Category: 8. Health

Fitness coach Navneeth Ramprasad, on April 11, shared an Instagram post and explained how avoiding healthy foods can worsen diabetes in your parents. “If your parents are diabetic and you’re not giving them these 5 foods every day, be prepared to spend a lot more on medical bills in a few years, especially the last one. Let’s be real: Most Indian households are still eating the same food that made us the diabetes capital of the world,” Navneeth added.

According to him, here are five foods that your parents must consume every day, if they are diabetic.

1. Fresh coconut and almonds

First thing in the morning, instead of tea or coffee. The healthy fats stabilise blood sugar, reduce morning crashes, and support brain health. Have 2 pieces of coconut and 5 soaked almonds. That’s it. Also read | Diabetes: 7 high-fibre foods that can prevent blood sugar spikes

2. Oats, Greek yoghurt and berries

For breakfast, instead of dosa, idly, or toast. Low GI carbs + protein + fiber + antioxidants = no sugar spikes and longer fullness.

3. Millet khichdi, sprouts and cooked veggies

For lunch, instead of white rice, sambar, and papad. Use foxtail millet or quinoa with moong dal, add steamed sprouts, and a bowl of high fiber veggies. Balanced plate = fiber, protein, slow carbs, and better post-lunch sugar control.

4. Tofu or tempeh for dinner

High-protein, low-carb, and essential for reversing insulin resistance. Add veggies, stir-fry or grill — just don’t end the day with wheat rotis alone.

5. Pumpkin seeds, just before bedtime (9–9:30 PM)

Prevents midnight sugar dips, supports sleep and magnesium levels. 1 small spoon (not more) of raw or lightly roasted seeds is perfect for diabetics who wake up tired or with sugar crashes at night. Also read | Smart eating for diabetes: Nutritionist-approved diet tips to keep your blood sugar in check

Note to readers: This article is for informational purposes only and not a substitute for professional medical advice. Always seek the advice of your doctor with any questions about a medical condition.

A UCSF analysis has found that the newer generation of much more effective diabetes medications are reaching only a fraction of the patients who are recommended to take them based on new guidelines.

Type 2 diabetes (T2D), a condition in which the body can’t use insulin to clear sugar from the bloodstream, affects 1 in 10 Americans. It comes with grave health risks, including cardiovascular and kidney disease.

The study assessed medications that patients received within a year of T2D diagnosis. During the period under review – 2014 to 2022 – groups like the American Diabetes Association and the American Heart Association began encouraging the use of newer medications over some older, less effective ones.

The analysis, which is based on more than 40,000 records from the University of California Health Data Warehouse, found some encouraging results. 

The use of sodium-glucose cotransporter 2 (SGLT2) inhibitors or glucagon-like peptide 1 (GLP-1) receptor agonists – two newer categories of drugs – increased, particularly among patients with cardiovascular or kidney disease.

Meanwhile, the use of sulfonylureas – a category of diabetes drug with severe side effects, now seen as a last resort in treatment – declined. And the use of metformin and insulins, the classic medications for diabetes, declined slightly. 

Still, by 2022, just 20% T2D patients were receiving GLP-1 drugs within a year of diagnosis, and less than 15% of patients were receiving SGLT2 drugs – reflecting a gap between what the professional guidelines recommend and the care that patients are receiving.

The researchers gave several reasons for why this might be. One is that GLP-1 drugs, like Wegovy and Ozempic, are expensive, and insurance doesn’t always cover them. Another is that not every provider knows that leading organizations recommend prescribing GLP-1 and SGLT2 drugs, like Jardiance or Farxiga, for T2D from the moment of diagnosis. 

Some of the most devastating consequences of diabetes come from its effects on the heart and kidney, and thankfully, we now have drugs that target those effects head on. But to maximize the benefit for the many hundreds of thousands of patients in the U.S., we need to increase access to these drugs and make sure that clinicians understand just how beneficial they are.” 

Jonathan Watanabe, PharmD, MS, PhD, the senior author of the study

A prospective cohort study led by Yang Shao, PhD, president and CEO of Geneseeq Technology Inc. and professor at Nanjing Medical University, Nanjing, published in Nature Medicine, on a blood test capable of simultaneously detecting 13 types of cancer. The test demonstrated high sensitivity and specificity and was able to identify early-stage cancers that often go unnoticed during routine screenings.

Traditional cancer screening methods are often invasive, expensive, and time-consuming, which can reduce patient adherence. In addition, several cancers — such as pancreatic cancer — are typically asymptomatic in their early stages and progress rapidly, with no established screening protocols currently available.

This prompted the development of less invasive approaches, such as multi-cancer early detection (MCED) blood tests that can detect a cancer signal from circulating cell-free DNA. These simple blood tests analyze plasma cell-free DNA using genetic and fragmentomic-based features from whole genome sequencing to simultaneously detect multiple cancer types. Although promising, current MCED tests still have relatively low sensitivity, typically less than 60%. Experts, including those from the American Cancer Society, cautioned that widespread use could create a false sense of reassurance and potentially deter patients from following up with standard screenings.

Researchers have developed an MCED blood test that detects 13 cancers: breast, cervical, colorectal, endometrial, esophageal, gastric, liver, lung, ovarian, pancreatic, prostate, biliary tract, and lymphoma. These cancers account for 66.6% of all new cases and 74% of cancer-related deaths worldwide. The test uses two main classifiers: the detection-of-cancer classifier, tasked with confirming the presence of cancer, and the tissue-of-origin classifier, responsible for pinpointing the primary site of malignancy by analyzing and integrating feature frameworks, including copy number variations, fragment size coverage, fragment size distribution, nucleosome footprint, and fragment-based methylation.

To develop the test, researchers analyzed 6553 blood samples, 3076 from patients with cancer and 3477 from healthy individuals, divided into a training dataset of 4807 samples and an internal validation dataset of 1746 samples.

Independent validation was performed using a prospectively enrolled cohort of 1465 participants in an age-matched fashion, comprising 732 patients with cancer and 733 non-cancer individuals between April and November 2021. In the third ongoing phase, 3724 asymptomatic adults aged 45-75 years in the Jinling cohort underwent both complete physical examinations and the MCED test in June 2023.

Positive Results

In independent validation, the MCED test showed an overall sensitivity of 87.4% and specificity of 97.8%. The sensitivity was particularly high for certain cancer types, such as 100% for liver and biliary tract cancer, 94.5% for lung cancer, and 82.3% for colorectal cancer. Even cancers that are difficult to diagnose early, such as pancreatic and ovarian cancers, showed a sensitivity of 76.9% for pancreatic cancer and 90.5% for ovarian cancer. Breast cancer had the lowest sensitivity at 63.8%.

The test was effective in detecting early-stage disease, with a sensitivity of 79.3% for stage I and 86.9% for stage II cancer. This increased to 92.4% for stage III and 97.1% for stage IV. When considering the top two tissue origin predictions, the accuracy increased to 90.7% for the internal set and 91.7% for the independent set. It performed best in identifying cancers of the colon-rectum, lungs, and liver but was less accurate for pancreatic and stomach cancers, correctly identifying the origin in 50% or fewer cases.

In a prospective screening cohort of asymptomatic individuals, the MCED test identified 23 of 43 cancer cases within 1 year, with an overall sensitivity of 53.5%. When limited to the 13 cancers that the test was designed to detect, the sensitivity increased to 62.1%. Most of these cases (93%) were early-stage cancers (stage 0, I, or II). The specificity remained high at 98.1%, with a positive predictive value (PPV) of 25% and a negative predictive value of 99.4%.

Notably, 8 of the 23 positive patients who received a positive MCED result had their cancers undetected through physical examination, and 4 had cancers for which there is currently no recommended screening, highlighting the potential of the MCED test to effectively detect cancers that would otherwise have gone undetected.

“Our study demonstrated high sensitivity, highlighting our classifier’s ability to detect cancer cases, even in populations with lower disease prevalence. This underscores the capacity of our classifier to effectively detect incident cancer cases under real-world screening conditions, facilitated by comprehensive physical examinations,” the authors concluded.

These findings suggest that the MCED test could be a valuable complement to existing screening methods, particularly for cancers without routine early detection tools. The ability to detect early-stage pancreatic and ovarian cancers is particularly promising. However, broader validation across diverse populations, cost-effectiveness analyses, and studies on the psychological impact of screening outcomes are critical before widespread clinical implementation.

One key limitation was that the PPV achieved was 25% for the MCED test, which was lower than the 38% reported in the PATHFINDER study published in 2023.

“The PATHFINDER trial enrolled participants with a higher cancer prevalence and utilized the MCED test results to trigger diagnostic workup, systematically investigating participants with positive test results, thus inherently enriching their cohort for cancer diagnoses within the workup pathway. Conversely, the Jinling study adopted a standardized comprehensive physical examination for all participants as the primary screening modality, independent of MCED test outcomes and within the context of lower cancer prevalence,” the researchers noted.

However, the absolute number of false positives in the Jinling study was low (20 of 3724 participants, or 0.54%). False-positive results can lead to unnecessary anxiety, further invasive diagnostic procedures, and potentially inappropriate treatment for patients. The researchers emphasized the need to improve the sensitivity of the MCED test for very early-stage cancers while reducing false positives.

This story was translated from Univadis Italy. 

Scientists at the National Institutes of Health (NIH) have found that two common types of hormone therapy may alter breast cancer risk in women before age 55. Researchers discovered that women treated with unopposed estrogen hormone therapy (E-HT) were less likely to develop the disease than those who did not use hormone therapy. They also found that women treated with estrogen plus progestin hormone therapy (EP-HT) were more likely to develop breast cancer than women who did not use hormone therapy. Together, these results could help to guide clinical recommendations for hormone therapy use among younger women.

The two hormone therapies analyzed in the study are often used to manage symptoms related to menopause or following hysterectomy (removal of uterus) or oophorectomy (removal of one or both ovaries). Unopposed estrogen therapy is recommended only for women who have had a hysterectomy because of its known association with uterine cancer risk.

Hormone therapy can greatly improve the quality of life for women experiencing severe menopausal symptoms or those who have had surgeries that affect their hormone levels. Our study provides greater understanding of the risks associated with different types of hormone therapy, which we hope will help patients and their doctors develop more informed treatment plans.”

Katie O’Brien, Ph.D., lead author of NIH’s National Institute of Environmental Health Sciences (NIEHS)

The researchers conducted a large-scale analysis that included data from more than 459,000 women under 55 years old across North America, Europe, Asia, and Australia. Women who used E-HT had a 14% reduction in breast cancer incidence compared to those who never used hormone therapy. Notably, this protective effect was more pronounced in women who started E-HT at younger ages or who used it longer. In contrast, women using EP-HT experienced a 10% higher rate of breast cancer compared to non-users, with an 18% higher rate seen among women using EP-HT for more than two years relative to those who never used the therapy.

According to the authors, this suggests that for EP-HT users, the cumulative risk of breast cancer before age 55 could be about 4.5%, compared with a 4.1% risk for women who never used hormone therapy and a 3.6% risk for those who used E-HT. Further, the association between EP-HT and breast cancer was particularly elevated among women who had not undergone hysterectomy or oophorectomy. That highlights the importance of considering gynecological surgery status when evaluating the risks of starting hormone therapy, the researchers noted.

“These findings underscore the need for personalized medical advice when considering hormone therapy,” said NIEHS scientist and senior author Dale Sandler, Ph.D. “Women and their health care providers should weigh the benefits of symptom relief against the potential risks associated with hormone therapy, especially EP-HT. For women with an intact uterus and ovaries, the increased risk of breast cancer with EP-HT should prompt careful deliberation.”

The authors noted that their study is consistent with previous large studies that documented similar associations between hormone therapy and breast cancer risk among older and postmenopausal women. This new study extends those findings to younger women, providing essential evidence to help guide decision-making for women as they go through menopause.

What can contribute to heart attack risk?

Dr Dhirendra Singhania, principal consultant of interventional cardiology at Yashoda Super Speciality Hospitals in Kaushambi, said in June 30 interview with NDTV that the ‘major causes of risk in heart attacks are steroids, lack of sleep, and hormonal therapies, especially for women’.

He said, “Everyone, whether a celebrity or a common man, if they are not following the rules of the body, they will have problems. In celebrities, they all try to maintain their body for fit appearances. Many times, we don’t know what they do to achieve that. Lack of sleep has been known as a cardiac risk factor – many celebrities are awake for almost the whole night at times.”

Highlighting the importance of approaching anti-ageing treatments with caution, and prioritising your health and safety, Dr Singhania added, “Steroids, drug overdoses, and hormonal therapies for women, such as hormone replacement therapy (HRT for menopause) and oral contraceptives, can contribute to heart attack risk.”

Be cautious with anti-ageing treatments

Before trying any anti-ageing treatments, it’s essential to consult a qualified doctor, especially if you have heart conditions or other health issues. In a May 2025 interview with HT Lifestyle, a dermatologist explained non-invasive skin treatments, the ideal age to start them, signs of ageing, and who should avoid these treatments in a complete guide. Click here to know what she said.

Note to readers: This article is for informational purposes only and not a substitute for professional medical advice. Always seek the advice of your doctor with any questions about a medical condition.

A new study from UCLA Health has uncovered how inflammation in brain blood vessels exacerbates damage in vascular dementia and demonstrated that targeting this process with a repurposed drug can promote brain repair and functional recovery in mice.

Published in Cell, the research combines laboratory and human data to pinpoint a critical signaling pathway that could lead to the first effective treatment for this understudied form of dementia.

Vascular dementia is the second leading cause of dementia. This disease co-occurs with Alzheimer’s disease in the leading cause of dementia, termed “mixed dementia.” There is no drug therapy that promotes recovery in vascular dementia. A key problem in this disease is that the brain damage expands from initial areas, to become larger over time. The UCLA team sought to identify what happens in the brain in these areas of expansion. To do this, the researchers identified all the molecules that communicate among the cells of the brain adjacent to the dementia lesions, and which ones are abnormally up or down in the disease compared to normal brain. By doing this both in laboratory models of vascular dementia and in human brain, the UCLA team was able to precisely identify the “interactome” in vascular dementia – all the molecules that signal or interact in the cells at risk.

We reasoned that the cell in the brain areas in which the disease expands will lose their normal signaling with each other. In other words, the cell-to-cell interaction is disturbed in a toxic way in vascular dementia. We set out to identify these cell-to-cell interactions or the “interactome” in vascular dementia.” 

Dr. S. Thomas Carmichael, study’s lead author and professor and chair Neurology at the David Geffen School of Medicine at UCLA

One molecular system jumped out as potentially significant. This system communicates between blood vessel cells and adjacent brain inflammatory cells, termed microglia. In vascular dementia, the CD39 (an enzyme) and the adenosine A3 receptor (A3AR) are downregulated together in these two cell types, synergistically by aging and vessel ischemic lesion. Because vascular dementia is a disease of aging, this double finding – a downregulation with both disease and aging – signaled a possibly significant role. CD39 generates through several steps the molecule adenosine, which binds to A3AR, and modifies inflammation, downregulating some of its harmful effects. 

To test this CD39/A3AR system as a possible drug target for treating vascular dementia, the group utilized a drug that is in clinical trials for psoriasis. When given to mice in a model of vascular dementia, this drug promoted repair of brain tissue and recovery of memory and gait functions.

“The most exciting finding was that delayed intervention still worked,” said lead author Dr. Min Tian, a postdoctoral scholar at UCLA Health. “This is crucial because vascular dementia is often diagnosed late. By targeting the crosstalk between blood vessels and brain cells, we’re addressing the root cause of damage, not just masking symptoms.”

While the results are promising, further studies are needed before human trials can begin. The team is now optimizing dosing and exploring biomarkers to track the therapy’s effectiveness.

The study, “Deconstructing the Intercellular Interactome in Vascular Dementia with Focal Ischemia for Therapeutic Applications,” will be online in Cell, June 30, 2025, and includes collaborators from UCLA’s neurology, pathology, neurobiology, physiology and psychiatry departments. Funding was provided by the National Institutes of Health, Ressler Family Foundation, The Dr. Miriam and Sheldon G. Adelson Medical Research Foundation, UCLA Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, including support from the Steffy Family Trust.

In radiation therapy, precision can save lives. Oncologists must carefully map the size and location of a tumor before delivering high-dose radiation to destroy cancer cells while sparing healthy tissue. But this process, called tumor segmentation, is still done manually, takes time, varies between doctors – and can lead to critical tumor areas being overlooked.

Now, a team of Northwestern Medicine scientists has developed an AI tool called iSeg that not only matches doctors in accurately outlining lung tumors on CT scans but can also identify areas that some doctors may miss, reports a large new study.

Unlike earlier AI tools that focused on static images, iSeg is the first 3D deep learning tool shown to segment tumors as they move with each breath – a critical factor in planning radiation treatment, which half of all cancer patients in the U.S. receive during their illness.

We’re one step closer to cancer treatments that are even more precise than any of us imagined just a decade ago.”

Dr. Mohamed Abazeed, senior author, chair and professor of radiation oncology at Northwestern University Feinberg School of Medicine

“The goal of this technology is to give our doctors better tools,” added Abazeed, who leads a research team developing data-driven tools to personalize and improve cancer treatment and is a member of the Robert H. Lurie Comprehensive Cancer Center of Northwestern University.

The study will be published June 30 in the journal npj Precision Oncology.

How iSeg was built and tested

The Northwestern scientists trained iSeg using CT scans and doctor-drawn tumor outlines from hundreds of lung cancer patients treated at nine clinics within the Northwestern Medicine and Cleveland Clinic health systems. That’s far beyond the small, single-hospital datasets used in many past studies.

After training, the AI was tested on patient scans it hadn’t seen before. Its tumor outlines were then compared to those drawn by physicians. The study found that iSeg consistently matched expert outlines across hospitals and scan types. It also flagged additional areas that some doctors missed – and those missed areas were linked to worse outcomes if left untreated. This suggests iSeg may help catch high-risk regions that often go unnoticed.

“Accurate tumor targeting is the foundation of safe and effective radiation therapy, where even small errors in targeting can impact tumor control or cause unnecessary toxicity,” Abazeed said.

“By automating and standardizing tumor contouring, our AI tool can help reduce delays, ensure fairness across hospitals and potentially identify areas that doctors might miss – ultimately improving patient care and clinical outcomes,” added first author Sagnik Sarkar, a senior research technologist at Feinberg who holds a Master of Science in artificial intelligence from Northwestern.

Clinical deployment possible ‘within a couple years’

The research team is now testing iSeg in clinical settings, comparing its performance to physicians in real time. They are also integrating features like user feedback and working to expand the technology to other tumor types, such as liver, brain and prostate cancers. The team also plans to adapt iSeg to other imaging methods, including MRI and PET scans.

“We envision this as a foundational tool that could standardize and enhance how tumors are targeted in radiation oncology, especially in settings where access to subspecialty expertise is limited,” said co- author Troy Teo, instructor of radiation oncology at Feinberg.

“This technology can help support more consistent care across institutions, and we believe clinical deployment could be possible within a couple of years,” Teo added.

This study is titled “Deep learning for automated, motion- resolved tumor segmentation in radiotherapy.”

For the first time, the extreme variability in dengue fever has been linked to a biological mechanism, potentially opening doors to new treatments and vaccines for the most common mosquito-borne disease worldwide. The study was published today in Proceedings of the National Academy of Sciences (PNAS) by researchers from the University of Pittsburgh, UPMC and Instituto Aggeu Magalhães in Brazil.

Cases of dengue fever, commonly known as “breakbone fever” for the excruciating joint pain that is the hallmark of the disease, have been rising around the world in recent years. More than half the global population is at risk.

There’s an urgent need for better prevention and treatment for this global threat. Dengue outbreaks can quickly overwhelm local hospitals.”

Priscila Castanha, Ph.D., MPH, lead author, assistant professor of infectious diseases and microbiology at Pitt’s School of Public Health

The course of the disease varies widely from person to person. Some are asymptomatic; others experience dengue’s painful flu-like symptoms and then recover within days or weeks. “But 5% have serious bleeding, shock and organ failure-they can be critically ill within two days,” said senior author Simon Barratt-Boyes, Ph.D., professor of infectious diseases and microbiology at Pitt Public Health and immunology at Pitt School of Medicine.

For decades, epidemiologic studies have documented a puzzling phenomenon: In countries with ethnically diverse populations-like Brazil, Colombia, Haiti and Cuba-people of African ancestry tend to have milder cases of dengue, while people of European ancestry have more severe disease. But no one could explain why.

In this study, the team used a model they developed with samples of human skin that had been donated by individuals who had undergone elective skin-reduction surgeries after profound weight loss. The participants consented to contributing their tissues to this study.

“We used skin because it is an immunologic organ and the body’s first line of defense against dengue infection,” said Barratt-Boyes. When maintained in culture under proper conditions, the tissue samples used in this model can survive and carry out their normal immune functions for days, providing a unique opportunity for scientific study, he added, “because the skin is where the story begins with all mosquito-borne diseases.”

The study focused on samples from individuals who had self-identified as having European or African ancestry. First, the researchers objectively measured the ancestral geographic origins written into the skin samples’ DNA by analyzing genetic markers known as single nucleotide polymorphisms. The team then injected each sample with dengue virus, observed the samples’ subsequent immune responses over a 24-hour period and compared them.

The team found that the inflammatory response was much greater in skin from people with higher proportions of European ancestry. And unfortunately, in severe dengue, this immune response is prone to “friendly fire.” The virus infects inflammatory cells, actually recruiting them to spread the infection instead of fighting it off. This dynamic is believed to be what is so damaging to blood vessels and organs in severe cases of dengue fever.

In the samples from donors of European ancestry, the team saw this friendly fire in action as myeloid cells mobilized to confront the virus, then themselves became infected. The turncoat cells then moved out of the skin and spread out into the dish-similar to how they would spread within the body, traveling through the bloodstream and into lymph nodes.

The team further showed that the problem was not the skin itself-it was indeed the inflammatory response. In the samples from individuals with higher proportions of African ancestry, the researchers added inflammatory molecules called cytokines, and the friendly fire ensued. Then, when the team blocked the inflammation within those same samples, the virus’s rate of infection in the cells plummeted.

“It makes sense that, in parts of the world where ancient populations were exposed to deadly mosquito-borne viruses-like the one that causes yellow fever, which is related to dengue viruses and has been around for a very long time-those with a limited inflammatory response had an advantage,” said Barratt-Boyes. “They then passed that advantage down to their descendants.” Ancient Europeans’ descendants, however, lack that ancestral exposure and the evolutionary adaptation it made possible.

The authors hope that, eventually, the mechanism they’ve identified could be exploited for precision medicine approaches to things like risk assessment, triage in an outbreak, therapies and vaccines. In future studies, they hope to describe this mechanism in further detail, including which specific gene variants contribute to protection from severe dengue. The current study’s broader analysis of geographic ancestry could be an important first step to that end.

“Ancestry does affect biology. Evolution has made its mark on everyone’s DNA,” said Castanha.

Other authors on the study are Michelle M. Martí, M.S., Parichat Duangkhae, Ph.D., Jocelyn M. Taddonio, M.S., Kristine L. Cooper, M.S., Megan Wallace, M.S., Gwenddolen Kettenburg, M.S., Geza Erdos, Ph.D., Hasitha Chavva, M.S., Aleena Alex, M.S., Pharm. D., J. Peter Rubin, M.D., Simon C. Watkins, Ph.D., Louis D. Falo, Jr., M.D., Ph.D., and Jeremy J. Martinson, Ph.D., all of Pitt; and Ernesto T. A. Marquesa, M.D., Ph.D., of Pitt and Instituto Aggeu Magalhães.

This research was supported by Pitt, the Institute for Precision Medicine, the Richard K Mellon Foundation for Pediatric Research and the National Cancer Institute (P30CA047904). 

Every year, tens of thousands of people with signs of Parkinson’s disease go unnoticed until the incurable neurodegenerative condition has already progressed.

Motor symptoms, such as tremors or rigidity, often emerge only after significant neurological damage has occurred. By the time patients are diagnosed, more than half of their dopamine-producing neurons may already be lost. This kind of diagnostic delay can limit treatment options and slow progress on early-stage interventions. While there are existing tests to detect biomarkers of Parkinson’s, including cell loss in the brain and inflammatory markers in blood, they typically require access to specialists and costly equipment at major medical centers, which may be out of reach for many.

Led by Jun Chen, an associate professor of bioengineering at the UCLA Samueli School of Engineering, researchers have developed a seemingly simple yet effective tool: a smart, self-powered magnetoelastic pen that could help detect early signs of Parkinson’s by analyzing a person’s handwriting.

The highly sensitive diagnostic pen, described in a UCLA-led study and published as a cover story in the June issue of Nature Chemical Engineering, features a soft, silicon magnetoelastic tip and ferrofluid ink – a special liquid containing tiny magnetic particles. When the pen’s tip is pressed against a surface or moved in the air, the pen converts both on-surface and in-air writing motions into high-fidelity, quantifiable signals through a coil of conductive yarn wrapped around the pen’s barrel. Although not intended for writing, the pen is self-powered leveraging changes in the magnetic properties of its tip and the dynamic flow of the ferrofluid ink to generate data.

To test the pen’s diagnostic potential, the team conducted a pilot study with 16 participants, three of whom had Parkinson’s disease. The pen recorded detailed handwriting signals, which were then analyzed by a neural network trained to detect motor patterns associated with the disease. The model was able to distinguish participants with Parkinson’s from healthy individuals with an average accuracy of 96.22%.

Detection of subtle motor symptoms unnoticeable to the naked eye is critical for early intervention in Parkinson’s disease. Our diagnostic pen presents an affordable, reliable and accessible tool that is sensitive enough to pick up subtle movements and can be used across large populations and in resource-limited areas.”

Jun Chen, study’s corresponding author

The researchers anticipate that this pen could transform early detection of Parkinson’s and other neurodegenerative conditions. Rather than waiting for symptoms to become disruptive, primary care physicians or geriatric specialists could administer a quick handwriting test during routine visits and use the data to inform earlier referrals or treatment.

Wei Wang, a professor who holds the Leonard Kleinrock Term Chair in Computer Science, and Song Li, a chancellor’s professor in bioengineering, are also authors on the paper. Other authors include graduate students Guorui Chen, Zhaoqi Duan, Kamryn Scott and Xun Zhao; research scientists Zeyang Liu; and postdoctoral scholars Trinny Tat and Yihao Zhou – all members of Chen’s Bioelectronics Research Group. They were joined by graduate student Junkai Zhang, who is advised by Wang. Chen is also a member of the California NanoSystems Institute at UCLA.

The study was funded by the U.S. Office of Naval Research, the National Institutes of Health, the National Science Foundation, the American Heart Association, the Science Hub for Humanity and Artificial Intelligence at UCLA, UCLA Samueli and a Caltech/UCLA joint NIH grant.