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The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in thousands of deaths in the world. Information about prediction model of prognosis of SARS-CoV-2 infection is scarce. We used machine learning for processing laboratory findings of 110 patients with SARS-CoV-2 pneumonia (including 51 non-survivors and 59 discharged patients). The maximum relevance minimum redundancy (mRMR) algorithm and the least absolute shrinkage and selection operator logistic regression model were used for selection of laboratory features. Seven laboratory features selected in the model were: prothrombin activity, urea, white blood cell, interleukin-2 receptor, indirect bilirubin, myoglobin, and fibrinogen degradation products. The signature constructed using the seven features had 98% [93%, 100%] sensitivity and 91% [84%, 99%] specificity in predicting outcome of SARS-CoV-2 pneumonia. Thus it is feasible to establish an accurate prediction model of outcome of SARS-CoV-2 pneumonia based on laboratory findings.

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.

Humans are largely omnivores, and meat has featured in the diets of most cultures. However, with the increasing population and pressure on the environment, traditional methods of meeting this fundamental food requirement are likely to fall short. Now, researchers at the University of Tokyo report innovative biofabrication of bovine muscle tissue in the laboratory that may help meet escalating future demands for dietary meat.

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.

This article traces the travel of biometric data of Syrian refugees in Jordan through a hastily evolving political economy characterized by a pervasive craving for the extraction, storage and brokering of displacement data. It analyzes iris-enrollment as problematic acts of quasi-citizenship for the displaced requiring the performance of social and economic docility in order to attain identity, cash and service provision. Quasi-objects in the form of digital footprints are fashioned through infrastructures that simultaneously seek to model, yet fail to capture, socioeconomic existence in displacement contexts. Discourses of anti-fraud, donor dictates, upward accountability and strategies of financial inclusion of 'the unbanked', facilitate the marketization of the creation of data-doubles in laboratories of displacement and loopholes for externalization. Driven by increasingly blurred lines between technological, humanitarian and financial interests, this development has transformative effects on both those displaced, and on a humanitarian sector tasked with safeguarding their rights.

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.

Simulating an earthquake on a miniature scale in a laboratory known unofficially as the "seismological wind tunnel," engineers and seismologists have produced the most comprehensive look to date at the complex physics of friction driving destructive thrust-fault earthquakes.