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The COVID-19 pandemic has underscored the critical need for robust scientific evidence to support policy decisions, such as around the effectiveness of various social distancing measures and the safety of drug therapies. Yet this need arises at a time of growing misinformation and poorly vetted facts repeated by influential sources. To address this gap, a group of scientists led by Kai Ruggeri, a professor at Columbia University Mailman School of Public Health, and James Green, chief scientist at NASA, has introduced a new framework to help set standards for the quality of evidence used in policymaking.

As scientists await the highly anticipated initial results of the Muon g-2 experiment at the U.S. Department of Energy's (DOE) Fermi National Accelerator Laboratory, collaborating scientists from DOE's Argonne National Laboratory continue to employ and maintain the unique system that maps the magnetic field in the experiment with unprecedented precision.

The COVID-19 syndemic is entering its most dangerous phase. There is a mounting breakdown of trust. Not only between politicians and the public. But also among politicians and publics with science and scientists. This breach of faith with science is far more threatening. For the public is slowly turning against those who have sought to guide the political response to COVID-19. As countries face a resurgence of coronavirus transmission, scientific advisers are recommending further restrictions to our liberties. There is now a palpable public reaction against these mandates. Whereas in March people were ready to stay at home to protect their health and health systems, the growing economic emergency that has followed national lockdowns is leading politicians to resist similar measures being applied once again. And it is scientists who are targets for public opprobrium. "Britain is in the grip of mad science", wrote one commentator last week. A UK Government minister was quoted as saying that "[Boris] Johnson has been totally captured by [Chris] Whitty and [Patrick] Vallance". "Boris is now a prisoner of the scientists", ran a newspaper headline. Robert Dingwall, a professor of sociology, wrote "we have found ourselves in the han

"My colleague Jamie Robins and I are working on a book that provides a cohesive presentation of concepts of, and methods for, causal inference. Much of this material is currently scattered across journals in several disciplines or confined to technical articles. We expect that the book will be of interest to anyone interested in causal inference, e.g., epidemiologists, statisticians, psychologists, economists, sociologists, political scientists, computer scientists… The book is divided in 3 parts of increasing difficulty: causal inference without models, causal inference with models, and causal inference from complex longitudinal data. We are making drafts of selected book sections available on this website. The idea is that interested readers can submit suggestions or criticisms before the book is published. To share any comments, please email me or visit @causalinference on Facebook. To cite the book, please use "Hernán MA, Robins JM (2018). Causal Inference. Boca Raton: Chapman & Hall/CRC, forthcoming.""

"When animals die, waves of microbes consume their corpses. Scientists have looked at how this "necrobiome" changes over the hours and days after an animal perishes. But Saitta's work suggests that microbes continue to colonize cadavers long after their flesh has decayed, after their bones have turned to stone, and after they've been buried several miles deep for millions of years.   MORE STORIES A Dinosaur So Well Preserved, It Looks Like a Statue ED YONG How a Fossil Can Reveal the Color of a Dinosaur CARI ROMM The Counterintuitive Way That Microbes Survive in Antarctica ED YONG The Scientist Who Stumbled Upon a Tick Full of 20-Million-Year-Old Blood SARAH ZHANG That came as a huge surprise to Tullis Onstott, a microbiologist from Princeton who worked with Saitta, and who always thought of fossils as inert and inanimate. "I thought that dinosaur bone must be some kind of sealed sarcophagus," he says. "It's not, by any means. It's basically a condo for bacteria. Now the question becomes: Is this true for all dinosaur bones?""

How do statistics so often lead scientists to deny differences that those not educated in statistics can plainly see? For several generations, researchers have been warned that a statistically non-significant result does not 'prove' the null hypothesis (the hypothesis that there is no difference between groups or no effect of a treatment on some measured outcome)1. Nor do statistically significant results 'prove' some other hypothesis. Such misconceptions have famously warped the literature with overstated claims and, less famously, led to claims of conflicts between studies where none exists.

If you want to understand an ecosystem, look at what the species within it eat. In studying food webs-how animals and plants in a community are connected through their dietary preferences-ecologists can piece together how energy flows through an ecosystem and how stable it is to climate change and other disturbances. Studying ancient food webs can help scientists reconstruct communities of species, many long extinct, and even use those insights to figure out how modern-day communities might change in the future. There's just one problem: only some species left enough of a trace for scientists to find eons later, leaving large gaps in the fossil record-and researchers' ability to piece together the food webs from the past.

How did life originate? Scientists have been studying the question for decades, and they've developed ingenious methods to try to find out. They've even enlisted biology's most powerful theory, Darwinian evolution, in the search. But they still don't have a complete answer. What they have hit is the world's most theoretically fertile dead end. When scientists look for life's origins, they usually work in one of two directions. They work backwards in time through the record of organisms that have lived on Earth, or they work forward from one of the many hypothetical prebiotic worlds in which life could have emerged.

BY NOW THERE'S little doubt about hydroxychloroquine: It doesn't work for treating Covid-19. But there's a bigger, more important lesson hidden in the story of its failure-a rarely-mentioned, but altogether crucial, error baked into the early research. The scientists who ran the first, promising laboratory experiments on the drug had used the wrong kind of cells: Instead of testing its effects on human lung cells, they relied on a supply of mass-produced, standardized cells made from a monkey's kidney. In the end, that poor decision made their findings more or less irrelevant to human health. Worse, it's possible that further research into novel Covid-19 cures will end up being compromised by the same mistake.

In a collaboration with Italian scientists as part of the European project Ecopotential, EPFL scientists built a model to predict the dynamics of two carabid species across the landscape of Gran Paradiso National Park in the Graian Alps, in Northern Italy, now combining field measurement with advanced remote sensing. The results are published in PNAS and the open-model is available on GitHub. "The main result of this work, which I deem important, is to suggest that an integrated ecohydrological framework blending field evidence, both theoretical and remotely acquired, has contributed substantially to our understanding of key indicators of ecological well-being, carabid beetles, in complex environments like iconic mountains," explains Andrea Rinaldo, who leads the Laboratory of Ecohydrology.

For protein molecules that contribute to metabolism, interactions with other components of their metabolic pathway can be crucial. Scientists at the Max Planck Institute for Developmental Biology in Tübingen have now investigated a natural enzyme complex that comprises 10 enzymes with five distinct activities. They found that the molecular architecture is surprisingly compact, yet offers individual enzymes maximum free moving space, which opens up novel perspectives for drug discovery. The scientists have published their results in Nature Chemical Biology.

While scientists still don't fully understand the diverse nature of RNA molecules, it is believed that the proteins binding to them, called RNA-binding proteins, are associated with many types of disease formation. Research led by biomedical scientists from City University of Hong Kong (CityU) has led to a novel detection method, called CARPID, to identify binding proteins of specific RNAs in living cells. It is expected that the innovation can be applied in various types of cell research, from identifying biomarkers of cancer diagnosis to detecting potential drug targets for treating viral diseases.