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Category: biological – Page 27

With their slender tails, human sperm propel themselves through viscous fluids, seemingly in defiance of Newton’s third law of motion, according to a recent study that characterizes the motion of these sex cells and single-celled algae.

Kenta Ishimoto, a mathematical scientist at Kyoto University, and colleagues investigated these non-reciprocal interactions in sperm and other microscopic biological swimmers, to figure out how they slither through substances that should, in theory, resist their movement.

When Newton conceived his now-famed laws of motion in 1686, he sought to explain the relationship between a physical object and the forces acting upon it with a few neat principles that, it turns out, don’t necessarily apply to microscopic cells wriggling through sticky fluids.

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Scientists are designing simplified biological systems, aiming to construct synthetic cells and better understand life’s mechanisms.

One of the most fundamental questions in science is how lifeless molecules can come together to form a living cell. Bert Poolman, Professor of Biochemistry at the University of Groningen, has been working to solve this problem for two decades. He aims to understand life by trying to reconstruct it; he is building simplified artificial versions of biological systems that can be used as components for a synthetic cell.

His work was detailed in two new papers published in Nature Nanotechnology and Nature Communications. In the first paper, he describes a system for energy conversion and cross-feeding of products of this reaction between synthetic cells, while he describes a system for concentrating and converting nutrients in cells in the second paper.

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The discovery of the quantum tunneling (QT) effect—the transmission of particles through a high potential barrier—was one of the most impressive achievements of quantum mechanics made in the 1920s. Responding to the contemporary challenges, I introduce a deep neural network (DNN) architecture that processes information using the effect of QT. I demonstrate the ability of QT-DNN to recognize optical illusions like a human. Tasking QT-DNN to simulate human perception of the Necker cube and Rubin’s vase, I provide arguments in favor of the superiority of QT-based activation functions over the activation functions optimized for modern applications in machine vision, also showing that, at the fundamental level, QT-DNN is closely related to biology-inspired DNNs and models based on the principles of quantum information processing.

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Mirroring the mechanisms that make human faces and bodies—and those of many multicellular organisms—symmetrical, bee colonies build symmetrical nests when they are placed on either side of a double-sided comb. The finding, published in Current Biology, extends examples of symmetry in biology to the behavior of communities and the architectural structures that they build.

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Wetware computing and organoid intelligence is an emerging research field at the intersection of electrophysiology and artificial intelligence. The core concept involves using living neurons to perform computations, similar to how Artificial Neural Networks (ANNs) are used today. However, unlike ANNs, where updating digital tensors (weights) can instantly modify network responses, entirely new methods must be developed for neural networks using biological neurons. Discovering these methods is challenging and requires a system capable of conducting numerous experiments, ideally accessible to researchers worldwide. For this reason, we developed a hardware and software system that allows for electrophysiological experiments on an unmatched scale. The Neuroplatform enables researchers to run experiments on neural organoids with a lifetime of even more than 100 days. To do so, we streamlined the experimental process to quickly produce new organoids, monitor action potentials 24/7, and provide electrical stimulations. We also designed a microfluidic system that allows for fully automated medium flow and change, thus reducing the disruptions by physical interventions in the incubator and ensuring stable environmental conditions. Over the past three years, the Neuroplatform was utilized with over 1,000 brain organoids, enabling the collection of more than 18 terabytes of data. A dedicated Application Programming Interface (API) has been developed to conduct remote research directly via our Python library or using interactive compute such as Jupyter Notebooks. In addition to electrophysiological operations, our API also controls pumps, digital cameras and UV lights for molecule uncaging. This allows for the execution of complex 24/7 experiments, including closed-loop strategies and processing using the latest deep learning or reinforcement learning libraries. Furthermore, the infrastructure supports entirely remote use. Currently in 2024, the system is freely available for research purposes, and numerous research groups have begun using it for their experiments. This article outlines the system’s architecture and provides specific examples of experiments and results.

The recent rise in wetware computing and consequently, artificial biological neural networks (BNNs), comes at a time when Artificial Neural Networks (ANNs) are more sophisticated than ever.

The latest generation of Large Language Models (LLMs), such as Meta’s Llama 2 or OpenAI’s GPT-4, fundamentally rely on ANNs.

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Between 1.8 billion and 800 million years ago, earthly life was in the doldrums. During this period, called the “boring billion,” the complexity of life remained minimal, dominated by single-celled organisms with only sporadic ventures into multicellular forms. This era set the stage for the later emergence of complex multicellular life, marking a key chapter in evolutionary history.

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The researchers’ recently published study describes a way to re-activate apoptosis in mutated cells, which would amount to forcing cancer to self-destruct through a bioengineered, bonding molecule.

Gerald Crabtree, one of the study’s authors and a professor of development biology, said he had the idea while hiking through Kings Mountain, California, during the pandemic period. The new compound would have to bind two proteins which already exist in the cancerous cells, turning apoptosis back on and making the cancer kill itself.

“We essentially want to have the same kind of specificity that can eliminate 60 billion cells with no bystanders,” Crabtree said, so that no cell gets destroyed if it isn’t the proper target of this new killing mechanism. The two proteins in question are known as BCL6, an oncogene which suppresses apoptosis-promoting genes in the B-cell lymphoma, and CDK9, an enzyme that catalyzes gene activation instead.

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On this episode, neuroscientist and author Robert Sapolsky joins Nate to discuss the structure of the human brain and its implication on behavior and our ability to change. Dr. Sapolsky also unpacks how the innate quality of a biological organism shaped by evolution and the surrounding environment — meaning all animals, including humans — leads him to believe that there is no such thing as free will, at least how we think about it today. How do our past and present hormone levels, hunger, stress, and more affect the way we make decisions? What implications does this have in a future headed towards lower energy and resource availability? How can our species manage the mismatch of our evolutionary biology with our modern day challenges — and navigate through a ‘determined’ future?

About Robert Sapolsky:

Robert Sapolsky is professor of biology and neurology at Stanford University and a research associate with the Institute of Primate Research at the National Museum of Kenya. Over the past thirty years, he has divided his time between the lab, where he studies how stress hormones can damage the brain, and in East Africa, where he studies the impact of chronic stress on the health of baboons. Sapolsky is author of several books, including Why Zebras Don’t Get Ulcers, A Primate’s Memoir, Behave: The Biology of Humans at Our Best and Worst, and his newest book coming out in October, Determined: Life Without Free Will. He lives with his family in San Francisco.

For Show Notes and More visit: https://www.thegreatsimplification.co…

00:00 — Episode highlight.
00:15 — Guest introduction.
03:10 — When did Robert know he wanted to study animal behavior?
04:40 — When was his last research trip?
05:46 — Challenges that come from differences from modern and ancestral environments.
07:20 — Physiology and our emotions.
09:37 — Divide in evolutionary beliefs.
12:13 — Behavioral science and religion.
14:40 — Past students’ impacted by Robert.
16:48 — Testosterone.
21:07 — Dopamine.
29:02 — Oxytocin.
32:19 — Hormones affecting social behavior.
38:21 — Changing the environmental stimuli of pregnant people to positively impact fetus’ development.
41:55 — Free will.
57:24 — Science of attractiveness.
58:55 — Do people have free will?
1:13:12 — Emergence.
1:18:17 — Quantum and indeterminacy.
1:19:18 — Complexity of free will.
1:23:46 — Difference between free will and agency.
1:26:43 — How to use Robert’s work to change policies around the world in a positive way.
1:29:15 — What’s the difference between a deterministic world and a fatalistic one?
1:34:39 — Robert’s thoughts on his newest book, Determined: Life Without Free Will.
1:40:48 — Key components in a new systems society understanding this science.
1:45:30 — What should listeners take away from this podcast?
1:47:32 — Robert’s recommendations for the polycrisis.
1:52:20 — What Robert cares most about in the world.
1:53:00 — Robert’s magic wand.
1:54:36 — Future topics of conversations.

#natehagens #thegreatsimplification #neuroscience #dopamine #freewill #testosterone

Continue reading “Robert Sapolsky: “The Brain, Determinism, and Cultural Implications” | The Great Simplification #88” | >