Macrophage Membrane-Derived Nanoparticles Shows Potential Against Candida Infections

By using tiny particles made from the membranes of human immune cells, scientists from the University of California, San Diego and the University of Missouri have created antifungal nanoparticles that target Candida albicans, a fungus responsible for oral and vaginal yeast infections as well as bloodstream infections. Tests in mice with severe Candida infections show that the macrophage-derived nanoparticles reduced the amount of fungus in major organs, including heart, kidneys, lungs, and spleen. The mice also had improved survival rates. 

Full details are published in Cell Biomaterials in a paper titled “Cell membrane-derived nanotherapeutic for combating Candida albicans infections.” In it, the scientists write that “this bioinspired nanodisc not only disrupts fungal membranes directly but also enhances host immune clearance, achieving potent antifungal activity.” 

Current treatment options for fungal infections are limited and there are growing concerns about drug resistance. Existing medications typically target specific parts of a fungal cell and can lose effectiveness as fungi evolve resistance. The nanoparticles described in the current paper have a more potent strategy. Besides damaging fungal membranes, they also boost the body’s natural immune defenses to better fight infections. 

According to the scientists, each nanodisc measures about 10-20 nanometers, about 1,000 times smaller than a normal macrophage. Their tiny size is an advantage as it allows them to fuse directly with fungal cell membranes and destabilize them, which is harder for full-sized macrophages.

To create the nanodiscs, the scientists isolated the outer membranes of the macrophages and broke up them up into tiny pieces. They then fused them onto disc-shaped nanoparticles made from a biodegradable polymer. Since the nanodiscs are built from macrophage cell membranes, they retain the same receptor proteins that the immune cells use to recognize and attack Candida. This means that the nanodiscs can identify and attach to fungal cells more effectively than those made from other cell types such as red blood cells. 

Once attached, the nanodiscs weaken the fungal cell’s protective outer membrane until tiny openings form. As the membrane breaks down, the cell’s contents leak out while external substances seep in ultimately killing the fungus. Because this treatment strategy physically damages the fungal cell rather than targeting a specific molecule, the developers believe that it may be harder for the fungus to evolve resistance. 

The nanodiscs also provide other countermeasures. They reverse the suppression of antifungal chemicals produced by macrophages during infection, and prevent Candida from forming biofilms that help to shield fungal cells from drugs and the immune system. Testing also revealed that the treatment was effective when administered both before and after infection suggesting that it could also be used as a preventative. 

For their next steps, the scientists will further evaluate the antifungal potency of the nanodiscs against a broader range of pathogenic fungal species.

The post Macrophage Membrane-Derived Nanoparticles Shows Potential Against <i>Candida</i> Infections appeared first on GEN – Genetic Engineering and Biotechnology News.

STAT+: Pharmalittle: We’re reading about bigger drug discounts in Germany, drugmakers embracing secrecy, and more

Good morning, everyone. Damian Garde here, filling in for Ed Silverman at Pharmalot’s satellite campus along the East River, where today’s cup of stimulation is filled not with coffee but rather a smoothie of curious color and questionable contents (what exactly is an “adaptogen”?). Anyway it’s Friday, as you’re almost certainly aware, and here are some tidbits to help you through the waning hours of another working week. …

German lawmakers passed a bill that would more than double the discount on branded medicines drugmakers must provide to the government, Reuters reports. The policy, part of an effort to plug a sizable budget gap in the country’s health insurance system, would increase the mandatory rebate from 7% to 15.5%. Industry groups have said the bill, if it clears Germany’s upper chamber, would deter investment and imperil the country’s access to new medicines.

The rapid rise of China’s biotech industry has led some American drug developers to do their work in near total secrecy, the Wall Street Journal observes. U.S. startups are increasingly loath to publish early data, disclose their scientific ambitions, or even publicize which diseases they hope to treat, all in fear that nimble Chinese firms will use that information to whip up competing drugs and beat them to the punch of starting clinical trials.

Continue to STAT+ to read the full story…

The Download: Claude’s inner workings and OpenAI’s “super app”

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

Anthropic found a hidden space where Claude puzzles over concepts

The AI firm Anthropic has got the clearest glimpse yet at what’s really going on inside large language models as they answer questions or carry out tasks. What they found ranges from the mundane to the unnerving. 

Researchers at the company built a tool called the Jacobian lens (or J-lens) and used it to uncover a hidden area, which they named the J-space, inside its flagship LLM, Claude.

The J-space contains words related to the response a model is working on but may not ultimately produce. If Claude were a person (which it is not), you might say these hidden words reveal what’s on its mind before it actually speaks. 

Read the full story on what they found.

—Will Douglas Heaven

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 OpenAI has unveiled its long-awaited “super app” 
ChatGPT Work blends its chatbot, coding tool, and new models. (Reuters $)
+ It’s designed to do your work for you and with you. (Ars Technica)
+ And arrived the same day as OpenAI’s GPT 5.6 models. (NYT $)
+ It’s also developing a fully automated researcher. (MIT Technology Review)

2  Humanoids have performed teleoperated surgery on living animals
In the world-first, they removed gallbladders from pigs. (Ars Technica)
+ The human work behind humanoids is hidden. (MIT Technology Review)
 
3 SK Hynix has landed the largest US listing by a foreign company
The South Korean chip giant raised $26.5 billion. (CNN)
+ Demand for AI data centres has led its profits to skyrocket. (Guardian)
+ But its jumbo share sale may be a sign of overheated times. (FT $)
+ South Korea’s hottest bachelors are chip workers. (MIT Technology Review)
 
4 Tencent is leading a deal to unwind Meta’s $2 billion Manus acquisition
It’s in talks to become the Chinese AI startup’s largest shareholder. (FT $)
+ Tencent will reportedly buy Manus for no less ​than $2 billion. (Reuters $)
+ Beijing had ordered Meta to unwind the acquisition. (Bloomberg $)
 
5 Resuscitated human retinas responded to light 10 hours after death
It’s a big step towards eye transplants that restore vision. (New Scientist $)
+ As is a new device that revives dead eyeballs. (MIT Technology Review)
 
6 Meta has started charging for AI access
A new version of Muse Spark has a paid tier for developers. (Quartz
+ Meta also plans to start producing an AI chip in September. (Reuters $)
 
7 OpenAI and Google have sold AI models to blacklisted China groups
Via Singapore-based subsidiaries of Alibaba, Baidu and Tencent. (FT $)

8 A daughter tested an AI “death bot” of her father
The technology provided both comfort and unease. (New Yorker $)

9 An astronomer says the hunt for alien life needs more statistics
He wants to replace speculation with mathematical frameworks. (Quanta)

10 Pokémon Go players turned Times Square into a giant battlefield
More than 1,500 fans finally fulfilled the game’s 2016 launch promise. (Wired $)
+ Pokémon Go is also training world models. (MIT Technology Review)

Quote of the day

“When we’re talking about AI, we love the hype, we get excited about it. The damn thing never actually lands in practice.”

—Vijay Janapa Reddi, an engineering professor at Harvard University, tells Wired why he’s skeptical about grand plans for AI.

One More Thing

a hand putting a pigeon into hatch in a missile

B.F. SKINNER FOUNDATION


Why we should thank pigeons for our AI breakthroughs

In 1943, psychologist B.F. Skinner led a secret government project to make bombs more precise. His idea: teach pigeons to guide missiles by pecking at targets on a screen inside a warhead. To train them, Skinner rewarded the birds with food when they made the right decisions, using trial and error to shape their behavior.

Unsurprisingly, the military never deployed Skinner’s kamikaze pigeons. Yet his experiments convinced him that pigeons were “an extremely reliable instrument” for studying learning.  

Decades later, those same principles would help power reinforcement learning, the technology behind some of today’s most advanced AI systems.

Discover how pigeons inspired one of AI’s most powerful techniques.

—Ben Crair

We can still have nice things

A place for comfort, fun, and distraction to brighten up your day. (Got any ideas? Drop me a line.)

+ Here’s a splendid selection of this year’s NSW architecture award winners.
+ Photographers have captured the Strawberry Moon’s golden glow in stunning detail.
+ Idiocracy is the film that best exemplifies the “American experience,” according to a new poll. Look back at the prescient comedy with this Screen Junkies trailer.
+ Get ready for the weekend with this psychedelic house journey from Jamie xx b2b Caribou.

Evolution of brain-computer interface technologies for stroke rehabilitation: a bibliometric integration of neural decoding and functional recovery (2016–2025)

IntroductionBrain-computer interface (BCI) technology represents a critical frontier in neurorehabilitation. This study aims to systematically analyze the global research landscape, hotspot distribution, and evolving trends of BCI interventions for upper limb rehabilitation in stroke survivors between 2016 and 2025.MethodsBibliometric analysis and systematic mapping were conducted using data from the Web of Science Core Collection and PubMed. Literature was retrieved using terms related to “stroke,” “brain-computer interface,” and “upper limb rehabilitation.” Screening followed the PRISMA guidelines. Visualization and quantitative mapping were performed using CiteSpace (v.6.4.R2) and VOSviewer (v.1.6.20) to evaluate publication volume, international collaboration, and keyword co-occurrence clusters.ResultsAnnual publications increased steadily from 37 in 2016 to 104 in 2025, with 65.6% published since 2020. The United States (n = 144), China (n = 83), and Italy were the most productive countries. Keyword analysis revealed a paradigm shift from functional electrical stimulation toward robotics-assisted therapy, motor imagery, and AI-driven decoding. Significant burst strengths were observed for “closed-loop systems,” “generative AI,” and “multi-modal feedback,” indicating these as the current primary frontiers.DiscussionBCI research for post-stroke recovery is transitioning from experimental signal processing to intelligent, multi-modal, and personalized clinical systems. Bibliometric evidence confirms that integrating BCI with robotic-assisted rehabilitation or functional electrical stimulation (FES) has become the mainstream clinical trend. Future efforts must focus on improving EEG signal stability and developing user-friendly hardware to facilitate the transition of BCI from research settings to daily clinical practice. China has emerged as the second most productive country, though international cooperation with European institutions remains an area for further growth.

Opinion: The primary care crisis paradox

In March, the Medicare Payment Advisory Commission (MedPAC) released its annual report to Congress on Medicare payment policy. The data related to physician payment are clear: By every metric we track, primary care in America is succeeding, and it has been for years. Nearly all Medicare beneficiaries have a primary care provider (PCP). Over three-quarters can see their PCP within two weeks. Patients in rural environments have less trouble finding a PCP and even shorter wait times. Services and spending on evaluation and management codes are increasing, and compensation among PCPs is rising faster than the rest of the field.

Yet this runs counter to the pervasive narrative that investing more in primary care is the key to solving the American health care crisis.

Read the rest…

New York boys club has a time-tested recipe to protect members’ mental health

NEW YORK — A couple of years ago, a reporter approached the Boys’ Club of New York looking to interview some of its middle-schoolers for a story about the mental health crisis in boys. 

It’s easy to see why. Many of the about 2,500 boys who participate in the 150-year-old organization’s after-school and weekend activities come from disadvantaged socioeconomic backgrounds, often living in single-parent households or facing the threat of immigration enforcement. With limited access to academic and developmental support, the risk factors are plentiful. 

Read the rest…

STAT+: How a Boston doctor built a following as a ‘loud and unafraid’ voice in the Trump era

Jeremy Faust cuts through a hallway of Boston’s Brigham and Women’s Hospital on his way to see a patient who is struggling to breathe. It’s the start of his evening shift, and the emergency department hums with ambient sound: bleeping monitors, the rumbling wheels of medical carts, the squeaky soles of hustling staff. People on gurneys line the corridor, some wincing in pain, others chatting with relatives.

On this Wednesday evening in May, Faust is working what is typically a quieter shift, as far as emergency departments go. Still, he is overseeing a team of doctors, students, and physician assistants, and will tend to more than two dozen patients before signing off for the night.

It’s an understatement to say Faust likes to keep busy. Minutes earlier, he’d posted an article on his influential Substack newsletter, Inside Medicine, providing an update on a major international news story. An alert sent to the newsletter’s nearly 85,000 subscribers announced his “scoop”: Twenty-six passengers aboard the MV Hondius, the hantavirus-hit cruise ship docked at the time off Cape Verde, had disembarked much earlier than previously known — raising the possibility they could spread the rare virus in the United States.

Continue to STAT+ to read the full story…

Blended Genome–Exome Sequencing Slashes Costs Without Quality Loss

A novel sequencing strategy that combines low-pass whole-genome sequencing with deep whole-exome sequencing in a single assay could significantly lower the cost of large-scale genomic studies without sacrificing analytical performance, according to a study published in Nature Genetics. The approach, known as blended genome–exome (BGE) sequencing, may help accelerate precision medicine initiatives by making comprehensive genomic profiling more accessible across diverse populations.

Researchers from Massachusetts General Hospital and the Broad Institute of MIT and Harvard developed BGE to overcome a persistent tradeoff in human genomics. High-coverage whole-genome sequencing offers the most comprehensive view of genetic variation but remains prohibitively expensive for many population studies. Genotyping arrays and exome sequencing are more affordable but either miss large portions of the genome or introduce bias by relying on variants selected primarily from European ancestry populations.

The BGE workflow integrates low-pass whole-genome sequencing at 1–4x coverage with deep exome sequencing at 30–40x coverage within a single library preparation and sequencing run on Illumina’s NovaSeqS4. The result is a unified dataset capable of supporting genome-wide association studies, rare variant discovery, copy number variant (CNV) detection, and polygenic analyses at approximately 28% of the cost of conventional 30x whole-genome sequencing.

The investigators validated the approach in more than 53,000 participants enrolled in the Populations Underrepresented in Mental Illness Associations Studies (PUMAS) Project, which includes African, African American, Hispanic/Latino, and Colombian cohorts. The scale and diversity of the study allowed the researchers to assess performance in populations that have historically been underrepresented in genomic research.

Imputed genotypes generated from BGE showed excellent agreement with Illumina Global Screening Array data, achieving concordance exceeding 95% for variants with minor allele frequencies above 1%. Importantly, performance remained consistent across multiple ancestry groups and local ancestry backgrounds, addressing one of the major limitations of conventional array-based genotyping.

The platform also demonstrated strong performance for clinically relevant structural variation. Using established computational pipelines, investigators achieved approximately 90% positive predictive value for protein-coding CNVs spanning three or more exons compared with deep whole-genome sequencing. In benchmarking studies, the method successfully detected all validated de novo coding CNVs in a reference autism cohort while maintaining low false-positive rates.

Beyond analytical performance, the study highlights potential operational advantages. By combining genome and exome sequencing into a single workflow, BGE simplifies laboratory processing, reduces the need for multiple assays, and minimizes sample attrition between sequencing platforms. These efficiencies could prove valuable for national biobanks, health system sequencing programs, and pharmaceutical research efforts that increasingly require genomic datasets from hundreds of thousands of participants.

The technology may also advance equity in precision medicine. Because low-pass genome sequencing does not depend on predefined variant content, it avoids many of the ascertainment biases associated with traditional genotyping arrays. The authors found that BGE captured substantially more coding and noncoding variants than array-based approaches while maintaining high-quality rare variant detection through deep exome coverage.

The researchers acknowledge that imputation performance remains influenced by the diversity of available reference panels, particularly for Indigenous American ancestry. However, as more globally representative reference datasets become available, they expect the accuracy of low-pass genome imputation to improve further.

As precision medicine increasingly depends on large, ancestrally diverse genomic datasets, technologies that balance cost, scalability, and comprehensive variant detection will be essential. BGE sequencing offers a practical alternative to deep whole-genome sequencing, enabling broader participation in genomic discovery while preserving much of the analytical power needed to identify clinically meaningful genetic variation.

The post Blended Genome–Exome Sequencing Slashes Costs Without Quality Loss appeared first on Inside Precision Medicine.

Mobile AI Tool Expands Access to Prenatal Ultrasonography

A portable AI tool can estimate the age of an unborn baby from scans as well as trained sonographers, potentially extending access to vital prenatal ultrasonography where it might not otherwise be available.

The findings, in JAMA Network Open, reveal the potential of artificial intelligence to expand access to diagnostic tasks such as ultrasonography using novice operators in low-resource settings.

An AI model trained on blind sweep ultrasonography scans performed as well as traditional sonographers on estimating gestational age when used by novice operators across diverse geographical and infrastructural contexts, with minimal fine tuning.

“This system could mitigate disproportionate maternal or fetal comorbidity in low-resource areas by providing access to an essential clinical tool, serving as a template for automating and democratizing other ultrasonography-based diagnostics in future obstetric work,” reported Ryan Gomes, PhD, from Google in California, and co-workers.

Determining gestational age is a fundamental component of prenatal care, allowing obstetric care that can include life-saving interventions to prevent pre- and post-term births and manage high-risk conditions.

But while traditional ultrasonography is recommended by the World Health Organization, it requires skilled sonographers and expensive equipment that may not be available, particularly in low-resource settings.

AI using low-cost portable devices offer a potentially accessibly alternative, with blind sweep ultrasonography—a set of protocolized sweeps that does not rely on real-time imaging interpretation—emerging as a particularly promising approach.

However, clinical sites vary significantly in workflow, staffing, patient demographics, and equipment, which could affect the accuracy of AI-based assessment.

Gomes and team therefore examined the value of an AI tool to estimate gestational age from blind sweep ultrasonography scans across a variety of settings.

The AI-based system was originally trained on data from suburban North Carolina and urban Zambia and validated in a Chicago urban academic center and a Kenyan urban clinic using a different portable probe.

The broader cohort included 2043 participants—consisting of 1008 in Chicago and 1035 in Nairobi.

Fine-tuning using 180 examinations from 120 Chicago participants—approximately 6% of original training size, split evenly for training and validation—targeted generalization to new hardware and gestational-age distributions.

The primary evaluation set of 385 participants—192 in Chicago and 193 in Nairobi—had gestational ages from 16 to 36 weeks.

The researchers found that the AI model effectively generalized to new clinical environments and institutions, achieving a mean absolute error of 4.2 days that was noninferior to the clinical standard.

Its robust performance in Nairobi, with a mean absolute error of 4.3 days without local-tuning mirrored results in Chicago, where this mean error was 4.1 days and underscored the model’s inherent adaptability and transfer-learning efficacy.

These mean absolute errors with the adapted model were similar to the standard of care.

“The lower sweep rejection rate in the Nairobi setting (1.8% vs 7.9% in Chicago) may suggest that approximately six hours of formal, interactive, hands-on training improves acquisition quality compared with informal and written instruction,” the authors noted.

Nonetheless, they conclude overall: “This generalizable accuracy, achieved with low-cost probes, represents an important step toward World Health Organization–recommended scalable prenatal implementation.”

The post Mobile AI Tool Expands Access to Prenatal Ultrasonography appeared first on Inside Precision Medicine.