Oscillator

There’s an excellent set of articles from Gizmodo this week “exploring the enhanced human future,” including:

-an interview with Michael Specter, “Synthetic Biology: Why Not Pursuing Crazy Biotech is dangerous”

-an article about tissue engineering and skin grafts: “Meat Band-Aids and Mass Production of Living Tissue”

-human/machine interfaces to enhance our hearing and sexual experiences (NSFW, obviously), replace our bowels after horrific motorcycle accidents, and much, much more!

According to gizmodo, this cyborg life is “about what happens when we treat our body less as a sacred object and more as what it is: Nature’s ultimate machine.” I find this stance fascinating, and perhaps too complicated for me to really think about now as I’m still recovering from an all too human cold, so I’ll leave off with some questions to mull over. Are we really machines, or does the ability to interface with non-living technology make us so? Is the dichotomy between “sacred objects” and “machines” a false binary? Is there another option? Are we really the ultimate machine? Can there be a pinnacle, an end, a goal for evolution?

via Seed via ScienceNow

earlyadaptor:

Craig Venter and colleagues compare consumer genetic tests and suggest ways to make them more useful.

An interesting study simply comparing the results from two different personal genomics companies. While the sequences sent back were almost perfectly matched, “For the seven diseases analyzed by the researchers, only about half of the risk factors provided by 23andme and Navigenics agreed for the five patients. For instance, for lupus and type 2 diabetes, three of the five subjects received conflicting results.”

The main difficulty with genomics these days isn’t the sequencing technology (although making it cheaper and even more accurate is always good), but in interpreting the data. Large-scale data collection like the Personal Genome Project will certainly help by connecting more and more data about people’s health to people’s sequences, but perhaps associations that are so hard to find may also be hard to generalize to the entire mail-order genomics population.