未来医学展望:多尺度生命形式为生物医学提供新道路
导语
10月2日,2023年诺贝尔生理学或医学奖宣布授予 Katalin Karikó 和Drew Weissman,表彰他们在核苷碱基修饰方面的发现,这些发现帮助开发出有效的 mRNA 疫苗来对抗 COVID-19。mRNA 疫苗被认为是一场药物形式的革命,相关技术疗法具有广阔的应用前景,不仅能对抗传染病,还可以利用 mRNA 技术来定制癌症疫苗。
目前的生物医学方法主要是通过使用 CRISPR、基因治疗、蛋白工程等,改变微观基因产物,自下而上操纵细胞的“硬件”。从根本上而言,人体的复杂性并非直接由基因组指定,生物体以细胞为基本单元,形成各种集体行为,在从细胞到组织、器官、生物体和生态系统的各个层次上都表现出多样性和组织性,生命的“软件”具有模块化、自上而下的控制和多尺度能力等显著特征,使得生命具有强大的适应能力,但同时也为医学理解和医疗医药研发带来巨大的难题。
塔夫茨大学发育与合成生物学教授 Michael Levin 与匹兹堡大学病理学系副教授 Eric Lagasse 近期于 Cell 子刊 Trends in Molecular Medicine 发表综述文章“未来医学展望:从分子通道到集体智能”,指出生命形式的多尺度能力为生物医学提供了一条新的道路,利用组织和器官的固有集体智能。综述尤其突出利用生物电学和行为神经科学的进展,设计诱导结构和功能的自我修复方法,勾勒出通往“身心医学”的路线图。通过放松细胞控制机制是静态的假设,利用控制论、行为科学和发育生物学的强大概念,可能会为当前的生物医学挑战提供明确的解决方案。
研究领域:生命复杂性,生物医学,集体智能,神经科学
Eric Lagasse、Michael Levin | 作者
刘培源 | 译者
论文题目:
Future medicine: from molecular pathways to the collective intelligence of the body
论文地址:https://www.cell.com/trends/molecular-medicine/fulltext/S1471-4914(23)00142-9
目录
八、结论
摘要
摘要
一、21世纪的再生医学:迈向解剖编译器
一、21世纪的再生医学:迈向解剖编译器
图1. 解剖编译器和多尺度能力。(A)人体的复杂性(在此以成年躯干的横截面显示)并非直接由基因组(编码亚细胞硬件-蛋白质)指定,而是由胚胎细胞团的活动产生的。(B)身体通过多尺度能力架构构建,其中每个层次处理信息以解决生理、转录、解剖和行为空间中的问题。(C)构建“解剖编译器”举例,用户能够指定任何解剖形状,并将其转换为一组刺激,必须提供给细胞以指导它们生长这种形状(如此处所示的三头扁虫)。解剖编译器不会是一个3D打印机或用于微观管理基因表达或干细胞命运的设备——实际上它将是一个将用户的解剖目标转换为细胞集体中目标形态信息的重新规范的通信设备。
二、身体智能:
解剖稳态、集体智能和功能需求驱动的修复
二、身体智能:
解剖稳态、集体智能和功能需求驱动的修复
三、“肝稳态”:
细胞智能及其在肝病临床应用中的例证
三、“肝稳态”:
细胞智能及其在肝病临床应用中的例证
图4 以肝细胞为中心的肝脏再生和功能需求视角。在部分肝切除后,肝细胞通过增殖、表型保真和肥大的方式,响应功能需求,恢复肝脏质量。在肝细胞移植到患有肝细胞疾病的肝脏时,健康的肝细胞取代不健康的肝细胞,以恢复肝脏功能。
四、利用身体智慧调节再生:
神经生物学和行为科学指引方向
四、利用身体智慧调节再生:
神经生物学和行为科学指引方向
五、发育生物电:
与局部高级解剖控制系统的操作接口
五、发育生物电:
与局部高级解剖控制系统的操作接口
六、通过利用组织智能
实现变革性再生医学的可能性
六、通过利用组织智能
实现变革性再生医学的可能性
七、身体心智:
迈向作为“身心医学”的生物医学
七、身体心智:
迈向作为“身心医学”的生物医学
八、结论
八、结论
参考文献
1. Bugaj, L.J. et al. (2017) Interrogating cellular perception and de- cision making with optogenetic tools. J. Cell Biol. 216, 25–282. Lobo, D. et al. (2014) A linear-encoding model explains the var- iability of the target morphology in regeneration. J. R. Soc. Inter- face 11, 201309183. Baluška, F. et al. (2022) Cellular sentience as the primary source of biological order and evolution. Biosystems 218, 1046944. Baluška, F. et al. (2022) Cellular and evolutionary perspectives on organismal cognition: from unicellular to multicellular organisms. Biol. J. Linn. Soc. 2022, blac0055. Reber, A.S. and Baluška, F. (2021) Cognition in some surprising places. Biochem. Biophys. Res. Commun. 564, 150–1576. Levin, M. (2023) Collective intelligence of morphogenesis as a teleonomic process. In Evolution 'On Purpose': Teleonomy in Living Systems (Corning, P.A. et al., eds), pp. 175–198, MIT Press7. Csermely, P. et al. (2020) Learning of signaling networks: molecular mechanisms. Trends Biochem. Sci. 45, 284–2948. Antebi, Y.E. et al. (2017) Combinatorial signal perception in the BMP pathway. Cell 170, 1184–11969. Mitchell, A. and Lim, W. (2016) Cellular perception and misperception: internal models for decision-making shaped by evolutionary experience. Bioessays 38, 845–84910. Wilson, M.Z. et al. (2017) Tracing information flow from Erk to target gene induction reveals mechanisms of dynamic and combinatorial control. Mol. Cell 67, 757–76911. Tweedy, L. et al. (2020) Seeing around corners: cells solve mazes and respond at a distance using attractant breakdown. Science 36912. Tweedy, L. and Insall, R.H. (2020) Self-generated gradients yield exceptionally robust steering cues. Front. Cell Dev. Biol. 8, 13313. Levin, M. (2019) The computational boundary of a 'self': developmental bioelectricity drives multicellularity and scale-free cognition. Front. Psychol. 10, 268814. Levin, M. (2022) Technological approach to mind everywhere:an experimentally-grounded framework for understanding diverse bodies and minds. Front. Syst. Neurosci. 16, 76820115. Price, J. and Allen, S. (2004) Exploring the mechanisms regulat- ing regeneration of deer antlers. Philos. Trans. R. Soc. Lond.Ser. B Biol. Sci. 359, 809–82216. Racovita, A. et al. (2022) Engineered gene circuits capable of reinforcement learning allow bacteria to master gameplaying. BioRxiv Published online June 21, 2022. https://doi.org/10. 1101/2022.04.22.48919117. Clawson, W.P. and Levin, M. (2022) Endless forms most beau- tiful 2.0: teleonomy and the bioengineering of chimaeric and synthetic organisms. Biol. J. Linn. Soc. 2022, blac07318. Blackiston, D. et al. (2021) A cellular platform for the develop- ment of synthetic living machines. Science. Robotics 6, eabf157119. Kriegman, S. et al. (2020) A scalable pipeline for designing reconfigurable organisms. Proc. Natl. Acad. Sci. U. S. A. 117, 1853–185920. Kriegman, S. et al. (2021) Kinematic self-replication in reconfigurable organisms. Proc. Natl. Acad. Sci. U. S. A. 11821. Gumuskaya, G. et al. (2023) Motile living biobots self-construct from adult human somatic progenitor seed cells. BioRxiv Pub- lished online February 22, 2023. https://doi.org/10.1101/ 2022.08.04.50270722. Emmons-Bell, M. et al. (2019) Regenerative adaptation to elec- trochemical perturbation in planaria: a molecular analysis of physiological plasticity. iScience 22, 147–16523. Baluška, F. and Levin, M. (2016) On having no head: cognition throughout biological systems. Front. Psychol. 7, 90224. Watson, R.A. et al. (2010) Associative memory in gene regula- tion networks. In Artificial Life XII, Proceedings of the Tenth In- ternational Conference on the Simulation and Synthesis of Living Systems (Fellerman, H. et al., eds), pp. 194–201, MIT Press25. Biswas, S. et al. (2021) Gene regulatory networks exhibit sev- eral kinds of memory: quantification of memory in biological and random transcriptional networks. iScience 24, 10213126. Biswas, S. et al. (2022) Learning in transcriptional network models: computational discovery of pathway-level memory and effective interventions. Int. J. Mol. Sci. 24, 28527. Freddolino, P.L. et al. (2018) Stochastic tuning of gene expres- sion enables cellular adaptation in the absence of pre-existing regulatory circuitry. Elife 7, e3186728. Rubin, H. (2006) What keeps cells in tissues behaving normally in the face of myriad mutations? BioEssays 28, 515–52429. Nagato, T. et al. (1995) Effect of denervation on morphogenesis of the rat fungiform papilla. Acta Anat. (Basel) 153,301–30930. McDowell, G. et al. (2016) From cytoskeletal dynamics to organ asymmetry: a nonlinear, regulative pathway underlies left-right patterning. Philos. Trans. R. Soc. Lond. Ser. B Biol. Sci. 371, 2015040931. Xiao, J. et al. (2020) Epidemiological realities of alcoholic liver disease: global burden, research trends, and therapeutic prom- ise. Gene Expr. 20, 105–11832. Delgado-Coello, B. (2021) Liver regeneration observed across the different classes of vertebrates from an evolutionary per- spective. Heliyon 7, e0644933. Michalopoulos, G.K. (2017) Hepatostat: liver regeneration and normal liver tissue maintenance. Hepatology 65, 1384–139234. Vogel, A. et al. (2004) Chronic liver disease in murine hereditary tyrosinemia type 1 induces resistance to cell death. Hepatology 39, 433–44335. Michalopoulos, G.K. and Bhushan, B. (2021) Liver regenera- tion: biological and pathological mechanisms and implications. Nat. Rev. Gastroenterol. Hepatol. 18, 40–5536. Miyaoka, Y. and Miyajima, A. (2013) To divide or not to divide: revisiting liver regeneration. Cell Div 8, 837. Iansante, V. et al. (2018) Human hepatocyte transplantation for liver disease: current status and future perspectives. Pediatr. Res. 83, 232–24038. Rhim, J.A. et al. (1994) Replacement of diseased mouse liver by hepatic cell transplantation. Science 263, 1149–115239. Nakamura, K. et al. (2007) Animal models of tyrosinemia. J. Nutr. 137, 1556S–1560S40. Faraj, W. et al. (2010) Auxiliary liver transplantation for acute liver failure in children. Ann. Surg. 251, 351–35641. McKiernan, P. (2013) Liver transplantation and cell therapies for inborn errors of metabolism. J. Inherit. Metab. Dis. 36, 675–68042. Shanmugam, N.P. et al. (2011) Auxiliary liver transplantation: a form of gene therapy in selective metabolic disorders. J. Clin. Exp. Hepatol. 1, 118–12043. Rela, M. et al. (1999) Auxiliary partial orthotopic liver transplantation for Crigler–Najjar syndrome type I. Ann. Surg. 229, 565–56944. Burdelski, M. and Rogiers, X. (1999) Liver transplantation in metabolic disorders. Acta Gastroenterol. Belg. 62, 300–30545. Dokmak, S. et al. (2013) Auxiliary liver transplantation with a small deceased liver graft for cirrhotic liver complicated by hepatocellular carcinoma. Transpl. Int. 26, e102–e10446. Ren, W. et al. (2012) Integrating repopulation and regeneration of the auxiliarily transplanted small liver graft: the solution for organ shortage and immunosuppression. Med. Hypotheses 79, 241–24547. Hoppo, T. et al. (2011) Rescue of lethal hepatic failure by hepatized lymph nodes in mice. Gastroenterology 140, 656–66648. Komori, J. et al. (2012) The mouse lymph node as an ectopic transplantation site for multiple tissues. Nat. Biotechnol. 30, 976–98349. Han, B. et al. (2022) Fat-associated lymphoid clusters as expandable niches for ectopic liver development. Hepatology 76, 357–37150. Nicolas, C.T. et al. (2020) Ex vivo cell therapy by ectopic hepatocyte transplantation treats the porcine tyrosinemia model of acute liver failure. Mol. Ther. Methods Clin. Dev. 18, 738–75051. Fontes, P. et al. (2020) Development of ectopic livers by hepatocyte transplantation into swine lymph nodes. Liver Transpl. 26, 1629–164352. Kuchling, F. et al. (2020) Morphogenesis as Bayesian inference: a variational approach to pattern formation and control in complex biological systems. Phys Life Rev 33, 88–10853. Calvo, P. and Friston, K. (2017) Predicting green: really radical (plant) predictive processing. J. R. Soc. Interface 14, 2017009654. Pezzulo, G. and Levin, M. (2016) Top-down models in biology: explanation and control of complex living systems above the molecular level. J. R. Soc. Interface 13, 2016055555. Kramer, B.A. et al. (2022) Multimodal perception links cellular state to decision-making in single cells. Science 377, 642–64856. Toettcher, J.E. et al. (2013) Using optogenetics to interrogate the dynamic control of signal transmission by the Ras/Erk module. Cell 155, 1422–143457. Fields, C. and Levin, M. (2022) Competency in navigating arbitrary spaces as an invariant for analyzing cognition in diverse embodiments. Entropy (Basel) 2458. Boyle, E.A. et al. (2017) An expanded view of complex traits: from polygenic to omnigenic. Cell 169, 1177–118659. Kolodkin, A. et al. (2012) Understanding complexity in neurodegenerative diseases: in silico reconstruction of emergence. Front. Physiol. 3, 29160. Waliszewski, P. et al. (1998) On the holistic approach in cellular and cancer biology: nonlinearity, complexity, and quasi-determinism of the dynamic cellular network. J. Surg. Oncol. 68, 70–7861. Mathews, J. and Levin, M. (2018) The body electric 2.0: recent advances in developmental bioelectricity for regenerative and synthetic bioengineering. Curr. Opin. Biotechnol. 52, 134–14462. Pio-Lopez, L. et al. (2022) Active inference, morphogenesis, and computational psychiatry. Front. Comput. Neurosci. 16, 98897763. Pezzulo, G. and Levin, M. (2015) Re-membering the body: applications of computational neuroscience to the top-down control of regeneration of limbs and other complex organs. Integr. Biol. (Camb) 7, 1487–151764. Koshland, D.E. (1983) The bacterium as a model neuron. Trends Neurosci. 6, 133–13765. Morimoto, B.H. and Koshland, D.E.J. (1991) Short-term and long-term memory in single cells. FASEB J. 5, 2061–206766. Yang, C.Y. et al. (2020) Encoding membrane-potential-based memory within a microbial community. Cell Syst. 10, 417–42367. Prindle, A. et al. (2015) Ion channels enable electrical communication in bacterial communities. Nature 527, 59–6368. Mathews, J. and Levin, M. (2017) Gap junctional signaling in pattern regulation: physiological network connectivity instructs growth and form. Dev. Neurobiol. 77, 643–67369. Levin, M. and Martyniuk, C.J. (2018) The bioelectric code: an ancient computational medium for dynamic control of growth and form. Biosystems 164, 76–9370. Fields, C. et al. (2020) Morphological coordination: a common ancestral function unifying neural and non-neural signaling. Physiology 35, 16–3071. Vandenberg, L.N. et al. (2011) V-ATPase-dependent ectodermal voltage and pH regionalization are required for craniofacial morphogenesis. Dev. Dyn. 240, 1889–190472. Levin, M. (2021) Bioelectric signaling: reprogrammable circuits underlying embryogenesis, regeneration, and cancer. Cell 184, 1971–198973. Harris, M.P. (2021) Bioelectric signaling as a unique regulator of development and regeneration. Development 148, dev18079474. Bates, E. (2015) Ion channels in development and cancer. Annu. Rev. Cell Dev. Biol. 31, 231–24775. Zhao, S. et al. (2020) Biomedical applications of electrical stimulation. Cell. Mol. Life Sci. 77, 2681–269976. Reid, B. and Zhao, M. (2014) The electrical response to injury: molecular mechanisms and wound healing. Adv. Wound Care (New Rochelle) 3, 184–20177. Zhao, M. et al. (2012) Electrical signaling in control of ocular cell behaviors. Prog. Retin. Eye Res. 31, 65–8878. Tseng, A. and Levin, M. (2013) Cracking the bioelectric code: probing endogenous ionic controls of pattern formation. Commun. Integr. Biol. 6, 1–879. Mathews, J. et al. (2022) Ion channel drugs suppress cancer phenotype in NG108-15 and U87 cells: toward novel electroceuticals for glioblastoma. Cancers (Basel) 1480. Churchill, C.D.M. et al. (2018) EDEn – Electroceutical Design Environment: an ion channel database with small molecule modulators and tissue expression information. iScience 11, 42–5681. Pai, V.P. and Levin, M. (2022) HCN2 channel-induced rescue of brain, eye, heart and gut teratogenesis caused by nicotine, ethanol and aberrant notch signalling. Wound Repair Regen. 30, 681–70682. Pai, V.P. et al. (2018) HCN2 Rescues brain defects by enforcing endogenous voltage pre-patterns. Nat. Commun. 9, 99883. Pai, V.P. et al. (2015) Endogenous gradients of resting potential instructively pattern embryonic neural tissue via Notch signaling and regulation of proliferation. J. Neurosci. Res. 35, 4366–438584. Chernet, B.T. and Levin, M. (2013) Transmembrane voltage potential is an essential cellular parameter for the detection and control of tumor development in a Xenopus model. Dis. Models Mech. 6, 595–60785. Chernet, B.T. et al. (2016) Use of genetically encoded, light-gated ion translocators to control tumorigenesis. Oncotarget 7, 19575–1958886. Chernet, B.T. and Levin, M. (2014) Transmembrane voltage potential of somatic cells controls oncogene-mediated tumorigenesis at long-range. Oncotarget 5, 3287–330687. Chernet, B.T. and Levin, M. (2013) Endogenous voltage potentials and the microenvironment: bioelectric signals that reveal, induce and normalize cancer. J. Clin. Exp. Oncol. Suppl 1, S1-00288. Levin, M. (2021) Bioelectrical approaches to cancer as a problem of the scaling of the cellular self. Prog. Biophys. Mol. Biol. 165, 102–11389. Goel, P. and Mehta, A. (2013) Learning theories reveal loss of pancreatic electrical connectivity in diabetes as an adaptive response. PLoS One 8, e7036690. Tseng, A.S. et al. (2010) Induction of vertebrate regeneration by a transient sodium current. J. Neurosci. 30, 13192–1320091. Oviedo, N.J. and Beane, W.S. (2009) Regeneration: the origin of cancer or a possible cure? Semin. Cell Dev. Biol. 20, 557–56492. Sahu, S. et al. (2017) Secrets from immortal worms: what can we learn about biological ageing from the planarian model system? Semin. Cell Dev. Biol. 70, 108–12193. Shreesha, L. and Levin, M. (2023) Cellular competency during development alters evolutionary dynamics in an artificial embryogeny model. Entropy 25, 13194. Tlsty, T.D. and Hein, P.W. (2001) Know thy neighbor: stromal cells can contribute oncogenic signals. Curr. Opin. Genet. Dev. 11, 54–5995. Maffini, M.V. et al. (2005) Stromal regulation of neoplastic development: age-dependent normalization of neoplastic mammary cells by mammary stroma. Am. J. Pathol. 167, 1405–141096. Telerman, A. et al. (2010) Tumor reversion holds promise. Oncotarget 1, 233–23497. Blackiston, D.J. and Levin, M. (2013) Ectopic eyes outside the head in Xenopus tadpoles provide sensory data for light-mediated learning. J. Exp. Biol. 216, 1031–104098. Blackiston, D.J. et al. (2017) Serotonergic stimulation induces nerve growth and promotes visual learning via posterior eye grafts in a vertebrate model of induced sensory plasticity. npj. Regen. Med. 2, 899. Murugan, N.J. et al. (2022) Acute multidrug delivery via a wearable bioreactor facilitates long-term limb regeneration and functional recovery in adult Xenopus laevis. Sci. Adv. 8, eabj2164100. Ozugur, S. et al. (2022) Transcardial injection and vascular distribution of microalgae in Xenopus laevis as means to supply the brain with photosynthetic oxygen. STAR Protoc. 3, 101250101. Ozugur, S. et al. (2021) Green oxygen power plants in the brain rescue neuronal activity. iScience 24, 103158102. Magisetty, R. and Park, S.M. (2022) New era of electroceuticals: clinically driven smart implantable electronic devices moving towards precision therapy. Micromachines (Basel) 13, 161103. Tan, T.H. et al. (2022) Odd dynamics of living chiral crystals. Nature 607, 287–293104. Chao, Z.C. et al. (2008) Shaping embodied neural networks for adaptive goal-directed behavior. PLoS Comput. Biol. 4, e1000042105. Kagan, B.J. et al. (2022) In vitro neurons learn and exhibit sentience when embodied in a simulated game-world. Neuron 110, 3952–3969106. Mehrali, M. et al. (2018) Blending electronics with the human body: a pathway toward a cybernetic future. Adv. Sci. (Weinh) 5, 1700931107. Staufer, O. et al. (2016) Functional fusion of living systems with synthetic electrode interfaces. Beilstein J. Nanotechnol. 7, 296–301108. Levin, M. et al. (2020) Applications and ethics of computer-designed organisms. Nat. Rev. Mol. Cell Biol. 21, 655–656109. Heyd, D. (2012) Is there anything unique in the ethics of synthetic biology? Perspect. Biol. Med. 55, 581–589110. Evers, A.W.M. et al. (2018) Implications of placebo and nocebo effects for clinical practice: expert consensus. Psychother. Psychosom. 87, 204–210111. Piedimonte, A. and Benedetti, F. (2016) Words and drugs: same mechanisms of action? J. Contemp. Psychother. 46, 159–166112. Lui, F. et al. (2010) Neural bases of conditioned placebo analgesia. Pain 151, 816–824113. Benedetti, F. et al. (2007) When words are painful: unraveling the mechanisms of the nocebo effect. Neuroscience 147, 260–271114. Saatcioglu, F. (2013) Regulation of gene expression by yoga, meditation and related practices: a review of recent studies. Asian J. Psychiatr. 6, 74–77115. Agnati, L.F. et al. (2012) Aspects on the integrative actions of the brain from neural networks to 'brain-body medicine'. J. Recept. Signal Transduct. Res. 32, 163–180116. Taylor, A.G. et al. (2010) Top-down and bottom-up mechanisms in mind-body medicine: development of an integrative framework for psychophysiological research. Explore 6, 29–41117. Lu, H.Y. et al. (2021) Multi-scale neural decoding and analysis. J. Neural Eng. 18, ac160f118. Betzel, R.F. and Bassett, D.S. (2017) Multi-scale brain networks. Neuroimage 160, 73–83119. Gershman, S.J. et al. (2021) Reconsidering the evidence for learning in single cells. Elife 10, e61907120. Nilsonne, G. et al. (2011) Learning in a simple biological system: a pilot study of classical conditioning of human macrophages in vitro. Behav. Brain Funct. 7, 47121. Zoghi, M. (2004) Cardiac memory: do the heart and the brain remember the same? J. Interv. Card. Electrophysiol. 11, 177–182122. Rogers, M.P. et al. (1983) Conditioned immunosuppression? Am. J. Psychiatr. 140, 1110–1111123. Rogers, M.P. et al. (1979) The influence of the psyche and the brain on immunity and disease susceptibility: a critical review. Psychosom. Med. 41, 147–164124. Rogers, M.P. et al. (1976) Behaviorally conditioned immunosuppression: replication of a recent study. Psychosom. Med. 38, 447–451125. Miller, N.E. (1978) Biofeedback and visceral learning. Annu. Rev. Psychol. 29, 373–404126. Ongaro, G. and Kaptchuk, T.J. (2019) Symptom perception, placebo effects, and the Bayesian brain. Pain 160, 1–4127. Beauregard, M. and O'Leary, D. (2008) Believing can make it so: the neuroscience of the placebo effect. Adv. Mind Body Med. 23, 14–18128. Mason, A.A. (1952) A case of congenital ichthyosiform erythrodermia of Brocq treated by hypnosis. Br. Med. J. 2, 422–423129. Mathews, J. et al. (2022) Cellular signaling pathways as plastic, proto-cognitive systems: implications for biomedicine. Patterns (NY) 4, 100737130. Busse, S.M. et al. (2018) Cross-limb communication during Xenopus hindlimb regenerative response: non-local bioelectric injury signals. Development 145, dev164210131. Friston, K. (2010) The free-energy principle: a unified brain theory? Nat. Rev. Neurosci. 11, 127–138132. Badcock, P.B. et al. (2019) The hierarchically mechanistic mind: a free-energy formulation of the human psyche. Phys Life Rev 31, 104–121133. Ramstead, M.J.D. et al. (2019) Variational ecology and the physics of sentient systems. Phys Life Rev 31, 188–205134. Adams, R.A. et al. (2016) Computational psychiatry: towards a mathematically informed understanding of mental illness. J. Neurol. Neurosurg. Psychiatry 87, 53–63135. Rubin, H. (2007) Ordered heterogeneity and its decline in cancer and aging. Adv. Cancer Res. 98, 117–147136. Rubin, H. (1992) Mechanisms for enduring biological change. Am. J. Phys. 262, L111–L113137. Rubin, H. (1990) On the nature of enduring modifications induced in cells and organisms. Am. J. Phys. 258, L19–L24138. Mathews, J. et al. (2023) Cellular signaling pathways as plastic, proto-cognitive systems: implications for biomedicine. Patterns (NY) 4, 100737139. Williams, K. et al. (2020) Regulation of axial and head patterning during planarian regeneration by a commensal bacterium. Mech. Dev. 163, 103614140. Eberhard, W. et al. (2014) Zombie bugs? The fungus Purpureocillium cf. lilacinum may manipulate the behavior of its host bug Edessa rufomarginata. Mycologia 106, 1065–1072141. Elya, C. et al. (2018) Robust manipulation of the behavior of Drosophila melanogaster by a fungal pathogen in the laboratory. Elife 7, e34414142. Loreto, R.G. and Hughes, D.P. (2019) The metabolic alteration and apparent preservation of the zombie ant brain. J. Insect Physiol. 118, 103918143. Davies, J. and Levin, M. (2023) Synthetic morphology via active and agential matter. Nat. Rev. Bioengineer. 1, 46–49144. Abramson, C.I. and Levin, M. (2021) Behaviorist approaches to investigating memory and learning: a primer for synthetic biology and bioengineering. Commun. Integr. Biol. 14, 230–247145. Strassmann, J.E. and Queller, D.C. (2010) The social organism: congresses, parties, and committees. Evolution 64, 605–616146. Rotenberg, M.Y. and Tian, B.Z. (2018) Talking to cells: semiconductor nanomaterials at the cellular interface. Adv. Biosyst. 2, 1700242147. Belwafi, K. et al. (2021) Embedded brain computer interface: state-of-the-art in research. Sensors (Basel) 21, 4293148. Levin, M. (2023) Darwin's agential materials: evolutionary implications of multiscale competency in developmental biology. Cell. Mol. Life Sci. 80, 142149. Krist, K.T. et al. (2021) A simple theory for molecular chemotaxis driven by specific binding interactions. J. Chem. Phys. 155, 164902150. McGregor, S. et al. (2012) Evolution of associative learning in chemical networks. PLoS Comput. Biol. 8, e1002739151. Craddock, T.J. et al. (2012) Cytoskeletal signaling: is memory encoded in microtubule lattices by CaMKII phosphorylation? PLoS Comput. Biol. 8, e1002421152. Metzcar, J. et al. (2023) A model of multicellular communication mediated through extracellular matrix microstructure. BioRxiv Published online February 3, 2023. https://doi.org/10.1101/2022.11.21.514608153. Sarris, M. and Sixt, M. (2015) Navigating in tissue mazes: chemottractant interpretation in complex environments. Curr. Opin. Cell Biol. 36, 93–102154. Little, G.E. et al. (2009) Specificity and plasticity of thalamocortical connections in Sema6A mutant mice. PLoS Biol. 7, e98155. Levin, M. et al. (2017) Endogenous bioelectric signaling networks: exploiting voltage gradients for control of growth and form. Annu. Rev. Biomed. Eng. 19, 353–387156. Fankhauser, G. (1945) Maintenance of normal structure in heteroploid salamander larvae, through compensation of changes in cell size by adjustment of cell number and cell shape. J. Exp. Zool. 100, 445–455157. McEwen, B.S. (1998) Stress, adaptation, and disease. Allostasis and allostatic load. Ann. N. Y. Acad. Sci. 840, 33–44158. Zimmer, C. et al. (2022) Information theory in vertebrate stress physiology. Trends Endocrinol. Metab. 33, 8–17159. Tschantz, A. et al. (2022) Simulating homeostatic, allostatic and goal-directed forms of interoceptive control using active inference. Biol. Psychol. 169, 108266160. Deans, C. (2021) Biological prescience: the role of anticipation in organismal processes. Front. Physiol. 12, 672457161. Colditz, I.G. (2020) A consideration of physiological regulation from the perspective of Bayesian enactivism. Physiol. Behav. 214, 112758162. Schulkin, J. and Sterling, P. (2019) Allostasis: a brain-centered, predictive mode of physiological regulation. Trends Neurosci. 42, 740–752163. Oviedo, N.J. et al. (2003) Allometric scaling and proportion regulation in the freshwater planarian Schmidtea mediterranea. Dev. Dyn. 226, 326–333164. Cooke, J. (1981) Scale of body pattern adjusts to available cell number in amphibian embryos. Nature 290, 775–778165. Levin, M. et al. (2018) Planarian regeneration as a model of anatomical homeostasis: recent progress in biophysical and computational approaches. Semin. Cell Dev. Biol. 87, 125–144166. Farinella-Ferruzza, N. (1956) The transformation of a tail into a limb after xenoplastic transformation. Experientia 15, 304–305167. Pilling, O.A. et al. (2017) Insights into transgenerational epigenetics from studies of ciliates. Eur. J. Protistol. 61, 366–375168. Fields, C. and Levin, M. (2017) Multiscale memory and bioelectric error correction in the cytoplasm–cytoskeleton–membrane system. Wiley Interdiscip. Rev. Syst. Biol. Med. 10, e1410169. Oviedo, N.J. et al. (2010) Long-range neural and gap junction protein-mediated cues control polarity during planarian regeneration. Dev. Biol. 339, 188–199170. Vandenberg, L.N. et al. (2012) Normalized shape and location of perturbed craniofacial structures in the Xenopus tadpole reveal an innate ability to achieve correct morphology. Dev. Dyn. 241, 863–878171. Slijper, E.J. (1942) Biologic anatomical investigations on the bipedal gait and upright posture in mammals – with special reference to a little goat born without forelegs II. Proc. Kon. Ned. Akad. Van Wetensch. 45, 407–415172. Kozo-Polyansky, B.M. (1924) Symbiogenesis: A New Principle of Evolution, Harvard University Press173. Noble, D. (2022) Modern physiology vindicates Darwin's dream. Exp. Physiol. 107, 1015–1028174. Levin, M. (2023) Bioelectric networks: the cognitive glue enabling evolutionary scaling from physiology to mind. Anim. Cogn. Published online May 19, 2023. https://doi.org/10.1007/s10071-023-01780-3175. Pio-Lopez, L. and Levin, M. (2023) Morphoceuticals: perspectives for discovery of drugs targeting anatomical control mechanisms in regenerative medicine, cancer and aging. Drug Discov. Today 28, 103585176. Pai, V.P. et al. (2012) Transmembrane voltage potential controls embryonic eye patterning in Xenopus laevis. Development 139, 313–323
(参考文献可上下滑动查看)
学者简介
大模型与生物医学:
AI + Science第二季读书会启动
详情请见:
生命复杂性系列读书会
生命是什么?生命怎样起源?生命怎样演化?这些是对生命现象的本质追问,除了传统的生物学研究,如今有大量来自信息、物理、计算机领域的工具方法,正在揭开生命复杂性谜题。基于此,集智俱乐部策划“生命复杂性”系列读书会,自2020年11月5日至今,近百名在从事相关问题研究的老师同学或感兴趣的朋友参与。
了解读书会具体规则、报名读书会请点击下方文章:
推荐阅读
点击“阅读原文”,报名读书会