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Making the Invisible Visible: Microscope Breakthrough Will Open Unprecedented View into Our Cells

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Biohub and UC Berkeley show that the laser phase plate, a revolutionary device with a laser 100 million times brighter than the Sun, dramatically improves images obtained through cryo-electron microscopy, giving scientists a new window into the molecular underpinnings of disease

BERKELEY, Calif. and REDWOOD CITY, Calif., June 11, 2026 /PRNewswire/ — In a landmark achievement in biological imaging, researchers at Biohub and the University of California, Berkeley today announced the successful demonstration of the laser phase plate, a novel device that dramatically improves the contrast of images produced by cryo-electron microscopes, opening up an entirely new view of human biology.

Cryo-electron microscopy (cryo-EM) is itself a revolutionary, Nobel Prize–winning technology that has become the backbone of structural biology, having revealed the atomic-level architecture of many of the molecular machines that drive nearly every cellular process. But the technique has been hampered by the inability to generate enough contrast to clearly image small molecules — more than 90% of the proteins found inside human cells are too small for cryo-EM to capture clearly.

Building on earlier demonstrations, Biohub and UC Berkeley scientists have now built and integrated a laser phase plate, one of the brightest lasers of its type in the world, into a state-of-the-art cryo-electron microscope, as described in two new publications. The result is a device that will open up views of the cell like never before, allowing scientists to see the processes and interactions that are at the root of health and disease.

“The cell is just filled with everything that you could ever want to know — but we can’t see it, and we can’t find it,” said David Agard, Founding Scientific Director of Imaging at Biohub. “To see all those interactions has been the dream of structural cell biologists for decades, and we’re on the brink of being able to see that. In my view, the laser phase plate is integral to making this happen.”

Potential disease mechanisms and therapeutic targets come into view

The laser phase plate was first proposed more than 15 years ago by physicist Holger Müller and biophysicist Robert Glaeser, both of UC Berkeley, but it was long thought to be nearly impossible to build. After years of effort, they were able to achieve a working prototype and demonstrate its applicability in cryo-EM in an older generation electron microscope.

Now Biohub and UC Berkeley researchers have each built a laser phase plate, installed in custom versions of the Thermo Scientific Krios microscope, and demonstrated strong contrast improvements in imaging of small proteins, as reported in two scientific papers. The entire optical cavity housing the laser phase plate — the heart of the system — is less than four inches wide, tucked inside microscopes that stand 14 feet tall.

The UC Berkeley paper, published online today in Science, demonstrates that the laser phase plate provides higher resolution for six different biological samples of different sizes and different sample preparation. Further, they showed that the smaller the sample, the greater the improvement. Specifically, the authors show reconstructed images of a protein from muscle called aldolase, which is relatively easy to image with conventional cryo-EM machines, and of hemoglobin — a protein that carries oxygen in blood — which is at the lower limit for current machines.

“With the more challenging of the two particles, hemoglobin, we saw a strong improvement with the laser, but with the less challenging one, aldolase, the improvement is very small, as expected,” said Jessie Zhang, a postdoc in Müller’s lab who is the co-first author of the study with postdoc Petar Petrov.

Müller, professor of physics at UC Berkeley, said that now that the advantages of the laser phase plate have been clearly demonstrated, he is excited about its potential to solve even more challenging bioimaging problems.

“If you look at all the proteins in a human, they all have various sizes. And all of these proteins are potential disease mechanisms and drug targets,” said Müller, corresponding author of the paper and also a faculty scientist at Lawrence Berkeley National Laboratory. “The problem is, the average human protein is too small to be imaged by cryo-EM. The laser phase plate could fill an enormous gap in our knowledge of protein structures that can’t be processed with today’s cryo-EM.”

Müller spent more than 10 years building a working prototype of the laser phase plate. Then in 2021 Biohub decided to make a big bet on the technology and supported him with a grant, which allowed him to ramp up development, purchase a state-of-the-art cryo-electron microscope, and customize it for the laser phase plate.

In addition to supporting Müller’s efforts, Biohub made an even bigger bet, building a next-generation version of the laser phase plate with twice the complexity, featuring a dual laser system. That system is described in a new preprint on biorxiv.org.

Developed at Biohub’s imaging lab in Redwood City, in collaboration with UC Berkeley and industry partners, the device uses two laser beams oriented perpendicular to each other, each in its own cavity and operating at about half the power required by the single-cavity system used in Müller’s microscope. At lower power, components are less likely to burn and aberrations are reduced, making the system easier to operate.

The concept of a dual laser system was first proposed by Müller and UC Berkeley colleagues two years ago in a paper that was just published last week in Nature Communications.

An engineering feat — and a long time coming

More than a decade ago, Müller and Glaeser first proposed the idea of creating an intense laser to shift the phase of the electron beam in cryo-electron microscopes, but many in the field considered such an instrument far too difficult to build.

Making the laser phase plate a reality required an extraordinary combination of precision, advanced engineering, and complex laser optics to generate the most intense steady-state laser ever. Inside the cavity, a laser beam is bounced back and forth between two concave mirrors almost 10,000 times, building up to an intensity of approximately 350 to 400 gigawatts per square centimeter — an energy 100 million times more intense than the surface of the Sun, concentrated into a spot about 1/1000th the width of a human hair.

The mirrors that make this possible are themselves a remarkable feat of engineering. Each mirror must be polished to “atomic-level smoothness” — a surface roughness of less than one angstrom, approximately the diameter of a single atom.

“The mirrors must be extremely lossless to prevent them from melting, and in fact are so lossless that they barely warm up, despite being bombarded by a laser that could easily cut inches of steel,” Müller said.

The precision required to operate the instrument is equally demanding. The angle of the mirrors must be aligned to within 1/1000th of a degree for the lasers to bounce effectively. Additionally, the laser beam and electron beam must be aligned to within 50 nanometers — on a standing wave that is 500 nanometers across — to maximize contrast while acquiring data.

“It’s like a surfer trying to hold perfectly to the peak of a wave, not for seconds, but for half an hour at a stretch,” said Bridget Carragher, Founding Technical Director of Imaging at Biohub. She and Agard are co-leads of Biohub’s Dynamic Structural Cell Biology group and co-corresponding authors of the Biohub preprint, along with Biohub engineer Pavel Olshin.

The next frontier

While the papers demonstrate the device’s power for imaging individual small proteins, researchers at both institutions believe the next frontier is cryo-electron tomography (cryo-ET) — a powerful newer variant of cryo-EM that captures proteins not in isolation but in their natural cellular environment, revealing how molecular machines actually assemble, interact, and malfunction in disease.

“We believe tomography is where we’ll see the really huge wins for cell biology,” Carragher said. “There’s still work to be done in wrangling the microscope, but we’re optimistic we’ll be doing data collection by the end of the year.”

All of Biohub’s tomography data – including tens of thousands of annotated tomograms – is freely shared with the community at its CryoET Data Portal, which aims to accelerate the entire cryo-ET pipeline.

“Doing a cell biology experiment with cryo-ET today can take up a postdoc’s entire career,” Agard said. “We need to speed that up, and the laser phase plate, along with better processing, all working seamlessly with AI algorithms, will get us there.”

Müller hopes that microscopes fitted with laser phase plates will be commercially available in the coming years, and that labs around the world will have this powerful technology in regular use.

“This technology is a step function change for biology,” said Stephani Otte, Biohub’s Vice President of Imaging Science. “We are going to be able to see how molecular machines operate inside the living cell, in context, for the first time. What was once invisible will become visible — and that changes everything about how we understand disease.”

About Biohub

Biohub is a 501(c)(3) biomedical research organization building the first large-scale initiative to combine frontier AI and frontier biology to solve disease. With its compute capacity, AI research and engineering, and state-of-the-art technology for measuring, imaging, and programming biology, Biohub is enabling scientists worldwide to use AI-powered biology to study how cells operate and organize as systems — ultimately understanding why disease happens and how to cure or prevent it. Learn more at biohub.org.

About UC Berkeley

Founded in 1868, UC Berkeley is the world’s No. 1 public university, with 63 Nobel laureates and 50 graduate programs ranked in the nation’s top 10. Berkeley researchers advance fundamental science while addressing society’s greatest challenges — from artificial intelligence to climate change to human health. The university enrolls nearly 46,000 students, with 28% of undergraduates receiving federal Pell Grants, reflecting its commitment to access. Learn more at berkeley.edu.

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SOURCE Biohub

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SmartOrg releases Version 10.x of its Decision Intelligence platform

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New release expands SmartOrg’s Decision Intelligence platform with a cleaner, more configurable experience and new product capabilities.

PALO ALTO, Calif., June 11, 2026 /PRNewswire-PRWeb/ — SmartOrg, Inc., a Palo Alto-based provider of Decision Intelligence solutions, today announced the release of version 10.x of its software platform, with its standard products Innovation Navigator® and Portfolio Navigator® now deployed by configuring modules on a newly integrated platform.

“This release is really about giving customers a better experience and more flexibility in how they apply the platform to their specific decision challenges.”

Combined in other ways, these modules support deployments optimized for other contexts.

“This release is really about giving customers a better experience and more flexibility in how they apply the platform to their specific decision challenges,” said David Matheson, President and CEO of SmartOrg. “We’re delighted to see customers using SmartOrg’s Decision Intelligence Platform in more targeted ways, for example in Technology Assessment, Energy Exploration and Drug Discovery. Version 10.x gives them a cleaner, more configurable foundation for doing that work.”

The release includes major updates to Innovation Navigator®, including flexible brainstorming canvases, enhanced Learning Plan modules, and upgraded Discovery Grid visualizations. These enhancements help innovation teams capture ideas, organize learning activities, and focus attention on the uncertainties that matter most.

Portfolio Navigator® also receives significant new capabilities, including a Maturity Matrix, Probability of Success calculator, and portfolio goal analysis. These features help leaders better assess projects, compare them, and support portfolio decisions.

“Version 10.x is part of our ongoing commitment to keeping SmartOrg’s software current, useful, and easier for customers to apply,” said Dave Wachenschwanz, Director of Development at SmartOrg. “The platform has significant upgrades in its user interface, improving consistency and usability.”

To see highlights of the new release, SmartOrg has published a short video overview from its development team that you can watch here: https://bit.ly/4xdA7QY

About SmartOrg

SmartOrg helps innovation, R&D, and strategy teams convert uncertainty to opportunity. Its software products—Innovation Navigator® and Portfolio Navigator®—apply quantitative methods to prioritize learning, build confidence in the business case, and guide investment decisions at both the project and portfolio levels to help organizations meet their growth objectives.

Media Contact

Doug Williams, SmartOrg, Inc., 1 3399270834, dwilliams@smartorg.com, https://smartorg.com

View original content to download multimedia:https://www.prweb.com/releases/smartorg-releases-version-10x-of-its-decision-intelligence-platform-302796404.html

SOURCE SmartOrg, Inc.

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Cathay Financial Holdings Leverages Open-Source Small Language Models to Identify Customer Intent

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Fine-tuning Small Language Models to Better Understand Local Financial Service Contexts, Domain Terminology, and Ambiguous Customer Queries

TAIPEI, June 12, 2026 /PRNewswire/ — To enhance operational efficiency and customer experience, Cathay Financial Holdings (Cathay FHC) continues to advance the application of generative AI in financial services through its generative AI technical framework, GAIA, and AI-as-a-Service (AIaaS) strategy. Building on last year’s validation of large language models (LLMs) for financial applications, Cathay FHC recently unveiled its latest AI research findings at NVIDIA GTC Taipei 2026, demonstrating how open-source small language models (SLMs) can be fine-tuned for customer intent classification and applied to future financial service scenarios.

The study evaluated several leading open-source models from Meta, TAIDE, TAME, NVIDIA and OpenAI. Preliminary results showed that, under the testing framework, fine-tuned SLMs may reduce dependence on complex prompt engineering and vector retrieval modules, potentially simplifying system architecture while lowering future operational and maintenance complexity.

The findings indicated that, when combined with carefully designed financial-domain datasets and targeted model fine-tuning, SLMs can further improve model stability, inference efficiency, and deployment controllability. In customer intent classification, the fine-tuned SLM achieved performance close to mainstream closed-source LLMs, approaching that of leading proprietary LLMs, providing enterprises with a practical reference for evaluating AI model training and deployment strategies.

From a data governance and privacy perspective, the study adopted a fully synthetic data approach, ensuring that no real customer information was used during model training. Through techniques including service-function clustering, single-intent and multi-intent dataset design, Taiwan-context localization, and keyword expansion, Cathay FHC strengthened the model’s ability to understand local financial service contexts, industry-specific terminology, and ambiguous customer queries.

Potential future applications include mortgage balance inquiries, credit card payment assistance, and branch service navigation, laying the groundwork for intelligent search, service routing, and next-generation customer engagement experiences.

From a technical architecture standpoint, Cathay FHC integrated NVIDIA AI tools—including NVIDIA NeMo Customizer, NVIDIA NeMo Curator, and NVIDIA TensorRT-LLM—together with NVIDIA Hopper architecture computing resources to support data generation, model fine-tuning, inference optimization, and experimental evaluation. Leveraging NVIDIA AI ecosystem, Cathay FHC continues to strengthen its capabilities in financial-domain model development, data governance, and application validation.

In recent years, Cathay FHC has steadily expanded AI innovation across a wide range of financial scenarios, building scalable technological foundations spanning internal process optimization, customer service enhancement, financial knowledge understanding, and model governance. As financial institutions navigate an increasingly regulated environment, stringent data governance requirements, and rapidly evolving customer expectations, Cathay FHC remains committed to advancing AI research in a compliant, secure, and resilient manner.

Looking ahead, Cathay FHC will continue exploring long-context classification, advanced financial document understanding, and cross-scenario AI applications. By developing model training and deployment approaches tailored to the financial sector, the company aims to accelerate innovation and create more intelligent, efficient, and customer-centric financial services.

View original content to download multimedia:https://www.prnewswire.com/apac/news-releases/cathay-financial-holdings-leverages-open-source-small-language-models-to-identify-customer-intent-302798631.html

SOURCE Cathay Financial Holdings

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First Advantage Set to Join S&P SmallCap 600

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NEW YORK, June 11, 2026 /PRNewswire/ — First Advantage Corporation (NASD: FA) will replace Kennedy-Wilson Holdings Inc. (NYSE: KW) in the S&P SmallCap 600 effective prior to the opening of trading on Tuesday, June 16. A consortium led by KW’s CEO with Fairfax Financial Holdings Limited (TSE: FFH) is acquiring Kennedy-Wilson Holdings in a deal expected to close soon, pending final closing conditions.

Following is a summary of the changes that will take place prior to the open of trading on the effective date:

Effective Date     

Index Name      

Action

Company Name

Ticker     

GICS Sector     

June 16, 2026

S&P SmallCap 600     

Addition     

First Advantage

FA

Industrials

June 16, 2026

S&P SmallCap 600

Deletion

Kennedy-Wilson Holdings     

KW

Real Estate

ABOUT S&P DOW JONES INDICES

S&P Dow Jones Indices is the largest global resource for essential index-based concepts, data and research, and home to iconic financial market indicators, such as the S&P 500® and the Dow Jones Industrial Average®. More assets are invested in products based on our indices than products based on indices from any other provider in the world. Since Charles Dow invented the first index in 1884, S&P DJI has been innovating and developing indices across the spectrum of asset classes helping to define the way investors measure and trade the markets.

S&P Dow Jones Indices is a division of S&P Global (NYSE: SPGI), which provides essential intelligence for individuals, companies, and governments to make decisions with confidence. For more information, visit www.spglobal.com/spdji/en/.

FOR MORE INFORMATION:

S&P Dow Jones Indices
index_services@spglobal.com 

Media Inquiries
spdji.comms@spglobal.com 

 

View original content:https://www.prnewswire.com/news-releases/first-advantage-set-to-join-sp-smallcap-600-302798639.html

SOURCE S&P Dow Jones Indices

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