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Rivers of Gas Flow Around Stars

Sunday, December 28, 2008

NASA - Rivers of Gas Flow Around Stars in New Space Image (12/8/08)
A new image from NASA's Spitzer Space Telescope shows a turbulent star-forming region, where rivers of gas and stellar winds are eroding thickets of dusty material.

The picture provides some of the best examples yet of the ripples of gas, or bow shocks, that can form around stars in choppy cosmic waters.

"The stars are like rocks in a rushing river," said Matt Povich of the University of Wisconsin, Madison. "Powerful winds from the most massive stars at the center of the cloud produce a large flow of expanding gas. This gas then piles up with dust in front of winds from other massive stars that are pushing back against the flow."

Swan nebula (M17) – click for 516×420 image

More: here

Zooming in on an early galaxy

Monday, December 22, 2008

One of the key questions about galaxies concerns the process in which they form. Galaxies are made up of stars, but in general stars do not form in isolation – except for the very first stars in the universe, which we discussed here.

More normally, stars form simultaneously in close proximity to each other as part of the larger process of galaxy formation. But galaxy formation can happen in one of at least two different ways. In the first case, the baryonic matter that will eventually form stars gradually contracts under gravitational force along with the larger mass of dark matter in which it is "trapped". This is a gradual process in which the entire galaxy is formed as the baryonic matter eventually collapses to a state that is dense enough for individual stars to form, much as stars form even today, albeit quite slowly, as in the Milky Way of the present time. (The present rate is only 2 or 3 per year on average.)

Alternatively, in the second case, relatively small groups of stars form within irregular protogalaxies, which then over long periods of time (billions of years) merge with each other to form galaxies as we are familiar with them today.

The first scenario is typically called "monolithic collapse" or formation by "gas accretion". The second is called the "hierarchical" or "merger" scenario.

Of course, both processes can occur. Conceivably some of the large galaxies we can see today were built up from the merger of many smaller galaxies, while others formed more or less in isolation. But the interesting question is whether one or the other of these scenarios was more common in the early days of the universe. (Since at the present time most matter available to feed galaxy growth is already part of a galaxy, most galaxy growth now is by merger.)

In the very early universe, that is for the first 2 or 3 billion years after the big bang (which was about 13.7 billion years ago), there would have been less opportunity for galaxy mergers, so one might expect that more of the galaxies back then formed in isolation rather than in a hierarchical process of mergers.

As explained in this article on redshift, galaxies that formed within the first 3 billion years after the big bang all have redshifts of about 2.2 or more.

Unfortunately, at such redshifts, the objects are at distances of 10.7 billion to more than 13 billion light-years, so it's nearly impossible to make out any details, even with the most powerful existing telescopes, and even using sophisticated technology like adaptive optics. Therefore, there's very little reliable information about the actual morphology of early galaxies, making it impossible at present to obtain enough evidence to decide between the two scenarios.

In particular, it's certainly not possible to discern the overall shape of such a distant galaxy, to determine whether it's an ordinary spiral, a more shapeless elliptical galaxy, or something else, such as a pair of merging galaxies. Morphological information is what one needs in order to discriminate between nice orderly spiral galaxies and galaxies that are distorted due to mergers.

Even though situating a telescope in space, such as the HST, or on the Moon solves the problem of atmospheric distortions, the only way to get better resolution is by using a larger mirror. Telescopes with larger optics are being planned, but fortunately nature itself provides some help even today, albeit in very rare circumstances, as we'll explain in a moment.

Although we can't easily determine the properties of such early galaxies, at least it's possible to find them relatively easily in surveys, without even having to study them spectroscopically. We just discussed the technique for finding these early galaxies by the Lyman break techniques.

It turns out that even though we cannot see the structure of these Lyman-break galaxies directly, we can do spectroscopic measurements that tell us a surprising amount of information about these galaxies. This information can tell us about galaxy rotation, whether there are strong outflows of gas (due to stellar winds or supernova ejecta), and even the approximate rate of star formation in the galaxy.

One thing that spectroscopic data allows astronomers to do is to map "velocity fields" in different parts of a galaxy. That is, we can determine how fast specific parts of the galaxy are moving relative to the galaxy as a whole. For example, in a rotating spiral galaxy, we should detect that the half of the galaxy rotating away from us has an additional redshift beyond the overall redshift of the galaxy, while the other half has a slightly lower redshift. If this pattern varies in a regular way from one end of the galaxy to the other, we can be fairly sure the galaxy is a spiral. On the other hand, if the relative velocities of different parts of the galaxy are irregular or "chaotic", we probably have a galaxy without much regular structure.

However, even this velocity field information we have is at a rather low resolution compared to the size of the galaxy. For historical reasons, astronomers customarily use a length scale called a parsec, or "parallax arcsecond", which is about 3.26 light-years. The resolution, for spectroscopic purposes, of an object at redshift z≳2.2 is about 1300 pc (parsecs), or 4000 light-years, and this is more than half the size of the visible part of a typical Lyman-break galaxy. (Our Milky Way is a lot larger, roughly 100,000 light-years in diameter.)

What can be done about this? Not a whole lot, actually, until we have telescopes with much better resolution – except in certain very special circumstances. Those circumstances exist when another large galaxy or galaxy cluster lies directly in the line of sight between us and the very distant galaxy we're interested in. Then we have what is called a gravitational lens. This works pretty much like an ordinary optical lens, because according to general relativity massive objects are capable of bending light.

A group of astronomers have now examined one example of exactly this circumstance. The distant galaxy in question is named J2135-0102 (a catalog number). It lies at z=3.075. So we see it as it was 2.13 billion years after the big bang. We know that there were already galaxies much less than a billion years after the big bang, so this one isn't that unusual.

Because of this gravitational lens, it has been possible to map the velocity field of J2135-0102 with a resolution of ~120 pc, about 5 times better than possible without the gravitational lens. The abstract of the research paper reveals what can be learned from this:

The formation and assembly of a typical star-forming galaxy at redshift z ≈ 3
Recent studies of galaxies ~2–3 Gyr after the Big Bang have revealed large, rotating disks, similar to those of galaxies today. The existence of well-ordered rotation in galaxies during this peak epoch of cosmic star formation indicates that gas accretion is likely to be the dominant mode by which galaxies grow, because major mergers of galaxies would completely disrupt the observed velocity fields. But poor spatial resolution and sensitivity have hampered this interpretation; such studies have been limited to the largest and most luminous galaxies, which may have fundamentally different modes of assembly from those of more typical galaxies (which are thought to grow into the spheroidal components at the centres of galaxies similar to the Milky Way). Here we report observations of a typical star-forming galaxy at z = 3.07, with a linear resolution of ~100 parsecs. We find a well-ordered compact source in which molecular gas is being converted efficiently into stars, likely to be assembling a spheroidal bulge similar to those seen in spiral galaxies at the present day. The presence of undisrupted rotation may indicate that galaxies such as the Milky Way gain much of their mass by accretion rather than major mergers.

So, the researchers have concluded that in the case of this small, but typical, Lyman-break galaxy, a fairly regular structure is present, and it is more likely due to gas accretion rather than hierarchical assembly.

That's the big news, but the researchers were able to deduce a few other things as well.

For example, from the rotation curve, J2135-0102 appears to have a mass of ~2×109 M (solar masses) within a radius of 1800 pc. (The Milky Way, by comparison, is about 5.8×1011 M.) The galaxy's rate of star formation has also been estimated at 40±5 M per year – much higher (per unit volume) than the Milky Way's rate of only 2 or 3 M per year. This high rate, however, does seem to be typical of the rate in other Lyman-break galaxies that have been studied.

Further reading:

Cosmic Eye Sheds Light On Early Galaxy Formation, Just Two Billion Years After Big Bang (10/8/08) – press release

Cosmic eye telescope used to spot distant galaxy (10/8/08) - news article in the Telegraph (UK)

Daniel P. Stark, A. Mark Swinbank, Richard S. Ellis, Simon Dye, Ian R. Smail, Johan Richard (2008). The formation and assembly of a typical star-forming galaxy at redshift z ≈ 3 Nature, 455 (7214), 775-777 DOI: 10.1038/nature07294


Lyman-break galaxies

Sunday, December 14, 2008

Now that we have a good foundation regarding the concept of redshift (see here), we can turn to a particular type of galaxy that is especially easily identified by redshift.

There's a class of very distant galaxies (like, around 12 billion light-years distant) that have been the subject of a fair amount of research in the past decade or so – because the technology to even find them in the first place is not much older than that.

The class is called "Lyman-break galaxies". The reason for the name will emerge from the following, so just accept it for now.

The first thing we need to consider is how such very distant galaxies can be detected out of everything that's out there, most of which is considerably closer. It isn't actually so hard to get an image of a galaxy that far away. The so-called Hubble Deep Field survey, conducted in 1995, captured some objects as far away as 12.7 billion light years – as they existed only about a billion years after the big bang.

How do we know, roughly, what the distance is to these objects? That, too, isn't so hard. Astronomers just measure the redshift in the light spectrum from the object. This is, roughly, the amount by which well-known emission/absorption spectral lines have been shifted to longer wavelengths.

Because of the redshift-distance relationship discovered by Edwin Hubble, the redshift is a very good indication of the distance of the object. An accurate calculation of distance for a given redshift depends on the values of certain additional parameters. But these values have now been pretty well determined independently. You can experiment with the relationship yourself at this page.

The Hubble Deep Field survey was able to identify objects with a redshift as high as 6. That corresponds to a distance of about 12.7 billion light-years. Of course, objects at that distance are quite faint, so the only ones we can detect were extremely bright when the light we see was emitted. Essentially all we can see at that distance are quasars, which are galaxies with an extremely active, bright nucleus. Ordinary galaxies, especially smaller ones, are generally undetectable at that distance.

However, the Hubble telescope, and a few newer ground-based telescopes, can detect fairly small galaxies at a distance corresponding to z=3 or a little more. These are the Lyman-break galaxies. z=3 corresponds to an object that is about 11.5 billion light-years away. So we are now seeing the object as it was 11.5 billion years ago, about 2.2 billion years after the big bang – about 16% of the present age of the universe.

Now, even though it is possible and relatively straightforward to measure spectra of objects at z=3, it's still tedious and time-consuming. One would like to have an easier way to identify such objects in a survey of thousands of objects in something like the Hubble Deep Field.

As it turns out, there is a clever trick for finding objects with z=3 without even measuring spectra. The trick depends on the fact that even the brightest stars do not emit much light beyond a certain point in the extreme ultraviolet region of the spectrum. The cutoff is around a wavelength of 91 nm (billions of a meter). This is the so-called Lyman limit, which corresponds to the most energetic photons that can be emitted by very hot hydrogen.

The reason for this cutoff lies in the details of the Lyman series of lines in the emission spectrum of atomic hydrogen. Each line in that series corresponds to the energy of a photon which can be emitted when an electron moves to the lowest possible energy level from a higher level. There is a line at the same place in the absorption spectrum, due to an electron being boosted by a photon of the right energy from a lower to a higher level.

Because energy is quantized, the spectrum is not continuous and consists of discrete lines. However, at shorter wavelengths the lines come closer and closer together, until they reach a limit at 91.1267 nm. This is the Lyman limit. It represents the energy required to remove an electron completely from a hydrogen atom, starting at the lowest energy level. A hydrogen atom cannot emit a photon of higher energy, no matter how hot the gas is.

Since stars consist mostly of hydrogen gas, even the hottest stars cannot emit light with photons much more energetic (shorter wavelengths) than the Lyman limit. Since stars do contain other elements, especially helium, very hot stars are capable of radiating photons that are somewhat more energetic, but in general very little of the total energy output is from even farther into the ultraviolet. (Remember that shorter wavelength means higher energy.)

Even for stars that do radiate more energetic photons, such photons can ionize neutral hydrogen atoms, hence they will be absorbed by interstellar or intergalactic clouds of hydrogen. In fact, any photon more energetic than the Lyman limit is likely to be absorbed quickly by a hydrogen atom, because it can completely eject the only electron, with perhaps some energy left over (emitted as a longer wavelength photon).

The result is that there is a rather sharp cutoff (or "break") in a stellar emission spectrum at 91 nm. So normal galaxies whose light comes mostly from stars have the same cutoff. (In a quasar, where much of the radiation is due to matter falling into a supermassive black hole, it's possible for a large proportion of the energy output to consist of photons more energetic than the Lyman limit. Such photons are created, for example, in particle collisions between massive particles accelerated to near the speed of light.)

Bottom line: light from normal galaxies has a sharp cutoff at the 91 nm wavelength, when viewed from a great distance.

Now recall from our redshift discussion that if the redshift is z, then the factor by which wavelength is lengthened is z+1. Therefore, at a redshift of 3, 91 nm photons are shifted to a wavelength of 364 nm, in the near ultraviolet part of the spectrum. A normal star like the sun radiates a lot at this wavelength, in the range often called UV-A. So does a common "black light".

Simple filters are easily made that allow light to pass only in a narrow range of wavelengths. A blue filter, for example, passes photons only around 440-490 nm. If you have a filter that passes only ultraviolet light in a band of wavelengths less than 364 nm, no light at all will get through from objects with z≥3. Objects with z<3 may still be visible through such a filter, since there will still be some shifted photons with wavelengths somewhat less than 364 nm. But some light from a z=3 object could pass through a filter that admits light with wavelengths greater than 364 nm, including a filter for light in the visible range.

Objects with z>3 will have their Lyman limit shifted all the way into the visible part of the spectrum, so they might not be visible even through a blue filter. In fact, if the criterion is objects that don't make it through a blue filter, one can estimate that 3.5≲z≲4.5. At z=6, Lyman limit photons are shifted to 637 nm – red light. A red filter would therefore pass visible light from a z=6 object, but blue or green filters would not.

Astronomers take advantage of this situation by using an ultraviolet filter, together with filters in the visible range (e. g. red, green, and blue). Any object which is visible through all the filters must have z<3, but an object visible through red and blue filters, and not the ultraviolet filter, should have z≈3. By adjusting the short wavelength filter, it's possible to select for objects at higher z in the same way.

The technique isn't foolproof. For example, a galaxy that has few hot stars with strong emission near 91 nm will have most of its light shifted so it doesn't pass through the UV filter, even if z≈2. Indeed, even an ordinary star in our galaxy could pass the test if it has little emission at UV wavelengths. Of course, such a star would be a lot cooler than our sun, and have a negligible redshift besides. So the actual redshift has to be confirmed by spectrometer measurement. However, the procedure is pretty efficient – around 75% of candidate objects actually have z≈3.

Thus it's relatively simple to do a survey for objects around specific redshift values, without going to the trouble of doing a spectroscopic measurement. Galaxies discovered in this way are, naturally enough, called Lyman-break galaxies (LBG for short) .

OK, that's all well and good, but what have we actually discovered about LBGs? There are some things we can learn just by counting them. However, ideally we could image them through telescopes in enough detail to learn something about their size, morphology, rate of star formation, evolution, and so on.

Such questions are easiest to deal with for the galaxies near z=3, because we can detect more of them than at higher redshifts (the more distant ones may be too small or dim to see at all), and because we can see more detail in them than more distant ones.

The first thing to note is that most LBGs will have fairly active star formation going on, because only young, newly-formed stars are hot enough to emit light near 91 nm.

The distribution of such galaxies is somewhat interesting. When the filters are arranged to be able to identify galaxies with 2.4≤z≤3.6, surveys find upwards of 400 candidates. The redshifts of these can then be measured with a spectrometer. There are several peaks in the distribution, around z=2.95, 3.15, and 3.35. By combining the redshift data with spatial direction of each object, actual clusters of galaxies can be identified.

The existence of distinct clustering at less than 2 billion years after the big bang is an indication that the spatial distribution of matter, including dark matter, at that time was already fairly lumpy.

Now, about the galaxies themselves. What are we able to say about them? Well, in terms of the spectra we can measure, the LBGs seem to be much like galaxies near us that have a lot of star-forming activity. (Such galaxies are called starburst galaxies.) The spectra indicate the presence of many very large, hot stars, of spectral class O and B. Such stars are normally rare, because they have very short lives. So if we can detect that there are many such stars, relatively speaking, it means that the rate of forming new stars of this type (and, presumably other types) is fairly high – much higher (in terms of stars per unit volume) than in our galaxy or most nearby galaxies today.

Another example of what can be inferred from the spectra is that the LBGs seem to have a lot of interstellar gas and dust, compared to nearby galaxies with rapid star formation. Uncertainties about just how much dust is there complicates estimation of how many stars might be present. The spectra also suggest that there are large outflows of gas and dust from the LBGs. These outflows are typically driven by very hot, massive stars' stellar winds and supernovae (which are the terminal stages of massive stars). Such characteristics indicate that rapid star formation in LBGs and nearby star-forming galaxies may have different causes.

The most interesting and most fundamental question about galaxy evolution is that of whether a typical galaxy grows in a "monolithic" way, in which most news stars are formed as the mass of baryonic matter gradually contracts gravitationally. Or, on the other hand, whether some stars form in small proto-galaxies, which go on to merge with each other, assembling large galaxies like our own, in the process undergoing bursts of new star formation. It's also possible that both processes occur to significant degrees.

This question is difficult to answer with spectroscopic data. We really need to have direct optical information about the shape ("morphology") of early and evolving galaxies. The problem is that, in most cases, galaxies with z≳2 are too small and faint to image optically with adequate resolution, even with the current generation of sophisticated ground-based telescopes using adaptive optics. That is, we can't see directly whether the early galaxies are amorphous blobs, regular ellipsoids, or picturesque spirals. However, there seem to be relatively few examples with highly elongated shapes, corresponding to a spiral galaxy seen mostly edge-on.

But it's hard to discern morphology reliably even using a space telescope like Hubble. The resolution is such that a single pixel may cover a large part of the object – a few percent of the area, or much more. In a subsequent article I'll discuss an interesting case where we've gotten lucky.

In general, the Hubble finds that LBGs at z≈3 seem to be fairly compact and regular. We still can't necessarily distinguish ellipsoids from spirals. But with z≳4, objects appear to be more diffuse and irregular.

The size of the objects, at least in terms of the parts not too faint to be detectable, seem to be on the order of 50,000 light-years or less – smaller than half the size of our galaxy. But this represents emissions in the ultraviolet part of the spectrum (which we see shifted to the visible part), so the extent of the objects in terms of emitted visible light could well be larger.

Much of our knowledge of LBGs at z≈3 was established over 10 years ago. Since then we have learned somewhat more about the issues of clustering, stellar types and gas/dust content in early galaxies, and galaxy morphology, by a variety of means. We will look at some recent studies about such topics before too long (hopefully).

It's worth noting that the Lyman-break technique can be also be used at smaller and larger values of z. At values of z>3 the Lyman-break will be shifted all the way into the visible part of the spectrum, while for z<3, the Lyman-break will occur at shorter UV wavelengths. All these can be handled by proper choice of filters.

For example, for z up to about 6, around 1 billion years after the big bang, we have, from 2003, a study that shows relatively few bright galaxies. Since this was in the period of reionization, which required many hot, bright stars, there must have been many more galaxies around that were just too small to be detected.

New insight into the cosmic renaissance epoch (8/21/03)
In particular, the astronomers conclude on the basis of their unique data that there were considerably fewer luminous galaxies in the Universe at this early stage than 500 million years later.

There must therefore be many less luminous galaxies in the region of space that they studied, too faint to be detected in this study. It must be those still unidentified galaxies that emit the majority of the energetic photons needed to ionise the hydrogen in the Universe at that particularly epoch.

Ironically, it was a little later that the Lyman-break technique was applied to closer objects, z≈1. In 2006 we have:

Ubiquitous Galaxies Discovered In The Early Universe (3/9/06)
For the first time, Denis Burgarella and his team have been able to detect less distant galaxies via the Lyman-break technique. The team collected data from various origins: UV data from the NASA GALEX satellite, infrared data from the SPITZER satellite, and data in the visible range at ESO telescopes. From these data, they selected about 300 galaxies showing a far-UV disappearance. These galaxies have a redshift ranging from 0.9 to 1.3, that is, they are observed at a moment when the Universe had less than half of its current age. ...

From their observations of this sample, the team also inferred various information about these galaxies. Combining UV and infrared measurements makes it possible to determine the formation rate for stars in these distant galaxies for the first time. Stars form there very actively, at a rate of a few hundred to one thousand stars per year (only a few stars currently form in our Galaxy each year). The team also studied their morphology, and show that most of them are spiral galaxies. Up to now, distant galaxies were believed to be mainly interacting galaxies, with irregular and complex shapes. Denis Burgarella and his colleagues have now shown that the galaxies in their sample, seen when the Universe had about 40% of its current age, have regular shapes, similar to present-day galaxies like ours.

Further reading:

Lyman-Break Galaxies

Mapping the Distant Universe

The Properties of Lyman-Break Galazies at z∼3 – excellent article

Searches for high-redshift galaxies


Warning of nut allergy 'hysteria'

Saturday, December 13, 2008

Warning of nut allergy 'hysteria'
Measures to protect children with nut allergies are becoming increasingly absurd and hysterical, say experts.

A peanut on the floor of a US school bus recently led to evacuation and decontamination for fear it might have affected the 10-year-old passengers.

Such extreme steps to reduce exposure to nuts are not isolated and are fuelling fear and anxiety, reports the British Medical Journal Online.

A UK allergy expert said a similar "epidemic" was present in Britain. ...

[Professor Nicolas Christakis, a professor of medical sociology at Harvard Medical School] said these responses were extreme and had many of the hallmarks of mass psychogenic illness (MPI), previously known as epidemic hysteria.

Often seen occurring in small towns, schools and other institutions, outbreaks of MPI involve healthy people in a flow of anxiety, most often triggered by a fear of contamination.

I think Professor Christakis is so right about this. And I think his observation applies to the way some people react to many things they don't understand, such as the use of pheromones to control destructive insect infestations. See here.

It's very sad, too, that this kind of ignorance is often spread by "journalists" who seem to deliberately ignore important distinctions they ought to understand, to say nothing of the underlying science. As I discussed in my item linked above.

Further reading:

Fear of nuts creating hysteria of epidemic proportions (12/10/08) – press release

Why are U. S. politicians so corrupt?

Wednesday, December 10, 2008

Because voters elect them based on their looks rather than their ethics. See here for more.


Saturday, December 6, 2008

There are some recent very interesting research results about very distant early galaxies that I want to discuss. Understanding these results depends on knowing a few basic concepts that one learns in any modern introduction to astronomy. I expect that most readers here know these concepts very well. But just to make sure that the necessary details are understood by anyone who happens along, I want to provide a tutorial for those who might need a refresher on the ideas.

Readers who are confident about these basics won't find anything new here except, perhaps, for the precise mathematical definition of redshift stated at the very end.

Fundamental to almost any science is the process of measurement. In astronomy, perhaps the most important quantity that can be measured through an optical telescope is brightness. But observed, measurable brightness all by itself is not too useful, because what's more important for an object such as a distant star or galaxy is not the observed brightness, but instead the intrinsic brightness – the amount of light actually emitted by the object, not what we are able to observe.

Since observed brightness falls off as the square of the distance, we can compute the intrinsic brightness from the observed brightness if we know the distance. Unfortunately, for most astronomical objects outside the solar system, there's no simple way to determine the distance. We can't just do it with a yardstick. There are a few indirect techniques for measuring astronomical distance, but most of these fail for things that are really distant, like most galaxies.

There is, however, one thing that's relatively easy to measure with a telescope, whether it's of the optical kind or one that works in some other part of the electromagnetic spectrum, like a radio telescope. And that is the relative strength of the electromagnetic signal at different wavelengths in the spectrum. This is what a spectrometer (literally, an instrument for measuring a spectrum) does in the optical part of the spectrum.

In a type of luminous object called (paradoxically) a "black body", the signal strength of electromagnetic radiation varies continuously across the spectrum in a known way, without sharp peaks or dips. But normally the signal strength from a star or a cloud of interstellar gas does not vary smoothly. Instead, there are usually particular wavelengths at which the signal is especially stronger or weaker than at most adjacent wavelengths. This is because of the way a hot gas of atoms or molecules emits or absorbs radiation unusually strongly at certain particular wavelengths.

These special wavelengths are the emission or absorption lines in the spectrum. When we know the kind of atom or molecule involved, these wavelengths can be measured in a laboratory, and each type of atom or molecule has its own characteristic "signature" of lines. If a gas of these atoms or molecules is emitting light, we get emission lines as peaks in the spectrum. And if a continuous spectrum of light passes through the gas (when it is cool enough not to emit light), we find absorption lines at the same wavelengths.

The most abundant elements in the universe are hydrogen and helium. The spectral signatures from these two gases are quite well known. But when we measure spectra from (for example) distant stars, we find slight shifts in where the lines are from where they "ought" to be. This shift is known as the Doppler shift, and it tells us precisely how fast the object is moving towards or away from us. (For very distant objects, the same shift occurs, but not for the usual reason, as we will explain later.) In most cases, especially for distant objects like galaxies, the shift is towards longer wavelengths. For visible light, that shift is in the direction of the red end of the visible spectrum, so it's called a "redshift".

The remarkable thing, which has been known for less than 100 years, is that light from very distant objects like galaxies is almost always shifted in the red direction, meaning that most such objects are moving away from us. The amount of the shift is easily computed to be proportional to the speed of the object along the line of sight. And what has been found that is even more remarkable than the existence of the shift in (usually) the red direction is that the amount of the shift (and hence the speed of the movement) varies directly with the actual distance to the object for most remote objects.

Because of the existence of this velocity-distance relationship, it becomes possible to infer the distance of an object from a measurement of its spectrum. This is why redshift is so important in astronomy. So let's have a look at the history of how this surprising, unexpected relationship was discovered.

Edwin Hubble, in the early 1920s, was the astronomer most responsible for the discovery of the velocity-distance relationship, and hence the first to understand that the universe as a whole is expanding.

Several other astronomers around 1920 recognized that shift of spectral lines from a galaxy might be interpreted as being the result of relative motion between the Earth and the galaxy. A blue shift would mean the object was moving in Earth's direction, while a red shift would mean it was moving away. Other interpretations of the red shift are possible. Indeed, some astronomers around 1920 (and even today) preferred other interpretations. But the interpretation of the red shift of spectra as a result of relative velocity has become accepted as the best way to interpret vast amounts of observational data.

In 1920 galaxies were not known to be enormous collections of stars like the Milky Way, and lying outside it. They were then just thought of as fuzzy stars – nebulae (from the Latin for "clouds"). But the interpretation of spectral redshift as due to relative velocity, followed by Hubble's discovery of a correlation between this redshift and actual distance, showed convincingly that galaxies had to be so remote that they could not be part of the Milky Way.

Naturally, the correlation between redshift (hence apparent velocity) and distance, which at the time could be stated as a simple proportion, became known as Hubble's Law. And the constant of proportionality became known as the "Hubble constant". (The relationship was actually a little more complicated, as we'll explain shortly.)

Hubble was able to derive an independent estimate of distance from Earth to relatively nearby galaxies by identifying stars in those galaxies whose intrinsic brightness could be accurately estimated. These stars are known as Cepheid variables. In this type of variable star, it was known that the regular period in which the brightness changes is directly related to the maximum brightness of the star. Thus a measurement of the period of such a star in any galaxy where the star could be identified indicates what its actual brightness is, and from its apparent brightness as seen from Earth, the actual distance can be determined.

Because Hubble could estimate in this way how far away a few galaxies were, he was able to determine that they were much too far away to actually lie within the Milky Way – contrary to what had been generally assumed up to that time. Indeed, the general supposition then was that the Milky Way comprised the entire universe, so Hubble's discovery was a big deal.

Hubble's Law simply states that the amount of redshift of a galaxy was proportional to its distance. The constant of proportionality, usually denoted by H (guess why) is called the "Hubble constant".

As it turns out, Hubble underestimated the actual distance of the galaxies he studied by nearly a factor of 10, due to errors in measuring the brightness of distant Cepheids. Consequently, the initial value figured for the Hubble constant was also off by the same factor.

This numerical problem was corrected soon enough. But it turns out that there are a couple of conceptual problems as well with the law. These became apparent before long when cosmologists tried to apply the equations of Einstein's general relativity theory to describing the expansion of the universe. Surprisingly enough, a fairly simple equation, called the Friedmann equation, first proposed by Alexander Friedmann in 1922, does a very good job.

The story of the Friedmann equation itself is quite interesting, but a little off topic right now. However, as cosmologists now understand the equation and use it to model the universe, a couple things in the conceptual understanding of Hubble's law are changed from Hubble's original idea. In the first place, Hubble's constant isn't in fact a constant at all, so cosmologists now prefer to call it "Hubble's parameter". It varies in a known way for objects that are very far apart, like billions of light years. But for relatively nearby galaxies it is pretty close to constant (the value is about 71, in case you're wondering).

The second conceptual point is that cosmological redshift is now understood to be due to the actual expansion of space itself, rather than the Doppler shift it was originally presumed to be. A classical Doppler shift results because the peak-to-peak distance of a periodic wave emitted by an object moving away from the observer is slightly longer than it would be if there were no relative motion, precisely because of the relative motion. The distance is increased by how far the source of the wave moves in the time between two peaks.

Now that cosmologists conceive of space itself as actually expanding with time, the redshift that a photon undergoes in traveling a long distance between points A and B results from the expansion of space that occurs in the time it takes for the photon to travel from A to B. The wavelength itself is stretched along with space.

Nevertheless, there is still a relatively simple, monotonic, though nonlinear, relationship between the distance of a remote galaxy and its observed redshift. Converting from a redshift to distance involves a variety of assumptions about certain parameters, such as the Hubble parameter and the curvature (if any) of space on a large scale. But these parameters have been measured in a variety of independent ways so that we now have fairly reliable estimates of their values. (You can go here if you want to play with this relationship yourself.)

The actual distances of remote objects are rather difficult (if not impossible) to determine with any accuracy, while redshift is pretty easy to measure with spectrometers. Consequently, astronomers customarily think of distance, which isn't directly observable, in terms of spectral redshift, which is. In fact, standard operating procedure is to report the redshift rather than the inferred distance.

The formal definition of redshift, denoted by z, is
z = (λ0 - λe) / λe
Here λ0 is the measured wavelength of a photon, while λe is the original wavelength of the photo when it was emitted.

For example, if the wavelength is exactly doubled, λ0 = 2λe, so z=1. If you rearrange terms in the definition of z, you get λ0 = (z+1)λe. That is, z+1 is the actual factor by which the wavelength is increased for any given z. (If this seems confusing, just remember that z=0 means no shift at all, so the factor of expansion is simply 1.)

In subsequent articles where I will discuss recent research results, there will be a lot of talk of redshift. The simple equation just shown can then be used to compare the change in photon wavelengths. A table or calculation such as noted above can be used to infer the distance of the object in question. And from this distance, one then knows how long ago the object emitted the light we see now, hence how long this time was after the big bang occurred (which is now estimated to be about 13.7 billion years ago).


Twine.com - bookmarking and social networking

Friday, November 28, 2008

I'm experimenting with Twine.com, which is a newish bookmarking and social networking site. That is, it's a combination of Del.icio.us (and the like) and (a rather simple) Facebook sort of thing.

The social networking isn't anywhere as nearly comprehensive as Facebook, but it's the same idea. The bookmarking, on the other hand, is as spiffy as Del.icio.us and others of that genre, with extras.

Bookmarks are organizied into groups called "twines", which can be public or private, and typically cover some recognizable topic area, or whatever people want to use them for. Each bookmark can also have a description and any number of tags, specified by the user creating the bookmark. Each bookmark also allows for comments, which anyone may add.

Underlying all this is "semantic web" technology. It's a cool computer-sciencey set of concepts and conventions for organizing heterogeneous collections of data in a way that (supposedly) is easier to search and navigate than the existing anarchy of Web pages, blog posts, etc. But I'm still waiting to see some compelling practical results...

In any case, I've set up some twines that I will use for bookmarking interesting scientific articles I come across. These items tend to be fairly non-technical, intended for an interested but not highly specialized audience, rather than articles from professional, refereed journals.

If you follow any of the links below, you will have to register with Twine, and should then get to see the various bookmark collections. You may choose to "join" any of the twines, which simply means that the system will keep track of the ones you have joined so you can visit them later. There is an option for receiving email notification of additions to individual twines. You can start your own twines too, if you like.

The social networking part is that you can set up a personal profile for youself, with whatever information you are willing to share. You can find out which other users have joined the same twines as you have, and "connect" with them if you have shared interests, as on Facebook or similar systems.

So, this is just an experiment to see if there is interest in something of this sort for groups of bookmarks to possibily interesting articles that deal with many of the topics written about here. If there doesn't seem to be much interest, or if I find it's too time consuming to be worth the effort, I'll stop.

On the other hand, if people give it a try, suggesting bookmarks of their own that are appropriate for one of the following twines, if desired, then maybe the experiment will yield something worthwhile.

You can leave comments to this post if you have questions or suggestions. Alternatively, you can send messages to other users on Twine itself.

Current twines I've started:

Scientific Readings: Neuroscience

Scientific Readings: Medical Biology and Biotechnology

Scientific Readings: Physics

Scientific Readings: Mathematics

Scientific Readings: Astronomy, Astrophysics, Cosmology

Politics as beauty contest

Sunday, November 23, 2008

Perhaps interest in politics has dropped off a lot now that the U. S. elections are over (for this year). But there's still some interesting political science that came up before the big event.

Even though political scientists, year in and year out, are as busy publishing as any other kind, quite a number of research announcements were noted recently outside of traditional professional venues. That has tapered off now, but there were a number of items that seem to call for some comment here. So I'll do some of that despite what is bound to be a declining interest in the subject.

A perennial favorite of election-oriented political research centers around questions of how the appearance of a candidate affects electoral success. That's no different this year. Here's a fairly typical example:

A Pretty Face Can Make A Difference In Whom You Vote For (10/30/08)
According to new Northwestern University research, it is not at all surprising that everyone also is talking about the great looks of vice presidential hopeful Palin.

Whether or not you believe the McCain campaign's $150,000 expenditure for Palin's wardrobe and the much-talked-about salary of her makeup artist are over the top, the decision to play up the looks of the former beauty queen is a winning strategy.

Even in 2008, a perception of competence -- a strong predictor of whether people will vote for political candidates -- is not enough to give women the winning edge in political contests, according to the new Northwestern psychology study.

For both men and women, female political candidates needed to be seen as attractive as well as competent to get their votes. ...

While gender bias related to a female candidate's attractiveness was consistent across both male and female voters, good looks was almost all that mattered in predicting men's votes for female candidates. And, true to prevailing stereotypes, competence was almost all that mattered in predicting men's votes for male candidates.

The idea that good looks positively affects electoral success has been researched many times – as well as being often suspected by a lot of people who aren't professional – in all kinds of elections from student councils on up. I discussed one study on this in a post here almost 2 years ago.

The new research I want to examine here was not entirely, or even primarily, about the importance of attractiveness in winning elections. Instead, experimental participants were first asked to rate candidates independently, based on their photos, on four different attributes: "competence", "dominance", and "approachability", as well as "attractiveness".

The politicians in question were actually candidates in 2006 U. S. Congressional elections. The politicians' photos were then presented in pairs actually competing with each other. Experiment participants were asked to chose which of each pair they would vote for if the office were actually the U. S. presidency.

The resulting data were analyzed in various ways. First, in comparison of participants' voting choice to how they had rated the candidates on each of the four attributes. Second, in comparison of candidates' gender and facial appearance to actual Congressional election outcomes. And third, in comparison between how the candidates won or lost in the simulated presidential election and in the actual Congressional election.

Since I want to focus just on the attractiveness issue, I won't attempt to summarize all the results here. You can find the summary in the research paper itself (citation below). I'll mention only two specific observations: (1) "Female candidates were more likely to win votes if they were more attractive." (2) "Male voters were significantly more likely to vote for candidates that appeared attractive." (I presume these statements represent correlations between opinions of attractiveness and voting behavior of each experimental participant.)

Now, it may be true as the research asserts, that attractiveness matters more for female candidates, while a perceptions of "competence" is relatively more important for male candidates. However, the attractiveness of male candidates (especially in contests exclusively between two males) is a still a net positive.

There's another possibility that should be considered even when voters seem to make their voting choices based on judgment of "competence" of male (or female, for that matter) candidates. Namely, that "attractiveness" (perhaps in a form not consciously associated with the term) might bias this judgment. One has to wonder exactly what visual characteristics might signify "competence" to voters, and whether certain factors – such as a "strong jawbone" (for a male) – don't contribute simultaneously to judgments of both attractiveness and competence.

Humans are fairly sophisticated in making judgments about traits like "competence", since evaluations of other people's character and ability are important in deciding whom to trust. The ability to do this reliably has a lot of evolutionary importance. This doesn't mean people are infallible about such judgments – clearly they aren't. But people probably can do better than chance in making such judgments, at least when not faced with situations where the person being judged is skilled at faking appearances. Perhaps it's more a case of detecting lack of competence, as might be signaled by poorly managed facial expressions (e. g. simply looking perplexed or "stupid").

But judgments about good looks and attractiveness are even more natural. We make them all the time, hardly giving any thought to the matter. Research has shown that people tend to make judgments about facial attractiveness very quickly. (See here.) This suggests people tend to use simple heuristics that may well be hard-wired.

Research apparently shows that even babies prefer to stare at beautiful faces. Note, too, how illustrated children's literature (and now movies) usually portrays virtuous or heroic characters as beautiful or handsome, while evil or villainous characters are ugly, often very ugly, and much to be feared. So there may be an element of social conditioning here, at least for children beyond infancy.

An interesting observation in the report of the research just mentioned, about the quickness of making judgments, is that "It seems that pretty faces 'prime' our minds to make us more likely to associate the pretty face with a positive emotion." ("Priming" is a hot topic in current psychological research.) So, comparatively speaking, a face that isn't "pretty" would be associated with less positive emotions. That alone would be enough to influence voting choices, if "everything else" is assumed to be equal.

There are different possible factors that may enter into such a judgment. So let's consider further what factors and heuristics might be used in judging facial attractiveness. It would be quite interesting to know how the various factors about to be mentioned perhaps have different effects on political choice.

A small number of factors are often suggested. One of the oldest is that the property of "youthfulness" is associated with attractiveness. That makes plenty of evolutionary sense, as fertility, reproductive capacity, and ability to nurture children all decline with age after the beginning of adulthood. It should be noted that youthfulness should be especially salient in the judgment of young people – such as the experimental subjects (college students, average age 19.5) in the research under discussion

A more recent suggestion is that "symmetry" is important, as that would tend to indicate general healthiness. (Recent research here.) That makes sense, too, but does it have any reasonably apparent relevance to voting decisions?

"Symmetry" is probably a looser criterion than in an older and fairly well-known theory of attractiveness, often called simply the "averageness" hypothesis. This holds that average phenotypes in a population are judged more attractive than phenotypes with notably atypical features. An average value on a particular facial metric (such as width of nose or chin) is considered to be what is "normal", yet for most features all to be close to average might be fairly unusual.

So "averageness" is used in a somewhat special sense here – literally, as having size and proportion of most important facial features being close to the overall average. Probably faces that have "averageness" in this sense are fairly rare, which might add to the quality of "attractiveness". So "averageness" as a descriptor of faces is not the same as "common" or "ordinary" or "typical".

Since averages of many faces will wipe out most asymmetry (e. g. some part being off center), an averaged face will be symmetrical. So facial symmetry is a more common characteristic than averageness. A symmetrical face could still have features that are far from average values in size or position.

Since facial symmetry will be more common in a population than faces that have the property of averageness (in the special sense used here), averageness is a more stringent criterion for attractivness. Consequently, a voter who perceives one candidate's face as more attractive than the candidate's opponent is making a more significant discrimination, which could have higher weight in the final choice. Indeed, two candidates might have equally symmetrical faces, or at least faces that are difficult to distinguish in terms of symmetry, yet differ considerably in averageness and hence (perhaps) in attractiveness.

And so, to the extent that people actually judge attractiveness based on averageness rather than symmetry, it will be more likely that judgment affects a voting decision. In other words, we would expect on these general considerations that attractiveness is more likely to affect voting decisions if the criterion is actually "averageness".

There is some amount of research supporting the idea that averageness is the important criterion for attractiveness, such as findings that images created by averaging photographs of many individuals tend to receive higher ratings for attractiveness. So at least for the sake of discussion, let's assume there's some validity to this notion.

Deviations from averageness do not imply deviations from symmetry, so they would not be expected to have the stronger negative implications for overall health and (hence) fertility that asymmetry does, so there would be a smaller indication of "riskiness". It would therefore be harder to understand the evolutionary importance of judging the riskiness of another person based on attractiveness if averageness is the underlying consideration. Is it possible that averageness is important in judging riskiness for other evolutionary reasons – reasons that apply to evaluating others in more general contexts than the context of mate selection?

Yes, I think so. As I wrote in my previous post, "people who are considered attractive within a population are those who are most 'typical' or 'average'. Or inversely, least atypical, least different from the largest number of people in the population. People who are considered less attractive have facial features that vary a lot from the norm, such as lips that are too thin or too thick (compared to the average), eyes too far apart or too close together, eyebrows that are too sparse or too bushy."

The evolutionary rationale at work here is that people who appear too "different" from the norm are more likely to belong to a different, more genetically distant tribe. Such people are probably less likely to deserve trust, and might even be "dangerous".

I think this matter of perceived trustworthiness vs. potential "danger" in the eyes of voters could be rather important, especially if it is unconsciously inferred from perceptions of a candidate's attractiveness. I've written more on that here, not too long ago, so I won't repeat it now.

More generally, I see conscious and unconscious issues of fear and perceived danger as especially important factors in a voter's attitudes towards, and relationship with, government. This is because, as a matter of both philosophy and sociology, one of the primary reasons for the existence of governments is to "protect" citizens from a variety of potential evils, whether they be dishonest businesspeople, common criminals, foreign and domestic terrorists, or whatever. I've written a lot more about that here.

The question, then, is whether the research now under discussion supports the idea of a connection between fear and voting behavior, or is even relevant to it. To be honest, the relevance is somewhat tentative, since it relies on the idea that there is a negative correlation between the attractiveness of a political candidate and whether a voter feels fear associated with the candidate at some level. It would be very interesting to see more research that addresses this issue more directly.

Regarding the present research itself, I have a few reservations as well. For example, the experimental participants were university students of average age 19.5 years. Quite possibly many of the participants had never even voted in a governmental election, and they certainly did not have a few decades of adult experience – with politicians, elections, and actual government performance – that could shape and inform their voting decisions. It's not surprising that individuals with little adult experience would base decisions on appearance factors.

Aside from that, there's also the question of whether the socioeconomic demographics of university students would skew the results from what would be found in the electorate as a whole. And then there's the whole other issue of possibly relevant cultural differences between the U. S. and other democratic countries.

So there's reason to suspect that typical, experienced voters, even in the U. S., might produce rather different results in a similar sort of experiment.

Here's the research paper, with some of the abstract:

The Political Gender Gap: Gender Bias in Facial Inferences that Predict Voting Behavior
Contrary to the notion that people use deliberate, rational strategies when deciding whom to vote for in major political elections, research indicates that people use shallow decision heuristics, such as impressions of competence solely from a candidate's facial appearance, when deciding whom to vote for. Because gender has previously been shown to affect a number of inferences made from the face, here we investigated the hypothesis that gender of both voter and candidate affects the kinds of facial impressions that predict voting behavior.

Joan Y. Chiao, Nicholas E. Bowman, Harleen Gill (2008). The Political Gender Gap: Gender Bias in Facial Inferences that Predict Voting Behavior PLoS ONE, 3 (10) DOI: 10.1371/journal.pone.0003666

Update on 11/24/08: I have extensively reworked the discussion about "attractiveness" and its relationship to "symmetry" and "averageness". One would like to see more experimental evidence to sort out these factors in general and specifically as to how they affect voting choice.

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Dopamine and obesity

Monday, November 17, 2008

Dopamine is a neurotransmitter that's well-known for its involvement in several notable medical and behavioral problems, such as Parkinson's disease and drug addiction. But it is connected with many other issues of medical and psychological importance.

Perhaps the main reason that dopamine is so interesting is that it plays a big role in the brain's pleasure and reward systems. And therefore it is inevitably involved in reward-motivated behaviors of all kinds, from gambling, investing, substance abuse, and sex, to – eating. After all, isn't a high percentage of behavior motivated by rewards? There are other motivations for particular behaviors – fear and physiological needs, for example – but reward covers an awful lot of it.

Consequently, problems in the reward system can lead to excesses in some behaviors (e. g., gambling, eating), and perhaps also deficiencies in other behaviors (e. g. loss of interest in normal pleasures, as might accompany depression).

And because of the importance of dopamine in the reward system, problems with dopamine signaling can lead to problems in the reward system, with predictable consequences.

In the research we're going to look at, dopamine signaling is impaired in the presence of a particular allele associated with the D2 receptor for dopamine (known as DRD2). The conclusion is reached via the observation of decreased activity, as mesured by fMRI, in a brain region called the dorsal striatum. It is known that the variant allele causes a lower density of D2 receptors in this region.

The bottom line of the research is that individuals with this variant allele tend to have impaired ability to enjoy rewards from foods that most people like, such as chocolate. As a result, such individuals are disposed to consume more food in order to achieve an acceptable level of satiation of reward.

It might be thought, instead, that since the desirable foods produce less reward in individuals with the variant allele, they might consume less, due to reduced interest. However, that's not how the reward system seems to work. It seems to require achievement of a certain signal level in order to reach satiation and thus decrease the motivated behavior.

This is similar to the way signaling works with another hormone connected with eating, namely leptin. Normally, leptin levels rise when food is consumed. There are receptors for leptin in the ventromedial nucleus of the hypothalamus, a region that is responsible for appetite. There leptin inhibits the activity of neurons that contain neuropeptide Y (NPY).

A connection has been found between obesity and insensitivity to leptin, much as diabetes results from decreased sensitivity to the hormone insulin. Preseumably, individuals with reduced sensitivity to leptin don't know when to stop eating. Much the same state of affairs seems to exist in individuals with the allele (which is a DNA restriction enzyme called TaqIA) that affects DRD2 receptor density in the dorsal striatum.

Obesity, Abnormal 'Reward Circuitry' In Brain Linked: Gene Tied To Dopamine Signaling Also Implicated In Overeating (10/16/08)
Using brain imaging and chocolate milkshakes, scientists have found that women with weakened "reward circuitry" in their brains are at increased risk of weight gain over time and potential obesity. The risk increases even more for women who also have a gene associated with compromised dopamine signaling in the brain.

The results, drawn from two studies using functional magnetic resonance imaging (fMRI) at the University of Oregon's Lewis Center for Neuroimaging, appear in the Oct. 17 issue of the journal Science. The first-of-its-kind approach unveiled blunted activation in the brain's dorsal stratium when subjects were given milkshakes, which may reflect less-than-normal dopamine output.

Here's the research paper, with abstract:

Relation Between Obesity and Blunted Striatal Response to Food Is Moderated by TaqIA A1 Allele
The dorsal striatum plays a role in consummatory food reward, and striatal dopamine receptors are reduced in obese individuals, relative to lean individuals, which suggests that the striatum and dopaminergic signaling in the striatum may contribute to the development of obesity. Thus, we tested whether striatal activation in response to food intake is related to current and future increases in body mass and whether these relations are moderated by the presence of the A1 allele of the TaqIA restriction fragment length polymorphism, which is associated with dopamine D2 receptor (DRD2) gene binding in the striatum and compromised striatal dopamine signaling. Cross-sectional and prospective data from two functional magnetic resonance imaging studies support these hypotheses, which implies that individuals may overeat to compensate for a hypofunctioning dorsal striatum, particularly those with genetic polymorphisms thought to attenuate dopamine signaling in this region.

The idea that problems with dopamine signaling might be related to overeating and obesity isn't new. The following research announced in July involved rats rather than humans and considered other dopamine insufficiency mechanisms, but the basic conclusions are the same:

Obesity Predisposition Traced To The Brain's Reward System (7/29/08)
The tendency toward obesity is directly related to the brain system that is involved in food reward and addictive behaviors, according to a new study. Researchers at Tufts University School of Medicine (TUSM) and colleagues have demonstrated a link between a predisposition to obesity and defective dopamine signaling in the mesolimbic system in rats.

The mesolimbic system is a system of neurons in the brain that secretes dopamine, a neurotransmitter or chemical messenger, which mediates emotion and pleasure. The release of the neurotransmitter dopamine in the mesolimbic system is traditionally associated with euphoria and considered to be the major neurochemical signature of drug addiction. ...

Pothos says, "These findings have important implications in our understanding of the obesity epidemic. The notion that decreased dopamine signaling leads to increased feeding is compatible with the finding from human studies that obese individuals have reduced central dopamine receptors." He speculates that an attenuated dopamine signal may interfere with satiation, leading to overeating.

Paper abstract:

Evidence for defective mesolimbic dopamine exocytosis in obesity-prone rats
In electrophysiology studies, electrically evoked dopamine release in slice preparations was significantly attenuated in OP [obesity-prone] rats, not only in the nucleus accumbens but also in additional terminal sites of dopamine neurons such as the accumbens shell, dorsal striatum, and medial prefrontal cortex, suggesting that there may be a widespread dysfunction in mechanisms regulating dopamine release in this obesity model. Moreover, dopamine impairment in OP rats was apparent at birth and associated with changes in expression of several factors regulating dopamine synthesis and release: vesicular monoamine transporter-2, tyrosine hydroxylase, dopamine transporter, and dopamine receptor-2 short-form. Taken together, these results suggest that an attenuated central dopamine system would reduce the hedonic response associated with feeding and induce compensatory hyperphagia, leading to obesity.

News reports of the human dopamine results:

E. Stice, S. Spoor, C. Bohon, D. M. Small (2008). Relation Between Obesity and Blunted Striatal Response to Food Is Moderated by TaqIA A1 Allele Science, 322 (5900), 449-452 DOI: 10.1126/science.1161550

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Non-coding RNA and gene expression

Sunday, November 16, 2008

Human DNA consists of about 3.4 billion base pairs. A portion of that is actually genes that code for proteins required by human cells – roughly 20,500 genes. (See here.)

However, it's been recognized for a long time that only about 1.5% of human DNA (in terms of base pairs) actually codes for proteins. Little is known about the purpose (if any) of the remaining 98.5%, even though, by some estimates, 80% of human DNA is transcribed into RNA at some time.

This remainder is often called "junk DNA". But it's also known that a lot of it can't really be "junk", and must serve some useful purpose, because the sequences of large portions of it are highly conserved in evolution, being found almost unchanged in the genomes of human ancestors going back hundreds of millions of years.

Some of the 98.5% really does seem to be without useful function, consisting of stuff like transposons, which are DNA sequences that seem to be copied repeatedly and randomly into various parts of the genome (over evolutionary time spans)

The function of other portions of that 98.5% includes such things as introns found within genes, gene regulatory sequences, and "RNA genes" that code for various kinds of RNA that doesn't wind up being translated into proteins.

Such non-coding RNA can be further classified into things like ribosomal RNA, microRNA, small interfering RNA, and "long non-coding RNA".

This last, known as "long ncRNA" for short, is especially intriguing, because some studies have shown that there may be roughly four times as much of it (in base units) as there is of messenger RNA that is ultimately translated into proteins.

Even though a lot of these long ncRNAs are routinely found floating around inside cells, we're still in the dark about what, if anything, they actually do. But some recent research has revealed a little more about some long ncRNAs:

Early-stage Gene Transcription Creates Access To DNA (10/6/08)
Previously thought to be inert carriers of the genetic instructions from DNA, so-called non-coding RNAs turn out to reveal a novel mechanism for creating access to DNA required by transcriptional activation proteins for successful gene expression, according to Boston College Biology Professor Charles Hoffman, a co-author of the study with researchers from two Japanese universities. ...

Hoffman and his colleagues examined how the yeast cell senses its cellular environment and makes decisions about whether or not to express a gene, in this case fbp1, which encodes an enzyme. What they found was a preliminary transcription phase with a flurry of switches flicked "on" and then "off" as seen by the synthesis of non-coding RNA before the final "on" switch is tripped.

The non-coding RNAs initiate over one thousand base pairs of nucleotides along the DNA away from the known start site for this gene. The group discovered that the process of transcribing non-coding RNAs is required for the eventual production of the protein-encoding RNA. The transient synthesis of these non-coding RNAs serves to unfurl the tightly wound DNA, essentially loosening the structure to allow for gene expression. [Emphasis added.]

And here's the research article, with some of the abstract, providing a somewhat more precise description of what's going on:

Stepwise chromatin remodelling by a cascade of transcription initiation of non-coding RNAs
Here we show that RNA polymerase II (RNAPII) transcription of ncRNAs is required for chromatin remodelling at the fission yeast Schizosaccharomyces pombe fbp1+ locus during transcriptional activation. The chromatin at fbp1+ is progressively converted to an open configuration, as several species of ncRNAs are transcribed through fbp1+. This is coupled with the translocation of RNAPII through the region upstream of the eventual fbp1+ transcriptional start site. Insertion of a transcription terminator into this upstream region abolishes both the cascade of transcription of ncRNAs and the progressive chromatin alteration. Our results demonstrate that transcription through the promoter region is required to make DNA sequences accessible to transcriptional activators and to RNAPII.

To expand on that just a bit, recall that chromatin is the form in which DNA is actually stored for safe keeping. It consists of the double-stranded DNA molecules wrapped around many protein complexes called nucleosomes. Before any stretch of DNA can actually be transcribed into messenger RNA, the DNA has to be unwound from the nucleosomes. The present research has determined that some long ncRNA takes part in this unwinding process.

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No more business as usual

Friday, November 14, 2008

A million thanks to SusanG at Daily Kos for mentioning this:

Obama's Victory: A Consumer-Citizen Revolt
As recently as this summer, while the economy unraveled (BusinessWeek, 7/14/08), I made two trips to Silicon Valley in the hopes of finding leaders who grasped the crisis—and the opportunity—inherent in the destruction of trust. I listened to Facebook executives but found them obsessed with how to monetize the site with advertising. Their users were not individuals, but "eyeballs." I asked Google (GOOG) CEO Eric Schmidt how he would develop and sustain the trust of his users. His response was to cite the provision of two classes of stock intended to insulate top management from investor pressures. I gave a talk on the crisis of trust. The response from self-described Internet court jester Esther Dyson was typical of what I had been hearing: "Personally, I'm not that concerned if people don't trust large institutions."

A few weeks later economic panic gripped the stock market. I flipped on ABC's Sunday morning news show with George Stephanopoulos only to hear economist Larry Summers explaining that the surprising depth of the economic meltdown was due to the loss of trust in institutions. What he didn't say was that this loss of trust is a vast sea whose level has been rising for decades. The subprime debacle and the ensuing credit freeze simply marked the moment when the sea wall was finally breached. ...

So can we invent a business model in which advocacy, support, authenticity, trust, relationship, and profit are linked? Can I write that sentence without invoking fear, disbelief, cynicism, or peals of laughter? The ugly practices that killed trust seem intractable to most people, whether they are the ones trapped inside the money machine or on the receiving end of its operations. But after this election, the answer to these questions has irreversibly changed. The answer today would have to be not only "yes we can" but also "yes we must."

No, this is not about "science" per se, unless one considers the philosophical side of economics (rather than the quantitative side) to be a science. Rather, it is the simple observation that anyone reading the daily news with an open mind can understand: Basing a modern large-scale economy primarily on the evolutionarily ancient motivation of greed and personal self-interest is not working out very well...

BDNF and depression

Tuesday, November 11, 2008

Back in March I wrote a little bit about the convoluted relationships among stress, learning, and memory (here). About the same time, I wrote about the relationship between memory and an important neural growth factor, BDNF (here).

It seems that BDNF is an important bridge connecting the topics of memory, stress, and depression. Back in March I also started to write more about how BDNF is linked to depression, but I got sidetracked. So the rest of this message is what I started to write about that connection, which is why the research covered is from March or earlier.

But before turning to that, it should be noted that there is more to say about the relationship between BDNF and stress, which I'll put off a little longer. There's also more to say about the relationship between BDNF and antidepressant drugs, some of which is more recent than March. I'll put that off too.

So let's just get into the older stuff about BDNF and depression, to start the ball rolling again.

Research has shown that one way in which BDNF is linked to depression is through the neurotransmitter serotonin – whose connection to mood, depression, anxiety, etc. is pretty well known (think Prozac).

In particular, BDNF seems to affect expression of the gene for the serotonin transporter (SERT). (The gene itself is called SLC6A4, which stands for "solute carrier family 6, member 4".) SERT is a cell membrane protein that transports serotonin from the synapse between neurons back into the neuron from whence it came – enabling "serotonin reuptake". Some forms of the gene for SERT seem to predispose individuals who carry it to mood disorder.

Here are some reports of recent research on BDNF, which give an idea of the variety of effects it has within the nervous system. (The summaries included here are mine.)

The yin and yang of genes for mood disorders (3/12/08)
This research studied conditions under which a variant of the gene for SERT (i. e. SLC6A4) predisposes the carrier to mood disorders. Apparently there are also at least two variants of the gene for BDNF. An individual with one form of BDNF is particularly susceptible to the deleterious form of the SERT gene, but with the other form of BDNF, an individual is completely protected against it.

Brain Chemistry Ties Anxiety And Alcoholism (3/4/08)
Production of BDNF is known to be stimulated by exposure to alcohol. The researchers in this study, whose leader author is Subhash Pandey, also knew from previous experiments that reduced levels of BDNF in the amygdalas of normal laboratory rats led to increased anxiety in the rats, followed by increased consumption of alcohol. The question was what happened due to deficiency of BDNF that increased anxiety, and how did consumption of alcohol reverse this effect by restoring BDNF.

It is also known that BDNF stimulate the production of another protein, Arc. If Arc could be suppressed in the amygdala even in the presence of normal levels of BDNF, and the rats experienced increased anxiety anyhow, this would show that it is probably a deficiency of Arc rather than of BDNF that is responsible for the anxiety. And indeed, when Arc was suppressed in spite or normal BDNF, the rats had higher anxiety. They also consumed more alcohol. But when Arc levels returned to normal, the anxiety returned to normal, and alcohol consumption did too.

The question then came down to how a deficiency of Arc increased anxiety. It was found that temporarily reduced levels of Arc resulted in reduced numbers of dendritic spines of neurons in the amygdala. Since axons of other neurons form synapses with dendritic spines, there will be fewer synapses when there are fewer spines. At the same time, anxiety also increased. Conversely, when levels of Arc returned to normal, either naturally or as a result of higher levels of BDNF due to alcohol consumption, the number of spines increased, and anxiety decreased. Once Arc had increased normally, alcohol consumption decreased too.

Earlier results: Brain Chemical Plays Critical Role In Drinking And Anxiety (8/8/06) – when expression of BDNF (which is regulated by CREB) is blocked, anxiety and alcohol consumption in rats increases.

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SIRT1 and cancer

Sunday, October 26, 2008

In the past we've had some discussion of the histone deacetylase (HDAC) enzyme SIRT1 and other related sirtuin proteins, especially with respect to their possible relationship with longevity. (See here, for example.)

Much of the focus has been on the HDAC properties of SIRT1 that can switch off various genes. But there have also been findings of more direct relations between SIRT1 and cancer. Some indicate that sirtuins, including SIRT1, may help suppress cancer in certain circumstances, while others suggest it may actually help promote cancer. We'll have to save a general discussion of this relationship for later.

But now we have some research that shows how SIRT1 is directly involved, and has a beneficial effect, in an important pathway that's quite relevant to breast cancer.

The background is that the BRCA1 gene (short for breast-cancer-associated gene 1) is a tumor suppressor gene that, when mutated, may lose its ability to suppress tumors. Defective BRCA1 is sometimes inherited, which helps explain familial tendencies to breast cancer.

So what does BRCA1 normally do to suppress tumors? Well, apparently it maintains expression of SIRT1, which in turn inhibits the expression of another protein, called Survivin. The latter is an inhibitor of programmed cell death (apoptosis), and therefore, when it is active, helps protect cancer cells, which might otherwise be killed by the immune system, chemotherapy, or radiation.

In a nutshell: defective BRCA1 leads to insufficient SIRT1, which leads to an inadequate ability to kill cancer cells.

New Findings May Improve Treatment Of Inherited Breast Cancer (10/9//08)
About 8% of breast cancer cases are caused by mutations in tumor suppressor genes, such as breast cancer associated gene-1 (BRCA1). BRCA1 is the most frequently mutated tumor suppressor gene found in inherited breast cancers and BRCA1 mutation carriers have a 50-80% risk of developing breast cancer by age 70. "Although work with animal models of BRCA1 mutation has provided some insight into the many biological processes linked with BRCA1, very little is known about the downstream mediators of BRCA1 function in tumor suppression," says lead study author Dr. Chu-Xia Deng from the Genetics of Development and Diseases Branch at the National Institutes of Health.

Dr. Deng and colleagues were interested in investigating the relationship among BRCA1, SIRT1 and Survivin. SIRT1 is a protein and histone deacetylase involved in numerous critical cell processes including metabolism, DNA repair and programmed cell death, known as apoptosis. Although SIRT1 has been implicated in tumorigenesis, no concrete role in cancer initiation or progression has been identified. Survivin is an apoptosis inhibitor that is dramatically elevated in many types of tumors. Research has suggested that Survivin may serve to maintain the tumor and promote growth.

The researchers found that BRCA1 functioned as a tumor suppressor by maintaining SIRT1 expression, which in turn inhibited Survivin expression. When BRCA1 was not functioning properly, SIRT levels decreased and Survivin levels increased, allowing BRCA1-deficient cells to overcome apoptosis and undergo malignant transformation.

This leads one to ask whether there are other ways that SIRT1 activation could be maintained when BRCA1 is defective. Fans of resveratrol will observe that this is something that resveratrol can do. And so the researchers gave it a try:
They went on to show that the compound resveratrol strongly inhibited BRCA1-mutant tumor growth in cultured cells and animal models. ... In the current paper, resveratrol enhanced SIRT1 activity, this leading to reduced Survivin expression and subsequent apoptosis of BRCA1 deficient cancer cells.

Ironically, previous research had indicated circumstances in which SIRT1 might promote growth of other types of cancers. It might, for instance, inhibit expression of other tumor-suppressor genes.

Another news account goes into this a little more:

Gene thought to promote tumor growth has opposite role in a kind of breast cancer (10/9/08)
These results were surprising in light of previous reports showing that high levels of SIRT1 enhance growth of other types of tumors. It now appears that SIRT1 can enhance or inhibit tumor growth — it all depends on the context, says Deng. ...

The researchers also found that a red wine chemical called resveratrol, recently touted as a powerful antiaging compound, was effective in combating BRCA1-associated tumor formation specifically.

How resveratrol is able to do this is unclear. “The work in this case is that SIRT1 has an antitumor effect, and this paper provides mechanistic insights into that,” comments Pere Puigserver, a Harvard biologist who studies SIRT1. But the resveratrol data should be taken with caution, he notes. While this new research clearly shows the direct relationship between BRCA1 and SIRT1, the direct link between resveratrol and SIRT1 is more difficult to demonstrate.

Nonetheless, molecular details of BRCA1-related breast cancer are emerging, and this new data places SIRT1 squarely inside the complex web of molecules that impact tumor growth.

One of the main reasons that sirtuins are suspected of having cancer-promoting properties in some circumstances is that they may inhibit the highly important p53 tumor suppressor gene. (P53, when functioning properly, promotes cell apoptosis when DNA defects are detected during cell division.) In just one example of many, here's research from earlier this year that suggests a tumor-promoting property of sirtuins:

Switching on cancer killer gene (5/8/08)
Scottish scientists have discovered how to control a major anti-tumour gene that could lead to more effective chemotherapy. According to a report in the Cancer Cell Journal, research conducted by the Universities of St Andrews and Dundee may eventually lead to the development of new cancer drugs.

The gene, called p53 and known as "the guardian of the genome", is damaged or switched off in most cancers. But the resrchers found that they could reboot it using two new biological compounds called "tenovins".

In a laboratory study, the academics found that these compounds could kick-start p53 by turning off enzymes called sirtuins. Sirtuins act like genetic switches and keep p53 under control, ensuring that the cells stay alive.

Other news accounts of this research: here, here.

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