What is the Study About?

• This research focuses on creating entirely new biological machines or “living systems” that can perform specific functions, such as moving, carrying objects, or working together as a group.
• Scientists use computer programs (AI) to design these systems by simulating different shapes and behaviors before actually building them with real biological tissues.
• The goal is to make technologies using living systems that can renew themselves and last longer than traditional materials like plastic or metal, which degrade over time.

What Makes Living Systems Different from Traditional Technology?

• Most technology is made from synthetic materials like steel and plastic, which can harm the environment and health over time.
• Living systems are more robust and complex than human-made technology. They can repair and regenerate themselves, which makes them more durable in the long run.
• If we could design and deploy living systems that are continuously adapted to new tasks, they could outlast and outperform our current technologies.

How Are These Living Systems Designed?

• AI uses a method called evolutionary algorithms to design living systems. This process starts with random designs and improves them through trial and error based on how well they perform a task.
• The AI helps discover novel configurations of biological cells that can work together to achieve a desired behavior, like moving or picking things up.
• Once a design is created on the computer, it’s turned into a real biological system by assembling cells in a controlled way.
• These designs are tested virtually before being made with real biological tissues. The designs are simulated in a virtual environment that predicts how they will behave in the real world.

How is the Biological System Built?

• To create these systems, stem cells from frogs (Xenopus laevis) are used. These cells are versatile and can be guided to form different types of tissues, like heart muscle or skin.
• The cells are harvested, shaped, and combined to form the physical structure of the biological machine.
• Contractile tissue, which can move like muscles, is added to the design to make it capable of locomotion.
• The final product is a living organism that can move, explore, and even repair itself in its environment.

What Are the Main Steps in the Pipeline?

• Step 1 – Evolutionary Design: AI generates random designs and tests them in simulations. The best-performing designs are kept, and the process repeats to improve them.
• Step 2 – Robustness Filtering: The designs that survive the random testing (e.g., noise or unexpected conditions) are chosen for further development.
• Step 3 – Build Filter: Designs that are easy to manufacture and scale for larger tasks are selected for construction.
• Step 4 – Construction: Using stem cells, researchers build the organism in real life by assembling tissues in specific ways.
• Step 5 – Testing and Observation: The organism is placed in its environment, and its behavior is observed and compared with the predictions made by the AI simulation.

What Behaviors Were Tested in the Organisms?

• Locomotion: The organisms were designed to move by using contractile tissue (heart muscle) to push against the surface of a dish. The goal was to see how well the organisms could move and how their movement matched the predicted design.
• Object Manipulation: Some organisms were designed to pick up objects in their environment. This was tested by placing objects around the organisms and observing if they gathered them.
• Object Transport: Designs were made to carry objects. The organisms were evaluated to see how well they could transport objects over distances.
• Collective Behavior: Multiple organisms were tested together to see how they interacted and worked as a group, such as moving together or avoiding each other.

Results and Observations:

• The AI-designed organisms performed the tasks as predicted in the simulations. For example, the locomotion behaviors matched the predicted movement patterns.
• When the organisms were tested in real life, some of them moved in the same direction and speed as predicted by the AI design.
• The organisms showed the ability to interact with their environment, like collecting debris or carrying objects.
• In some cases, the organisms also exhibited collective behaviors, like grouping together or moving in sync.

Key Advantages of Living Machines:

• Living systems are capable of self-repair and regeneration, unlike traditional machines made from synthetic materials.
• They can be used for a variety of tasks, such as drug delivery, environmental cleanup, and medical applications.
• These organisms are created from the patient’s own cells, which means they are naturally biocompatible and less likely to cause harm in the body.

Future Implications:

• The methods used in this research could lead to new types of medical treatments, like custom living organisms for drug delivery or even internal surgery.
• These organisms could also help with environmental cleanup by seeking out and breaking down toxic waste or pollutants.
• In the future, this approach could be used to create more complex living systems with new functions and behaviors.

研究的目的是什么？

• 这项研究的重点是创建完全新的生物机器或“生命系统”，这些机器可以执行特定的功能，比如移动、搬运物体或作为一个群体一起工作。
• 科学家们使用计算机程序（AI）设计这些系统，通过模拟不同的形状和行为，在实际构建之前先进行测试。
• 目标是使用活的系统制造技术，这些技术能够自我更新，并且比传统的塑料或金属材料更耐用。

生命系统与传统技术的不同之处？

• 大多数技术是由合成材料如钢铁和塑料制成的，这些材料随时间会对环境和健康产生危害。
• 生命系统比人类制造的技术更强大、更复杂。它们可以自我修复和再生，因此在长期使用中更具耐用性。
• 如果我们能够设计并部署持续适应新任务的生命系统，它们的自我更新能力将使它们超越目前的技术。

这些生命系统是如何设计的？

• AI使用一种称为进化算法的方法来设计生命系统。这个过程从随机设计开始，并通过反复试验改进它们，直到它们完成任务。
• AI帮助发现新的生物细胞配置，这些细胞可以协同工作，执行诸如移动或拾取物体等任务。
• 一旦设计在计算机上完成，它就会通过控制方式将其转化为现实生物系统。
• 这些设计在虚拟环境中进行测试，预测它们在现实世界中的行为。

如何构建这些生物系统？

• 为了构建这些系统，科学家使用来自青蛙（Xenopus laevis）的干细胞。这些细胞具有多能性，可以引导它们形成不同类型的组织，如心肌或皮肤。
• 这些细胞被收集、塑形并结合，形成生物机器的物理结构。
• 通过添加能够像肌肉一样运动的收缩组织，使其能够实现运动。
• 最终的产品是一个可以移动、探索，甚至在它的环境中自我修复的生物体。

管道中的主要步骤是什么？

• 第1步 – 进化设计：AI生成随机设计并在模拟中测试它们。最好的设计被保留，并且通过这个过程不断改进。
• 第2步 – 稳健性筛选：在随机测试（例如噪声或意外条件）下能够保持最佳表现的设计会被选择出来。
• 第3步 – 构建筛选：选择那些容易制造并能够扩展到更复杂任务的设计进行构建。
• 第4步 – 构建：使用干细胞，通过指定的方式将组织组合，创建生物机器。
• 第5步 – 测试和观察：将生物体放入环境中，观察它的行为，并与AI模拟的预测行为进行对比。

在生物体中测试了哪些行为？

• 运动：生物体被设计成通过使用收缩组织（心肌）推压托盘表面来移动。目标是看生物体能否顺利移动，并且它们的运动是否与预期的设计匹配。
• 物体操控：一些生物体被设计成能够拾取环境中的物体。这个目标是通过把物体放在它们的周围，观察它们是否能够收集起来。
• 物体运输：有些设计被做成能够运输物体。测试它们能否将物体搬运到指定的地方。
• 集体行为：多个生物体被放置在同一个环境中，测试它们如何互动并作为一个群体协作。

结果和观察：

• AI设计的生物体在任务中表现得和模拟中预期的一样。例如，运动行为与预期的运动模式匹配。
• 当这些生物体在现实中被测试时，它们中的一些能朝着相同的方向和速度移动，和AI设计的预测一致。
• 这些生物体表现出与环境的互动能力，比如聚集垃圾或搬运物体。
• 在一些情况下，这些生物体还表现出了集体行为，例如一起分组或同步移动。

生命机器的主要优势：

• 生命系统具有自我修复和再生能力，而传统的人工材料做的机器无法做到这一点。
• 这些生命系统可以被用于多种任务，如药物递送、环境清理和医疗应用。
• 这些生物体是用患者自己的细胞构建的，因此它们自然具备生物相容性，较少引起体内的排斥反应。

未来的意义：

• 这项研究中的方法可以导致新的医疗治疗方式，比如定制的生命体用于药物递送或内部手术。
• 这些生物体还可以帮助清理环境中的有毒物质或污染物。
• 未来，这种方法可以用于创建更复杂的生命系统，拥有新的功能和行为。