Introduction: Engineering with Agential Materials

• Biomedicine and bioengineering problems often boil down to controlling morphogenesis (cellular decision-making).
• This control won’t be solved solely by hardware approaches (genomics). Biology uses a multi-scale competency architecture of nested problem solvers.
• Evolution exploits a bioelectrical interface, which cells use to shape behavior and maintain structures.
• We can read/write memories into the physiological layer of control, impacting birth defects, regeneration, cancer, and synthetic bioengineering. Focus of this particular is with “Engineering agential materials.” where behavior and congnitve tools can exploit this behaviour.
• The endgame is an “anatomical compiler”: specifying a desired organism/organ at the anatomical level, and the system translates this into stimuli to build it.
• This isn’t about micromanaging cell positions, but communicating goals to cell collectives.

Biology’s Unique Approach to Building: Agential Materials

• Biology uses “agential materials”—materials with an agenda/own goals—not just passive, active, or computational materials.
• *Example*: Single-celled Lacrymaria show how complex behaviours even single cells are capable of.
• We transition from chemistry-based systems to systems amenable to high-level descriptions (behavioral science, psychoanalysis) during development.
• Biology operates in “multiscale competency.” that isn’t based on *only* nested doll structural ideas of building blocks, but a *functional* one. Each layers solve their own problems.
• Engineered constructs are far behind biological systems in terms of adaptability, robustness, and plasticity.
• Example of Plasticity: caterpillar-butterfly: how stored memory adapts with the biological hardware, even when the structure “largely dissolves”.
• Example #2 of plasticity: Train a flatworm, chop it up, grows new brain. When that happens, information and “memory” comes back.
• Example #3, even when eyes aren’t originally planned by the “blueprints,” this tadpole’s biological hardware adapts regardless.

Beyond 3D Space: Expanding Our View of Intelligence

• We must widen our understanding of “problem spaces” beyond 3D. Intelligence exists in gene expression, physiological states, and anatomical states.
• Anatomical space: Cells navigate the space of all possible configurations to create the body’s structure.
• It’s tempting to attribute fully to the “blueprint” of the genome. But this cannot be. There exists the important intermediate step: developmental physiology

The Challenges of Understanding Morphogenesis

• Genome primarily encodes *nanoscale* hardware (protein sequences), cells then use developmental physiology for construction, meaning a blueprint from just genes isnt really that helpful and simple.
• We need to understand how cell groups know *what* to build and *when* to stop, how to convince them to repair/rebuild. We want to know their inherent plasticity limits.
• Current biosciences are good at manipulating molecules/cells but lack large-scale form/function control. Like old days of computing, too hardware-centric
• Analogy to early computing: We need to move beyond “rewiring the hardware” (molecular manipulation) to higher-level control via “software” (information processing, decision-making).
• Intelligence (William James definition): ability to reach the same goal by different means. Not about brain size, natural/engineered origins, but about *competency* levels.
• This aligns with goal-directedness ideas of congnition.

Anatomical Homeostasis: Evidence for Morphogenetic Intelligence

• Developmental self-assembly isn’t just about increasing complexity, but *adaptive* problem-solving, aka homeostasis.
• Embryo splitting: Doesn’t create half-bodies, but whole organisms from various starting points. This suggests it isn’t a feedforward problem-solving structure.
• Regeneration (axolotl example): Regeneration stops *when the correct structure is achieved*, implying an error-reduction scheme (anatomical homeostasis).
• This *how* applies to other examples: Childrens fingers, newt kidney.
• Adaptation to altered cellular parameters (newt kidney tubule): Cells adjust size/number, use different molecular mechanisms to maintain overall structure, showing flexibility.
• *Important:* You cannot make assumption on priors of organisms when “engineering,” e.g. you cannot rely on certain number of chromosomes. It has to work. The enginnering paradigm has changed.
• Response to disrupted morphology (tadpole face rearrangement): Organs move along *novel paths* to achieve the correct arrangement, challenging the “hardwired” development idea.
• Implying*What evolution produces* aren’t merely specific solutions to problems but also machines capable of problems solving in various spaces (anatomical, physiological, chemical, behavioral).
• In other words, Evolution produces problem solving agents, which use a feedback scheme (pattern homestasis) that responds to injuries, errors, problems (set of feeback loops) which attempts to “reach” the normal final form, as seen before.

Bioelectricity: The Morphogenetic Memory

• Prediction based on previous points: There exists a literal recoreded explicit memory set.
• Analogy to neural networks: Cells store memories and communicate via electrical signals (ion channels, gap junctions), similar to brains.
• Can we decode somatic electrical networks, as neuroscience does for neural networks, and see how information moves *through* anatomical space (Not just 3D space) ? All cells have this bioelectrical infrastructure.
• Tools: Voltage-sensitive dyes to visualize electrical patterns, computer simulations, manipulation of ion channels/gap junctions (optogenetics, drugs) – no external fields/radiation, but manipulation of the cell’s natural interface.
• Goal:* treat morphogensis as behaviour (of cell collectives) where cells, collective, navigate morphospace in anatomical space.
• “Electric face”: Early embryos show a pre-pattern of future facial features in their bioelectrical activity, *before* anatomical structures develop, but is also “causal,” manipulating bioelectricity impacts and disrupts anatomy.
• Pathological Pattern: Examples is: Inject a tumor, oncogenese and so on will create metastasis but these patterns *show earlier* than anatomy, where the tumor breaks free. implies we can measure patterns with “tools” from bioelctricity earlier, potentially diagnosing disease much faster and earlier.
• Can you change, insert “eyes” into tissues and spaces. Answer: Yes:

Reprogramming Morphogenesis with Bioelectricity: Case 1 – Tadpoles

• Ectopic eye induction: Inducing eyes in the *gut* region of tadpoles by manipulating voltage patterns. These eyes have *all correct biological structure*. It even reucrits neighbour cells, *implying instruction.*
• This is a *modular, high-level trigger*: We provide a simple pattern, and cells handle the complexity of eye construction, much like a high-level subroutine.
• A frog bioregenerator coctail triggers the regrowth of legs and toes and muscles.
• It is also “functional” – tadpole limbs respond to light/touch.

Reprogramming Morphogenesis with Bioelectricity: Case 2 – Planaria

• Planaria: Amazing regenerative capacity. Each fragment “knows” what a complete planarian should look like, as holographic in structure. They are effectively immortal as well (can ask). Also how can a fragmnet know how many heads there should be, in fact, the correct numbr should be (hint: there are other forms of bioelectrical patterns, there must be a form/circuit pattern to describe it):
• Head number control: An electrical circuit determines head number. We can *rewrite* this circuit (with ion channel drugs) to create two-headed worms.
• Crucially, the electrical map is not of the two-headed worm, but of the *normal*, one-headed form. It represents the *set point* for anatomical homeostasis.
• Similar: it can make the heads of *other species.* (Different by “100 and 15 million years,” even! But these differences aren’t genetic, so there is not issue!) And even: crazier “shapes.”
• The memory in Planaria shows all properties of memory.
• Latent Morphospace: Can trigger *other shapes*, with their appropriate “shapes,” cells/other, different by large changes of million of year diffences between animals, yet done without “genetics,” only by “guiding” morphogenetic bioelctric networls: These structures can “exsit” in morphospace!
• It can make shapes never even made or considered! These spaces and shape changes exist! The idea “morphogenetic fields are limted is not only incorrect,” these latent shape/morphgenetic structures are likely numerous. Another example: galls on tree/plant “hacked” by wasps that completely changes the morphology (even the genome isn’t different, yet structure change).

Implications, Connections, and Clinical Applications

• We must move from controlling at *low levels* and moving toward high levels using tools of analysis of biolectrical pattern of a “competent material” which can exploit intelligence to move and act.
• Bioelectricity provides an entry point to control these goals, including in clinical settings.
• Cancer as a failure mode of “goal constriction”: Disconnected cells revert to smaller, unicellular-scale goals, resulting in proliferation. But by enforcing electrical connectivity (even with a strong oncogene present), we can “force” cooperation toward normal tissue construction.

Xenobots: Uncovering Hidden Potential

• Synthetic bioengineering (Xenobots): Isolated frog skin cells self-assemble into novel organisms (xenobots) with unique behaviors (movement, kinematic self-replication). Shows there is potential “other structures” in different combinations of existing cells and how they organize.
• Engineering *by subtraction*, freeing these *existing frog* cells allow them to self-form, moving past their initial roles and instructions of “building blocks.” They can row, move, and they are “super interesting”!
• Shows other properties as expected of “smart agent”: can even “heal itself”. and ” kinematic self replication: fulfills “von nuemans” dream.
• *Example of new “smart form/material:” * Anthrobots are a *human form* made from only normal tracial cells, showing, the inherent multiceullar property/abilities for them to organize, grow, structure, and make changes! These aren’t even frog or “new/unknown” cells! When applied onto another damage site of neurons, shows they *themselves, apply change* implying that existing cells are already already well positioned to engage on tissue engineering/damage when we change these “bioelectrical, instructions.”
• Evolutionary backstrory – these changes can exist:

Conclusion: Embracing the Agential Nature of Living Material

• Cells/tissues possess numerous competencies. Our job is to understand/program them, leveraging their inherent intelligence. We are at the *earily days*.
• “endless forms most beautiful,” “exploring” are ideas to use when combining engineering design to biology.
• Crispr, synthetic biology, and biorobotics can be unlocked by understanding the “intelligent, agential nature” of the material, moving beyond molecular control.
• Bioelctricity, top down congtrol over shape space and its innate potential is a way. We can control over the various properties of cells by analyzing it like cogntive agents: competencies, goals. Tools include: voltage analysis, AI tools.

引言：利用具能动性的材料进行工程设计

• 生物医学和生物工程问题通常归结为控制形态发生（细胞决策）。
• 这种控制不仅仅依靠硬件方法（基因组学）就能解决。生物学采用的是一种嵌套了问题解决者的多尺度能力架构。
• 进化利用了生物电界面，细胞利用它来塑造行为和维持结构。
• 我们可以读取/写入记忆到生理控制层，影响出生缺陷、再生、癌症和合成生物工程。 本次特别关注的是“工程能动材料”，其中的行为和认知工具可以利用这种行为。
• 最终目标是一个“解剖编译器”：在解剖层面上指定所需的生物体/器官，系统将其转化为刺激以构建它。
• 这并不是关于微观管理细胞位置，而是将目标传达给细胞群体。

生物学独特的构建方法：能动材料

• 生物学使用“能动材料”——具有议程/自身目标的材料——而不仅仅是被动、主动或计算材料。
• *例子*：单细胞喇叭虫 (Lacrymaria) 展示了即使是单细胞也能够完成多么复杂的行为。
• 我们在发育过程中从基于化学的系统过渡到适合高级描述（行为科学、精神分析）的系统。
• 生物学在“多尺度能力”中运作。这种能力不*仅仅*是基于嵌套玩偶的构建块结构思想, 而是一个 *功能的* 能力. 每个层次解决它们自己的问题.
• 工程构造在适应性、鲁棒性和可塑性方面远远落后于生物系统。
• 可塑性示例：毛毛虫-蝴蝶：即使结构“大部分溶解”，存储的记忆如何适应生物硬件。
• 可塑性示例 #2：训练涡虫，切碎它，长出新的大脑。当这种情况发生时，信息和“记忆”会回来。
• 示例 #3，即使眼睛最初不是由“蓝图”规划的，这只蝌蚪的生物硬件也能适应。

超越三维空间：扩展我们的智能观

• 我们必须拓宽我们对“问题空间”的理解，使其超越三维。 智能存在于基因表达、生理状态和解剖状态中。
• 解剖空间：细胞导航所有可能构型的空间以创建身体的结构。
• 将全部归因于基因组的“蓝图”是很诱人的。 但这不可能。 存在着重要的中间步骤： 发育生理学

理解形态发生的挑战

• 基因组主要编码*纳米级*硬件（蛋白质序列），细胞随后利用发育生理学进行构建，这意味着仅从基因获得的蓝图并不是那么有用和简单。
• 我们需要了解细胞群如何知道要构建*什么*以及*何时*停止，如何说服它们修复/重建。我们想知道它们固有的可塑性极限。
• 目前的生物科学擅长操纵分子/细胞，但缺乏大规模形式/功能控制。 就像计算的旧时代一样，过于以硬件为中心。
• 与早期计算的类比：我们需要超越“重新布线硬件”（分子操纵），通过“软件”（信息处理、决策）实现更高级别的控制。
• 智能（威廉·詹姆斯的定义）：通过不同手段达到相同目标的能力。与大脑大小、自然/工程起源无关，而是与*能力*水平有关。
• 这符合认知的目标导向思想。

解剖稳态：形态发生智能的证据

• 发育自组装不仅仅是增加复杂性，而是*适应性*问题解决，又名稳态。
• 胚胎分裂：不会产生半个身体，而是从各个起点产生完整的生物体。这表明它不是一个前馈问题解决结构。
• 再生（蝾螈示例）：再生在*达到正确的结构时*停止，这意味着误差减少方案（解剖稳态）。
• 这个*如何*适用于其他示例：儿童手指，蝾螈肾脏。
• 对改变的细胞参数（蝾螈肾小管）的适应：细胞调整大小/数量，使用不同的分子机制来维持整体结构，显示出灵活性。
• *重要提示：*在“工程设计”时，您不能对生物体的先验做出假设，例如，您不能依赖于一定数量的染色体。 它必须有效。 工程范式已经改变。
• 对形态破坏（蝌蚪面部重排）的反应：器官沿着*新路径*移动以实现正确的排列，挑战了“硬连线”发育理念。
• 暗示 *进化产生什么* 不仅仅是问题的具体解决方案，而且也是能够在各种空间（解剖、生理、化学、行为）中解决问题的机器。
• 换句话说，进化产生问题解决主体，它们使用一个反馈方案（模式稳态），对损伤、错误、问题（一组反馈回路）做出反应，试图“达到”正常的最终形式，如前所述。

生物电：形态发生记忆

• 基于前几点的预测：存在一个字面上记录的显式记忆集。
• 类比神经网络：细胞存储记忆并通过电信号（离子通道、间隙连接）进行通信，类似于大脑。
• 我们能像神经科学对神经网络所做的那样，解码体细胞电网络，并观察信息如何*穿过*解剖空间（不仅仅是3D空间）？ 所有细胞都有这种生物电基础设施.
• 工具：电压敏感染料可视化电模式、计算机模拟、操纵离子通道/间隙连接（光遗传学、药物）——没有外部场/辐射，而是操纵细胞的自然界面。
• 目标: 将形态发生视为（细胞群体）的行为，其中细胞集体在解剖空间中的形态空间中导航。
• “电脸”：早期胚胎在其生物电活动中显示出未来面部特征的预模式，在解剖结构发育*之前*， 但也是“因果关系”，操纵生物电会影响和破坏解剖结构。
• 病理模式：例子是：注射肿瘤，致癌基因等将产生转移，但这些模式*比解剖结构更早*显示出来，其中肿瘤脱离。 意味着我们可以更快、更早地用生物电学的“工具”测量模式，潜在地更快、更早地诊断疾病。
• 你能改变、插入“眼睛”到组织和空间中吗？ 答案：是的。

用生物电重编程形态发生：案例 1 – 蝌蚪

• 异位眼诱导：通过操纵电压模式在蝌蚪的*肠道*区域诱导眼睛。 这些眼睛具有*所有正确的生物结构*。它甚至会招募相邻的细胞，*暗示指令*。
• 这是一个 *模块化、高级的触发器*: 我们提供一个简单的模式, 细胞处理眼睛构造的复杂性, 很像一个高级子程序.
• 青蛙生物再生剂混合物触发腿、脚趾和肌肉的再生。
• 它也是“功能性的”——蝌蚪的四肢对光/触摸有反应。

用生物电重编程形态发生：案例 2 – 涡虫

• 涡虫：惊人的再生能力。每个碎片都“知道”完整的涡虫应该是什么样子，如结构中的全息图。它们实际上也是不朽的（可以问）。 而且，一个片段怎么知道应该有多少个头，事实上，正确的数字应该是（提示：还有其他形式的生物电模式，必须有一种形式/电路模式来描述它）：
• 头部数量控制：一个电路决定头部数量。我们可以用离子通道药物*重写*这个电路来制造双头蠕虫。
• 关键的是，电图不是双头蠕虫的图，而是*正常*、单头形式的图。它代表了解剖稳态的*设定点*。
• 类似地：它可以制造*其他物种*的头部。（差异“100 到 1500 万年”，甚至！但这些差异不是遗传的，所以没有问题！） 甚至：更疯狂的“形状”。
• 涡虫中的记忆显示了记忆的所有属性。
• 潜形态空间：可以触发具有其适当的”形状”, 细胞和其他的不同， 在不同的百万年变化的差异的大变之间通过仅通过生物电学*引导”进行操纵, “基因,” 就可以进行触发: 这些机构可以”存在于形态空间”!
• 它可以形成前所未有，甚至从未被思考过的图形.这些空间形状改变*存在*！ “形态发生学区域被限制不但是不正确的。” 这些潜在性的形态或者模型架构都是更*无数* 另一个例子: 树上的树瘿/植物”被黑客”攻击后的蜂虫将会全面性形态变化 (即使在基因*没有*不同,结构还是*变了*)

影响、联系和临床应用

• 我们必须从*低层次*的控制转向利用“能动材料”的生物电模式分析工具进行高层次控制，这种材料可以利用智能移动和行动。
• 生物电为控制这些目标提供了一个入口点, 包括在临床设置中.
• 癌症作为“目标收缩”的失效模式：断开连接的细胞恢复到更小的、单细胞尺度的目标, 导致增殖。 但通过加强电连接性 (即使存在强致癌基因), 我们可以 “强迫” 合作进行正常组织建设.

异种机器人：揭示隐藏的潜力

• 合成生物工程 (异种机器人)：分离的青蛙皮肤细胞自组装成具有独特行为 (运动、运动学自我复制) 的新型生物体 (异种机器人)。 表明在现有细胞的不同组合及其组织方式中存在潜在的“其他结构”。
• 通过*减法*进行工程设计, 释放这些*现有的青蛙* 细胞允许他们自行形成, 移动 past 他们最初的角色和“构建块”的指令。 他们可以划、移动, 而且他们 “超级有趣”!
• 显示“智能主体”预期的其他属性：甚至可以“自我修复”。 和“运动学自我复制：实现“冯诺伊曼”的梦想。
• *新的“智能形式/材料”示例：* Anthrobots 是一种*人类形式*, 仅由正常的气管细胞制成, 表明, 固有的多细胞属性/能力, 让他们组织、生长、结构和进行改变！ 这些甚至不是 甚至不是青蛙或“新/未知”细胞！ 当应用于神经元的另一个损伤部位时，表明它们 *他们自己，应用改变*意味着现有细胞已经 当我们在更改这些”生物电子学指令。”
• 进化 backstrory- 这些改变可以*存在*：

结论：拥抱生物材料的能动性

• 细胞/组织具有多种能力。 我们的工作是理解/编程它们，利用它们固有的智能。 我们在*早期阶段*。
• “无尽的形式最美丽”, “探索” 是结合工程设计与生物学时要使用的想法。
• Crispr、合成生物学和生物机器人技术可以通过理解材料的“智能、能动性质”来解锁，超越分子控制。
• 生物电, 从顶端去操纵对于形态的空间是其中的道路. 我们可以通过分析的特性: competencencies , goals. 其中的用具包括: 分析电压, AI 用具。