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Science

Submission + - SPAM: Nanomedicine kills brain cancer cells

destinyland writes: Scientists from the University of Chicago and the U.S. Department of Energy have developed the first nanoparticles that seek out and destroy GMB brain cancer cells. Nanoparticles killed up to 80% of the brain cancer cells after just five minutes of exposure to white light, showing the promise of nanomedicine — highly-specific intervention at the molecular scale. Because nanomedicine could repair brain cells or damaged nerve and muscle tissue, the NIH has established eight Nanomedicine Development Centers around the country for their Nanomedicine Roadmap Initiative. Researchers have also used gold nanospheres to search out and then "cook" skin cancer cells with light — "It's basically like putting a cancer cell in hot water and boiling it to death," says one researcher. And the NIH Roadmap ultimately predicts "novel tiny sensors... that search for, and destroy, infectious agents."
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Comment Re:Exomorons? (Score 1) 64

You see, exomorons have their stupidity on the outside, so we can determine at a glance that they're idiots. For our normal everyday endomorons, we have to talk to them for a while or observe their actions. If we can find some exomorons, we may be able (at a later date) to cross-breed them with endomorons and save everyone else a lot of time. Unfortunately, I have a sneaking suspicion that there may be selective pressures against displaying one's stupidity for all to see, so any species we create that does so may be doomed to extinction. I can only hope we make all the endomorons extinct first...

Comment Re:Story meaning? (Score 1) 313

One study after another cites the previous study, and almost no one knows where that 42 billion dollar figure came from, but it's impressive, so everyone continues to quote it.

Ars did an article on attempting to trace one such oft-quoted figure of losses, and slashdot discussed it. This $42 billion figure is probably from the same source.

tl;dr: big-dollar piracy numbers probably come from some unsubstantiated source from 1993 or earlier.

Comment Re:Sometimes better design beats better algorythms (Score 1) 87

This brings up an interesting point. The Netflix algorithm is working from flawed/incomplete data generated from poor design decisions, so no matter how good the algorithm gets it still won't be able to accurately predict what movies will actually interest people based on a very subjective unidimensional rating. For example, the same person might rate a movie differently under differing conditions, and the rating itself may hinge entirely on one thing in the movie (s)he did(n't) like, whereas the movie might have been overall pretty good. It's like asking someone, 'on a scale of 1 to 5, what is your favorite color?'; it has next to no relation to its supposed objective.

On top of all this, people are capricious at best when it comes to movie tastes; they might not even like a movie based on its own merits, but something completely orthogonal to the question such as it being the movie they saw on their first date. As such, no set of ratings from any given user can really be accurately matched with those of another to provide suggestions, since they may have liked/hated those movies for entirely separate reasons. Granted, some of these things can't easily be transcribed into data for formulaic processing, but you'd think Netflix could at least add an optional 'detailed rating' section (e.g., rate by pace, plot, action, acting, dialogue, etc.) to better describe why a user did or didn't like a flick.

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