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Tag: Biology

  • An Artificial Neuron Mimics Real Ones Using Electronics and Biology

    An Artificial Neuron Mimics Real Ones Using Electronics and Biology

    Scientists have developed an artificial neuron that closely replicates the behavior of real ones — it fires, learns, and reacts to chemical signals — marking a breakthrough that could revolutionize computing, medicine, and the integration of technology with biology.
    Scientists have created an artificial neuron that is a huge leap forward in bioelectronics
    Image Credits: Depositphotos

    Scientists have developed an artificial neuron that closely replicates the behavior of real ones — it fires, learns, and reacts to chemical signals — marking a breakthrough that could revolutionize computing, medicine, and the integration of technology with biology.

    Neurons are remarkable biological components that drive complex functions like thinking, feeling, and moving by transmitting electrical and chemical signals across vast networks. It’s no surprise that scientists are eager to replicate these efficient and powerful cells.

    Now, engineers at the University of Massachusetts (UMass) Amherst have developed an artificial neuron that not only imitates the behavior of real neurons but also matches them in size, energy efficiency, signal strength, timing, and responsiveness to chemical cues.

    “Our brain handles massive amounts of data,” said Shuai Fu, lead author of the study and a graduate student in electrical and computer engineering at UMass Amherst. “Yet it uses remarkably little power — especially when compared to the energy demands of systems like ChatGPT.”

    Building a Low-Power, Bio-Inspired Neuron with Protein Nanowires

    The researchers designed their artificial neuron using a special type of memristor—a memory resistor—constructed with protein nanowires derived from the microbe Geobacter sulfurreducens. This bacterium naturally produces conductive nanowires, which, when used in the memristor, significantly lower the voltage needed for switching. As a result, the device operates at very low voltages (around 60 mV) and tiny currents (approximately 1.7 nA), closely matching the performance of real biological neurons.

    “Earlier artificial neurons required 10 times more voltage and 100 times more power than ours,” said Jun Yao, PhD, associate professor of electrical and computer engineering at UMass Amherst and the study’s senior author. “Our version uses just 0.1 volts — similar to the voltage used by actual neurons in the body.”

    To mimic the electrical behavior of real neurons, the team incorporated the memristor into a simple resistor-capacitor (RC) circuit. This setup allowed the artificial neuron to replicate key phases of neural activity: the gradual charge buildup before firing (integration), the sharp spike during firing (depolarization), the return to resting state (repolarization), and the refractory period—a brief pause before the next spike—just like its biological counterpart.

    Diagrams showing connecting the artificial neuron to a heart muscle cell, the sensing signals it recorded, and the neuron firing in response
    Shuai Fu et al. (2025)

    Bridging Biology and Electronics

    The researchers next incorporated chemical sensors capable of detecting ions like sodium and neurotransmitters such as dopamine. These sensors altered the circuit’s electrical behavior in response to chemical cues, effectively mimicking neuromodulation—the way real neurons adapt their activity based on chemical signals in their environment.

    To test real-world compatibility, the team connected the artificial neuron to live, beating human heart cells (cardiomyocytes). They showed that the neuron could interpret biological signals in real time, including detecting how the heart cells responded to the drug norepinephrine—an important step toward integrating artificial neurons directly with living tissue.

    “We already have wearable electronics that monitor the body, but they tend to be bulky and inefficient,” said Jun Yao. “They require electrical amplification just to analyze body signals, which adds complexity and drains power. Our low-voltage neurons, by contrast, can sense these signals directly—without any amplification.”

    Of course, this is still an early-stage prototype, and the experiments were performed under controlled lab conditions. The system isn’t yet ready for use inside living organisms. Still, the breakthrough marks a significant step forward in bioelectronics, potentially laying the groundwork for future technologies that seamlessly integrate electronics with biology.

    In the future, these artificial neurons could help repair or replace damaged brain circuits, enhance brain-machine interfaces (BMIs), or act as real-time sensors to monitor cell health and drug responses. Thanks to their low energy consumption and compatibility with biological signal levels, they also hold promise for enabling more efficient, brain-inspired computing systems.

    Read the original article on: New Atlas

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  • Revealing the Biology of Insulin Production

    Revealing the Biology of Insulin Production

    Credit: iStock.

    The finding of insulin has been a life-saving breakthrough for countless individuals suffering from diabetes worldwide, yet there remains limited knowledge about the initial stages of insulin production.

    However, university of Michigan researchers have made progress in understanding a crucial aspect of insulin production. By examining messenger RNAs involved in insulin synthesis in fruit flies, they identified a chemical tag on the mRNA that plays a vital role in translating it into insulin protein. Altering this tag can impact the quantity of insulin produced.

    The study, conducted by Daniel Wilinski and Monica Dus, was published in the journal Nature Structural and Molecular Biology.

    Messenger RNAs and Their Decorative Tags

    Genes in an organism’s cells contain information that is transcribed into proteins through messenger RNAs. These RNAs act as photocopies of DNA and carry protein information to the cell’s cytoplasm, where protein synthesis occurs. The RNAs are decorated with small molecules called “tags,” which can influence RNA function and protein production.

    In fact, the researchers found fruit flies to be an excellent model for studying insulin production, as their insulin cells are located in their brains and are easily accessible. They focused on a specific tag called RNA N-6 adenosine methylation, or m6A.

    Experimental Approaches and Insights

    To investigate the m6A tag, the researchers first identified which RNAs had the tag. They then labeled insulin cells with a fluorescent molecule and used microscopy to observe insulin production under two conditions: when the m6A enzyme responsible for tagging the mRNA was knocked out, and when the m6A tags were removed using CRISPR.

    In both cases, the flies’ ability to produce insulin was significantly reduced. This finding indicates that the presence of the m6A tag is essential for efficient insulin production. The researchers also noted that this tag is conserved in various species, including fish, mice, and humans, suggesting a similar regulatory mechanism for insulin production in humans.

    Implications for Obesity and Diabetes Management

    Given the rising obesity and diabetes epidemic worldwide, the discovery of this regulatory mechanism holds promise for understanding and addressing these metabolic diseases. Low levels of such chemical tags have been observed in people with type 2 diabetes, indicating potential avenues for therapeutic interventions.

    ”The study provides valuable insights into the molecular biology of insulin and its regulation, shedding light on aspects that still require further exploration. However, by understanding insulin better, researchers hope to pave the way for more effective treatments and strategies to combat diabetes and related metabolic conditions”.

    Read the original article on Phys.

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