Implementing a Smartphone and Wearable-Based Stress Management Intervention in Women With Coronary Artery Spasms to Reduce Cardiac Symptoms: Multicenter, Single-Arm, 1-Way Crossover Study

Background: Mental stress is a well-known trigger of cardiac symptoms in patients with coronary artery spasms. Hence, stress management is recommended along with medical therapy. However, specific programs for patients with coronary spasms are lacking. We collaborated with patients to develop a smartphone-based app as a tailored solution. The app provides biofeedback based on heart rate variability–driven stress level estimations. Objective: This study aimed to evaluate the effect of a biofeedback-driven smartphone stress management app on cardiac symptoms in women with coronary vasospasms. Methods: We enrolled 117 women aged 18 to 70 years diagnosed with coronary vasospasms, as confirmed by a gold standard coronary function test. A multicenter, single-sequence, 2-period crossover study was conducted, comprising a 4-week control period followed by a 4-week period using the Wavy intervention app. The intervention comprised breathing-based exercises that were prompted when measured stress levels were too high. The primary outcome was the Seattle Angina Questionnaire Summary Score, and the secondary outcomes included the 36-Item Short Form Health Survey and the Perceived Stress Scale-10 items. Additionally, the user experience and the impact of the breathing exercise on heart rate variability were evaluated. Results: A total of 102 patients completed the study, yet no significant improvements were observed in the Seattle Angina Questionnaire following the intervention period, with the control group scores at 50.4 (SD 15.4) and the intervention group scores at 50.9 (SD 15.0; <i>P</i>=.92). Similarly, no differences were found in the 36-Item Short Form Health Survey and the Perceived Stress Score. However, the 1236 breathing relaxation exercises performed during the study led to a significant improvement in heart rate variability, as indicated by a median root mean square of successive differences increase from 18.59 (IQR 8.38-36.58) milliseconds before the exercises to 34.93 (IQR 24.19-50.64) milliseconds after the exercises (<i>z</i>=−13.72; <i>P</i><.001). Furthermore, two-thirds of participants (68/102, 66.7%) indicated that they would use a more refined version of the app in the future. Conclusions: A 4-week intervention using the Wavy app did not significantly alleviate anginal symptoms in female patients with coronary vasospasms. However, the breathing exercises demonstrated a notable improvement in heart rate variability, suggesting a reduction in stress levels. Patient feedback indicated broad support for the app and its wearable-based functionality, emphasizing the need for substantial refinements. Future development should incorporate patient perspectives to optimize the app as a comprehensive lifestyle management tool. Clinical Trial: ClinicalTrials.gov NCT06171893; https://classic.clinicaltrials.gov/ct2/show/NCT06171893

Governing AI for Mental Health: Fragmented State Approaches and the Case for a Federal Framework

State-level regulation of AI used for mental health is emerging in the absence of a federal framework. States are taking different approaches to regulation, resulting in a fragmented regulatory landscape. This Viewpoint aims to identify the governance approaches that US states are using to regulate the use of AI in mental health and analyze the limitations of each. A 4-state case analysis was conducted using the statutory text of bills and laws in Illinois, Utah, New York, and Nevada. Two governance approaches were identified. The first regulates the use of AI in clinical contexts, and the second regulates the technology itself. Some states have combined elements of both approaches to address AI use more comprehensively. While these approaches aim to mitigate harm, they differ in where they believe risk lies in the use of AI for mental health support. The limitations of these divergent approaches include uneven protections for consumers and regulatory uncertainty for developers, vendors, deployers, and clinicians. Because AI in mental health operates across both clinical and consumer domains, neither approach alone can address the risks associated with its use for mental health support. A coordinated, risk-based federal regulatory floor is needed to ensure consistent protections across states.
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STAT+: Preliminary trial results suggest a path to a safer Alzheimer’s treatment

An interim look at an Alzheimer’s disease clinical trial evaluating an amyloid-targeting treatment from ProMIS Neurosciences showed low rates of brain bleeding and no incidences of brain swelling — results reported Tuesday that suggest the drug could be safer than approved treatments. 

In a blinded analysis that pooled safety data from patients receiving the ProMIS drug and a placebo, the total rate of ARIA was 4.4%, with all cases mild and asymptomatic, the company said. 

None of the patients experienced ARIA-E, which is the more severe side effect that causes brain swelling. All the cases were characterized as ARIA-H, which involves tiny bleeds in the brain. 

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Samsung’s chip workers are jumping ship to rival SK Hynix 

Lee, an engineer at Samsung’s semiconductor division, clocks out when his shift ends. He used to work longer hours, going the extra mile to excel at his projects. But lately, he’s been coming straight home to work on his job application for the chipmaker’s South Korean rival SK Hynix, sharing tips with his coworkers on how to draft a stellar personal statement. Even his boss encourages him to make the move.

“My team lead tells us all to jump ship to SK Hynix,” says Lee. He and his coworkers are feeling demoralized by the $476,000 bonus that SK Hynix is set to pay its employees, flush with record profits from making the high-bandwidth memory (HBM) chips that power Nvidia’s AI accelerators. The figure dwarfs what chip workers at Samsung are set to receive and is sparking an exodus.

As the AI boom heats up, the semiconductor titans are waging a fierce talent war with flashy bonuses, aggressive recruiting, and even a courtroom injunction. Who wins could tilt the race to dominate the next generation of the HBM chips at the heart of the AI boom.

“Except for our two team leads, my entire team [of 30 people] just applied to SK Hynix,” Lee says, referring to a job posting the company published in July. Lee, who has worked at Samsung for three years, even applied for an entry-level position at its rival. A coworker, who has worked at Samsung for eight years, applied for the same one. They both got rejected. But they’re hopeful that they’ll get a callback for a posting seeking a more experienced engineer.

All employees at Samsung and SK Hynix that MIT Technology Review spoke with asked to be identified by just their last name or a pseudonym because they feared retaliation from their employer. Samsung declined to comment, and SK Hynix did not respond to requests for comment.

After prolonged negotiations with its labor union, Samsung struck a deal in May to pay out 10.5% of the semiconductor division’s operating profits to employees as bonuses annually for 10 years, mostly in company stock that vests over three years. The move came after SK Hynix agreed last year to pay out 10% of operating profits to employees, which translates to $476,000 per employee this year—mostly in cash.  

But at Samsung, each division’s bonus is tied to its own bottom line. Chip workers in its memory division, which is also reaping a windfall from making HBM chips, are getting paid a bonus of roughly $400,000 per employee this year. But those who, like Lee, work in Samsung’s foundry division, which manufactures logic chips that companies like Tesla and Google design and has been operating at a loss, are getting a bonus of roughly $135,000. 

Employees told MIT Technology Review that Samsung said it can’t give as many bonuses to divisions that aren’t performing well. Lee, after watching the labor union wrestle with the company for months, says he has felt disappointed by what he ended up with: “Even if Samsung does well in the future, I don’t think any of it will trickle down to me.” 

The workers’ lagging bonuses are making SK Hynix suddenly look appealing. According to a survey by the Samsung labor union in June, 81.5% of employees in the company’s foundry division, and nearly half of employees in the semiconductor division as a whole, said they wanted to go to another company in the next two years. In April, Samsung labor union chief Choi Seung-ho said more than 200 members of the union had left for SK Hynix over the past four months. On Blind, an anonymous workplace forum, a chorus of disgruntled engineers at Samsung confess that they want to defect to SK Hynix for the bigger bonuses. 

For decades, SK Hynix lived in Samsung’s shadow. It was the smaller, scrappier memory maker that elite engineering students at universities looked past when applying for jobs. But in 2019, Samsung downsized its HBM team, betting the market would stay niche, while SK Hynix doubled down on the technology. Then the AI boom supercharged the demand for HBMs, which feed AI chips the enormous amounts of data they need at ultra-high speed, driving prices to unprecedented levels. SK Hynix now leads the global market for HBMs, while Samsung is playing catch-up. Both companies topped $1 trillion in market value in May, and SK Hynix briefly dethroned Samsung as South Korea’s most valuable company in June.

Predicting that demand for memory chips will continue to surge, the semiconductor titans are making aggressive investments to expand their business. Last month, the companies unveiled plans to invest more than $2 trillion by 2040, including a semiconductor “mega-cluster” in Yongin, a city south of Seoul. To staff the expansion, SK Hynix added 2,152 employees in the first half of 2026 alone and aims to double its manufacturing capacity in five years. Samsung plans to hire 60,000 employees over the next five years, especially for its semiconductor division. Even so, the pipeline will fall short: South Korea’s semiconductor industry will need about 304,000 workers by 2031 and faces a shortage of roughly 54,000, according to the Korea Semiconductor Industry Association.

Now the longtime rivals are showering workers with big bonuses to keep—and poach—talent. “[SK Hynix] seems to target Samsung engineers when hiring because it’s a rival,” says Baek, a manager at SK Hynix. “From what I heard internally, the big performance bonuses we got were aimed at luring away talent from our competitor.”

Courts are starting to weigh in. In July, Samsung won an injunction barring two former chip workers from working at SK Hynix for 18 months, on the grounds that chips are a national core technology deserving protection. “With competition in the semiconductor industry fierce, it’s necessary to establish a fair market order,” the court ruled.

The talent exodus threatens a crucial advantage that Samsung still holds in the HBM race. “Samsung is the only memory maker in the world that owns a foundry business,” says Park Jun-young, a semiconductor expert at the Industrial Anthropology Laboratory, a research institute, who worked at Samsung for a decade. 

With the latest generation of the technology, known as HBM4, the logic chip at the base of each memory stack must be manufactured with the kind of advanced process that only foundries run. Samsung can do this in-house, while SK Hynix outsources it to the Taiwanese foundry giant TSMC. “If Samsung keeps losing engineers in the foundry … the collaboration between memory division and foundry division could become difficult,” says Park. “SK Hynix, which used to have only a memory team and is now hiring foundry engineers, could do better research on HBMs.”

Choi, an engineer who has worked at Samsung for seven years, says he was once a star on his team, getting glowing performance reviews from his managers. But lately, he and his coworkers have been busy applying for every SK Hynix job posting they see. “We tell each other when the next SK Hynix job posting is up,” he says. “There’s always more work to do beyond our basic duties. But there’s no point in doing it.”

Opinion: STAT+: Dementia finally has a business model

In the nine years since my last visit to the Docklands’ Excel conference center for the 2017 annual Alzheimer Association International Conference, or AAIC, little of London’s infrastructure has changed. I traveled via the same low-ceilinged, clattering trains with signs advising riders to “mind the gap” and “mind the step.” The center has the same weird jack-o’-lantern-esque façade and forgettable restaurants and hotels. I was even here for the same conference.

Same meeting, in the same place, but what transpired was quite different. In just nine years, how we think about the aging brain has transformed.

One moment captured this. It was a speaker’s remark at a breakfast meeting convened by the Davos Alzheimer’s Collaborative. The 5-year-old organization describes itself as “uniting leading organizations worldwide to build an innovation ecosystem that will accelerate breakthroughs, develop and scale promising solutions and equip every healthcare system to end Alzheimer’s disease everywhere.”

Continue to STAT+ to read the full story…

STAT+: From ‘lost cause’ to gold rush: Biotechs swarm to cure AATD 

Biotechs are spending billions to cure a rare liver disorder most Americans have never heard of. The contentious race features dueling technologies, patent wars, a broken alliance, and a boiling competition between the U.S. and Chinese drug industries.

The disease, known as alpha-1 antitrypsin deficiency (AATD), is a slow-moving disaster for patients. Thanks to a single misspelled letter of DNA, their livers produce a mutant version of a protein that normally travels through the bloodstream and protects the lung from damage. 

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STAT+: CMS evaluates one year of health tech progress, announces eight new pledge categories

It was a skit worthy of an Agatha Christie whodunit reveal: Against the perhaps-too-joyous strains of a jazzy “When The Saints Go Marching In,” a gaggle of health IT professionals and Medicare staffers accompanied a Spirit Halloween-style coffin prop onstage at Health and Human Services headquarters on Monday. Some wore black veils, some held white roses. 

The coffin read, “RIP CLIPBOARD,” referring to the decades-old information-gathering staple of health care provider waiting rooms.

“So who killed the clipboard?” asked Zac Jiwa, a federal Medicare official. Health IT officials and experts, reading from cue cards, denied that it was standards implementation, health information exchange networks, electronic health records, or apps — all parts of the various health data initiatives that private industry promised Medicare a year ago that it would improve.

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Parkinson’s Disease Medication Monitored with Fingertip Sweat Patch

Engineers and neuroscientists at the University of California (UC) San Diego have developed a soft, wearable fingertip patch that continuously tracks a Parkinson’s disease (PD) patient’s levodopa medication levels by measuring chemicals in their sweat, with no batteries required. Tests in healthy volunteers and in Parkinson’s disease patients showed that measurements generated using the device were comparable to those obtained by standard laboratory blood tests.

The wearable device offers a way to continuously track real-time concentrations of levodopa in the body and could enable doctors to precisely customize daily medication schedules for patients at home.

The research was led by Tamoghna Saha, PhD, a postdoctoral researcher in the lab of Joseph Wang, DSc, professor in the Aiiso Yufeng Li Family Department of Chemical and Nano Engineering at the UC San Diego Jacobs School of Engineering. Saha is co-first author of the team’s published paper in PNAS titled “A wearable patch for continuous levodopa monitoring in sweat: Towards exertion and power-free pharmacodynamic assessment in Parkinson’s disease.” In their paper the authors wrote in summary, “Overall, our easy-to-use, energy-efficient wearable supports real-time, stimulation-free monitoring, potentially enabling at-home dosage adjustments and paving the way for future autonomous closed-loop L-dopa therapeutic system development.”

Parkinson’s disease is the second most common and fastest-growing neurodegener­ative disorder worldwide, the author wrote. “While no cure for PD exists, levodopa (L-dopa) is the most effective symptomatic treatment, which is typically administered via oral tablets or capsules, and in advanced cases, through inhaled powder or continuous intrajejunal or subcutaneous infusions.” Prescribing the right dose is challenging: reducing levodopa leaves patients unable to move, while too much triggers severe, uncontrollable jerking movements. Initially, the drug’s effects can last several hours.

But as the disease progresses, the therapeutic window narrows down to two hours. Currently, clinicians must rely on subjective patient diaries to adjust treatment. Unfortunately, these methods fail to catch dangerous dosing gaps. “Precision management of Parkinson’s disease (PD) requires frequent levodopa (L-dopa) dose adjustments, yet current monitoring relies on subjective symptom reporting and infrequent blood testing,” the team continued.

Levodopa monitoring patch showing the assembly of the hydrogel and levodopa sensor with the paper fluidic channel on the fingertip. [Tamoghna Saha.]
Levodopa monitoring patch showing the assembly of the hydrogel and levodopa sensor with the paper fluidic channel on the fingertip. [Tamoghna Saha.]

Saha and the engineering team developed the new finger patch technology in joint collaboration with the lab of Irene Litvan, MD, MPhil, professor in the department of neurosciences at UC San Diego School of Medicine. The project is part of a longstanding collaboration between the Wang and Litvan teams to develop wearable levodopa monitors that can improve personalized care for people living with PD.

 

Worn on the fingertip, which is packed with a high density of sweat glands, the patch is equipped with a specially engineered absorbent gel that acts like a sweat sponge. The gel contains a highly-concentrated mixture of salts and benign solvents—and that draws sweat out of the pores, since water naturally flows toward areas with higher salt concentrations. Collected sweat is drawn into a serpentine fluidic channel with a self-powered levodopa biosensor connected to a wireless transmitter.

When levodopa in the patient’s sweat comes into contact with enzymes embedded in the patch it triggers a chemical reaction, which in turn generates a small, measurable voltage. This chemical reaction is what powers the patch. The amount of voltage generated also serves as an indicator of the patient’s levodopa level, such that lower voltage signals low levels, while higher voltage signals high levels.

Unassembled integrated levodopa monitoring patch. [David Baillot (University of California, San Diego, San Diego, CA).]
Unassembled integrated levodopa monitoring patch. [David Baillot (University of California, San Diego, San Diego, CA).]

Experimental results from three to five healthy participants and four individuals with PD indicated that levodopa concentrations in sweat measured by the patch are strongly correlated with blood concentrations measured by high-performance liquid chromatography. The patches captured pharmacodynamic responses and patient-specific levodopa clearance trends that could be used to calibrate dosage estimates for individuals.

The data revealed that individuals with Parkinson’s clear levodopa from their systems significantly faster than healthy individuals. This result explains why a patient’s Parkinson’s symptoms can deteriorate so suddenly, the researchers noted.

This technology could lay the groundwork for a closed-loop system, where a levodopa monitoring patch could communicate with a pump to automatically deliver the precise doses of the drug right when the body needs it, the authors suggested. “This approach establishes a foundation for real-time, at-home therapeutic optimization and advances the development of future closed-loop treatment systems for PD.”

The post Parkinson’s Disease Medication Monitored with Fingertip Sweat Patch appeared first on GEN – Genetic Engineering and Biotechnology News.

Lessons From Building a Large, Public HIV-Related Database in Support of the Ending the HIV Epidemic in the US Initiative

The HIV epidemic remains a national priority in the United States, and the Ending the HIV Epidemic initiative has renewed the call for expanded prevention and treatment strategies capable of reducing new HIV infections by 90% by 2030. Achieving this goal requires robust, integrated data for understanding HIV-related needs, barriers to care, and the effectiveness of interventions. However, despite the existence of numerous publicly available datasets, few integrate multiple domains such as HIV outcomes, social determinants of health, and community-level factors. The lack of unified data and difficulty linking datasets hampers efforts for meaningful cross-domain analyses to tailor HIV management and treatment strategies. The resulting fragmentation constitutes a methodological gap: implementation teams lack replicable guidance for constructing unified HIV and contextual databases from public sources. In this viewpoint, we describe our experience building a unified compilation of publicly available HIV and community data to identify factors influencing HIV outcomes and interventions. The completed database comprises 242 variables drawn from 8 public sources mapped across clinic, zip code, county, and state levels of geography. Rather than simply reporting what we built, we position four core decisions as transferable methodological advances: (1) treating source identification as a bounded phase before construction begins, (2) adopting automated data engineering tools from the outset rather than manual entry, (3) establishing a shared data dictionary before the first variable is entered, and (4) integrating quality control throughout the workflow rather than as a final phase. The build required approximately 350 total project hours and revealed an initial spot-check error rate of approximately 33%, which we attribute primarily to manual data entry. By sharing the approach used to develop this database and making the final resource publicly accessible through the Yale Center for Methods in Implementation and Prevention Science, we aim to reduce barriers to data access and encourage similar data integration efforts. The methodological framework described in this paper is intentionally designed to be replicable with modest resources, and we present it as a practical model for research teams operating without specialized infrastructure. Consolidating HIV, social determinants of health, and contextual variables into a unified data source is a critical step toward enabling deeper, more comprehensive analysis and supporting ongoing efforts to end the HIV epidemic in the US.
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