“The increase in early-onset colorectal cancer is a global phenomenon,” said Dr. Hyuna Sung, senior principal scientist, cancer surveillance research at the American Cancer Society and lead author of the study. “Previous studies have shown this rise in predominately high-income Western countries, but now, it is documented in various economies and regions worldwide.”

The primary study objective was to examine contemporary CRC incidence trends in young versus older adults using data through 2017 from 50 countries/territories. Data were compiled using the Cancer Incidence in Five Continents Plus and trends were examined for age-standardized incidence rates of CRC ranging from 1943-2017. Temporal trends were visualized and quantified by age at diagnosis (25-49 years and 50-74 years). Average annual percentage changes (AAPC) were estimated for the last 10 years of data.

During the past decade, incidence rates of early-onset CRC (25-49 years) were stable in 23 countries, but increased in 27 countries, with the greatest annual increases in New Zealand (4.0%), Chile (4.0%) and Puerto Rico (3.8%). Fourteen of the 27 countries/territories showed either stable (Puerto Rico, Argentina, Norway, France, Ireland) or decreasing rates (Israel, Canada, the USA, England, Germany, Scotland, Slovenia, Australia, and New Zealand) in older adults. The rise in early-onset CRC was faster among men than women in Chile, Puerto Rico, Argentina, Ecuador, Thailand, Sweden, Israel, and Croatia, while young women experienced faster increases in England, Norway, Australia, Türkiye, Costa Rica, and Scotland. For the remaining 13 countries with increasing trends in both age groups, the annual percentage increase in young compared to older adults was larger in Chile, Japan, Sweden, the Netherlands, Croatia, and Finland, smaller in Thailand, Martinique, Denmark, Costa Rica, and similar in Türkiye, Ecuador, and Belarus. For the last five years, the incidence rate of early-onset CRC was highest in Australia, Puerto Rico, New Zealand, the U.S., and the Republic of Korea (14 to 17 per 100,000) and lowest in Uganda and India (4 per 100,000).

“The global scope of this concerning trend highlights the need for innovative tools to prevent and control cancers linked to dietary habits, physical inactivity, and excess body weight. Ongoing efforts are essential to identify the additional factors behind these trends and to develop effective prevention strategies tailored to younger generations and local resources worldwide,” added Sung. “Raising awareness of the trend and the distinct symptoms of early-onset colorectal cancer (e.g., rectal bleeding, abdominal pain, altered bowel habits, and unexplained weight loss) among young people and primary care providers can help reduce delays in diagnosis and decrease mortality.”

“This flagship study reveals that increasing rates of early onset bowel cancer, affecting adults aged 25-49, is a global issue. Concerningly, this research has revealed for the first time ever that rates are rising more sharply in England than in many other countries around the world,” said Michelle Mitchell, chief executive of Cancer Research UK.”A cancer diagnosis at any age has a huge impact on patients and their families — so while it’s important to note that rates in younger adults are still very low compared to people over 50, we need to understand what’s causing this trend in younger people. More research is needed — like team PROSPECT, a global Cancer Grand Challenges team who has been awarded £20m to uncover the causes of bowel cancer in younger adults, and strategies to prevent it.”

Other ACS researchers contributing to the study include Rebecca Siegel, Chenxi Jiang, and senior author Dr. Ahmedin Jemal. Yin Cao, an associate professor of surgery and of medicine at Washington University School of Medicine in St. Louis and a research member of Siteman Cancer Center, based at Barnes-Jewish Hospital and Washington University Medicine, is a contributing author.

The extraordinary images — taken with NASA’s James Webb Space Telescope — show a galaxy that glitters with 10 distinct star clusters that formed at different times, much like our own Milky Way.

Cocooned in a diffuse arc, and resembling fireflies “dancing” on a summer night, the newly discovered galaxy — which the Wellesley team have dubbed the “Firefly Sparkle” — was taking shape around 600 million years after the Big Bang, around the same time that our own galaxy was beginning to take shape.

Wellesley College astronomer Lamiya Mowla is co-lead author of the paper, which was published Wednesday, Dec. 11, in Nature.

Mowla says the discovery is particularly important because the mass of the Firefly Sparkle is similar to what the Milky Way’s mass might have been at the same stage of development. (Other galaxies Webb has detected from this time period are significantly more massive.)

“These remarkable images give us an unprecedented picture of what our own galaxy might have looked like when it was being born,” Mowla says. “By examining these photos of the Firefly Sparkle, we can better understand how our own Milky Way took shape.”

Glimpses of a young galaxy forming in a way so similar to our own are unparalleled, Mowla says. The JWST images show a Milky Way-like galaxy in the early stages of its assembly in a universe that’s only 600 million years old.

“As an observational astronomer studying the structural evolution of astronomical objects in the early Universe, I want to understand how the first stars, star clusters, galaxies, and galaxy clusters formed in the infant Universe and how they changed as the Universe got older,” Mowla notes. Of the Firefly Sparkle, she says, “”I didn’t think it would be possible to resolve a galaxy that existed so early in the universe into so many distinct components, let alone find that its mass is similar to our own galaxy’s when it was in the process of forming.

“There is so much going on inside this tiny galaxy, including so many different phases of star formation,” Mowla told NASA. “These images are the very first glimpse of something that we’ll be able to study — and learn from — for many years to come.”

Mowla, who co-led the project with Kartheik Iyer, a NASA Hubble Fellow at Columbia University in New York, is an assistant professor of physics and astronomy at Wellesley, and a 2013 graduate of the college.

But a study in Scientific Reports highlights a hidden challenge of using AI in medical imaging research — the phenomenon of highly accurate yet potentially misleading results known as “shortcut learning.”

The researchers analyzed more than 25,000 knee X-rays from the National Institutes of Health-funded Osteoarthritis Initiative and found that AI models can “predict” unrelated and implausible traits such as whether patients abstained from eating refried beans or beer. While these predictions have no medical basis, the models achieved surprising levels of accuracy by exploiting subtle and unintended patterns in the data.

“While AI has the potential to transform medical imaging, we must be cautious,” says the study’s senior author, Dr. Peter Schilling, an orthopaedic surgeon at Dartmouth Health’s Dartmouth Hitchcock Medical Center and an assistant professor of orthopaedics in Dartmouth’s Geisel School of Medicine.

“These models can see patterns humans cannot, but not all patterns they identify are meaningful or reliable,” Schilling says. “It’s crucial to recognize these risks to prevent misleading conclusions and ensure scientific integrity.”

The researchers examined how AI algorithms often rely on confounding variables — such as differences in X-ray equipment or clinical site markers — to make predictions rather than medically meaningful features. Attempts to eliminate these biases were only marginally successful — the AI models would just “learn” other hidden data patterns.

“This goes beyond bias from clues of race or gender,” says Brandon Hill, a co-author of the study and a machine learning scientist at Dartmouth Hitchcock. “We found the algorithm could even learn to predict the year an X-ray was taken. It’s pernicious — when you prevent it from learning one of these elements, it will instead learn another it previously ignored. This danger can lead to some really dodgy claims, and researchers need to be aware of how readily this happens when using this technique.”

The findings underscore the need for rigorous evaluation standards in AI-based medical research. Overreliance on standard algorithms without deeper scrutiny could lead to erroneous clinical insights and treatment pathways.

“The burden of proof just goes way up when it comes to using models for the discovery of new patterns in medicine,” Hill says. “Part of the problem is our own bias. It is incredibly easy to fall into the trap of presuming that the model ‘sees’ the same way we do. In the end, it doesn’t.”

“AI is almost like dealing with an alien intelligence,” Hill continues. “You want to say the model is ‘cheating,’ but that anthropomorphizes the technology. It learned a way to solve the task given to it, but not necessarily how a person would. It doesn’t have logic or reasoning as we typically understand it.”

Schilling, Hill, and study co-author Frances Koback, a third-year medical student in Dartmouth’s Geisel School, conducted the study in collaboration with the Veterans Affairs Medical Center in White River Junction, Vt.

Where does all that energy come from? For many years, scientists believed it came from shocks that occur in extreme astrophysical environments — when, for example, a star explodes before forming a black hole, causing a huge explosion that kicks up particles.

That theory was plausible, but, according to new research published this week in The Astrophysical Journal Letters, the observations are better explained by a different mechanism. The source of the cosmic rays’ energy, the researchers found, is more likely magnetic turbulence. The paper’s authors found that magnetic fields in these environments tangle and turn, rapidly accelerating particles and sharply increasing their energy up to an abrupt cutoff.

“These findings help solve enduring questions that are of great interest to both astrophysicists and particle physicists about how these cosmic rays get their energy,” said Luca Comisso, associate research scientist in the Columbia Astrophysics Lab, and one of the paper’s authors.

The paper complements research published last year by Comisso and collaborators on the sun’s energetic particles, which they also found emerge from magnetic fields in the sun’s corona. In that paper, Comisso and his colleagues discovered ways to better predict where those energetic particles would emerge.

Ultra-high energy cosmic rays are orders of magnitude more powerful than the sun’s energetic particles: They can reach up to 10²⁰ electron volts, whereas particles from the Sun can reach up to 10¹⁰ electron volts, a 10-order-of-magnitude difference. (To give an idea of this vast difference in scale, consider the difference in weight between a grain of rice with a mass of about 0.05 grams and a 500-ton Airbus A380, the world’s largest passenger aircraft.) “It’s interesting that these two extremely different environments share something in common: their magnetic fields are highly tangled and this tangled nature is crucial for energizing particles,” Comisso said.

“Remarkably, the data on ultra-high energy cosmic rays clearly prefers the predictions of magnetic turbulence over those of shock acceleration. This is a real breakthrough for the field,” said Glennys R. Farrar, an author on the paper and professor of physics at New York University.

The research was supported by the National Science Foundation.