Cancer is even more complicated than we thought

There's some really interesting—and rather disturbing—research coming out of the UK on the nature of cancer cells and why advanced-stage cancers are so difficult to treat.

Scientists have long known that the same type of cancer can play out in very different ways, from a genetic perspective, in one patient compared to another. But this new research shows that, even within the same patient—even within the same tumor—different samples of cancer cells have more genetic differences than they have similarities.

That's a very big deal. It means that cancer cells aren't just cells that grow uncontrollably. They also mutate. Which means that they evolve. That fact has serious implications for cancer treatment. Just like bacteria can evolve to become resistant to antibiotics, cancer cells can evolve resistance to the treatments we throw at them. At Not Exactly Rocket Science, Ed Yong explains how this discovery fits into the bigger picture of why curing cancer is so damned difficult:

For a start, cancer isn’t a single disease, so we can dispense with the idea of a single “cure”. There are over 200 different types, each with their own individual quirks. Even for a single type – say, breast cancer – there can be many different sub-types that demand different treatments. Even within a single subtype, one patient’s tumour can be very different from another’s. They could both have very different sets of mutated genes, which can affect their prognosis and which drugs they should take.

And now we know that's true within a tumor, as well. Read the rest

Scary science, national security, and open-source research

I've been following the story about the scientists who have been working to figure out how H5N1 bird flu might become transmissible from human to human, the controversial research they used to study that question, and the federal recommendations that are now threatening to keep that research under wraps. This is a pretty complicated issue, and I want to take a minute to help you all better understand what's going on, and what it means. It's a story that encompasses not just public health and science ethics, but also some of the debates surrounding free information and the risk/benefit ratio of open-source everything.

H5N1, the famous bird flu, is deadly to humans. Of the 566 people who have contracted this form of influenza, 332 have died. But, so far, the people who have caught bird flu don't seem to have contracted the disease from other humans, or passed it on. Instead, they got it from birds, often farm animals with whom the victims were living in close contact. H5N1 was first identified 14 years ago, and there's never been a documented case of it being passed from person to person.

But that doesn't mean such a leap is impossible.

That's because of how the influenza virus works. Influenza is made up of eight pieces of RNA, containing 10 genes, and they all replicate independently of one another and there's no system for error correction*. That means you have more opportunity for mutations to arise that change what the virus does and who it can infect. Read the rest

Time-lapse video of lab-grown snowflakes

Back in December, researchers at Caltech posted a research paper to arXiv that attempts to explain why the shape and structure of snowflakes change significantly depending on relatively small shifts in temperature.

In order to study this, they had to grow snowflakes in laboratory conditions. It was not an easy thing to figure out how to do. On his Snowcrystals page, physicist Kenneth G. Libbrecht show you how it's done.

There are many ways to grow snowflakes, but my favorite starts with something called a vapor diffusion chamber. This is essentially nothing more than an insulated box that is kept cold on the bottom (say -40C) and hot on the top (say +40C). A source of water is placed at the top, and water vapor diffuses down through the box, producing supersaturated air. The cold, supersatured air at the center of the chamber is ideal for growing ice crystals.

While working with this diffusion chamber, we rediscovered a wonderful technique for growing synthetic snow crystals that was first published in 1963 by meteorologist Basil Mason and collaborators [1]. One starts by putting a wire into the diffusion chamber from below, so that small ice crystals begin growing on the wire's tip. Then apply a high voltage to the wire, say +2000 volts, and voila -- slender ice needles begin growing from the wire.

Video Link Read the rest

Fish mimics mimic octopus

This is a great find by Not Exactly Rocket Science's Ed Yong. A tourist and a couple of researchers from the California Academy of Sciences have documented an instance of Pacific-dwelling jawfish hiding from predators by blending into the stripes of well-known camouflage guru, the mimic octopus.

This relationship is probably a rare occurrence. The black-marble jawfish is found throughout the Pacific from Japan to Australia, while the mimic octopus only hangs around Indonesia and Malaysia. For most of its range, the jawfish has no octopuses to hide against. Instead, Ross and Rocha think that this particular fish is engaging in “opportunistic mimicry”, taking advantage of a rare chance to share in an octopus’s protection.

Video Link

Thanks, Atvaark! Read the rest

Forecast uncertain: Chaos theory, weather prediction, and brain cancer

A diagnosis of brain cancer is basically a death sentence. It's a terrible thing for anyone to deal with, and it's only made worse by all the uncertainty. Doctors don't really understand how brain cancer works very well. Beyond death, there's often not a lot that they can tell patients about what to expect—how the cancer will affect the brain, how fast it will spread, where it will spread to.

Eric Kostelich is one of the researchers who is trying to change that, by approaching the problem of brain cancer  from a new angle. Kostelich is a mathematician. In particular, he's interested in how we can use math to better predict the behavior of complex and chaotic systems. Right now, this mostly means that he studies the weather. In fact, he's part of a team that developed a new algorithm for weather prediction, called the Local Ensemble Transform Kalman Filter. But Kostelich thinks that the LETKF could have applications outside the nightly news.

In a recent study, published December 21 in Biology Direct, he joined forces with cancer researchers, to see whether the statistical methods that make chaotic weather patterns more predictable could do the same thing for chaotic behavior in cancer cells. The results are promising. A couple of weeks ago, I spoke to Kostelich to find out more about the history of forecasting uncertainty, how algorithms like LETKF work, and what we might learn if we apply these systems to cancer. 

 Maggie Koerth-Baker: When you set out to apply the methods used to forecast the weather to cancer, why did you choose brain cancer?  Read the rest

Coffee: An antidepressant and religion preventative?

A recently published study found a correlation between higher rates of coffee drinking in women and decreased risk of depression. Naturally, that finding made headlines. But blogger Scicurious has a really nice analysis of the paper that picked up a significant flaw in the way the data is being interpreted. There was a correlation between drinking more coffee and a lowered risk of depression. But that wasn't the only correlation the researchers found—just the only correlation they made a big deal of in their conclusions.

On her blog, Scicurious lists the other correlations and explains why it's hard to draw any solid conclusion from this data set:

1) Smoking. The interaction between depression risk, smoking, and coffee consumption was “marginally” significant (p=0.06), but they dismiss it as being due to chance because it was “unexpected”. Um. Wait. Nicotine is a STIMULANT. It is known to have antidepressant like effects in animal models (though the withdrawal is no fun). This is not unexpected.

2) Drinking: heavy coffee drinkers drink more. But note that they don’t say that drinking coffee puts you at risk for drinking alcohol.

3) Obesity: heavy coffee drinkers are, on average, thinner, but not more physically active. They do not conclude that coffee drinking prevents obesity.

4) Church going: heavy coffee drinkers are less likely to go to church. Less likely to go to church, less likely to develop depression…heck, forget depression, maybe coffee prevents religion now! Now THAT would be a heck of a finding.

Here’s the thing.

Read the rest