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Chip design can rapidly and efficiently test for multiple pathogens simultaneously, potentially reducing foodborne illness. Researchers have developed a new method for detecting foodborne pathogens that is faster, cheaper, and more effective than existing methods. Their microfluidic chip uses light to detect multiple types of pathogens simultaneously and is created using 3D printing, making it easy to fabricate in large amounts and modify to target specific pathogens. The researchers hope their technique can improve screening processes and keep contaminated food out of the hands of consumers.

Every so often, a food product is recalled because of some sort of contamination. For consumers of such products, a recall can trigger doubt in the safety and reliability of what they eat and drink. In many cases, a recall will come too late to keep some people from getting ill.

In spite of the food industry’s efforts to fight pathogens, products are still contaminated and people still get sick. Much of the problem stems from the tools available to screen for harmful pathogens, which are often not effective enough at protecting the public.

A study of 17 commonly used synthetic ‘forever chemicals’ has shown that these toxic substances can readily be absorbed through human skin.

New research, published today in Environment International proves for the first time that a wide range of PFAS (perfluoroalkyl substances) — chemicals which do not break down in nature – can permeate the skin barrier and reach the body’s bloodstream.

PFAS are used widely in industries and consumer products from school uniforms to personal care products because of their water and stain repellent properties. While some substances have been banned by government regulation, others are still widely used and their toxic effects have not yet been fully investigated.

Researchers from the Complexity Science Hub and the University of Veterinary Medicine Vienna have dissected the complex interactions involved in zoonoses, which annually affect over two billion people worldwide. They introduce the concept of a “zoonotic web,” a detailed network representation of the relationships between zoonotic agents, their hosts, vectors, food sources, and the environment.

The Department of Energy’s Oak Ridge National Laboratory has publicly released a new set of additive manufacturing data that industry and researchers can use to evaluate and improve the quality of 3D-printed components. The breadth of the datasets can significantly boost efforts to verify the quality of additively manufactured parts using only information gathered during printing, without requiring expensive and time-consuming post-production analysis.

Data has been routinely captured over a decade at DOE’s Manufacturing Demonstration Facility, or MDF, at ORNL, where early-stage research in coupled with comprehensive analysis of the resulting components has created a vast trove of information about how 3D printers perform. Years of experience pushing the boundaries of 3D printing with novel materials, machines and controls have provided ORNL with the unique ability to develop and share comprehensive datasets. The newest dataset is now available for free through an .

The conventional manufacturing industry benefits from centuries of quality-control experience. However, additive manufacturing is a newer, non-traditional approach that typically relies on expensive evaluation techniques for monitoring the quality of parts. These techniques might include destructive mechanical testing or non-destructive X-ray computed tomography, which creates detailed cross-sectional images of objects without damaging them.