I found this at Uncommon Descent:

When we visited the zoo the other day, my wife snapped this photo just outside of the Panda play area. I guess when they put together the verbage for the sign, they neglected to consult Gould because I didn’t read “looks jury-rigged” anywhere on there.

Further down in the comment thread, Markus Rammerstorfer has posted snippets from a Nature article on the Panda's Thumb:

The way in which the giant panda, Ailuropoda melanoleuca, uses the radial sesamoid bone — its ‘pseudo-thumb’ — for grasping makes it one of the most extraordinary manipulation systems in mammalian evolution..... We have shown that the hand of the giant panda has a much more refined grasping mechanism than has been suggested in previous morphological models.
Endo, H et al. (1999): Role of the giant panda’s ‘pseudo-thumb’ Nature 397: 309-310

Sub-optimality is not, of course, a decisive blow to ID. Nevertheless, it's nice to see another example of how first assumptions based on evolutionary theory have been proven incorrect by further research. At the very least, it shows that sub-optimality claims need to be based on solid research, and not the ad-hoc "it is obviously not optimal" claim which passes for an argument against design in some circles.

There is an interesting exchange going on between Salvador Cordova of Uncommon Descent and Dave Thomas of Panda's Thumb.

First, Dave posts about his genetic algorithm for finding Steiner trees ("the shortest networks of straight-line segments connecting a given collection of fixed points"). He claims his algorithm (explained in detail in an earlier post) is not targeted because it does not contain the optimal solution, but selects for incrementally better ones randomly. He challenges ID'ers to come up with a solution to the 6-node Steiner Tree problem. I think his aim was to prove how much better his genetic algorithm was than the intelligent attempts of design proponents.

Next, Salvador responds with a genetic algorithm he designed, which correctly finds the sum of the first 1,000 integers. The algorithm does not have a direct target (i.e., it is not explicitly searching for the answer), but instead uses Gauss's algorithm - obviously targeted in a secondary sort of way, which he implies is akin to Dave's Steiner tree algorithm.

Finally, Dave insists his algorithm is not targeted and is in no way analagous to Salvador's, which is blatantly targeted, and Salvador replies that of course his algorithm is targeted, and that the smoke and mirrors in his algorithm are indeed similar to Dave's.

The contentious issue here is what, exactly, constitutes a "target". Salvador's point is that if your cost function is intentionally designed to approach the solution you are looking for, the absense of the actual optimum value is a technicality. Dave's algorithm is clearly only good at finding Steiner trees because he designed the cost function to reward better Steiner trees. As johnnyb points out in a comment to Salvador's latest reply:

The problem is that the fitness function cannot be directly related to the problem being solved. Natural selection simply says the animal must survive or be better at reproduction, but somehow guides processes such as eye formation. Therefore, in a fitting scenario the selection algorithm should not directly correspond with what you are searching for, in fact there should be a large disconnect.

 This is exactly right, and so succinct I wish I'd come up with it myself. There may or may not be a genetic algorithm for constructing a structure like the human eye (depending on the number and structure of interdependencies between its parts). If one exists, then its cost function will be specifically designed for producing an object like the eye, whether the "target" is explicit or not. There is no evidence that a vague cost function like "survive" is capable of doing anything interesting.

A recent article in Nature explored the means by which certain proteins called chaperonins work. Chaperonins are proteins which help other proteins fold correctly. Specifically, they provide a "cage" in which the target protein can fold without interference. Artificially growing or shrinking the size of the cage can make certain proteins fold more quickly or slowly, but the overall size of the cage seems to be optimal given the number of proteins which this chaperonin interacts with.

Because the cell is so crowded with large molecules, it is energetically favorable for newly transcribed proteins to fold compactly, reducing the volume they occupy. If it weren't for chaperonins, this tendency would cause partially complete amino acid chains to bind with each other (there are many of these chains in close proximity because mRNA is transcribed by many ribosomes at once).

The upshot is that chaperonins use the energetic effects of crowding to stimulate folding while at the same time eliminating the negative effects of crowding - promiscuous binding to anything in the area. This is a neat trick. In the final paragraph of the article, the author (who, of course, credits natural selection with chaperonin design) even exhorts human designers to follow the example of chaperonins:

It is a testament to the ingenuity of natural selection that the chaperonin cage not only combats aggregation caused by crowding outside the cage but also uses crowding to accelerate protein folding inside the cage. Nanoengineers trying to improve the yield of therapeutic proteins could profit from studying the tricks of the chaperonin nanocage.

PZ Meyers has an interesting (and a bit over-my-head) post on the evolution median-fins over at his blog Pharyngula. Snipping the biology and leaving the punchline, he says:

A story is beginning to emerge, though, that shows that midline fin development and evolution is a wonderful example of a general principle: modularity and the reuse of hierarchies of genes.... The redeployment of previously refined genetic modules is going to turn out to be a universal property of evolved systems, I expect.

Modularity (perhaps even hierarchical modularity) in biological systems is becoming more and more evident, and I agree that we should expect to see a lot more of it in the future. But which is a more likely source of good engineering principles like modularity? Stochastic processes, or intelligence? Might there be different sorts or degrees of modularity that could serve as predictions of one theory or the other? In particular, is there any sort of modularity that is not predicted by evolutionary theory?

This past week, Kansas Republican primary voters removed two conservatives from the Kansas Board of Education. The board now has a majority of evolution-only members, and the state's science standards (which currently call for the teaching of both the strengths and weaknesses of Darwinian theory) will likely be changed.

The Washington Post weighs in with an editorial. I would like to critique some of the statements made in this editorial.

The trouble with this liberal-seeming pose is that there is no scientific controversy over whether evolution happens or over its essential mechanisms.

Of course evolution happens. Evolution is simply non-cyclical change over time. The main question is whether blind evolutionary processes can possibly explain 1) the emergence of the first life 2) the full diversity of life. Should students be able to know that there is no real scientific consensus on how the first life originated?

Intelligent design can lead only to unintelligent students, or at least badly educated ones.

I think that a well-educated student should know about both intelligent design and evolution. And I do not see any problem with discussing the potential criticisms of Darwinian theory in the science classes of public schools.

AP reports, "After 10 years, life-on-Mars rebuked." The absence of even simple life in planets other than Earth appears to strengthen the Privileged Planet argument. By the way, you can watch the Privileged Planet documentary here (.ram file) with RealPlayer.

I found this sentence in the AP article interesting:

Some bacteria produce extraordinarily small and pure magnetite crystals, then align the magnetic grains to make a microscopic compass needle that helps them navigate.

I did not know that bacteria were that clever.

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