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Got a sore throat and the sniffles? The recent rise of rapid at-home tests has made it easier to find out if you have a serious illness like COVID-19 or just a touch of spring allergies. 

But while quick and convenient, these at-home tests are less sensitive than those available at the doctor’s office, meaning that you may still test negative even if you are infected.

A solution may come in the form of a new, low-cost biosensing technology that could make rapid at-home tests up to 100 times more sensitive to viruses like COVID-19. The diagnostic could expand rapid screening to other life-threatening conditions like prostate cancer and sepsis, as well.

Created by researchers at the University of California, Berkeley, the test combines a natural evaporation process called the “coffee-ring effect” with plasmonics and AI to detect biomarkers of disease with remarkable precision in just minutes. 

“This simple yet effective technique can offer highly accurate results in a fraction of the time compared to traditional diagnostic methods,” said Kamyar Behrouzi, who recently completed a Ph.D. in micro-electromechanical systems and nanoengineering at UC Berkeley. “Our work paves the way for more affordable, accessible diagnostics, especially in low-resource settings.”

The technology was developed with the support of seed funding from the CITRIS and Banatao Institute at UC Berkeley and is described in a recent study published in the journal Nature Communications.

Combining coffee rings and nanoparticles

Look closely at any coffee or wine stain, and you might observe that the outline of the stain is much darker than the interior. This is due to a physical phenomenon called the coffee-ring effect: As a droplet of liquid evaporates, it generates a flow that pushes suspended particles towards the edge of the droplet. If the particles are pigmented, as they are in coffee and wine, the resulting stain will be darker around the rim than in the middle. 

In 2020, Behrouzi was developing a biosensor for detecting COVID-19 when he noticed that droplets of his experimental solution were leaving ring-shaped stains as they dried. He realized that this coffee-ring effect could be used to easily concentrate particles of the COVID-19 virus, potentially making them easier to detect. 

“We figured out that we could use this coffee-ring effect to build something even better than what we initially set out to create,” Behrouzi said.

The rapid test technology uses tiny particles called plasmonic nanoparticles that interact with light in unique ways. To conduct the test, a user first adds a droplet of liquid containing disease-relevant proteins – such as from a cheek or nasal swab – to a membrane. As the droplet dries, it concentrates any disease biomarkers at the coffee ring. The user then adds a second droplet containing plasmonic nanoparticles that have been engineered to stick to the disease biomarkers. If the biomarkers are present, the nanoparticles will aggregate in certain patterns that change how light interacts with the membrane. This change can be detected by eye or using an AI-powered smartphone app. 

The technology gives results in less than 12 minutes and is 100 times more sensitive at detecting COVID-19 than equivalent tests. 

One of the key proteins that we are able to detect with this method is a biomarker of sepsis, a life-threatening inflammatory response to a bacterial infection that can develop rapidly in people over 50. Every hour is critical, but culturing bacteria to determine the source of the infection can take a few days. Our technique could help doctors detect sepsis in 10 to 15 minutes.”

Liwei Lin, Study Senior Author, Distinguished Professor of Mechanical Engineering at UC Berkeley

The researchers have created a prototype of a home testing kit, similar to at-home COVID testing kits, that includes 3D-printed components to help guide the placement of the sample and plasmonic droplets. 

“During the COVID-19 pandemic, we relied on at-home tests to know if we were infected or not,” Lin said. “I hope that our technology makes it easier and more accessible for people to regularly screen for conditions like prostate cancer without leaving the home.”

Additional co-authors of the study include Zahra Khodabakhshi Fard, Chun-Ming Chen, Peisheng He and Megan Teng of UC Berkeley. 

The climate we live in affects our lives in profound ways: hot summers, cold winters, dry spells and wet weather all leave their mark.

For growing children, one way seasons and storms are recorded is in their teeth. As we have shown in new research, teeth contain a week-by-week climatic history of their owner’s childhood.

To establish this, we studied the teeth of wild chimpanzees, captive macaque monkeys, and a woman born in Brisbane in January 1990. Her infancy included distinctive weather events – but its more powerful use is to reveal the climates that shaped individual lives thousands or even millions of years ago.

How does it work?

You wouldn’t know it, but changes in rainfall and temperature cause subtle changes in drinking water. Specifically, they affect the proportions of different atomic variants of oxygen (the isotopes oxygen-18 and oxygen-16).

Under a microscope, you can see tiny lines inside teeth that correspond to daily layers of growth. Using a machine called the Sensitive High Resolution Ion MicroProbe (SHRIMP) at the Australian National University, we vaporised spots of enamel corresponding to these lines and analysed the oxygen isotopes in the vapour.

Once we know about the balance of oxygen isotopes, we can work backwards to determine changes in drinking water and the corresponding climatic conditions.

Brisbane, 1990

Our Australian tooth donor began her life during a wet summer during which a cyclone dumped enormous amounts of rain on Brisbane and surrounds, and months of high rainfall in the region persisted through to autumn.

Her tooth enamel formed during the summer of 1990 showed oxygen isotope trends that were consistent with the rainfall patterns at the time. The minimum values occurred close in time to the wettest period, and the maximum values happened towards the end of the long dry spell that began later in the year.

After she reached her first birthday, these climate markers became more challenging to interpret. This likely happened because she began to consume more cooked foods, which carry a different isotope balance from raw food and breast milk.

Diet records

Thankfully, the SHRIMP can also help us learn more about these dietary changes by measuring nitrogen isotopes in the tooth dentine (which is found under the outer layer of enamel). There is a known relationship between the balance of nitrogen-15 and nitrogen-14 and the protein in a child’s diet.

In an earlier study, we looked at these records in the same tooth. Mothers’ milk contains high levels of nitrogen-15, and our donor showed a clear signal of rising values from birth. Shortly after six months of age, her nitrogen isotope ratio began to fall, as her mother gradually began offering her fruits and vegetables to supplement her exclusive milk diet.

During our donor’s second year of life, she was fed more solid foods, including bread, cheese, eggs, and yogurt – leading to a further decline in the isotopic ratio. She continued breastfeeding at night for a few months into her third year, and finally as she ceased nursing entirely, her nitrogen values reached a minimum.

From 35 years ago to 17 million years ago

Fine-scaled isotopic studies such as these are a world first. Teeth are typically sampled with hand-held drills or small saws to measure inputs from water and food.

These coarse sampling methods are relatively common and inexpensive, but they cannot show short-term changes in the composition of teeth. This limits how well they can be used to identify important environmental or dietary changes.

Our new technique has many applications. We’ve studied Neanderthal children from the Rhône basin of southeastern France, who experienced some rough seasons 250,000 years ago. By SHRIMPing thin tooth slices, and relating this to enamel formation ages, we were even able to estimate the seasons in which one child was born and weaned 2.5 years later.

We have just begun to produce isotopic weaning curves for humans who lived several hundred to several thousand years ago, yielding new insights into ancient maternal behaviour and infant health.

This technology can also be applied to much more ancient fossils, including apes who lived in Africa 17 million years ago. In this instance, isotopic differences between fossils were consistent with other evidence that a changing climate played an important role in influencing the anatomy and development of humanity’s forebears.

Teeth hold many more tales, and technological breakthroughs such as those at the Australian National University will continue to reveal hidden details of our ancient humanity as well as the unintended consequences of our modern lifestyles.

LOS ANGELES – Alzheimer’s disease may not begin with a single red flag—but rather with patterns that unfold in a predictable sequence. That’s the finding of a new UCLA Health study, which offers fresh insight into how the disease develops and how clinicians could better predict who’s most at risk.

Instead of looking at isolated health conditions, researchers used advanced data modeling to map how various diagnoses accumulate over time before Alzheimer’s onset. Their work, published July 7 in eBioMedicine, could lead to more personalized prevention strategies and earlier interventions.

The study analyzed nearly 25,000 patients in the University of California Health system and confirmed its findings using data from the All of Us Research Program—a national cohort representing diverse populations across the U.S.

What are the four pathways to Alzheimer’s disease?

The backstory:

Researchers identified four distinct diagnostic sequences that frequently lead to Alzheimer’s disease. Each reflects a different type of progression:

• Mental health pathway: Psychiatric diagnoses like depression increase the risk of cognitive decline.
• Encephalopathy pathway: Brain dysfunction conditions accumulate and intensify over time.
• Mild cognitive impairment pathway: Early memory and thinking problems gradually worsen.
• Vascular disease pathway: Heart-related issues, including hypertension, contribute to dementia risk.

Each pathway had unique clinical and demographic traits, suggesting that different groups may face different risks depending on their medical history.

What we know:

About 26% of Alzheimer’s progressions followed identifiable diagnostic sequences.

These patterns, such as hypertension followed by depression, predicted Alzheimer’s onset more reliably than single diagnoses.

Advanced methods—including machine learning and network analysis—helped identify these progression models.

What we don’t know:

It’s unclear how soon these diagnostic trajectories can be translated into clinical screening tools.

More research is needed to test whether interrupting these sequences can delay or prevent Alzheimer’s.

The pathways show correlation, not causation—so other factors may still be at play.

How this research could change early Alzheimer’s care

What they’re saying

“We found that multi-step trajectories can indicate greater risk factors for Alzheimer’s disease than single conditions. Understanding these pathways could fundamentally change how we approach early detection and prevention,” said Mingzhou Fu, first author and pre-doctoral student in medical informatics at UCLA.

Lead author Dr. Timothy Chang, assistant professor of Neurology at UCLA Health, said:

“Recognizing these sequential patterns rather than focusing on diagnoses in isolation may help clinicians improve Alzheimer’s disease diagnosis.”

What’s next:

Researchers say these trajectory models could support:

• Risk stratification, identifying who’s most likely to develop Alzheimer’s
• Targeted intervention, disrupting dangerous diagnostic chains early
• Personalized care, based on the pathway a patient is following

The next step will be translating these insights into tools doctors can use in real-time to flag risk earlier and possibly intervene before symptoms appear.