The Sciences
Artificial intelligence outstrips clinical tests in predicting the progression of Alzheimer’s disease
Dementia presents a substantial healthcare challenge globally, impacting more than 55 million individuals with an annual economic burden estimated at $820 billion.
Scientists from Cambridge have created an AI tool that can predict with 80% accuracy whether individuals showing early signs of dementia will remain stable or progress to Alzheimer’s disease in four out of five cases.
This innovative approach has the potential to decrease reliance on invasive and expensive diagnostic procedures, leading to better treatment outcomes during early stages when interventions like lifestyle adjustments or new medications may be most effective.
Dementia presents a substantial healthcare challenge globally, impacting more than 55 million individuals with an annual economic burden estimated at $820 billion. The prevalence of dementia is projected to nearly triple over the next five decades.
Alzheimer’s disease is the primary cause of dementia, responsible for 60-80% of cases. Early detection is critical because treatments are most likely to be effective during this stage. However, accurate early diagnosis and prognosis of dementia often require invasive or costly procedures such as positron emission tomography (PET) scans or lumbar punctures, which are not universally accessible in memory clinics. Consequently, up to one-third of patients may receive incorrect diagnoses, while others may be diagnosed too late for treatment to be beneficial.
“We’ve created a tool which, despite using only data from cognitive tests and MRI scans, is much more sensitive than current approaches at predicting whether someone will progress from mild symptoms to Alzheimer’s – and if so, whether this progress will be fast or slow”
Professor Zoe Kourtzi
Scientists from the Department of Psychology at the University of Cambridge have led a team in developing a machine learning model that predicts the progression of mild memory and cognitive issues to Alzheimer’s disease more accurately than current clinical tools. Their research, published in eClinical Medicine, utilized non-invasive and cost-effective patient data — including cognitive assessments and structural MRI scans showing grey matter deterioration — from over 400 individuals in a US-based research cohort.
The model’s efficacy was then tested using real-world data from an additional 600 participants in the same US cohort, alongside longitudinal data from 900 individuals from memory clinics in the UK and Singapore. The algorithm successfully differentiated between individuals with stable mild cognitive impairment and those who progressed to Alzheimer’s disease within a three-year timeframe. It achieved an 82% accuracy in correctly identifying those who developed Alzheimer’s and an 81% accuracy in identifying those who did not, using only cognitive tests and MRI scans.
Compared to current clinical standards, which rely on markers like grey matter atrophy or cognitive scores, the algorithm demonstrated approximately three times greater accuracy in predicting Alzheimer’s progression. This significant improvement suggests the model could substantially reduce instances of misdiagnosis.
“We’ve created a tool which, despite using only data from cognitive tests and MRI scans, is much more sensitive than current approaches at predicting whether someone will progress from mild symptoms to Alzheimer’s – and if so, whether this progress will be fast or slow,” said Senior author Professor Zoe Kourtzi from the Department of Psychology at the University of Cambridge.
“This has the potential to significantly improve patient wellbeing, showing us which people need closest care, while removing the anxiety for those patients we predict will remain stable. At a time of intense pressure on healthcare resources, this will also help remove the need for unnecessary invasive and costly diagnostic tests,” he added.
Earth
Study Reveals How Ocean Bacteria Drive Plastic Biodegradation
Plastic biodegradation is emerging as a critical solution to the global waste crisis, and new research from Massachusetts Institute of Technology offers important insights into how this process actually works in nature.
A new study by researchers at Massachusetts Institute of Technology has shed fresh light on how bacteria in marine environments collaborate to break down biodegradable plastics—offering critical insights into tackling the global plastic waste crisis.
Biodegradable plastics have long been seen as a potential solution to mounting environmental pollution. However, scientists have struggled to determine how long these materials persist in real-world conditions and how microbial communities contribute to their breakdown.
The study, published in Environmental Science and Technology, marks one of the first efforts to identify the specific roles individual bacterial species play in plastic biodegradation.
“Plastic biodegradation is highly dependent on the microbial community where the plastic ends up,” says lead author Marc Foster, a PhD researcher in the MIT-WHOI Joint Program. “It’s also dependent on the chemistry of the plastic itself.”
Unlike earlier studies that focused on single microbes, the MIT team examined how multiple bacterial species work together—a more realistic representation of how plastics degrade in nature.
The researchers studied a widely used biodegradable plastic known as an aromatic aliphatic co-polyester, commonly found in shopping bags, food packaging, and agricultural films.
Samples of this plastic were first exposed to seawater in the Mediterranean, allowing natural bacterial communities to form biofilms on their surface. Scientists then isolated and analysed these microbes in the lab.
Key findings include:
- One bacterium, Pseudomonas pachastrellae, was able to break down the plastic polymer into smaller chemical components.
- Other bacterial species were needed to consume those individual chemicals, including terephthalic acid, sebacic acid, and butanediol.
- No single bacterium could complete the entire degradation process alone.
When researchers combined five complementary bacterial species, they were able to replicate the full degradation process observed in a larger microbial community.
“This complementary function was essential,” Foster explains. “None of the bacteria alone could achieve the same level of degradation as when they worked together.”
Why Plastic Biodegradation Rates Vary
The findings suggest that the speed and efficiency of plastic biodegradation depend on several key factors:
- Microbial diversity in the environment
- Chemical composition of the plastic
- Environmental conditions such as temperature and depth
Notably, the study also found that the same bacterial community could not degrade a different type of plastic, indicating that microbial systems may be highly material-specific.
Implications for Future Plastic Recycling Solutions
The research represents an important step toward developing microbial recycling systems that could convert plastic waste into useful materials.

By understanding how bacteria interact with plastics at a molecular level, scientists could:
- Design plastics that degrade more predictably
- Engineer microbial communities for faster plastic breakdown
- Develop biological recycling technologies
Foster notes that future work will explore how to optimise bacterial combinations and improve enzyme interactions with plastic surfaces.
A Step Forward in Tackling the Plastic Waste Crisis
With more than half of global plastic waste ending up in landfills or the environment, understanding plastic biodegradation is crucial for sustainable material design.
This study highlights a fundamental shift in perspective: plastic degradation is not driven by a single organism, but by complex microbial collaboration.
As research advances, such insights could help bridge the gap between biodegradable materials and real-world environmental outcomes—bringing science closer to solving one of the planet’s most pressing pollution challenges.The study, published in Environmental Science and Technology, marks one of the first efforts to identify the specific roles individual bacterial species play in plastic biodegradation.
“Plastic biodegradation is highly dependent on the microbial community where the plastic ends up,” says lead author Marc Foster, a PhD researcher in the MIT-WHOI Joint Program. “It’s also dependent on the chemistry of the plastic itself.”
Unlike earlier studies that focused on single microbes, the MIT team examined how multiple bacterial species work together—a more realistic representation of how plastics degrade in nature.
Earth
Life may have learned to breathe oxygen hundreds of millions of years earlier than thought
Early life on Earth has found an interetsing turning point. A new study by researchers at Massachusetts Institute of Technology suggests that some of Earth’s earliest life forms may have evolved the ability to use oxygen hundreds of millions of years before it became a permanent part of the planet’s atmosphere.
Oxygen is essential to most life on Earth today, but it was not always abundant. Scientists have long believed that oxygen only became a stable component of the atmosphere around 2.3 billion years ago, during a turning point known as the Great Oxidation Event (GOE). The new findings indicate that biological use of oxygen may have begun much earlier, potentially reshaping scientists’ understanding of how life evolved on Earth.
The study, published in the journal Palaeogeography, Palaeoclimatology, Palaeoecology, traces the evolutionary origins of a key enzyme that allows organisms to use oxygen for aerobic respiration. This enzyme is present in most oxygen-breathing life forms today, from bacteria to humans.
Scientists have long believed that oxygen only became a stable component of the atmosphere around 2.3 billion years ago, during a turning point known as the Great Oxidation Event (GOE). The new findings indicate that biological use of oxygen may have begun much earlier, potentially reshaping scientists’ understanding of how life evolved on Earth
MIT geobiologists found that the enzyme likely evolved during the Mesoarchean era, between 3.2 and 2.8 billion years ago—several hundred million years before the Great Oxidation Event.
The findings may help answer a long-standing mystery in Earth’s history: why it took so long for oxygen to accumulate in the atmosphere. Scientists know that cyanobacteria, the first organisms capable of producing oxygen through photosynthesis, emerged around 2.9 billion years ago. Yet atmospheric oxygen levels remained low for hundreds of millions of years after their appearance.
While geochemical reactions with rocks were previously thought to be the main reason oxygen failed to build up early on, the MIT study suggests biology itself may also have played a role. Early organisms that evolved the oxygen-using enzyme may have consumed small amounts of oxygen as soon as it was produced, limiting how much could accumulate in the atmosphere.
“This does dramatically change the story of aerobic respiration,” said Fatima Husain, postdoctoral researcher in MIT’s Department of Earth, Atmospheric and Planetary Sciences, said in a media statement. “Our study adds to this very recently emerging story that life may have used oxygen much earlier than previously thought. It shows us how incredibly innovative life is at all periods in Earth’s history.”
The research team analysed thousands of genetic sequences of heme-copper oxygen reductases—enzymes essential for aerobic respiration—across a wide range of modern organisms. By mapping these sequences onto an evolutionary tree and anchoring them with fossil and geological evidence, the researchers were able to estimate when the enzyme first emerged.
“The puzzle pieces are fitting together and really underscore how life was able to diversify and live in this new, oxygenated world
Tracing the enzyme back through time, the team concluded that oxygen use likely appeared soon after cyanobacteria began producing oxygen. Organisms living close to these microbes may have rapidly consumed the oxygen they released, delaying its escape into the atmosphere.
“Considered all together, MIT research has filled in the gaps in our knowledge of how Earth’s oxygenation proceeded,” Husain said. “The puzzle pieces are fitting together and really underscore how life was able to diversify and live in this new, oxygenated world.”
The study adds to a growing body of evidence suggesting that life on Earth adapted to oxygen far earlier than previously believed, offering new insights into how biological innovation shaped the planet’s atmosphere and the evolution of complex life.
The Sciences
Researchers crack greener way to mine lithium, cobalt and nickel from dead batteries
A breakthrough recycling method developed at Monash University in Australia can recover over 95% of critical metals from spent lithium-ion batteries—without extreme heat or toxic chemicals—offering a major boost to clean energy and circular economy goals.
Researchers at Monash University, based in Melbourne, Australia, have developed a breakthrough, environmentally friendly method to recover high-purity nickel, cobalt, manganese and lithium from spent lithium-ion batteries, offering a safer alternative to conventional recycling processes.
The new approach uses a mild and sustainable solvent, avoiding the high temperatures and hazardous chemicals typically associated with battery recycling. The innovation comes at a critical time, as an estimated 500,000 tonnes of spent lithium-ion batteries have already accumulated globally. Despite their growing volume, recycling rates remain low, with only around 10 per cent of spent batteries fully recycled in countries such as Australia.
Most discarded batteries end up in landfills, where toxic substances can seep into soil and groundwater, gradually entering the food chain and posing long-term health and environmental risks. This is particularly concerning given that spent lithium-ion batteries are rich secondary resources, containing strategic metals including lithium, cobalt, nickel, manganese, copper, aluminium and graphite.
Existing recovery methods often extract only a limited range of elements and rely on energy-intensive or chemically aggressive processes. The Monash team’s solution addresses these limitations by combining a novel deep eutectic solvent (DES) with an integrated chemical and electrochemical leaching process.
Dr Parama Banerjee, principal supervisor and project lead from the Department of Chemical and Biological Engineering, said the new method achieves more than 95 per cent recovery of nickel, cobalt, manganese and lithium, even from industrial-grade “black mass” that contains mixed battery chemistries and common impurities.

“This is the first report of selective recovery of high-purity Ni, Co, Mn, and Li from spent battery waste using a mild solvent,” Dr Banerjee said.
“Our process not only provides a safer, greener alternative for recycling lithium-ion batteries but also opens pathways to recover valuable metals from other electronic wastes and mine tailings.”
Parisa Biniaz, PhD student and co-author of the study, said the breakthrough represents a significant step towards a circular economy for critical metals while reducing the environmental footprint of battery disposal.
“Our integrated process allows high selectivity and recovery even from complex, mixed battery black mass. The research demonstrates a promising approach for industrial-scale recycling, recovering critical metals efficiently while minimising environmental harm,” Biniaz said.
The researchers say the method could play a key role in supporting sustainable energy transitions by securing critical mineral supplies while cutting down on environmental damage from waste batteries.
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