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Plexision Announces Funding to Bring Artificial Intelligence to Transplant Outcome Care

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Insider Brief

  • Plexision has received a $365,000 investment from the Richard King Mellon Foundation to enhance its AI- and ML-powered blood tests for predicting complex transplant outcomes.
  • The company’s platform integrates immune cell function with machine learning to rank risks of rejection and infection, enabling faster, more precise clinical decisions within 6–24 hours.
  • Validated through multi-center studies, Plexision’s tests like PlexABMR™ and PlexEBV™ have shown strong predictive accuracy and will be showcased at the 2025 World Transplant Congress.

PRESS RELEASE — Plexision, a biotechnology company, has announced a $365,000 investment from the Richard King Mellon Foundation. The funds will be used to accelerate the integration of artificial intelligence (AI) and machine learning (ML) capabilities across Plexision’s suite of cell-based blood tests, significantly improving predictive accuracy for complex transplant outcomes.

Despite advances in transplant medicine, managing immunosuppressive drugs remains a delicate balance. Too little medication can lead to rejection, which can be cell- or antibody-mediated, while too much can increase the risk of infections with different viruses, and in some cases, lymphoma related to Epstein-Barr virus (EBV). Legacy testing tools on the market offer limited visibility into a patient’s immune status, and provide reactive, binary results. To distinguish between the various types of rejection and infection, clinicians often integrate other clinical data to make treatment decisions.

Plexision’s blood tests predict the most common rejection subtypes and post-transplant infections, all using a common platform of immune cell function. When integrated with machine learning, this test panel ranks risks of multiple outcomes across an outcome category in each patient, including the likelihoods of stable graft function, and T-cell-mediated and antibody-mediated rejection. This approach also identifies the presence or absence of an infection, including infection-related lymphoma. These capabilities have been developed and validated in multi-center studies to be reported at the World Transplant Congress in San Francisco, CA between August 2–6, 2025.

“Plexision is redefining transplant diagnostics by predicting rejection subtypes and infection risks using blood tests derived from a single immune cell function platform,” said Dr. Rakesh Sindhi, a transplant surgeon, Co-founder and Chief Scientific Officer, Plexision.

The expanded use of AI will enhance the platform’s ability to rank and predict the likelihood of multiple outcomes in each patient, making it a powerful clinical decision support tool for caregivers delivering precision transplant medicine. The company’s proprietary technology delivers results in as little as 6 to 24 hours, enabling timely intervention.

“This funding enables us to take the next step in making transplant care truly personalized. By expanding our artificial intelligence and machine learning capabilities, we are transforming how clinicians will interpret immunologic signals, moving from singular binary ‘yes/no’ answers to ranked predictions tailored to each patient,” added Sindhi.

All tests are performed at Plexision’s CLIA-approved and CAP-accredited reference laboratory in Pittsburgh, PA, using blood samples shipped in from clinical partners. Results are used with other clinical data to optimize management of individual transplant patients.

Plexision’s innovations have demonstrated strong clinical performance. For example, the company’s PlexABMR™ test recently predicted antibody-mediated rejection in kidney transplant recipients with 81% positive predictive value and 75% negative predictive value in a multi-center trial. Another test predicted EBV infection, a cause of life-threatening infection-related lymphoma in transplant patients. These findings will also be featured at the 2025 World Transplant Congress.

To learn more about Plexision, visit https://plexision.com/ or email [email protected] to schedule a meeting with the company at the World Transplant Congress.

About Plexision

Plexision’s reference laboratory performs cell-based blood tests for personalized management of transplant rejection, infections in immunocompromised patients, and immune therapy in oncology. Transplant rejection testing services include the FDA-approved Pleximmune™ blood test to predict transplant rejection in children with liver or intestine transplants, the lab-developed Pleximark™ test to predict kidney transplant rejection, and the recently developed PlexABMR™ to predict antibody-mediated rejection. Tests that predict infection includes the lab-developed PlexCMV™, currently the most sensitive test to capture protective cell-mediated immunity in high-CMV-risk transplants. The PlexEBV™ test predicts EBV infection, which can cause post-transplant lymphoma. These tests measure cell-mediated immunity to cytomegalovirus and EBV, respectively. Plexision also performs custom R & D projects that require integration of cellular biomarker targets in all phases of development of drugs, vaccines, and gene therapy products, from pre-clinical to post-marketing. The company’s portfolio of cell-based blood tests can be adapted to assess disease risk for several immunological disorders and develop personalized dosing recommendations. The company’s reference laboratory in Pittsburgh, PA, is CLIA-approved, CAP-accredited and GMP-compliant. To learn more, visit www.plexision.com or email [email protected].

About Richard King Mellon Foundation

Founded in 1947, the Richard King Mellon Foundation is the largest foundation in Southwestern Pennsylvania, and one of the 50 largest in the world. The Foundation’s 2023 year-end net assets were $2.9 billion, and its Trustees in 2023 disbursed more than $176 million in grants and program-related investments. The Foundation focuses its funding on six primary program areas, delineated in its 2021–2030 Strategic Plan.

Contacts

Jason Vancura
Marketbridge for Plexision
[email protected]

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AI Research

MIT Researchers Develop AI Tool to Improve Flu Vaccine Strain Selection

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Insider Brief

  • MIT researchers have developed VaxSeer, an AI system that predicts which influenza strains will dominate and which vaccines will offer the best protection, aiming to reduce guesswork in seasonal flu vaccine selection.
  • Using deep learning on decades of viral sequences and lab data, VaxSeer outperformed the World Health Organization’s strain choices in 9 of 10 seasons for H3N2 and 6 of 10 for H1N1 in retrospective tests.
  • Published in Nature Medicine, the study suggests VaxSeer could improve vaccine effectiveness and may eventually be applied to other rapidly evolving health threats such as antibiotic resistance or drug-resistant cancers.

MIT researchers have unveiled an artificial intelligence tool designed to improve how seasonal influenza vaccines are chosen, potentially reducing the guesswork that often leaves health officials a step behind the fast-mutating virus.

The study, published in Nature Medicine, was authored by lead researcher Wenxian Shi along with Regina Barzilay, Jeremy Wohlwend, and Menghua Wu. It was supported in part by the U.S. Defense Threat Reduction Agency and MIT’s Jameel Clinic.

According to MIT, the system, called VaxSeer, was developed by scientists at MIT’s Computer Science and Artificial Intelligence Laboratory and the MIT Jameel Clinic for Machine Learning in Health. It uses deep learning models trained on decades of viral sequences and lab results to forecast which flu strains are most likely to dominate and how well candidate vaccines will work against them. Unlike traditional approaches that evaluate single mutations in isolation, VaxSeer’s large protein language model can capture the combined effects of multiple mutations and model shifting viral dominance more accurately.

“VaxSeer adopts a large protein language model to learn the relationship between dominance and the combinatorial effects of mutations,” Shi noted. “Unlike existing protein language models that assume a static distribution of viral variants, we model dynamic dominance shifts, making it better suited for rapidly evolving viruses like influenza.”

In retrospective tests covering ten years of flu seasons, VaxSeer’s strain recommendations outperformed those of the World Health Organization in nine of ten cases for H3N2 influenza, and in six of ten cases for H1N1, researchers said. In one notable example, the system correctly identified a strain for 2016 that the WHO did not adopt until the following year. Its predictions also showed strong correlation with vaccine effectiveness estimates reported by U.S., Canadian, and European surveillance networks.

The tool works in two parts: one model predicts which viral strains are most likely to spread, while another evaluates how effectively antibodies from vaccines can neutralize them in common hemagglutination inhibition assays. These predictions are then combined into a coverage score, which estimates the likely effectiveness of a candidate vaccine months before flu season begins.

“Given the speed of viral evolution, current therapeutic development often lags behind. VaxSeer is our attempt to catch up,” Barzilay noted.



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Analysis and Trading in One

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We had just discussed new crypto projects with AI integrations, and now ChadFi launches an AI terminal: analysis and trading in one. It is worth noting that the platform is at an early stage of development, but states that its AI-powered platform’s beta version already implements research, analysis, and execution in a single cycle.

They present the operational sequence as Data Collection – AI Analysis – Insights Generation – Trade Execution – Feedback Loop, that is, the analytical pipeline and the execution loop are closed within a single interface.

What Is the Actual Working Stage of the Platform?

At the moment, they state three core components: Deep Analysis engine, SpoonFed Setups, and All-in-One Execution. Thus, some functions are already available in the terminal, with the expansion of integrations with centralized venues planned for the next release.

Deep Analysis engine works across five data domains:

  • Technical indicators for the detection of chart patterns

  • Project fundamentals

  • On-chain flows and address activity

  • Social sentiment via X metrics

  • Smart money activity

Among the specific AI Analysis functions the platform offers:

  • AI-Powered Token Analysis

  • Personalized Entry and Exit Recommendations

  • Advanced Technical Analysis Tools

  • Real-Time Market Monitoring

  • Customizable Alerts and Notifications

  • Sentiment Analysis

AI has been helping major players in market analysis and decision-making long before this became popular and before AI-powered platforms began appearing every week. Learn more about the AI in Cryptocurrency Trading: Technical Review & Market Capabilities.

The output layer forms SpoonFed Setups – predefined scenarios for entry and position management that convert observations across multiple layers into actionable steps. The scenarios are then transferred into the execution loop, and the Feedback Loop feeds the result back into the analytics workspace.

Also, the platform states real-time whale monitoring, comprehensive wallet profiling taking into account historical performance and behavioral characteristics, visualization of liquidity movement between addresses, protocols, and segments, as well as observation of narrative rotation. These signals enter the overall pipeline and are used as one of the sources for SpoonFed Setups.

All-in-One Execution is designed for single-interface operation and supports multiple take-profit and stop-loss orders, and the built-in contract safety scanners serve as a mechanism for preliminary checks for common smart contract risks and the presence of dangerous patterns.

To make all this truly convenient for each individual user, their interface supports layout customization and a Customizable Dashboard with watchlists 2.0 and a set of widgets to assemble data layers on one screen for a specific task.

To avoid missing important signals, the Alerts and Notifications system is configured by conditions and delivery channels. For collaboration and social distribution, sharing of setups and interaction via X, Discord, and Telegram are supported.

A Good Initiative, but Is It a Worthy Product?

It is too early to state definitively. It is necessary to pass the beta stage and see how this will actually work at the level of a full-fledged system.

Also, they do not provide information about which AI models they use, how they train them, or how data management and model policies are arranged. If there are problems with the AI models, then one of the key functionalities of the platform would be eliminated.

However, even in this case, a focus on a customizable and detailed visibility toolkit, where the activity of influential addresses is concentrated and how market focus shifts across segments, can be valuable on its own. But again, only if data handling is implemented with genuine quality and reliability.



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Minus-AI Launches the Coolest Video Ad Agent for the AI Era

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Minus-AI

Singapore, Sept. 01, 2025 (GLOBE NEWSWIRE) — Minus-AI: The Coolest AI Video Ad Agent

 

https://youtu.be/HDyhkczn21k 

Minus-AI, a Singapore-based AI-native startup, has officially launched its breakthrough platform that transforms brand information into cinematic, multi-shot video ads in just minutes. Positioned at the intersection of AI marketing, content marketing, AI video ads, and AI video generation, Minus-AI is redefining how businesses of every size create and scale their marketing.

The company proudly states its vision in one bold slogan: “Minus-AI is the coolest AI video ad agent.”

(Frame generated by Minus AI)

A Startup with Momentum

Founded in late 2024, Minus-AI immediately attracted over one million USD in angel investment from renowned figures in the global film and entertainment industry. This rapid validation underscores both the technical depth of the team and the enormous demand for next-generation AI marketing solutions.

Minus-AI’s co-founders bring complementary expertise:

Dr. Luo, who previously served as Senior Principal Scientist at Autodesk Research, brings expertise in reinforcement learning and AI-driven creativity. His collaborations with creatives have been featured at various international venues. With Minus AI, he set out on a mission to build tools that harness the power of AI to enhance creative processes.

Ms. Cai, a graduate of New York University (NYU), was the founder of one of the earliest VR education startups in China, which quickly achieved profitability. With a background bridging creative technology and business execution, she now leads product and commercialization at Minus-AI.

Together, they represent the fusion of advanced AI research and creative entrepreneurship.

The Meaning of “Minus-AI”

As Dr. Luo explains, the name Minus-AI carries a philosophy:

“Minus-AI stands for reducing meaningless labor and leaving time for what truly matters. The dash in Minus-AI is also a minus sign — cutting away the unnecessary.”

This philosophy reflects the company’s mission: to simplify the complexity of content marketing, giving businesses a direct path from idea to finished ad, without wasted effort.

(Minus-AI logo design)

Five Core Advantages of Minus-AI

1. Trendy Ideas, Done for You

Most businesses struggle to keep up with fast-moving social media trends. Minus-AI solves this by embedding hotspots and viral formats directly into its system. From concept to creative format, the platform delivers fresh ideas already tailored to your product and the cultural moment.



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