Archeologists in the early 20th century posited the volcano erupted around 1500 BCE, during the Egyptian New Kingdom period, and created a history around this assumption. But beginning in the 1970s, advances in radiocarbon dating have thrown that timeline into chaos, with many experts insisting the eruption happened as much as 100-plus years earlier.

Sturt Manning, Distinguished Professor of Arts and Sciences in Classical Archaeology in the College of Arts and Sciences, is hoping to settle one of modern archaeology’s longstanding disputes. By parsing the available data and combining it with cutting-edge statistical analysis, he has zeroed in on a much narrower range of dates for the eruption: approximately 1609-1560 BCE, during the preceding Second Intermediate Period of Egypt, when the Hyksos — a Canaanite-origin dynasty — controlled Lower Egypt. While not yet a precise date, to the year, for resolving the big-picture question of the correct historical period, the finding clarifies many years of debate.

“This has been the single most contested date in Mediterranean history for over 40 years,” said Manning, who directs the Cornell Tree-Ring Laboratory. “It’s been one of these endless disputes, to the point where people just say, ‘there’s a problem here, we can’t solve it, let’s move on.’ I’m hoping with this paper people may suddenly go, ‘You know what, this actually limits and defines the problem in a way that we’ve never been able to do before, and narrows it down to where, usefully, we can say it’s in the Second Intermediate Period. So we should start writing a different history.'”

For Manning, the Thera eruption has been like Mount Everest — a challenge that he has wanted to tackle since early in his career. Accurately dating the event has become more feasible in recent years with the increased sophistication of Bayesian statistical analysis, enabling chronological modeling that can integrate massive amounts of data and archaeological observations to better define the probability parameters for an unknown event.

The parameters have been fairly well understood for years, Manning said, thanks to the extensive geological and archaeological research that’s been conducted. The missing piece of the puzzle has been an often-raised concern that volcanic carbon dioxide emissions could have contaminated organic samples from Thera and caused incorrect age assessments.

Last spring, Manning realized he could solve the problem by looking elsewhere — hundreds of kilometers away from Thera — to regions of the Aegean Sea that experienced the tsunami effects caused by the eruption. Manning incorporated dates obtained for these episodes into his model to test for, and discount, the volcanic carbon dioxide caveat. On Thera itself, he also spotted the importance of a short but clearly observed gap in time between the abandonment of the town at Akrotiri and the huge eruption, and he incorporated this previously overlooked constraint into the modeling.

“It’s been observed for years that there is some short interval in the archaeological sequence between when the city of Akrotiri was abandoned by its human population and before its burial under meters of pumice from the eruption. Even though several hectares have been excavated, no human skeletons have been found, so clearly people had warning of impending peril and left. No one’s allowed for that in the past,” Manning said. “By putting that extra qualification in, we tighten the statistical analysis.”

The modeling identified the most likely range of dates for the eruption to be: between about 1609-1560 BCE (95.4% probability), or about 1606-1589 BCE (68.3% probability).

The new timeline synchronizes the civilizations of the eastern Mediterranean while also ruling out several ancillary theories, such as the idea that the Thera eruption was responsible for destroying Minoan palaces on the coast of Crete as the first excavator of Akrotiri, Spyridon Marinatos, proposed in 1939.

“That seems not to be the case,” Manning said. “Because when we date the destruction levels on Crete, they seem to be upwards of a century later.”

Because his analysis pegs the Thera eruption earlier than the original proposed date, but not as early as radiocarbon dating had initially suggested, Manning hopes the new timeline may be more palatable for experts on both sides of the long-running debate.

“This demonstrates, as with so much of science, that people have to make hypotheses based on the initial information, but as you get more and more information and better analysis, you revise and refine,” he said. “In this case, the answer seems to be between the original position and the first radiocarbon indications pointing as much as 100-150 years earlier. Hopefully this new analysis, based on a large dataset and a recent, better-defined radiocarbon calibration curve released in 2020, should be more palatable for the overall archaeological and historical fields. It changes the historical context, but at the same time, is not trying to push things quite so far out of the envelope.”

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Materials provided by Cornell University. Original written by David Nutt, courtesy of the Cornell Chronicle. Note: Content may be edited for style and length.

But new research from the University of Georgia shows people who rely on algorithms for assistance with language-related, creative tasks didn’t improve their performance and were more likely to trust low-quality advice.

Aaron Schecter, an assistant professor in management information systems at the Terry College of Business, had his study “Human preferences toward algorithmic advice in a word association task” published this month in Scientific Reports. His co-authors are Nina Lauharatanahirun, a biobehavioral health assistant professor at Pennsylvania State University, and recent Terry College Ph.D. graduate and current Northeastern University assistant professor Eric Bogert.

The paper is the second in the team’s investigation into individual trust in advice generated by algorithms. In an April 2021 paper, the team found people were more reliant on algorithmic advice in counting tasks than on advice purportedly given by other participants.

This study aimed to test if people deferred to a computer’s advice when tackling more creative and language-dependent tasks. The team found participants were 92.3% more likely to use advice attributed to an algorithm than to take advice attributed to people.

“This task did not require the same type of thinking (as the counting task in the prior study) but in fact we saw the same biases,” Schecter said. “They were still going to use the algorithm’s answer and feel good about it, even though it’s not helping them do any better.”

Using an algorithm during word association

To see if people would rely more on computer-generated advice for language-related tasks, Schecter and his co-authors gave 154 online participants portions of the Remote Associates Test, a word association test used for six decades to rate a participant’s creativity.

“It’s not pure creativity, but word association is a fundamentally different kind of task than making a stock projection or counting objects in a photo because it involves linguistics and the ability to associate different ideas,” he said. “We think of this as more subjective, even though there is a right answer to the questions.”

During the test, participants were asked to come up with a word tying three sample words together. If, for example, the words were base, room and bowling, the answer would be ball.

Participants chose a word to answer the question and were offered a hint attributed to an algorithm or a hint attributed to a person and allowed to change their answers. The preference for algorithm-derived advice was strong despite the question’s difficulty, the way the advice was worded, or the advice’s quality.

Participants taking the algorithm’s advice were also twice as confident in their answers as people who used the person’s advice. Despite their confidence in their answers, they were 13% less likely than those who used human-based advice to choose correct answers.

“I’m not going say the advice was making people worse, but the fact they didn’t do any better yet still felt better about their answers illustrates the problem,” he said. “Their confidence went up, so they’re likely to use algorithmic advice and feel good about it, but they won’t necessarily be right.

Should you accept autocorrect when writing an email?

“If I have an autocomplete or autocorrect function on my email that I believe in, I might not be thinking about whether it’s making me better. I’m just going to use it because I feel confident about doing it.”

Schechter and colleagues call this tendency to accept computer-generated advice without an eye to its quality as automation bias. Understanding how and why human decision-makers defer to machine learning software to solve problems is an important part of understanding what could go wrong in modern workplaces and how to remedy it.

“Often when we’re talking about whether we can allow algorithms to make decisions, having a person in the loop is given as the solution to preventing mistakes or bad outcomes,” Schecter said. “But that can’t be the solution if people are more likely than not to defer to what the algorithm advises.”

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Materials provided by University of Georgia. Original written by J. Merritt Melancon. Note: Content may be edited for style and length.

An invasion of inflammatory immune cells, called monocytes, into fat tissue is a hallmark of obesity, but what leads to this harmful phenomenon is unclear. Many immune cells, including monocytes, are produced in the bone marrow, which is very sensitive to environmental changes. Scientists have already shown that fat cells in the bone marrow rapidly expand in response to a high-fat diet.

“We wanted to know if bone marrow tissue was an early responder to a high-fat diet that could serve as a precursor to the inflammation observed in obesity,” says senior author Amira Klip, Senior Scientist in Cell Biology at SickKids, and Professor in the Departments of Paediatrics, Biochemistry, and Physiology at the University of Toronto, Canada. “Do high-fat diet-induced changes in the bone marrow lead to the production of the inflammatory monocytes that invade fat tissue in people with obesity?”

Klip and colleagues found that mice fed a high-fat diet begin to experience metabolic disturbances throughout their body and in the bone marrow within three weeks. Fat cells in the bone marrow multiply and take on white fat cell characteristics. Metabolic changes in the monocytes at the bone marrow cells also occur — they use less oxygen to break down sugar into energy, and lactic acid builds up in the cells and surrounding fluid. The team also found that mitochondria, cellular factories that break down sugar into energy, break apart into fragments within the monocytes and become less efficient. This process of mitochondrial fragmentation is associated with insulin resistance.

Over several weeks, the number of monocytes in the bone marrow shifts to include less of a monocyte called Ly6C^low to more of a monocyte called Ly6C^high, the same type of monocyte that invades fat tissue in people with obesity. This accumulation of Ly6C^high monocytes in the bone marrow starts before monocytes build up in fat tissue in the rest of the body to become inflammatory macrophages — the mature form of monocytes.

“These results show that high-fat diets can cause remodelling in bone marrow fat cells that disrupt the normal balance of monocytes, and can subsequently lead to invasive Ly6C^high monocytes spilling into the body,” continues Klip.

The team further demonstrated that white fat tissue can spur these changes in experiments using cell samples from mice fed a high-fat diet. They also found that brown fat tissue, which is more abundant in leaner people, can cause a shift towards the non-invasive Ly6C^low monocytes.

“Our study reveals how high-fat diets trigger a cascade of inflammation in the body that involves the bone marrow,” concludes Klip. “More research is needed to understand this process further and find out if there are ways to prevent or reverse this process. It will also be important to know if the bone marrow is also an early responder to obesity in humans. Learning more could lead to new therapies for treating obesity and preventing complications such as diabetes.”

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Materials provided by eLife. Note: Content may be edited for style and length.

“In an advanced stage, 90% of melanoma (skin cancer) patients will develop brain metastases,” explains Prof. Satchi-Fainaro. “This is a puzzling statistic. We expect to see metastases in the lungs and liver, but the brain is supposed to be a protected organ. The blood-brain barrier keeps harmful substances from entering the brain, and here it supposedly doesn’t do the job — cancer cells from the skin circulate in the blood and manage to reach the brain. We asked ourselves with ‘whom’ the cancer cells ‘talk’ to in the brain to infiltrate it.”

The researchers from Tel Aviv University found that in melanoma patients with brain metastases, the cancer cells “recruit” cells called astrocytes, star-shaped cells found in the spinal cord and brain which are responsible for homeostasis, or maintaining stable conditions, in the brain.

“The astrocytes are the first to come to correct the situation in the event of a stroke or trauma, for example,” says Prof. Satchi-Fainaro, “and it is with them that the cancer cells interact, exchanging molecules and corrupting them. Moreover, the cancer cells recruit the astrocytes so that they do not inhibit the spread of the metastases. As such, they create local inflammation in the melanoma cells-astrocytes interaction areas that increase the permeability through the blood-brain barrier, as well as the division and migration of the cancer cells. The communication between them is reflected in the fact that the astrocytes begin to secrete a protein that promotes inflammation called MCP-1 (also known as CCL2), and in response to this, the cancer cells begin to express its receptors CCR2 and CCR4, which we suspected to be responsible for the destructive communication with the astrocytes.”

To test their hypothesis, Prof. Satchi-Fainaro and her team tried to inhibit the expression of the protein and its receptors in genetically-engineered lab models and in 3D models of primary melanoma and brain metastases. To this end, the researchers used both an antibody (biological molecule) and a small molecule (synthetic), designed to block the MCP-1 protein. They also employed CRISPR technology to genetically edit the cancer cells and cut out the two genes that express the two relevant receptors, CCR2 and CCR4. With each of the methods, the researchers were able to delay the spread of metastases.

“These treatments succeeded in delaying the penetration of the cancer cells into the brain and their subsequent spread throughout the brain,” says Prof. Satchi-Fainaro. “It’s important to note that melanoma metastases in the brain are very aggressive with a poor prognosis of 15 months following surgery, radiation and chemotherapy. We reached a 60% to 80% delay, depending on the stage of the intervention. We achieved the best results with the treatment conducted immediately after surgery to remove the primary melanoma, and we were able to prevent the metastases from penetrating the brain; therefore, I believe that the treatment is suitable for the clinic as a preventive measure. Both the antibody and the small molecule we used — which are primarily intended to treat sclerosis, diabetes, liver fibrosis, and cardiovascular diseases, as well as serve as a biomarker for other types of cancer — have already been tested on humans as part of clinical trials. Therefore, these treatments are considered safe, and we can try to repurpose them for melanoma.”

The research was conducted in collaboration with additional scientists and physicians from Tel Aviv University, including Prof. Adi Barzel, Dr. Asaf Madi, Prof. Iris Barshack, Prof. Eran Perlson, and Prof. Inna Slutsky. International researchers also participated in the study, including Prof. Eytan Ruppin from the US National Institutes of Health (NIH) , Prof. Henry Brem and Thomas Hyde from Johns Hopkins University-, and Prof. Helena Florindo from the University of Lisbon.

The study was funded by the European Research Council (ERC), the Melanoma Research Alliance (MRA), the Kahn Foundation, the Israel Cancer Research Fund (ICRF), and the Israel Science Foundation (ISF).

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Materials provided by Tel-Aviv University. Note: Content may be edited for style and length.