Through substantial leadership turnover and workforce cuts, the FDA has continued to support the advanced therapy sector, actively working to remove obstacles to innovation.
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The Intelligence Foundation Model Could Be The Bridge To Human Level AI
Cai Borui and Zhao Yao from Deakin University (Australia) presented a concept that they believe will bridge the gap between modern chatbots and general-purpose AI. Their proposed “Intelligence Foundation Model” (IFM) shifts the focus of AI training from merely learning surface-level data patterns to mastering the universal mechanisms of intelligence itself. By utilizing a biologically inspired “State Neural Network” architecture and a “Neuron Output Prediction” learning objective, the framework is designed to mimic the collective dynamics of biological brains and internalize how information is processed over time. This approach aims to overcome the reasoning limitations of current Large Language Models, offering a scalable path toward true Artificial General Intelligence (AGI) and theoretically laying the groundwork for the future convergence of biological and digital minds.
The Intelligence Foundation Model represents a bold new proposal in the quest to build machines that can truly think. We currently live in an era dominated by Large Language Models like ChatGPT and Gemini. These systems are incredibly impressive feats of engineering that can write poetry, solve coding errors, and summarize history. However, despite their fluency, they often lack the fundamental spark of what we consider true intelligence.
They are brilliant mimics that predict statistical patterns in text but do not actually understand the world or learn from it in real-time. A new research paper suggests that to get to the next level, we need to stop modeling language and start modeling the brain itself.
Borui Cai and Yao Zhao have introduced a concept they believe will bridge the gap between today’s chatbots and Artificial General Intelligence. Published in a preprint on arXiv, their research argues that existing foundation models suffer from severe limitations because they specialize in specific domains like vision or text. While a chatbot can tell you what a bicycle is, it does not understand the physics of riding one in the way a human does.
Early experiments in accelerating science with GPT-5
Most strikingly, the paper claims four genuinely new mathematical results, carefully verified by the human mathematicians involved. In a discipline where truth is eternal and progress is measured in decades, an AI contributed novel insights that helped settle previously unsolved problems. The authors stress these contributions are “modest in scope but profound in implication”—not because they’re minor, but because they represent a proof of concept. If GPT-5 can do this now, what comes next?
The paper carries an undercurrent of urgency: many scientists still don’t realize what’s possible. The authors are essentially saying, “Look, this is already working for us—don’t get left behind.” Yet they avoid boosterism, emphasizing the technology’s current limitations as clearly as its strengths.
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Screening of Single-Domain Antibodies to Adeno-Associated Viruses with Cross-Serotype Specificity and a Wide pH Tolerance
Adeno-associated virus (AAV) vectors are the preferred gene delivery tool in gene therapy owing to their safety, long-term gene expression, broad tissue tropism, and low immunogenicity. Affinity ligands that can bind multiple AAV serotypes endure harsh clean-in-place (CIP) conditions and are critical for industrial-scale purification. However, current ligands lack broad serotype recognition and adequate alkaline stability, which limits their reusability in large-scale manufacturing. In this study, we employed a competitive biopanning strategy to isolate a single-domain antibody (VHH) that simultaneously binds AAV2, AAV8, and AAV9. The VHH retained structural integrity and binding activity after exposure to 0.1 M NaOH, demonstrating robust alkaline stability.
Adipokines as Clinically Relevant Therapeutic Targets in Obesity
Adipokines provide an outstanding role in the comprehensive etiology of obesity and may link adipose tissue dysfunction to further metabolic and cardiovascular complications. Although several adipokines have been identified in terms of their physiological roles, many regulatory circuits remain unclear and translation from experimental studies to clinical applications has yet to occur. Nevertheless, due to their complex metabolic properties, adipokines offer immense potential for their use both as obesity-associated biomarkers and as relevant treatment strategies for overweight, obesity and metabolic comorbidities. To provide an overview of the current clinical use of adipokines, this review summarizes clinical studies investigating the potential of various adipokines with respect to diagnostic and therapeutic treatment strategies for obesity and linked metabolic disorders.
Asimov Press (@asimovpress)
We just released a curated list of 125+ essays about biology and science. These articles cover pharmaceuticals, the history of molecular biology, timeless arguments and theories, and more. All of them inspired or taught or challenged us to think more deeply.
Check it out here on Substack or on our custom website: https://read.asimov.com
Disrupting medicine: DNA Origami as the new cornerstone of nano robotics
Session by SPRIND with Klaus Wagenbauer, CEO of Plectonic Biotech, Nicola Kegel, CEO of Nanogami, Christian Sigl, CEO of Capsitec, and Hendrik Dietz, Professor & Founder, Technical University of Munich at the \.
Interfacing with the Brain: How Nanotechnology Can ContributeClick to copy article linkArticle link copied!
Interfacing artificial devices with the human brain is the central goal of neurotechnology. Yet, our imaginations are often limited by currently available paradigms and technologies. Suggestions for brain–machine interfaces have changed over time, along with the available technology. Mechanical levers and cable winches were used to move parts of the brain during the mechanical age. Sophisticated electronic wiring and remote control have arisen during the electronic age, ultimately leading to plug-and-play computer interfaces. Nonetheless, our brains are so complex that these visions, until recently, largely remained unreachable dreams. The general problem, thus far, is that most of our technology is mechanically and/or electrically engineered, whereas the brain is a living, dynamic entity. As a result, these worlds are difficult to interface with one another.
