from the three countries and have them transferred back to Russia. Concomitantly, Secretary of State James Baker hopped from one capital to another, urging the presidents of the new nations to sign the NPT and START using a combination of carrots (in the form of monetary rewards) and sticks (in the form of possible sanctions and threats from Russia). All three nations agreed that they were better off without nuclear weapons, and the result was a transfer of thousands of strategic and tactical weapons back to Russia. A third important and massive effort involved blending down the enriched uranium from Soviet weapons to reactor grade and shipping it back to the US for use in US nuclear reactors; Americans may be amused to know that about 10 percent of their current electricity derived from nuclear energy comes from nuclear weapons that their former foe had targeted against their cities. Curiously, the biggest reformer in this drama was President George H W Bush who orchestrated the largest arms reductions in history (he abolished entire classes of weapons, including missiles with multiple warheads and all ground-based weapons), and he needs to get much more credit for doing this than what has been given to him.

In the third part Rhodes first briefly talks about the dismantling of South Africa's nuclear program, which is a fine lesson for nations wanting to eschew nuclear weapons. In case of South Africa, the same reasons- internal strife, border conflicts and international alienation because of the government's apartheid policies- that provoked the country to acquire weapons also encouraged them to give them up. An uglier reason was their fear in the 80s that the weapons might fall into the hands of the black government.

Rhodes then describes in detail the difficult relationship between the US and North Korea in the context of North Korea's nuclear ambitions. Along the way, Rhodes also provides perspective by noting that the US had mercilessly bombed the North during the Korean War; since then the North Koreans have constantly been in a kind of perpetual state of war, surrounded by giant powers like Russia and China. It's also worth keeping in mind that the US had stationed hundreds of nuclear weapons in South Korea as a deterrent until about 1990. Although these actions by the US do not justify the North's nuclear efforts, they do explain the paranoia and deep sense of insecurity that has fueled North Korea's animosity towards the US. Again, there are heroes in this story, but one singled out by Rhodes is former President Jimmy Carter who went to North Korea of his own volition in 1994 and successfully mediated the Koreans' proposal to stop reprocessing in return for light water reactors; the consequence of this diplomacy was the so-called "Agreed Framework" to regulate North Korea's commercial nuclear program, which unfortunately broke down in 2003 in the face of North Korean non-compliance and disagreements. Since then, North Korea has always had to be kept on a tight leash and there have been several moments of tension between the two countries, but Rhodes's accounts make it clear how diplomacy has averted another Korean War. Rhodes also has succinct discussions of efforts to develop and implement a framework for the CTBT, which was signed by Clinton but unfortunately not ratified by the Senate.

The last part of the book concerns the run-up to the second Gulf War. This story has been told before but Rhodes tells it succinctly and well. Meticulous weapons inspections in Iraq between 1992 and 1998 had unearthed no evidence of a WMD capability, although Iraq had also not furnished clear documentation of the dismantling of its WMD capability. As Rhodes tells it, regime change had already been on the table, especially pushed by neoconservatives like Dick Cheney and Paul Wolfowitz but even contemplated by former Vice President Al Gore. But even after 9/11, it does not seem like Bush was thinking of attacking Iraq. However, as the record indicates, something changed in his thinking in the next two months, and invading Iraq became a concrete strategy in his mind. Rhodes thinks that a major reason for this shift in his thinking may have been the anthrax attacks which followed 9/11. It seems that these attacks really rammed the threat of terrorism home; at one point alarms even went off in the White House and Dick Cheney suspected that he himself may have been contaminated. Nonetheless, as is well-known now, Bush and his associates decided to invade Iraq fueled by the tried and tested strategy of threat-inflation and on evidence that was dubious at best. Rhodes clearly establishes the prevarications of the administration's claims about WMDs in Iraq, based on discredited reports about uranium shipments from Niger to Saddam (reports discredited even by the CIA) as well as Chinese imports of supposed aluminum tubes for centrifuges, which turned out to be parts for short-range rockets. At best Iraq was years behind the difficult goal of building a nuclear weapon, a goal which would have needed extensive operations of enrichment and processing which would most likely have been detected. No matter how you cut it, there was no concrete justification for invading Iraq except one based on ideology and belief. Bush also seriously damaged arms reduction efforts by withdrawing from the ABM treaty, by his belligerent rhetoric against North Korea (which withdrew from the NPT and tested a nuclear weapon in 2006) and Iran, by lifting sanctions on Pakistan (a particularly recalcitrant and prolific proliferator) and by agreeing to supply India (which had not signed the NPT) with nuclear-related equipment. And yet in the midst of this tragedy it is easy to miss Bush's one success in arms control in which he signed major arms reductions with Russia; these reductions brought down the number of warheads on US delivery vehicles from about 10,000 at the end of the Cold War to about 2600.

This brings us to the final, eloquent part of Rhodes's book where he talks about the possible abolishment of nuclear weapons. He describes the very serious problem of nuclear terrorism; in his view, while it may be very difficult for terrorists to use a sophisticated nuclear weapon, it may be much easier for them to acquire enough material for a crude explosive. Even state-owned nuclear weapons are susceptible to accident, miscalculation and misunderstanding. The bottom line is that as long as nuclear weapons are around, there is always a possibility that they may be used. The only, truly final solution for reducing the threat of nuclear weapons is to get rid of them. How do we achieve this? I would have appreciated more detail from Rhodes in this regard, but he describes promising developments. For one thing, simple laws of physics dictate that without nuclear material one cannot make nuclear weapons. So securing nuclear material is key and the Nunn-Lugar initiative has set a worthy bipartisan example for achieving this goal. Many recent initiatives to reduce the threat of nuclear weapons have also been refreshingly bipartisan. Efforts to ban nuclear testing have already been fine-honed for decades, and getting all nations on board the CTBT would mean a lot; in this context Rhodes singles out Australian diplomat Richard Butler and his Canberra Commission for special praise. The fact is that, in spite of nuclear proliferation, there have been hundreds of nations which have found it prudent not to develop nuclear weapons for various reasons (not the least of which is their expense; according to Rhodes it costs the US 50 billion dollars just to maintain its current stockpile of weapons), so there is hope.

In the end though, only political will, strong leadership and international cooperation can rid the world of these terrible weapons. At some point, owning a nuclear weapon needs to become a crime. It is absolutely necessary to stop regarding these weapons as partisan, parochial concerns which can be leveraged to score political points in elections. To underscore this point, Rhodes recounts a fascinating idea put forth by the Scottish writer Gil Elliot in his book "Twentieth Century Book of the Dead". Elliot talks about the international efforts to prevent and cure infectious disease and believes that war should similarly be treated as an international anathema that is to be abolished. Efforts to eradicate disease through public health campaigns crossed boundaries and saw even countries who were otherwise very hostile towards each other mutually cooperating. This was because disease was not seen as some other country's problem but as a common threat. Because of their sheer destructive power, nuclear weapons similarly pose a common threat to all of humanity. Rhodes says that only when nuclear weapons are similarly and completely depoliticized to the extent that infectious diseases are, only when the world sees them not as instruments of aggression and patriotism owned by specific nations but as a common scourge that threatens all of humanity irrespective of our political leanings and differences, only then will we all work together to abolish them.

Name the Bug # 22

noreply@blogger.com (Christopher Taylor) — Sun, 29 Aug 2010 21:18:00 -0700

Another ID challenge as a preview for tomorrow's post. I know at least one of my regular readers will be able to get this easily if she sees it, so from her (she knows who she is) I'm going to require a species-level identification or close to. Everyone else, see what you can do:

The figure is in ventral view and the specimen is 130 µm wide. Attribution to follow.

Update: Identity now available here. Figure from Steidinger & Williams (1970).

Update

EcoPhysioMichelle — Sun, 29 Aug 2010 13:23:00 -0700

Thanks to all for your well-wishes in the last post. My symptoms are getting a little worse (and a little more disgusting) but my mental state is getting a lot better. I still don't know what's wrong with me exactly. I'm having a culture of a gross and personal nature taken tomorrow, so hopefully in a few days we'll either know what's wrong or be able to rule out a good number of things. My big fear is that I'll have to have an endoscopy of some kind to figure out the source of the problem. I really don't like things going in places they aren't supposed to go. :(

Cross your fingers for me.

Miles to go before...

noreply@blogger.com (Wavefunction) — Sat, 28 Aug 2010 18:01:00 -0700

A New York Times article describes a study conducted by the NIH that basically asked scientists to simply sift through the massive evidence of the past twenty years to answer one question; what factors can cause or prevent Alzheimer's disease? The answer is unsurprisingly depressing- there is basically no proven therapy, personal habit, dietary supplement or mental task that correlates with the prevention of AD. AD is still as much a disease without a cure or preventative remedy as it ever was. We have almost as much work to do as Alois Alzheimer would have in 1908.

The bad news about AD has just kept on coming in over the last few years. Part of the reason is the very disappointing verdict on the role of beta-amyloid, reached after dozens of clinical trials which targeted the clump of protein in AD brains and failed to reverse the debilitating effects of the disease. Along with these studies, there has been a panoply of articles suggesting everything from crossword puzzle solving to Gingko biloba extracts that could possibly prevent the disease.

But as the NYT article reports, most of these recommendations are based on faulty 'studies' which are typically called "observational" studies. These studies are essentially accounts of observations made after someone has started on a measure that's assumed to be preventative. In addition, most of these observations are self-reported. Thus, evidence from such observations is spotty at best and is a far cry from the double-blind controlled clinical trials required to establish efficacy. After sifting through the evidence, the NIH study group concluded that they were sure only about one measure- Gingko biloba. And here the verdict was that Gingko biloba does not prevent AD. Apart from this, most other factors touted as preventive measures- including cognitive stimulation, vitamin E and antioxidants- could not be correlated with decreased incidence of AD with any degree of certainty. There's just no good evidence.

Part of the problem is simply the amount of time patients enrolled in trials would have to be observed in order to draw any conclusion about prevention. AD typically emerges around age 50, but its effects become apparent only in the late 60s and early 70s. A true clinical trial to study prevention would probably have to start during the young years and subjects would have to be followed for at least two to three decades, an expensive and complicated endeavor.

Yet the reports cited in the NYT should not be as depressing as they appear. For one thing, many people now think that the real reason none of the therapies for AD are working is simply because they are administered too late. Two new promising studies based on PET scans and spinal taps could make it easier to detect AD earlier and start treatment immediately. Plus, it's precisely the fragmented nature of the reported observations that provides opportunity for studying them further. Also, as depressing as the amyloid-targeting trials were, at least they provide good evidence of something that does not seem to be working. In science, the misses are almost as important as the hits. Finally, it's not like long-term studies cannot be attempted; the famous Framingham study followed the inhabitants of a small Massachusetts town not just over years but over generations to establish the connection between high cholesterol and heart disease. Perhaps a Framingham-style study for Alzheimer's is due.

Until these deep questions are resolved though, AD patients and their families will keep on living their private version of hell and will keep on trying to stave off the terrible malady by trying anything that remotely seems to work. The least we can all do is keep on searching.

From bull horns to under the lens of Anton

noreply@blogger.com (Wavefunction) — Fri, 27 Aug 2010 17:03:00 -0700

In 1989, a young computer scientist named David Shaw was working at Morgan Stanley, one of the first Wall Street firms interested in using computer algorithms for trading. Shaw was an expert in parallel processing, speeding up calculations by executing them in a parallel process over multiple processors. Previously he had been a computer science professor at Columbia University had tried to sell his computer skills to a number of companies, but only Morgan Stanley was genuinely interested. As Shaw started working at the company, he began to think not just of programming strategies but of creative ways in which they could be applied to trading. In a meeting where he was supposed to talk only about his algorithms, he went one step beyond and described better methods for trading using these algorithms. Eyebrows went up in the room. Shaw was essentially seen as overstepping his bounds as a programmer. The higher-ups told him clearly that his job was simply building the computer architecture. He could leave the trading to them. Shaw quit and started his own company. Ten years later, it was one of the most successful hedge funds in the world and Shaw was a billionaire. One can only speculative how much the Morgan Stanley executives cried over the loss they had suffered when Shaw left.

But now D E Shaw is a totally different animal.

One of the most anticipated talks at the ACS meeting was by this Wall Street mover turned pure scientist. He is a remarkable and brilliant man. What other Wall Street hedge fund manager who made billions using mathematical algorithms for trading (and was known as “King Quant” at one point) basically retires from the dizzying world of finance to fully engage himself with computer simulations of proteins? Well, Shaw has done this, and is blazing his way toward some potentially revolutionary research. At the very least it is inspirational to see men with money actually care about basic scientific research.

He heads D E Shaw Research, a company totally separate from the financial powerhouse that has as its long-term goal, a fundamental transformation in the process of drug discovery. As the story goes, Shaw got somewhat bored of making millions and wanted to attack scientific problems that could benefit from the application of advanced computer algorithms. He got his old job as computer science professor at Columbia University and started looking around for the right problem. Fortunately for the field of biochemistry, Shaw started having discussions with a friend of his, the well-known physical chemist Richard Friesner at Columbia who is also the chief scientific advisor for the computational chemistry company Schrodinger. Friesner piqued Shaw’s interest and started giving him little problems in computational chemistry and biology which Shaw solved during his spare time. Finally he realized that MD simulations of proteins which had previously been typically restricted to the nanosecond time range stood a chance of being truly and very significantly useful if they could be expanded to the 10 microsecond-millisecond range, since this is the time scale on which most interesting biological motions such as large conformational changes occur.

Shaw started D E Shaw research and collected a team of highly talented chemists, biologists and computer scientists to tackle the problem. After a decade or so, these efforts have manifested themselves as Desmond, a protein MD program that has vastly accelerated computer simulations of proteins. Desmond essentially relies on many ingenious methods to simplify the calculation of forces and velocities involved in a typical MD computation. It especially calculates the non-bonded forces- the sheer number of which constitutes the bottleneck in these kinds of calculations- with unprecedented efficiency. What is even more remarkable is that Shaw’s group has designed ‘Anton’, a 512 node state-of-the-art machine, a special purpose machine explicitly designed for protein MD and named after Anton van Leeuwenhoek, the legendary 17th century Dutch scientist who trained the microscope on the microbial world and unearthed a wondrous universe teeming with life. Just like the 17th century Anton probed the events of the bacterial world, the 21st century Anton seeks to probe the molecular-level events of the protein world, The machine does only MD, and it does this using a razor sharp scalpel.

To give an idea of the kind of quantum leap Anton provides for MD simulation, Shaw gave some numbers, and I can swear I saw some people who were almost nodding off suddenly become wide awake. According to Shaw, the fastest supercomputer which does parallel processing today can crunch about 200 ns/day for a typical sized protein. Anton surpasses this number by two orders of magnitudes and spews out 17,400 ns or 17 microseconds per day. Such numbers would have been unthinkable a decade ago; until Desmond appeared on the scene, the world record for long protein MD simulations had been held by a group from the University of Illinois, with a total time of 10 microseconds.

So what’s the significance of being able to simulate in this time scale? Tremendous. It’s like the difference between nuclear weapons and the biggest conventional bombs previously used. When nukes arrived on the scene, some politicians like Winston Churchill shrugged them off by thinking that they were “just bigger bombs”. But as the old saying goes, quantity can have a quality all of its own. Nuclear weapons heralded a completely new era of warfare because of the ability of a single weapon to raze a whole city. The basic unit of destruction changed from a human being to entire cities. Desmond and Anton promise such conceptual transformations. As mentioned before, breaking the 10 microsecond barrier is a real turning point since most interesting physiological events happen on time scales of microseconds-milliseconds.

Entering the world of millisecond simulations is like unlocking the door to a rainforest with millions of exotic species that you suspected existed, but which you had no way of viewing and studying. In the last few years, Desmond has been used to study highly significant conduction events in ion channels, has been used to reconcile experimental and conceptual contradictions in the structure of GPCRs, and has been used to study very large conformational changes in kinases. All these events are very slow with respect to conventional MD. Shaw showed some spectacular examples of proteins actually folding and unfolding multiple times. In some cases his group has obtained quantitative agreement with kinetics and NMR experiments.

I think it was the end of the talk which made a few jaws drop. When you have a protein structure and want to find out a small molecule which can modulate its activity, one of the key goals is to first find out where the small molecule binds. With the kinds of time scales available, Shaw can achieve this with a devastatingly straightforward simulation. In a video that appeared a little surreal, he simply let the molecule roam all around the protein surface and find the binding pocket. Like a curious dog sniffing around for the buried bone, the little guy went in and out of crevices and gullies, lingered for some time outside the binding site, and then, with a little hesitation, finally ensconced himself firmly in his cozy home, having surmounted all the challenges of entropy and desolvation that he had to face.

This may not always be the best method to find binding sites and MD admittedly is not going to transform the process of drug discovery by itself, but what we witnessed in that room on Thursday was a different ball game. One in which the ball had been hit out of the park. More surprises should follow.

Name the Bug: Psectra diptera

noreply@blogger.com (Christopher Taylor) — Thu, 26 Aug 2010 21:00:00 -0700

The points for this one go to Kai, who successfully identified this as a flightless hemerobiid lacewing:

Psectra diptera, from MacLachlan (1868).

Psectra diptera is found in both Europe and North America but is apparently nowhere very common (a live photo can be seen here). Gunnar pretty much gave the reasons for identifying this insect as a lacewing in his comment: the high density of veins (particularly cross-veins) in the wings and the long, filamentous antennae (but lost out on the marks by assuming that it must be a fossil).

Of course, lacewings normally have four wings, not two. Many basic references on insects will indicate that the only group of insects with a single pair of developed wings* is the Diptera, the true flies, but diptery is also found among Strepsiptera, mayflies, scale insects, lacewings, Psocodea and snowfleas** (and probably a couple of others that I've forgotten). Different processes seem to have resulted in wing loss in different lineages—among lacewings and psocops, for instance, it is associated with loss of flying ability, but Diptera and mayflies are capable of aerobatics that few other insects can rival.

*Technically, Diptera do still have their hindwings: they've been altered into small knobbed rods called halteres. Hindwing halteres are unique to flies among living insects. Strepsiptera have the forewings altered into halteres; scale insects have knobless filaments called hamulohalteres; and hindwing halteres were present in the Cretaceous lacewing Mantispidiptera.

**Though the appendages of male snowfleas are just so freakishly bizarre (as described in the linked post) that I rather feel calling them wings is a little like calling a whale's flippers 'legs'. It may be correct in an evolutionary sense but it's a little ridiculous by any other measure.

As noted by the commenter 'Reprobus', Strepsiptera are a little different from the other entries in the list in that they have lost the forewings instead of the hindwings. Relatively few groups of insects have larger hindwings than forewings: Orthoptera (crickets and grasshoppers), stick insects, earwigs, some beetles. All of these have the forewings protectively hardened to some degree, and in earwigs and beetles the forewings have become entirely hardened into protective cases called elytra. The evolutionary affinities of Strepsiptera are decidedly contentious (see the post linked to above) but some authors have suggested a relationship to beetles (and one recent molecular study has provided further support for this relationship: Longhorn et al., 2010). If so, strepsipterans may have been derived from ancestors that also had hardened forewings that were no longer functional when flying, potentially explaining why that was the pair that was lost.

REFERENCES

Longhorn, S. J., H. W. Pohl & A. P. Vogler. 2010. Ribosomal protein genes of holometabolan insects reject the Halteria, instead revealing a close affinity of Strepsiptera with Coleoptera. Molecular Phylogenetics and Evolution 55 (3): 846-859.

MacLachlan, R. 1868. A monograph of the British Neuroptera-Planipennia. Transactions of the Royal Entomological Society of London 1868: 145-224.

Trojan horse predators

Lab Rat — Thu, 26 Aug 2010 11:00:00 -0700

A while ago, Angry by Choice wrote a post about a fungi that kills its nematode prey by making little lasso ropes to catch the worm in. At the time, I thought there must be some exciting way that bacteria could cause wormy destruction, but it wasn't I read a paper from Lucas (reference below) that I actually found one.

It's not as visually exciting as the little fungi nooses, but it's just as chemically exciting. As bacteria are not capable of forming phyiscal structures to capture a worm, they make chemical ones, specifically volatile chemicals which diffuse easily and can be sensed by the worm.

In layman terms they smell good. They smell like food.

This is officially the best MS Paint picture I've ever done

Nematodes don't have a huge number of well programmed behaviours in their little nematode brains, but "move towards food" aka "positive olfactory chemotaxis" is one of the most robust and common behaviors. And the bacteria take full advantage of this. They secrete chemicals that are based on modified quorum sensing molecules (usually used for bacterial communication), which cause the worms to not only arrive where the bacteria are waiting, but also to happily gobble them up, after all they do smell like food.

Once eaten, the bacteria end up in the worms digestive tract, where they start to secrete enzymes - two digestive proteases called Bace16 and Bae16. Although previous work had assumed that these two proteases worked on the outside of the worms cuticle the paper used flourescent labeling studies to show that both Bace16 and Bae16 had their effects once inside the worm. Bace16 (labelled in red) and Bae16 (labelled in green) were both injected into an unsuspecting worm, which was then visualised every hour:

Images taken after 2hs, 5hrs, 8hrs and 24hrs

It's a little hard to see in the small picture above, but it is clear that the worm is getting ill, breaking apart, and finally just decomposing due to the action of the two proteases. The bacteria is not using the proteases to break into the worm, but to break out of it, digesting the worm in the process. This was further proved by making bacterial strains with the genes for Bace16 and Bae16 knocked out. Infection with the knockout strains led to far less virulent bacteria, and worms that survived for far longer.

It's an interesting new type of predation - a kind of Trojan Horse predator. Rather than chasing its prey, or directly infecting it, the bacteria gets itself eaten and then destroys the worm from the inside out. The paper suggests that as well as being interesting, this knowledge could help lead to more efficient biocontrol strategies for the elimination of nematode worms, now we know the active series of events involved in nematode predation by bacteria.

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Niu Q, Huang X, Zhang L, Xu J, Yang D, Wei K, Niu X, An Z, Bennett JW, Zou C, Yang J, & Zhang KQ (2010). A Trojan horse mechanism of bacterial pathogenesis against nematodes. Proceedings of the National Academy of Sciences of the United States of America PMID: 20733068
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Gone for a while.

EcoPhysioMichelle — Thu, 26 Aug 2010 04:25:00 -0700

I'm going to be MIA for a while. Health issues.

Name the Bug # 21

noreply@blogger.com (Christopher Taylor) — Wed, 25 Aug 2010 21:46:00 -0700

Yes, the ID challenge today is an actual insect, for once. And, as a clue to identity, consider first the point that it only has a single pair of wings, rather than the more usual complement of two.

Attribution to follow.

Update: Identity now available here. Figure from MacLachlan (1868).

Eusociality and a blow to kin selection

Ben Allen — Wed, 25 Aug 2010 13:48:00 -0700

A new paper hit the internet today. "The Evolution of Eusociality" by Martin Nowak, Corina Tarnita, and E.O. Wilson re-frames an old evolutionary question and strikes a blow in an increasingly heated debate.

Eusociality is when individual organisms act as a collective reproducing unit. The best-known examples are ants and honeybees, but recently discovered examples include certain beetles, shrimp, and mole rats. Typically all reproduction is done by a single queen, and the rest of the colony exists only to support and protect the queen. Eusociality represents the highest degree of social organization found in nature.

The evolutionary origins of eusociality are something of a puzzle. To transition to eusociality, individuals must give up their own reproductive potential to support that of the queen. This is the ultimate sacrifice, as far as evolution is concerned. If evolution favors those who produce the most offspring, how can it select for actually giving up the chance to reproduce?

The classical answer to this question is kin selection: the idea that cooperative acts can occur between close relatives. Dawkins explained this using the concept of "selfish genes" that promote cooperation with others who have the same gene. One proponent, J.B.S. Haldane, famously said he would jump into a river to save two brothers, or eight cousins.

Ants and honeybees, the two oldest-known examples of eusocial animals, have a special genetic structure in which siblings share 3/4 of their genes, as compared to 1/2 in most sexual reproducers. It seemed reasonable that these close genetic relationships made possible such large-scale organization and extreme altruism.

However, as more eusocial species were discovered, including mammals, this association fell apart. There no longer appears to be any significant relationship between eusociality and relatedness of siblings.

Nowak, Tarnita, and Wilson provide a new model which focuses on the competition between reproductive units, which can be individual or collective. But perhaps more importantly, they thoroughly deconstruct the mathematics underlying kin selection theory.

The big debate in evolutionary theory right now is between those who believe all cooperation can be explained by kin selection (in its more mathematical guise of inclusive fitness theory), and those who believe that the more standard natural selection concept has more explanatory power. This debate has become increasingly heated in recent years.

Backed by rigorous mathematics, the authors argue that

Inclusive fitness theory is not a simplification over the standard approach. It is an alternative accounting method, but one that works only in a very limited domain. Whenever inclusive fitness does work, the results are identical to those of the standard approach. Inclusive fitness theory is an unnecessary detour, which does not provide additional insight or information.

The import of this argument might not be apparent to those not immersed in the field, but this paper could be a turning point in how the evolution of cooperation is understood. Social behavior cannot all be reduced to selfish genes. There are in fact many mechanisms allowing cooperation to evolve. Understanding these mechanisms will continue to be a fascinating question in evolutionary theory.