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Statistical validation of results, as Shaffer described it, simply involves testing the null hypothesis: that the pattern you detect in your data occurs at random. If you can reject the null hypothesis—and science and medicine have settled on rejecting it when there's only a five percent or less chance that it occurred at random—then you accept that your actual finding is significant. The problem now is that we're rapidly expanding our ability to do tests. Various speakers pointed to data sources as diverse as gene expression chips and the Sloan Digital Sky Survey, which provide tens of thousands of individual data points to analyze. At the same time, the growth of computing power has meant that we can ask many questions of these large data sets at once, and each one of these tests increases the prospects than an error will occur in a study; as Shaffer put it, "every decision increases your error prospects." She pointed out that dividing data into subgroups, which can often identify susceptible subpopulations, is also a decision, and increases the chances of a spurious error. Smaller populations are also more prone to random associations. In the end, Young noted, by the time you reach 61 tests, there's a 95 percent chance that you'll get a significant result at random. And, let's face it—researchers want to see a significant result, so there's a strong, unintentional bias towards trying different tests until something pops out. Young went on to describe a study, published in JAMA, that was a multiple testing train wreck: exposures to 275 chemicals were considered, 32 health outcomes were tracked, and 10 demographic variables were used as controls. That was about 8,800 different tests, and as many as 9 million ways of looking at the data once the demographics were considered.

The team observed viruses as they evolved over hundreds of generations to infect bacteria. They found that when the bacteria could evolve defences, the viruses evolved at a quicker rate and generated greater diversity, compared to situations where the bacteria were unable to adapt to the viral infection. The study shows, for the first time, that the American evolutionary biologist Leigh Van Valen was correct in his 'Red Queen Hypothesis'. The theory, first put forward in the 1970s, was named after a passage in Lewis Carroll's Through the Looking Glass in which the Red Queen tells Alice, 'It takes all the running you can do to keep in the same place'. This suggested that species were in a constant race for survival and have to continue to evolve new ways of defending themselves throughout time. Dr Steve Paterson, from the University's School of Biosciences, explains: "Historically, it was assumed that most evolution was driven by a need to adapt to the environment or habitat. The Red Queen Hypothesis challenged this by pointing out that actually most natural selection will arise from co-evolutionary interactions with other species, not from interactions with the environment. "This suggested that evolutionary change was created by 'tit-for-tat' adaptations by species in constant combat. This theory is widely accepted in the science community, but this is the first time we have been able to show evidence of it in an experiment with living things." Dr Michael Brockhurst said: "We used fast-evolving viruses so that we could observe hundreds of generations of evolution. We found that for every viral strategy of attack, the bacteria would adapt to defend itself, which triggered an endless cycle of co-evolutionary change. We compared this with evolution against a fixed target, by disabling the bacteria's ability to adapt to the virus. "These experiments showed us that co-evolutionary interactions between species result in more genetically diverse populations, compared to instances where the host was not able to adapt to the parasite. The virus was also able to evolve twice as quickly when the bacteria were allowed to evolve alongside it."

"As far as we can tell, this is the first time this type of behavior has been reported in cells that are part of a larger organism," says Peter T. Cummings, John R. Hall Professor of Chemical Engineering, who directed the study that is described in the March 10 issue of the Public Library of Science journal PLoS ONE. The discovery was the unanticipated result of a study the Cummings group conducted to test the hypothesis that the freedom with which different cancer cells move - a concept called motility - could be correlated with their aggressiveness: That is, the faster a given type of cancer cell can move through the body the more aggressive it is. "Our results refute that hypothesis—the correlation between motility and aggressiveness that we found among three different types of cancer cells was very weak," Cummings says. "In the process, however, we began noticing that the cell movements were unexpectedly complicated." Then the researchers' interest was piqued by a paper that appeared in the February 2008 issue of the journal Nature titled, "Scaling laws of marine predator search behaviour." The paper contained an analysis of the movements of a variety of radio-tagged marine predators, including sharks, sea turtles and penguins. The authors found that the predators used a foraging strategy very close to a specialized random walk pattern, called a Lévy walk, an optimal method for searching complex landscapes. At the end of the paper's abstract they wrote, "...Lévy-like behaviour seems to be widespread among diverse organisms, from microbes to humans, as a 'rule' that evolved in response to patchy resource distributions." This gave Cummings and his colleagues a new perspective on the cell movements that they were observing in the microscope. They adopted the basic assumption that when mammalian cells migrate they face problems, such as efficiently finding randomly distributed targets like nutrients and growth factors, that are analogous to those faced by single-celled organisms foraging for food. With this perspective in mind, Alka Potdar, now a post-doctoral fellow at Case Western Reserve University and the Cleveland Clinic, cultured cells from three human mammary epithelial cell lines on two-dimensional plastic plates and tracked the cell motions for two-hour periods in a "random migration" environment free of any directional chemical signals. Epithelial cells are found throughout the body lining organs and covering external surfaces. They move relatively slowly, at about a micron per minute which corresponds to two thousandths of an inch per hour. When Potdar carefully analyzed these cell movements, she found that they all followed the same pattern. However, it was not the Lévy walk that they expected, but a closely related search pattern called a bimodal correlated random walk (BCRW). This is a two-phase movement: a run phase in which the cell travels primarily in one direction and a re-orientation phase in which it stays in place and reorganizes itself internally to move in a new direction. In subsequent studies, currently in press, the researchers have found that several other cell types (social amoeba, neutrophils, fibrosarcoma) also follow the same pattern in random migration conditions. They have also found that the cells continue to follow this same basic pattern when a directional chemical signal is added, but the length of their runs are varied and the range of directions they follow are narrowed giving them a net movement in the direction indicated by the signal.

The ability of NASA's Mars Reconnaissance Orbiter to continue charting the locations of these hidden glaciers and ice-filled valleys -- first confirmed by radar two years ago -- adds clues about how these deposits may have been left as remnants when regional ice sheets retreated. The subsurface ice deposits extend for hundreds of kilometers, or miles, in the rugged region called Deuteronilus Mensae, about halfway from the equator to the Martian north pole. Jeffrey Plaut of NASA's Jet Propulsion Laboratory, Pasadena, Calif., and colleagues prepared a map of the region's confirmed ice for presentation at this week's 41st Lunar and Planetary Science Conference near Houston. The Shallow Radar instrument on the orbiter has obtained more than 250 observations of the study area, which is about the size of California. "We have mapped the whole area with a high density of coverage," Plaut said. "These are not isolated features. In this area, the radar is detecting thick subsurface ice in many locations." The common locations are around the bases of mesas and scarps, and confined within valleys or craters. Plaut said, "The hypothesis is the whole area was covered with an ice sheet during a different climate period, and when the climate dried out, these deposits remained only where they had been covered by a layer of debris protecting the ice from the atmosphere."