Posted: 28 Aug 2008 04:27 PM CDT
Along with chimps, orangutans, elephants, and dolphins, some birds are smart enough to recognize themselves in the mirror. We're naturally inclined to think of mammals as the creatures most likely to have a developed sense of self, but it turns out that magpies are also quite self-aware.
How do you know when an animal recognizes itself in the mirror? You need some way to tell whether an animal thinks a mirror image is another animal, or whether the animal recognizes itself.
Researchers get at this problem by marking the animal in some way and watching how it behaves. In this case, a group of German researchers stuck a yellow sticker on the bird, in a place where the bird would only notice the sticker when looking in a mirror:
Image from Prior, et. al, PLoS Biology 6(8): e202
The test birds, seeing the sticker in the mirror image, frequently started searching their own bodies for the mark - a sign that these birds knew they were looking at an image of themselves.
These results add to the evidence that, like some mammals, certain bird species have brains that can carry out more complex cognitive functions. Most animals don't have much use for the kind of self-awareness exhibited in this mirror test. But self-awareness can be useful, the German researchers argue: in the social environment of these birds, more self-aware individuals might be better at using past experience to predict the behavior of other birds in their social group.
Posted: 28 Aug 2008 11:35 AM CDT
Mumps was a common childhood disease when I was a child. We grew up learning that it was better to get mumps as a child because getting it as an adult would make you sterile. No doubt that idea arose from symptoms like swollen glands, swollen testicles, etc. When I looked in PubMed though, I couldn't find much data on sterility (at least not easily).
I did find data on hearing loss.Read the rest of this post... | Read the comments on this post...
Posted: 28 Aug 2008 09:55 AM CDT
This looks pretty cool. They propose a method of doing association studies by considering several SNPs at once instead of one SNP at a time. Even though this makes biological sense, it seems like the analysis would get messy and cumbersome. They seem to address these issues and analyze their method on previous data sets. They use a "Bayesian inspired" method called: stochastic search maximisation algorithm.
I'll need to read this paper more closely to see exactly how this method compares to previous single-SNP analyses, one of which, they describe in the paper, is on T2D.
Simultaneous Analysis of All SNPs in Genome-Wide and Re-Sequencing Association Studies
Clive J. Hoggart, John C. Whittaker, Maria De Iorio, David J. Balding
PLoS Genetics 4(7)
Abstract: Testing one SNP at a time does not fully realise the potential of genome-wide association studies to identify multiple causal variants, which is a plausible scenario for many complex diseases. We show that simultaneous analysis of the entire set of SNPs from a genome-wide study to identify the subset that best predicts disease outcome is now feasible, thanks to developments in stochastic search methods. We used a Bayesian-inspired penalised maximum likelihood approach in which every SNP can be considered for additive, dominant, and recessive contributions to disease risk. Posterior mode estimates were obtained for regression coefficients that were each assigned a prior with a sharp mode at zero. A non-zero coefficient estimate was interpreted as corresponding to a significant SNP. We investigated two prior distributions and show that the normal-exponential-gamma prior leads to improved SNP selection in comparison with single-SNP tests. We also derived an explicit approximation for type-I error that avoids the need to use permutation procedures. As well as genome-wide analyses, our method is well-suited to fine mapping with very dense SNP sets obtained from re-sequencing and/or imputation. It can accommodate quantitative as well as case-control phenotypes, covariate adjustment, and can be extended to search for interactions. Here, we demonstrate the power and empirical type-I error of our approach using simulated case-control data sets of up to 500 K SNPs, a real genome-wide data set of 300 K SNPs, and a sequence-based dataset, each of which can be analysed in a few hours on a desktop workstation.
Posted: 28 Aug 2008 08:56 AM CDT
Posted: 28 Aug 2008 08:20 AM CDT
Okay so maybe it’s not so new since the book’s been out for several months…Anyway, my review of Masha Gessen’s Blood Matters: From Inherited Illness to Designer Babies, How the World and I Found Ourselves in the Future of the Gene, appears in the current issue of Nature Genetics:
Posted: 28 Aug 2008 05:44 AM CDT
I’ve just come back from the dentist. I had a root canal treatment for my toothache.
That was lots of fun.
I think I’ll go and get some nice paper cuts now; maybe pour some lemon in them….
Posted: 28 Aug 2008 04:15 AM CDT
Did anyone actually read GINA (Genetic Information Nondiscrimination Act) before lauding it for protecting the public or condemning it as over-regulation?
From GINA at The Library of Congress:
So, according to this:
Um, isn’t this is the worst for both effective health care and patient fairness? Doesn’t this mean that health plans can simply demand any genetic test when deciding payment (and hold that decision hostage to get that test… and what if a decision is urgent)? Doesn’t this mean that health care will be institutionally less effective because rather than instituting a single, preventive genomic test to be consulted to make better medical decisions for one’s entire life(which GINA makes illegal), instead, patients will only get ad-hoc and myopic genomic tests as demanded by health plans for payment decisions? Won’t this make health care less effective while creating a new market for inefficient, interventionist specialty genomic tests?
So, what happens when a project like the Coriell Personal Medicine Collaborative shows that using genomic personalized health care makes health care better and cheaper?
I’m embarrassed that I relied on the hype surrounding GINA and didn’t read the law to form my own opinions.
Further, if I’m right about this (I want to consult a lawyer), I’d be deeply embarrassed for the journalists and industry representatives who should have noted this rather than publishing fluffy, feel-good fed PR. Hypothetically. I’m going to get a legal opinion before I start stomping around, naming names, and posting links!
Posted: 28 Aug 2008 02:56 AM CDT
Actually, I have no particular reason to believe that Neanderthals should be dumber than Homo sapience. Well, they were around for thousands of years with very little if any development in the kind of tools they used (or left behind, in any case) while we have managed to improve on tool design quite frequently.
At least lately, I don’t know how fast we were innovating in the stone age.
In any case, what I wanted to go with this is to this page that describes a study of Neanderthal and Homo sapience tools and conclude that they were equally efficient.
Does this mean that Neanderthals were as smart as us? I guess it doesn’t necessarily, but at least they were as technically advanced.
How did we outcompete them, exactly, and why are they gone?
Posted: 28 Aug 2008 12:13 AM CDT
Image via Wikipedia All of you know about it already, but I shall happily add to the noise. Last evening I had one of those “Holy S**t” moments. Was sitting in a coffee shop, catching up with the days news, when I saw a flurry of activity on Friendfeed around Ubiquity. Turns out Ubiquity is a new project by Mozilla Labs, which for want of a better description is like Quicksilver for the browser, a mini command line available with an Alt-space.
Ubiquity for Firefox from Aza Raskin on Vimeo.
Ubiquity is still young, and may never catch on although I have a feeling it will, at least among the geek crowd, and being a Firefox plugin = low friction. But you can see the promise right away. You can, very quickly, using simple commands access search, Wikipedia, maps, insert material into documents, send email, etc.
Here are some examples
But that’s just a start. It doesn’t take a leap of faith to see entire vocabularies being created to support certain data types and activities. An early example comes from Rajarshi Guha, who very quickly rustled up a couple of commands. Maybe we can have a repository somewhere someday for a set of standardized commands in bioinformatics/cheminformatics
The example above isn’t quite working perfectly, but you can see what we can do, and this is just the tip of the iceberg. There are a lot of mashups possible, including getting related papers, targets, compounds, structures, and being able to package them up and email them, or put them in a document, and as our web gets a little more structured, I can imagine myself sitting inside that command line and following an entire graph of information that streams through, ready to be manipulated and used for something even more interesting.
The web is a moving target, our browsers are moving targets, our capabilities to manipulate are moving targets, and efforts like Ubiquity show us a glimpse into the future. Will be fun being part of that future (and blogging about it)
Update: I should have known Pawel would take a stab. An even cooler example (Sorry Rajarshi, I like proteins better)
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Posted: 27 Aug 2008 08:41 PM CDT
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