‘Self-Driving’ Microscope Predicts Neurodegenerative Disease

The accumulation of misfolded proteins in the brain is central to the progression of neurodegenerative diseases such as Huntington’s, Alzheimer’s, and Parkinson’s. But to the human eye, proteins that are destined to form harmful aggregates are indistinguishable from normal proteins. The formation of such aggregates also tends to happen randomly and relatively rapidly — on the scale of minutes. The ability to identify and characterize protein aggregates is essential for understanding and fighting neurodegenerative diseases.

Now, using deep learning, École Polytechnique Fédérale de Lausanne (EPFL) researchers have developed a “self-driving” imaging system that leverages multiple microscopy methods to track and analyze protein aggregation in real time — and even anticipate it before it begins. In addition to maximizing imaging efficiency, the approach minimizes the use of fluorescent labels, which can alter the biophysical properties of cell samples and impede accurate analysis.

“This is the first time we have been able to accurately foresee the formation of these protein aggregates,” said recent EPFL Ph.D. graduate Khalid Ibrahim. “Because their biomechanical properties are linked to diseases and the disruption of cellular function, understanding how these properties evolve throughout the aggregation process will lead to fundamental understanding essential for developing solutions.”

The project is the result of a longstanding collaboration between the labs of Aleksandra Radenovic, head of the Laboratory of Nanoscale Biology and Hilal Lashuel of the school of sciences. The work unites complementary expertise in neurodegeneration and advanced live-cell imaging technologies.

“This project was born out of a motivation to build methods that reveal new biophysical insights, and it is exciting to see how this vision has now borne fruit,” Radenovic said.

In their first collaborative effort, led by Ibrahim, the team developed a deep learning algorithm that was able to detect mature protein aggregates when presented with unlabeled images of living cells. The new study builds on that work with an image classification version of the algorithm that analyzes such images in real time: when this algorithm detects a mature protein aggregate, it triggers a Brillouin microscope, which analyzes scattered light to characterize the aggregates’ biomechanical properties like elasticity.

Normally, the slow imaging speed of a Brillouin microscope would make it a poor choice for studying rapidly evolving protein aggregates. But thanks to the EPFL team’s AI-driven approach, the Brillouin microscope is only switched on when a protein aggregate is detected, speeding up the entire process while opening new avenues in smart microscopy.

“This is the first publication that shows the impressive potential for self-driving systems to incorporate label-free microscopy methods, which should allow more biologists to adopt rapidly evolving smart microscopy techniques,” Ibrahim said.

Because the image classification algorithm only targets mature protein aggregates, the researchers still needed to go further if they wanted to catch aggregate formation in the act. For this, they developed a second deep learning algorithm and trained it on fluorescently labelled images of proteins in living cells. This “aggregation-onset” detection algorithm can differentiate between near-identical images to correctly identify when aggregation will occur with 91% accuracy. Once this onset is spotted, the self-driving system again switches on Brillouin imaging to provide a never-before-seen window into protein aggregation. For the first time, the biomechanics of this process can be captured dynamically as it occurs.

Lashuel emphasized that in addition to advancing smart microscopy, this work has important implications for drug discovery and precision medicine. “Label-free imaging approaches create entirely new ways to study and target small protein aggregates called toxic oligomers, which are thought to play central causative roles in neurodegeneration,” he said. “We are excited to build on these achievements and pave the way for drug development platforms that will accelerate more effective therapies for neurodegenerative diseases.”

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Novel 3D Laser Scanner Helps Harvest with Purpose

Due to a shortage of skilled workers, researchers around the world are working to develop harvesting robots that could provide support to agricultural businesses. Currently, however, according to Andreas Nüchter, from Julius-Maximilians-Universität (JMU) Würzburg, initial prototypes have yet to reach high levels of functionality for the necessary applications.

In response, researchers at the University of Würzburg have developed a 3D laser scanner system that aims to provide a better understanding of the condition of plants — for example, by reliably measuring the water content of fruits. This knowledge is crucial for determining the right time to harvest, according to Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB) researcher Manuela Zude-Sasse, who led the development team.

“For the production of horticultural products, knowledge of the stage of ripeness is very important in order to be able to optimally control cultivation, harvest time and storage,” Zude-Sasse said.

“Against the backdrop of increasingly variable growth factors due to global warming, precise data on fruit development is becoming increasingly important — for scientific modelling as well as for the future use of commercial harvesting robots.”

The development team installed the system on a test site in Potsdam, Germany, and initial tests have been successful, team members said. For testing, the 3D laser scanner was mounted on a sensor conveyor station that circles a plantation of 120 apple trees. Harvesting robots, or the imaging and sensing systems embedded into or onto them, must be able to ‘read’ apple trees and other plants correctly, since no two plants look exactly alike.

The plant scanner is further designed to withstand wind and weather, and to operate in temperatures between 0 °C - 40 °C. The sensor system works on the principle of structured light: It projects three wavelengths: 520 nm, 660 nm, and 830 nm onto the plants. The reflected signals provide precise spatial information about the plants. Because the signals are available separately for each wavelength, they open possibilities for recording physiological properties of the plants, such as water content.

The sensor system will be used continuously on the ATB test site until November to monitor the 120 apple trees. The researchers designed the 3D laser scanner exclusively for experimental use, they said, with the goal of improving the data basis for modelling work and the specifications for future harvesting robots.

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Spectrometer Measures from UV to NIR, Small Enough for Smartphone

Researchers at North Carolina State University (NCSU) have successfully demonstrated a spectrometer that is orders of magnitude smaller than current technologies and can accurately measure wavelengths of light from ultraviolet to the near-infrared (NIR). The technology makes it possible to create hand-held spectroscopy devices and holds promise for the development of devices that incorporate an array of the new sensors to serve as next-generation imaging spectrometers, the researchers said.

Spectrometers are used in applications ranging from manufacturing to biomedical diagnostics to discern the chemical and physical properties of various materials based on how light changes as it interacts with those materials. Despite their widespread use, even the smallest spectrometers on the market are fairly cumbersome.

“We’ve created a spectrometer that operates quickly, at low voltage, and that is sensitive to a wide spectrum of light,” said Brendan O’Connor, corresponding author of a paper on the work and a professor of mechanical and aerospace engineering at NCSU. “Our demonstration prototype is only a few square millimeters in size — it could fit on your phone. You could make it as small as a pixel, if you wanted to.”

The technology makes use of a tiny photodetector capable of sensing wavelengths of light after the light interacts with a target material. Applying different voltages to the photodetector manipulates which wavelengths of light it is most sensitive to.

“If you rapidly apply a range of voltages to the photodetector, and measure all of the wavelengths of light being captured at each voltage, you have enough data that a simple computational program can recreate an accurate signature of the light that is passing through or reflecting off of the target material,” O’Connor said. “The range of voltages is less than one volt, and the entire process can take place in less than a millisecond.”

Previous attempts to create miniaturized photodetectors have relied on complex optics, used high voltages, or have not been as sensitive to such a broad range of wavelengths.

In proof-of-concept testing, the researchers found their pixel-sized spectrometer was as accurate as a conventional spectrometer and had sensitivity comparable to commercial photodetection devices.

“In the long term, our goal is to bring spectrometers to the consumer market,” O’Connor said. “The size and energy demand of the technology make it feasible to incorporate into a smartphone, and we think this makes some exciting applications possible. From a research standpoint, this also paves the way for improved access to imaging spectroscopy, microscopic spectroscopy, and other applications that would be useful in the lab.

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Lasers Improve Phototherapy-Drug Delivery Platform

Photoimmunotherapy targets cancer cells with microscopic, nano-engineered cancer drugs that are light-activated at the lesion site. Although the technology is increasingly used to treat metastatic cancer, tools to improve the effectiveness of photoimmunotherapy in gynecologic oncology have been lacking. Responses to treatment vary from person to person, and no method has existed to readily monitor whether the drugs are delivered effectively or have the desired therapeutic effect.

Researchers from the University of Maryland (UMD), in collaboration with medical laser manufacturer Modulight, demonstrated that the efficacy, safety, and consistency of photoimmunotherapy can be improved by integrating targeted, light-based techniques for drug delivery with laser-assisted endoscopy and fluorescence-guided treatment planning.

The researchers designed a drug delivery system using targeted, photo-activable, multi-agent liposomes (TPMAL). TPMAL consists of chemotherapy drugs that are labeled with fluorescent markers. It improves therapeutic delivery and monitors the growth of metastases in difficult-to-treat locations within the body.

A laser-assisted endoscopic camera created by Modulight captures and uploads information from TPMAL to Modulight Cloud, a cloud services platform. Modulight Cloud analyzes the multispectral fluorescence emission from TPMAL in real time to enable fluorescence-guided drug delivery and fluorescence-guided light dosimetry. The real-time connectivity enables simultaneous treatment monitoring, remote protocol development, and rapid transfer and viewing of data.

The data acquired by the camera can be used to customize fluorescence-guided therapy. Doctors can use the data to determine, in real time, how well the drug-carrying liposomes are reaching and delivering treatment to metastatic cancer sites. They can also use the data to calculate the precise amount of laser light needed during photoimmunotherapy to minimize tissue damage.

The optimal accumulation of TPMAL in tumors can occur at different times for different patients. Fluorescence-guided drug delivery identifies the time when the TPMAL fluorescence signal is near peak levels in tumors, thereby informing the initiation of photoimmunotherapy for the best outcome.

The TPMAL levels in tumors can vary among patients. Fluorescence-guided light dosimetry monitors the photobleaching of photosensitizers during photoimmunotherapy, so that the light dose can be adjusted accordingly, in real time, to improve the consistency of treatment effects.

“Patients undergoing cancer treatment exhibit varying tolerances and individualized responses,” said UMD professor Huang Chiao Huang. “Through continuous monitoring of their progress, we can promptly determine if treatment adjustments are needed while they are actively receiving care. There is no need to postpone decisions until the next scheduled session.”

The researchers demonstrated their approach in mouse models with peritoneal carcinomatosis, a type of cancer that can be caused by metastatic ovarian cancer. They observed a fourteenfold improvement in drug delivery to metastatic tumors. The information captured by the endoscopic camera prompted fluorescence-guided light dosimetry in over 50% of the mice. By combining TPMAL, laser-assisted imaging, and fluorescence-guided intervention, the researchers achieved a more homogeneous response to treatment in the mice and improved tumor control without causing side effects.

Although nearly half of the women with advanced ovarian cancer achieve complete remission after surgery and chemotherapy, many patients will relapse due largely to residual submillimeter lesions. These residual micro-metastases are difficult to detect and often develop resistance to standard treatments. New approaches are needed to address these drug-resistant micro-metastases.

The UMD-Modulight study shows that a combination of targeted photomedicine drug delivery, imaging, and monitoring of treatment responses can help prevent the return and spread of cancer while minimizing the side effects of treatment. Together, the three techniques can give doctors the ability to make immediate adjustments in treatment to achieve better outcomes.

“This approach ensures that the treatment remains both effective and uniform,” Huang said. “This process is repeated as necessary for each patient, resulting in a personalized dosage tailored to maximize treatment effectiveness within a single session.”

The team is now working to establish a comprehensive panel of biomarkers that would allow doctors to promptly determine the optimal dosage for each patient during a treatment session.

“The goal is to minimize the number of treatment cycles required while minimizing burden on the patient’s body, in contrast to conventional treatment approaches,” Huang said.

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Holographic Imaging Measures Cellular Structures without Distorting Them

Biomolecular condensates — membraneless, microscopic structures that concentrate proteins and other molecules in cells — are crucial to the organization of cellular biochemistry. Insight into the development and behavior of condensates could lead to better treatments for infectious diseases, cancer, and neurological disorders.

Researchers at New York University (NYU) aimed to measure condensate composition and dynamics without relying on conventional techniques, like fluorescence labeling or surface attachment, which can damage fragile condensate samples. Until now, scientists have needed to distort condensate samples to study them.

“It’s been the elephant in the room for scientists,” professor Saumya Saurabh said. “Our research provides a precise and noninvasive way to study biomolecular condensates.”

To overcome the limitations of conventional techniques, the team used label-free holographic microscopy to investigate the behavior of a condensate-forming protein in vitro. The researchers flowed thousands of droplets through a holographic microscope in a microfluidic channel to visualize and characterize each particle individually. The holographic characterization was free from perturbations and was able to gather data on thousands of particles in minutes. Precise information about the droplet’s size, shape, and refractive index was encoded in the hologram of each μm-scale droplet.

The researchers used this technique to examine PopZ, a condensate-forming protein that influences cell growth. The precision and speed provided by the digital holography technique enabled the team to monitor the kinetics of the condensate’s formation, growth, and aging over time.

By systematically varying the concentration and valence of cations, the researchers found that multivalent ions influence condensate organization and dynamics. “I was surprised by their complex and incredibly sensitive response to different ionic species,” researcher Julian von Hofe said. “Even a small change in ionic valency drastically altered both condensate concentration and dynamics.”

The researchers used superresolution microscopy to explore the architecture of PopZ at the nanoscale. Data acquired through superresolution imaging revealed that the condensates were not uniform droplets, but exhibited intricate nanoscale organization, and that PopZ droplet growth deviated from classical models. These findings were supported by molecular dynamics simulations, which provided atomic-level insights into the biocondensate assemblies.

The study thus demonstrated the value of holographic microscopy as a hypothesis-generating tool that provides noninvasive insight into condensate substructure, that can be further tested and refined using complementary, minimally perturbative methods.

“Being able to see ‘under the hood’ for the first time has revealed some big surprises about this important class of systems,” professor David Grier said.

Although the researchers observed the condensates in vitro, their findings could contribute to a more complete understanding of condensate behavior within living cells. “The intricate reality of biomolecular condensates, as revealed by our findings, goes far beyond simple liquid-liquid phase separation,” Saurabh said.

A better understanding of how biomolecular condensates are organized and grow, made possible through holographic microscopy and superresolution imaging, could help shape disease modeling and future drug development. For example, the proteins that form plaques in ALS are fluid condensates in good health. “Understanding how a spherical condensate forms into a deadly plaque is an opportunity to better understand ALS,” Saurabh said.

The biomolecular condensates in the cells can also house drug molecules that are intended for a different purpose. This phenomenon could help explain why drugs that are designed to target a specific protein still cause side effects. By using holographic microscopy to analyze condensate dynamics with extreme precision, scientists can identify the subtle differences in condensate composition and architecture that occur when drug molecules enter a condensate.

“For example, we can now explore the chemical space of drug modifications to precisely control their partitioning, achieving the specificity needed to prevent them from entering condensates,” Saurabh said. “This opens new avenues for how we think about designing drugs and their potential side effects.”

This work highlights the power of holographic microscopy, especially when used with superresolution imaging, to probe the properties and mechanistic underpinnings of biomolecular condensates. “Our collaboration has introduced fast, precise, and effective methods for measuring the composition and dynamics of macromolecular condensates,” Grier said.


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Handheld Device Allows Imaging and Treatment of Oral Cancer

 

Oral cancer is a growing public health concern, particularly in South Asia, where it affects tens of thousands each year. In India alone, oral cancer accounts for 40% of all cancers, largely driven by the widespread use of tobacco-based products. The situation is worsened by limited access to early screening and treatment, especially in rural and underserved areas. Most cases are diagnosed at advanced stages, when treatment is more difficult and survival rates are lower.

To address this problem, a team of researchers has developed a compact, affordable device that can both image suspicious lesions and deliver light-based therapy to treat them.

The device uses a smartphone-coupled intraoral probe with specialized LEDs and filters to capture white-light and fluorescence images to pinpoint oral cancers. It also includes laser diodes to activate a light-sensitive compound called protoporphyrin IX (PpIX), which accumulates in cancerous tissue after the application of a precursor drug, 5-aminolevulinic acid (ALA). When exposed to light, PpIX produces reactive molecules that destroy cancer cells while sparing healthy tissue. This approach, known as photodynamic therapy, has shown promise in treating early oral cancers with minimal side effects.

To evaluate the device, the researchers conducted a series of preclinical tests. The team used tissue-mimicking phantoms and cell cultures to test the device’s ability to detect PpIX fluorescence and monitor its breakdown (photobleaching) during treatment. The device showed a strong linear response to increasing PpIX concentrations and could detect changes in fluorescence that corresponded to effective light dosing.

Simulated 3D oral tissues embedded with cancer cells were used to assess how deeply the device could detect and treat lesions. The system successfully imaged PpIX fluorescence up to 2.5 mm deep and showed effective photobleaching at depths relevant to early-stage oral cancers. To further test the technology, the device was used to deliver photodynamic therapy and monitor treatment in an animal model. There, tumors treated with the device shrank significantly compared to untreated controls. Histological analysis revealed tumor cell death extending up to 3.5 mm deep, consistent with light delivery simulations.

One of the device’s key features is its capability to monitor treatment in real time. By measuring the decrease in PpIX fluorescence during light exposure, the system provides feedback on how much therapeutic dose has been delivered. This could help ensure that each treatment is effective, even in settings without advanced medical infrastructure.

The researchers also used ratiometric imaging — comparing red and green fluorescence signals — to improve the accuracy of lesion detection and treatment monitoring. This method helps distinguish cancerous tissue from surrounding healthy areas, even in complex tissue environments.

The study demonstrates that a low-cost, portable device can perform both diagnosis and treatment of early oral cancer with promising accuracy and effectiveness. By combining imaging and therapy in a single tool, the technology could streamline care in regions where access to specialists is limited.

Future work will focus on clinical trials and refining the device for broader use. The team envisions a system that not only guides treatment but also adapts in real time, making photodynamic therapy more accessible and effective for patients around the world.


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Material Innovation Keys Scalable Spectrometer Design for Diverse Applications

 

A smartphone-inspired spectrometer platform, built with low-cost plastic materials instead of glass, could make spectral imaging more accessible across the scientific, industrial, and consumer domains.

The spectrometer spans the visible to SWIR range and is fabricated using mass-producible, non-lithographic methods. These properties could make it suitable for in-home health care monitoring, food quality testing, agricultural sensing, and many other applications that require affordable, broadband sensing capabilities.

The spectrometer design is the result of a collaboration among researchers at the University of Cambridge, Zhejiang University, Zhejiang Sci-Tech University, and Nanyang Technological University, with backgrounds in materials science, optical engineering, and signal processing.

Plastic optical components are used in smartphone cameras to achieve high performance in an ultracompact format. Inspired by this approach, the research team took a similar path, using transparent shape memory epoxies to stress-engineer optical dispersive elements made from plastic. The epoxy used for the spectrometer, bisphenol A epoxy, is highly transparent across the visible to SWIR range.

Shape memory epoxies can be mechanically stretched at elevated temperatures to program precise, stable stress distributions into the material. These stresses create birefringence, an optical effect where light is split according to its wavelength.

Through temperature-controlled mechanical stretching, the team was able to stress-engineer the epoxy and tailor its optical properties. Shape memory epoxies provide superior stress storage compared to other plastic materials, which enables a wide range of spectral encoding through stress engineering.

“By shaping the internal stress within the polymer, we are able to engineer spectral behavior with high repeatability and tunability, something that’s incredibly difficult to achieve with conventional optics,” professor Gongyuan Zhang said.

The resulting films act as spectral filters, encoding information that can be read by standard CMOS image sensors and reconstructed via algorithms. The researchers demonstrated that the planar, stress-engineered epoxy films can be used to form a spectrometer device when they are integrated with a commercial CMOS image sensor and a spectral reconstruction algorithm is used for computational processing of the pixel outputs.

The use of large-scale stretched epoxy films as filters significantly enhances the yield of the spectrometer. The team realized miniaturized spectrometers with broad coverage across both the visible (400-800 nm) and NIR (800-1600 nm) ranges.

The epoxy film layer also enables the spectrometer to serve as a line-scanning device for spectral imaging on 2D images, facilitating the acquisition of corresponding spectral data cubes, and demonstrating the spectrometer’s potential as a portable tool for hyperspectral imaging.

The stress-engineered films can be fabricated in a single step, without the need for lithography or expensive nanofabrication, making the spectrometers suitable for mass production and integration into consumer electronics like mobile phones and wearable technologies.

“We’ve shown that you can use programmable plastics to cover a much broader range of the spectrum than typical miniaturized systems — right into the SWIR,” professor Zongyin Yang said. “That’s really important for applications like agricultural monitoring, mineral exploration, and medical diagnostics.”

The new spectrometer design could be used to detect pollutants, verify the authenticity of drugs, monitor blood sugar noninvasively, and even to sort recyclable materials in real-time. By eliminating the trade-offs between size, cost, and spectral range, the spectrometer could help advance research in computational photonics and sustainable sensing technologies.

“This work shows how mechanical design principles can be used to reshape photonic functionality,” professor Tawfique Hasan said. “By embedding stress into transparent polymers, we have created a new class of dispersive optics that are not only lightweight and scalable but also adaptable across a wide spectral range. This level of flexibility is very difficult to achieve with traditional optics relying on static, lithographically defined structures.”

As the team continues to refine the design and explore commercial pathways, the stress-engineered, plastic spectrometer could become a building block for the next generation of intelligent, compact sensors embedded in devices for everyday use.


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