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Category: bioengineering – Page 3

Lab-grown brains with all major cell types support next-generation therapy research

A new 3D human brain tissue platform developed by MIT researchers is the first to integrate all major brain cell types, including neurons, glial cells and the vasculature into a single culture. Grown from individual donors’ induced pluripotent stem cells, these models—dubbed Multicellular Integrated Brains (miBrains)—replicate key features and functions of human brain tissue, are readily customizable through gene editing, and can be produced in quantities that support large-scale research.

Although each unit is smaller than a dime, miBrains may be worth a great deal to researchers and drug developers who need more complex living lab models to better understand brain biology and treat diseases.

“The miBrain is the only in vitro system that contains all six major cell types that are present in the human brain,” said Li-Huei Tsai, Picower Professor, director of The Picower Professor of Learning and Memory, and senior author of the study describing miBrains, published in the Proceedings of the National Academy of Sciences.

Algorithm precisely quantifies flow of information in complex networks

Networks are systems comprised of two or more connected devices, biological organisms or other components, which typically share information with each other. Understanding how information moves between these connected components, also known as nodes, could help to advance research focusing on numerous topics, ranging from artificial intelligence (AI) to neuroscience.

To measure the directional flow of information in systems, scientists typically rely on a mathematical construct known as transfer entropy, which essentially quantifies the rate at which information is transmitted from one node to another. Yet most strategies for calculating transfer entropy developed so far rely on approximations, which significantly limits their accuracy and reliability.

Researchers at AMOLF, a institute in the Netherlands, recently developed a computational algorithm that can precisely quantify transfer entropy in a wide range of complex networks. Their algorithm, introduced in a paper published in Physical Review Letters, opens new exciting possibilities for the study of information transfer in both biological and engineered networks.

These Tiny Robots Can Swarm, Adapt, and Heal Themselves

Scientists designed microrobots that use sound to swarm, adapt, and heal themselves — working together like a living organism. The discovery could transform medicine, environmental cleanup, and robotics.

Nature’s Blueprint for Robot Swarms

Animals such as bats, whales, and insects have long relied on sound to communicate and find their way. Drawing inspiration from this, an international group of scientists has developed a model for tiny robots that use sound waves to move and work together in large, coordinated swarms that behave almost intelligently. According to team leader Igor Aronson, Huck Chair Professor of Biomedical Engineering, Chemistry, and Mathematics at Penn State, these robotic collectives could eventually take on challenging missions like exploring disaster areas, cleaning polluted environments, or performing medical procedures inside the human body.

Engineered “natural killer” cells could help fight cancer

The researchers tested these CAR-NK cells in mice with a human-like immune system. These mice were also injected with lymphoma cells.

Mice that received CAR-NK cells with the new construct maintained the NK cell population for at least three weeks, and the NK cells were able to nearly eliminate cancer in those mice. In mice that received either NK cells with no genetic modifications or NK cells with only the CAR gene, the host immune cells attacked the donor NK cells. In these mice, the NK cells died out within two weeks, and the cancer spread unchecked.

The researchers also found that these engineered CAR-NK cells were much less likely to induce cytokine release syndrome — a common side effect of immunotherapy treatments, which can cause life-threatening complications.

Fundamental engineering principles can help identify disease biomarkers more quickly

People often compare the genome to a computer’s program, with the cell using its genetic code to process environmental inputs and produce appropriate responses.

But the machine metaphor can be extended even further to any , and applying established concepts of engineering to biology could revolutionize how scientists make their observations within biology, according to research from University of Michigan.

In a paper published in Proceedings of the National Academy of Sciences, Indika Rajapakse, Ph.D., Joshua Pickard, Ph.D. (now an Eric and Wendy Schmidt Postdoctoral Fellow at the Broad Institute), and their team propose that fundamental principles of and observability can be applied to study that change over time.

Dr. Aliza Apple, Ph.D. — VP, Catalyze360 AI/ML and Global Head, Lilly TuneLab, Eli Lilly

Accelerating Promising Biotech Innovation — Dr. Aliza Apple, Ph.D. — Vice President, Catalyze360 AI/ML and Global Head, Lilly TuneLab, Eli Lilly and Company.

Dr. Aliza Apple, Ph.D. is a Vice President of Catalyze360 AI (https://www.lilly.com/science/partners/catalyze-360 and Global Head of Lilly TuneLab (https://tunelab.lilly.com/) at Eli Lilly where she leads the strategy, build and launch of Lilly’s external-facing AI/ML efforts for drug discovery.

Lilly Catalyze360 represents a comprehensive approach to enabling the early-stage biotech ecosystem, agnostic of the therapeutic area, designed to accelerate emerging and promising science, strategically removing barriers to support biotech innovation.

In her previous role at Lilly, Dr. Apple served as the COO and head of Lilly Gateway Labs West Coast, where she supported the local biotech ecosystem through early engagement and providing tailored offerings to meet their needs.

Prior to Lilly, Dr. Apple served as a co-founder at Santa Ana Bio, a venture-backed precision biologics company focused on autoimmune disease, and as an advisor to the founders of Firefly Biologics.

Continue reading “Dr. Aliza Apple, Ph.D. — VP, Catalyze360 AI/ML and Global Head, Lilly TuneLab, Eli Lilly” | >

“The Embodied Mind of a New Robot Scientist” by Michael Levin

This is a ~58 minute talk titled “The Embodied Mind of a New Robot Scientist: symmetries between AI and bioengineering the agential material of life and their impact on technology and on our future” which I gave as a closing Keynote to the ALIFE conference in Japan (https://2025.alife.org/). This is a different talk than any I’ve done before, in that besides going over the remarkable capacities of living material, I discuss 1) the symmetries between how all agents navigate their world and how science discoveries are made, and 2) a new robot scientist platform that we have created. With respect to the latter, I discuss how the body and mind of this new embodied AI can serve as a translation and integration layer between human scientists and living matter such as the cells which make up Xenobots.

Generative AI Designs Synthetic Gene Editing Proteins Better than Nature

Researchers from Integra Therapeutics, in partnership with the Pompeu Fabra University (UPF) and the Centre for Genomic Regulation (CRG), Spain, have used generative AI to design synthetic proteins that outperform naturally occurring proteins used for editing the human genome. Their use of generative AI focused on PiggyBac transposases, naturally occurring enzymes that have long been used for gene delivery and genetic engineering, and uncovered more than 13,000 previously unidentified PiggyBac sequences. The research, published in Nature Biotechnology, has the potential to improve current gene editing tools for the creation of CAR T and gene therapies.

“Our work expands the phylogenetic tree of PiggyBac transposons by two orders of magnitude, unveiling a previously unexplored diversity within this family of mobile genetic elements,” the researchers wrote.

For their work, the researchers first conducted extensive computational bioprospecting, screening more than 31,000 eukaryotic genomes to uncover the 13,000 new sequences. From this number, the team was able to validate 10 active transposases, two of which showed similar activity to PiggyBac transposases currently used in both research and clinical settings.

Scientists reverse Alzheimer’s in mice using nanoparticles

A research team co-led by the Institute for Bioengineering of Catalonia (IBEC) and West China Hospital Sichuan University (WCHSU), working with partners in the UK, has demonstrated a nanotechnology strategy that reverses Alzheimer’s disease in mice.

Unlike traditional nanomedicine, which relies on nanoparticles as carriers for therapeutic molecules, this approach employs nanoparticles that are bioactive in their own right: “supramolecular drugs.” The work has been published in Signal Transduction and Targeted Therapy.

Instead of targeting neurons directly, the therapy restores the proper function of the blood-brain barrier (BBB), the vascular gatekeeper that regulates the brain’s environment. By repairing this critical interface, the researchers achieved a reversal of Alzheimer’s pathology in animal models.

Fat particles could be key to treating metabolic brain disorders

Evidence challenging the long-held assumption that neuronal function in the brain is solely powered by sugars has given researchers new hope of treating debilitating brain disorders. A University of Queensland study led by Dr. Merja Joensuu and published in Nature Metabolism showed that neurons also use fats for fuel as they fire off the signals for human thought and movement.

“For decades, it was widely accepted that relied exclusively on glucose to fuel their functions in the brain,” Dr. Joensuu said. “But our research shows fats are undoubtedly a crucial part of the neuron’s in the brain and could be a key to repairing and restoring function when it breaks down.”

Dr. Joensuu from the Australian Institute for Bioengineering and Nanotechnology along with lab members Ph.D. candidate Nyakuoy Yak and Dr. Saber Abd Elkader from UQ’s Queensland Brain Institute set out to examine the relationship of a particular gene (DDHD2) to hereditary spastic paraplegia 54 (HSP54).

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