Researchers have developed an innovative tissue culture-free, or “ex vitro,” genetic transformation method for woody plants that overcomes a major barrier in plant biotechnology. Using Agrobacterium rhizogenes, the technique directly transforms plant roots and enables the regeneration of fully transgenic trees without labor-intensive tissue culture procedures. Initially demonstrated in poplar and being expanded to shrub willow and other commercially valuable species, the approach simplifies genetic engineering, reduces costs, and increases scalability. By making transformation feasible in species previously resistant to modification, the technology could accelerate advances in forestry, bioenergy crops, plant breeding, and environmental resilience. The patent-pending innovation is at TRL 5 and available for licensing. This technology could support the development of trees with improved growth, pest resistance, climate adaptability, and bioenergy performance, contributing to sustainable forestry, renewable energy production, and ecosystem restoration efforts.

Researchers have developed an innovative inducible cell line platform that enables high-throughput screening of small molecules targeting toxic expanded CAG repeat RNA, a key driver of neurodegenerative disorders such as Huntington’s disease and spinocerebellar ataxias (SCAs). The system uses engineered HEK293 cells with dual reporter constructs, multiplex RT-qPCR, and luciferase-based assays to distinguish effects on disease-causing versus normal transcripts with high sensitivity. An inducible promoter reduces cellular toxicity and supports long-term studies, overcoming limitations of existing screening models. The platform has already identified lead compounds for SCAs, accelerating therapeutic discovery and preclinical validation. The patent-pending technology is at TRL 4 and available for licensing. This technology could speed the development of disease-modifying therapies for Huntington’s disease, SCAs, and related neurodegenerative disorders, potentially improving treatment options, slowing disease progression, and enhancing quality of life for affected patients and families.

This technology introduces a novel artificial intelligence model that improves the detection of previously unseen electromagnetic waveforms by combining time-domain and frequency-domain signal representations. Using a cosine similarity loss function, the system enhances extraction of class-specific features, enabling more accurate identification of unknown signals than conventional approaches. Testing demonstrated approximately a 10% improvement in detection accuracy compared to models lacking this capability. Potential applications include electronic warfare, spectrum management, intelligence and surveillance operations, radio astronomy, and communication security. By providing more reliable waveform classification and interference detection, the technology supports improved situational awareness and spectrum utilization. The patent-pending technology is at TRL 3 and available for licensing.

Researchers have developed a novel platform combining the ASD interrogator (ASDint), a specialized neural network model, and the Synaptic Neuronal Circuit (SyNC), a hardware architecture designed to analyze synaptic dysfunctions associated with Autism Spectrum Disorder (ASD) and related neurological conditions. The system enhances traditional spiking neural networks by incorporating retrograde messenger analysis, enabling more biologically accurate modeling of glutamatergic synapses. SyNC delivers real-time synaptic simulations through GPU-accelerated or ASIC-based hardware, improving computational efficiency and research capabilities. The technology could advance understanding of disease mechanisms, support therapeutic development, and accelerate neuroscience research. As a patent-pending, licensable innovation at TRL 4, it demonstrates early-stage commercialization potential. Improved tools for studying synaptopathies may help researchers develop more effective treatments for ASD and other neurological disorders, potentially improving patient outcomes and quality of life.

This technology enables the direct rescue of segmented negative-sense RNA viruses from complementary DNA (cDNA) in non-cancerous Vero cells, a cell substrate accepted for human vaccine manufacturing. Using triggered endosome escape technology and T7 polymerase-driven expression systems, the method improves the delivery and expression of viral components needed to generate infectious viruses from cDNA. By replacing traditional tumorigenic BHK cells, the platform offers a safer, more scalable, and potentially more regulatory-friendly approach to developing live-attenuated vaccines. Potential applications include vaccine development for influenza and other segmented RNA viruses, virology research, and rapid-response vaccine platforms. The technology is patent-pending, available for licensing, and currently in an early development stage.

Recently, Food Science of Animal Products (FSAP) has been officially included in the Emerging Sources Citation Index (ESCI) by Web of Science, a leading global provider of scientific and scholarly research information. All articles published by FSAP since 2023 will be included in ESCI. Its first impact factor will be released in 2027.

The Research Highlighter-MatchMaker Project, developed at the University at Albany, uses artificial intelligence and natural language processing to help researchers identify funding opportunities, find collaborators, and connect with research communities. By integrating publication data from Scopus and funding information from SPIN, the platform delivers personalized recommendations through searchable tools and automated email alerts. Users can search by researcher, topic, or proposal text, enabling more accurate matching than traditional keyword-based systems. The technology has the potential to accelerate interdisciplinary collaboration, improve grant competitiveness, and expand access to research opportunities, particularly for early-career researchers. The patent-pending technology is at TRL 3 and available for licensing.

This technology improves neural network security by introducing controlled weight perturbations during training, creating models that are more resistant to unauthorized access, snooping, cryptanalysis, and other attacks. Unlike traditional approaches that rely on external security measures, the method embeds protection directly into the training process, securing the network from the first layer onward and extending safeguards throughout the model. The approach is particularly well suited for mobile, edge, and IoT devices with limited computing resources, while also strengthening machine learning models delivered through APIs. By enhancing security without significant performance penalties, the technology supports safer deployment of AI systems in connected environments. The patent-pending technology is at TRL 3 and available for licensing.

Researchers at the University at Buffalo have developed AudioSight, a smartphone-based screening platform that objectively assesses hearing-related disorders using pupil responses to sound. The system combines a low-cost 3D-printed smartphone attachment, near-infrared illumination, and artificial intelligence to analyze audio-evoked pupillary responses. Advanced machine learning models process features such as response latency, dilation speed, and recovery time to generate risk scores for conditions including hidden hearing loss, tinnitus, and hyperacusis. Designed for self-administration and remote use, the technology could expand access to hearing screening for children, older adults, cognitively impaired individuals, and underserved populations. The TRL 6 technology is available for licensing or collaboration. AudioSight could make hearing-disorder screening more accessible, affordable, and objective by enabling at-home assessment and teleaudiology services. Earlier identification of hearing disorders may improve treatment outcomes, reduce barriers to care, and support populations that have difficulty completing conventional hearing tests.