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George Whitesides has developed a prototype for paper "chip" technology that could be used in the developing world to cheaply diagnose deadly diseases such as HIV, malaria, tuberculosis, hepatitis and gastroenteritis. The first products will be available in about a year, he said. His efforts, which find their inspiration from the simple designs of comic books and computer chips, are surprisingly low-tech and cheap. Patients put a drop of blood on one side of the slip of paper, and on the other appears a colorful pattern in the shape of a tree, which tells medical professionals whether the person is infected with certain diseases. Water-repellent comic-book ink saturates several layers of paper, he said. The ink funnels a patient's blood into tree-like channels, where several layers of treated paper react with the blood to create diagnostic colors. It's not entirely unlike a home pregnancy test, Whitesides said, but the chips are much smaller and cheaper, and they test for multiple diseases at once. They also show how severely a person is infected rather than producing only a positive-negative reading.

This is the largest nationally representative study to date of the toll taken by sepsis and pneumonia, two conditions often caused by deadly microbes, including the antibiotic-resistant bacteria MRSA. Such infections can lead to longer hospital stays, serious complications and even death. "In many cases, these conditions could have been avoided with better infection control in hospitals," said Ramanan Laxminarayan, Ph.D., principal investigator for Extending the Cure, a project examining antibiotic resistance based at the Washington, D.C. think-tank Resources for the Future. "Infections that are acquired during the course of a hospital stay cost the United States a staggering amount in terms of lives lost and health care costs," he said. "Hospitals and other health care providers must act now to protect patients from this growing menace." Laxminarayan and his colleagues analyzed 69 million discharge records from hospitals in 40 states and identified two conditions caused by health care-associated infections: sepsis, a potentially lethal systemic response to infection and pneumonia, an infection of the lungs and respiratory tract. The researchers looked at infections that developed after hospitalization. They zeroed in on infections that are often preventable, like a serious bloodstream infection that occurs because of a lapse in sterile technique during surgery, and discovered that the cost of such infections can be quite high: For example, people who developed sepsis after surgery stayed in the hospital 11 days longer and the infections cost an extra $33,000 to treat per person. Even worse, the team found that nearly 20 percent of people who developed sepsis after surgery died as a result of the infection. "That's the tragedy of such cases," said Anup Malani, a study co-author, investigator at Extending the Cure, and professor at the University of Chicago. "In some cases, relatively healthy people check into the hospital for routine surgery. They develop sepsis because of a lapse in infection control—and they can die." The team also looked at pneumonia, an infection that can set in if a disease-causing microbe gets into the lungs—in some cases when a dirty ventilator tube is used. They found that people who developed pneumonia after surgery, which is also thought to be preventable, stayed in the hospital an extra 14 days. Such cases cost an extra $46,000 per person to treat. In 11 percent of the cases, the patient died as a result of the pneumonia infection.

By reworking a theory first proposed by physicists in the 1920s, the researchers discovered a new way to predict important characteristics of a new material before it's been created. The new formula allows computers to model the properties of a material up to 100,000 times faster than previously possible and vastly expands the range of properties scientists can study. "The equation scientists were using before was inefficient and consumed huge amounts of computing power, so we were limited to modeling only a few hundred atoms of a perfect material," said Emily Carter, the engineering professor who led the project. "But most materials aren't perfect," said Carter, the Arthur W. Marks '19 Professor of Mechanical and Aerospace Engineering and Applied and Computational Mathematics. "Important properties are actually determined by the flaws, but to understand those you need to look at thousands or tens of thousands of atoms so the defects are included. Using this new equation, we've been able to model up to a million atoms, so we get closer to the real properties of a substance." By offering a panoramic view of how substances behave in the real world, the theory gives scientists a tool for developing materials that can be used for designing new technologies. Car frames made from lighter, strong metal alloys, for instance, might make vehicles more energy efficient, and smaller, faster electronic devices might be produced using nanowires with diameters tens of thousands of times smaller than that of a human hair.

"People tend to conform their factual beliefs to ones that are consistent with their cultural outlook, their world view," Braman says. The Cultural Cognition Project has conducted several experiments to back that up. Participants in these experiments are asked to describe their cultural beliefs. Some embrace new technology, authority and free enterprise. They are labeled the "individualistic" group. Others are suspicious of authority or of commerce and industry. Braman calls them "communitarians." In one experiment, Braman queried these subjects about something unfamiliar to them: nanotechnology — new research into tiny, molecule-sized objects that could lead to novel products. "These two groups start to polarize as soon as you start to describe some of the potential benefits and harms," Braman says. The individualists tended to like nanotechnology. The communitarians generally viewed it as dangerous. Both groups made their decisions based on the same information. "It doesn't matter whether you show them negative or positive information, they reject the information that is contrary to what they would like to believe, and they glom onto the positive information," Braman says.

"Basically the reason that people react in a close-minded way to information is that the implications of it threaten their values," says Dan Kahan, a law professor at Yale University and a member of The Cultural Cognition Project. Kahan says people test new information against their preexisting view of how the world should work. "If the implication, the outcome, can affirm your values, you think about it in a much more open-minded way," he says. And if the information doesn't, you tend to reject it. In another experiment, people read a United Nations study about the dangers of global warming. Then the researchers told the participants that the solution to global warming is to regulate industrial pollution. Many in the individualistic group then rejected the climate science. But when more nuclear power was offered as the solution, says Braman, "they said, you know, it turns out global warming is a serious problem."And for the communitarians, climate danger seemed less serious if the only solution was more nuclear power.

In his new book, "The Double Helix and the Law of Evidence" (Harvard University Press), Kaye focuses on the intersection of science and law, and emphasizes that DNA evidence is merely information. "There's a popular perception that with DNA, you get results," Kaye said. "You're either guilty or innocent, and the DNA speaks the truth. That goes too far. DNA is a tool. Perhaps in many cases it's open and shut, in other cases it's not. There's ambiguity."

One of the book's key themes is that using science in court is hard to do right. "It requires lawyers and judges to understand a lot about the science," Kaye noted. "They don't have to be scientists or technicians, but they do have to know enough to understand what's going on and whether the statements that experts are making are well-founded. The lawyers need to be able to translate that information into a form that a judge or a jury can understand." Kaye also believes that lawyers need to better understand statistics and probability, an area that has traditionally been neglected in law school curricula. His book attempts to close this gap in understanding with several sections on genetic science and probability. The book also contends that scientists, too, have contributed to the false sense of certainty, when they are so often led by either side of one particular case to take an extreme position. Scientists need to approach their role as experts less as partisans and more as defenders of truth. Aiming to be a definitive history of the use of DNA evidence, "The Double Helix and the Law of Evidence" chronicles precedent-setting criminal trials, battles among factions of the scientific community and a multitude of issues with the use of probability and statistics related to DNA. From the Simpson trial to the search for the last Russian Tsar, Kaye tells the story of how DNA science has impacted society. He delves into the history of the application of DNA science and probability within the legal system and depicts its advances and setbacks.

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.

During evolution, living species have adapted to environmental constraints according to the mechanism of natural selection; when a mutation that aids the survival (and reproduction) of an individual appears in the genome, it then spreads throughout the rest of the species until, after several hundreds or even thousands of generations, it is carried by all individuals. But does this selection, which occurs on a specific gene in the genome of a species, also occur on the same gene in neighboring species? On which set of genes has natural selection acted specifically in each species? Researchers in the Dynamique et Organisation des Génomes team at the Institut de Biologie of the Ecole Normale Supérieure (CNRS/ENS/INSERM) have studied the genome of humans and three other primate species (chimpanzee, orangutan and macaque) using bioinformatics tools. Their work consisted in comparing the entire genomes of each species in order to identify the genes having undergone selection during the past 200,000 years. The result was that a few hundred genes have recently undergone selection in each of these species. These include around 100 genes detected in man that are shared by two or three other species, which is twice as many as might be anticipated as a random phenomenon. Thus a not inconsiderable proportion of the genes involved in human adaptation are also present in the chimpanzee, orangutan or macaque, and sometimes in several species at the same time. Natural selection acts not only by distancing different species from each other when new traits appear. But by acting on the same gene, it can also give rise to the same trait in species that have already diverged, but still have a relatively similar genome. This study thus provides a clearer understanding of the group of genes that are specifically implicated in human evolution (during the past 200,000 years), as it allows the identification of those genes which did not undergo selection in another primate line. An example that has been confirmed by this study is the well-known case of the lactase gene that can metabolize lactose during adulthood (a clear advantage with the development of agriculture and animal husbandry). The researchers have also identified a group of genes involved in some neurological functions and in the development of muscles and skeleton.