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Ebola

Researchers trained a machine-learning model to predict animal reservoirs or insect vectors for dozens of "orphan" viruses with unknown natural sources.

This Week in PNAS

In PNAS this week: population structure in Helicoverpa, AMP-activated protein kinase levels in nicotine-exposed mice, and more.

The researchers found that the expression of certain genes was better at helping them predict when Ebola would develop than indications of infection like fever.

The Fraunhofer USA team will partner with a Fraunhofer Society institute in Germany in order to reduce the cost for its patented microchip that detects viruses including Ebola.

This Week in PLOS

In PLOS this week: approach to diagnose hemorrhagic fevers, recessive disease mutations in mixed-breed dogs, and more.

The researchers found multiple enzymes that indicate causes of dysregulated adaptive immunity and tissue damage in fatal Ebola virus disease.

The German company said the open-access platform, called Pharos V8, can provide real-time PCR results in 10 minutes.   

An OpenArray panel designed to simultaneously test for 17 viruses and 13 bacteria and protozoa was able to detect pathogens from human blood donor samples with an accuracy of about 95 percent.

Presenters at ASM have used next-generation sequencing to examine Ebola, Zika, and respiratory virus infection and transmission.

The tool has been applied to determine the pathogenic cause of hemorrhagic fever, and is powering a new test for respiratory disease pathogens.

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Newsweek discusses the privacy issues raised by digital medicine.

A group of statisticians wants to eliminate researchers' reliance on 'statistical significance,' according to NPR.

In Nature this week: genetic analysis of Anatolian farmers, cotton genome analysis, and more.

Matt Hancock, the UK health secretary, is calling for the swift rollout of predictive genetic tests, the Guardian reports.