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Enlarge / This artist's reconstruction shows "Lola" as a young girl, with items that likely would have been part of her daily life, but we have no way of knowing how old she was when she chewed and discarded the lump of birch-bark pitch. (credit: Tom Björklund)

5,700 years ago, a woman in what is now Denmark chewed a lump of birch-bark pitch for a while and then dropped it. Millennia later, the DNA she left behind reveals her entire genome, a census of the bacteria living in her mouth, and a few hints about a recent meal.

Meet “Lola”

If you’re a hunter-gatherer who needs to haft a stone tool, birch-bark pitch makes a handy adhesive, but you might have to chew it to make it pliable enough to work with. Pitch is watertight and contains an antiseptic compound called betulin, so it’s great at preserving DNA. In fact, archaeologists in Scandinavia have found more human DNA in bits of chewed pitch than they have in skeletons (which have been relatively rare at prehistoric Scandinavian sites we've studied thus far).

But this is the first time researchers have managed to sequence an ancient person's whole genome from a lump of chewed pitch. Only about a third of the DNA bioarchaeologist Hannes Schroeder, of the University of Copenhagen, sampled was human; the other 68 percent came from the ancient woman’s microbiome and traces of a prehistoric meal. This single discarded piece of ancient chewing gum tells us that the ancient woman, who Schroeder and his colleagues have nicknamed Lola, was probably lactose intolerant, ate duck and hazelnuts, and may recently have had pneumonia. She also had blue eyes, dark brown hair, and dark skin.

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A widely circulating piece of Android malware primarily targeting US-based phones used a clever trick to reinfect one of its targets in a feat that stumped researchers as to precisely how it was pulled off.

xHelper came to light last May when a researcher from security firm Malwarebytes published this brief profile. Three months later, Malwarebytes provided a deeper analysis after the company’s Android antivirus app detected xHelper on 33,000 devices mostly located in the US, making the malware one of the top Android threats. The encryption and heavy obfuscation made analysis hard, but Malwarebytes researchers ultimately concluded that the main purpose of the malware was to act as a backdoor that could remotely receive commands and install other apps.

On Wednesday, Malwarebytes published a new post that recounted the lengths one Android user took to rid her device of the malicious app. In short, every time she removed two xHelper variants from the device, the malware would reappear on her device within the hour. She reported that even performing a factory reset wasn't enough to make the malware go away.

Enlarge / Artist's impression of AI playing sports. (credit: Pali Rao / Getty Images)

Artificial Intelligence, machine learning, and other technologies are changing the world in which we live and work in some subtle, and not-so-subtle, ways. And we're diving into just a few of them in this podcast series produced in association with Darktrace.

One of the most visible places where analytics based on AI and machine learning are working their way into our popular awareness is in the realm of professional sports. From the virtual lines drawn on a football field to show the line of scrimmage and first-down markers, to Major League Baseball stat casts predicting the probability of successful base stealing, AI has become part of how we consume sports.

In this episode, Ars editors Sean Gallagher and Lee Hutchinson talked with Tim Wade, vice president at NTT's Advanced Technology Group, about how NTT provides AI-based analytics for the Tour de France, the iconic 21-stage cycling competition. Wade's team uses wireless communications, helicopters, and a data center in a truck to turn sensor data from each of the competitors' bicycles into live statistics and analysis of the race—including an algorithm that predicts pile-ups in the peloton.