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A promising new foundation for conflict and control: Bridging the gap to verification. Comment on “Active inference and cognitive control: Balancing deliberation and habits through precision optimization” by Riccardo Proietti, Thomas Parr, Alessia Tessari, Karl Friston, & Giovanni Pezzulo 冲突和控制的一个有希望的新基础:弥合与核查之间的差距。评论Riccardo Proietti、Thomas Parr、Alessia Tessari、Karl Friston和Giovanni Pezzulo的《主动推理和认知控制:通过精确优化平衡深思熟虑和习惯》
IF 14.3 1区 生物学 Q1 BIOLOGY Pub Date : 2026-03-01 Epub Date: 2025-11-24 DOI: 10.1016/j.plrev.2025.11.008
Antonino Visalli
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引用次数: 0
The limits of information: comment on “informational embodiment: computational role of information structure in codes and robots” by Alexandre Pitti, Max Austin, Kohei Nakajima, Yasuo Kuniyoshi 信息的极限:评Alexandre Pitti、Max Austin、Kohei Nakajima、Yasuo Kuniyoshi的“信息体现:信息结构在代码和机器人中的计算作用”
IF 14.3 1区 生物学 Q1 BIOLOGY Pub Date : 2026-03-01 Epub Date: 2025-11-05 DOI: 10.1016/j.plrev.2025.11.004
Anna Loi , Vicente Raja
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引用次数: 0
Why the memory palace is mightier than the memory pharmacy 为什么记忆宫殿比记忆药房更强大。
IF 14.3 1区 生物学 Q1 BIOLOGY Pub Date : 2026-03-01 Epub Date: 2025-12-20 DOI: 10.1016/j.plrev.2025.12.011
Boris N. Konrad, Martin Dresler
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引用次数: 0
General integration theory of cognitive emergent: Comment on "Brain dynamics shape cognition–spatiotemporal neuroscience" by Georg Northoff, Angelika Wolman and Jianfeng Zhang 认知涌现的一般整合理论:评Georg Northoff、Angelika Wolman和张剑锋的“脑动力学塑造认知-时空神经科学”。
IF 14.3 1区 生物学 Q1 BIOLOGY Pub Date : 2026-03-01 Epub Date: 2026-01-20 DOI: 10.1016/j.plrev.2026.01.004
Feiyan Chen , Fan Liu , Jingcheng Wang , Rengqin Sun , Hongjian He , Xi-Nian Zuo
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引用次数: 0
On implementation of nonlocal terms in models in ecology and evolution. Comment on ‘Nonlocal models in biology and life sciences: Sources, developments, and applications’ by S. Pal & R. Melnick 生态学和进化中模型中非局部项的实现。对S. Pal和R. Melnick著的《生物学和生命科学中的非局部模型:来源、发展和应用》的评论
IF 14.3 1区 生物学 Q1 BIOLOGY Pub Date : 2026-03-01 Epub Date: 2025-12-26 DOI: 10.1016/j.plrev.2025.12.013
Andrew Yu Morozov
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引用次数: 0
Remodeling of non-coding RNA regulatory networks: Decoding the pathological mechanisms and new therapeutic paradigms of cardiovascular diseases 非编码RNA调控网络的重塑:解码心血管疾病的病理机制和新的治疗范式。
IF 14.3 1区 生物学 Q1 BIOLOGY Pub Date : 2026-03-01 Epub Date: 2025-12-16 DOI: 10.1016/j.plrev.2025.12.007
Wangzheqi Zhang , Lei Duan , Changli Wang , Yan Liao , Rui Zhao , Zhaoyu Li , Haoling Zhang , Zengwu Wang , Jing-jing Zhang
The essential role of non-coding RNAs (ncRNAs) in cardiovascular disease (CVD) research instigates a shift from empirical studies to those based on molecular mechanisms, targeted interventions, and personalized health management in the world of precision medicine. This review systematically summarizes the expression profiles and multilayered regulatory mechanisms of various ncRNAs such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and small nucleolar RNAs (snoRNAs) in a variety of cardiovascular diseases (CVDs) ranging from congenital heart disease to atherosclerosis (AS), cardiomyopathies, heart failure (HF), and arrhythmias. The central roles of key pathological pathways like epigenetic changes, competing endogenous RNA (ceRNA), inflammation and cell fate determination will be highlighted. From a diagnostic point of view, ncRNAs have good potentials as early-stage biomarkers, in applications such as exosomal liquid biopsy, disease classification, and prognosis. Emerging technologies, notably locked nucleic acid (LNA) oligonucleotides, adeno-associated virus serotype 9 (AAV9)-based delivery systems and engineered exosomes, are unlocking new avenues for intervention on the therapeutic front. These developments, coupled with drug repurposing strategies and tissue-specific delivery platforms, can make ncRNA-targeted therapies more specific and controllable. At the same time, interdisciplinary innovations, like single-cell multi-omics, spatial transcriptomics, CRISPR-dCas9 systems, and deep learning assist clinical translation greatly. However, the real-world application of ncRNA-based therapies is constrained by many challenges like low delivery efficiency, functional redundancy, and microenvironmental dependence. Future directions must aim to create integrative platforms that can dynamically identify and modulate ncRNA functions to link mechanistic studies to personalized therapies and subsequently expedite clinical translation of ncRNA discoveries. In this sense, three cross-scale principles-network topology and ceRNA competition dynamics; spatiotemporal gradients modeled by exosome transport and tissue microenvironments; and energetic/stoichiometric constraints like Dicer processing capacity and miRNA-target ratios- provide an analytical framework that appears recurrently across diverse CVD phenotypes and tighten the mechanistic unity of this review.
非编码rna (ncRNAs)在心血管疾病(CVD)研究中的重要作用促使精准医学领域从实证研究转向基于分子机制、靶向干预和个性化健康管理的研究。本文系统总结了各种ncRNAs的表达谱和多层调控机制,如微rna (miRNAs)、长链非编码rna (lncRNAs)、环状rna (circRNAs)和小核核rna (snoRNAs)在各种心血管疾病(cvd)中的表达谱和多层调控机制,这些心血管疾病包括先天性心脏病、动脉粥样硬化(as)、心肌病、心力衰竭(HF)和心律失常。关键病理途径如表观遗传变化、竞争内源性RNA (ceRNA)、炎症和细胞命运决定的中心作用将被强调。从诊断的角度来看,ncrna作为早期生物标志物具有良好的潜力,可用于外泌体液体活检、疾病分类和预后。新兴技术,特别是锁定核酸(LNA)寡核苷酸、基于腺相关病毒血清型9 (AAV9)的递送系统和工程外泌体,正在为治疗前沿的干预开辟新的途径。这些发展,加上药物再利用策略和组织特异性递送平台,可以使ncrna靶向治疗更具特异性和可控性。与此同时,单细胞多组学、空间转录组学、CRISPR-dCas9系统、深度学习等跨学科创新也极大地辅助了临床翻译。然而,基于ncrna的治疗方法的实际应用受到许多挑战的限制,如低递送效率、功能冗余和微环境依赖性。未来的方向必须旨在创建能够动态识别和调节ncRNA功能的综合平台,将机制研究与个性化治疗联系起来,并随后加快ncRNA发现的临床翻译。从这个意义上讲,三个跨尺度原理-网络拓扑和ceRNA竞争动态;外泌体运输和组织微环境模拟的时空梯度和能量/化学计量学约束,如Dicer处理能力和mirna -靶标比,提供了一个分析框架,该框架反复出现在不同的CVD表型中,并加强了本综述的机制统一性。
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引用次数: 0
Biological models with nonlocal terms: Future scopes of research: Comment on “Nonlocal models in biology and life sciences: Sources, developments, and applications” by S. Pal & R. Melnick 具有非局部术语的生物模型:未来的研究范围:对S. Pal & R. Melnick著的《生物学和生命科学中的非局部模型:来源、发展和应用》的评论
IF 14.3 1区 生物学 Q1 BIOLOGY Pub Date : 2026-03-01 Epub Date: 2025-11-20 DOI: 10.1016/j.plrev.2025.11.005
Malay Banerjee , Kalyan Manna , Indrajyoti Gaine
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引用次数: 0
Neural cellular automata: Applications to biology and beyond classical AI 神经细胞自动机:在生物学和经典人工智能之外的应用。
IF 14.3 1区 生物学 Q1 BIOLOGY Pub Date : 2026-03-01 Epub Date: 2025-11-29 DOI: 10.1016/j.plrev.2025.11.010
Benedikt Hartl , Michael Levin , Léo Pio-Lopez
Neural Cellular Automata (NCA) represent a powerful framework for modeling biological self-organization, extending classical rule-based systems with trainable, differentiable (or evolvable) update rules that capture the adaptive self-regulatory dynamics of living matter. By embedding Artificial Neural Networks (ANNs) as local decision-making centers and interaction rules between localized agents, NCA can simulate processes across molecular, cellular, tissue, and system-level scales, offering a multiscale competency architecture perspective on evolution, development, regeneration, aging, morphogenesis, and robotic control. These models not only reproduce canonical, biologically inspired target patterns but also generalize to novel conditions, demonstrating robustness to perturbations and the capacity for open-ended adaptation and reasoning through embodiment. Given their immense success in recent developments, we here review current literature of NCAs that are relevant primarily for biological or bioengineering applications. Moreover, we emphasize that beyond biology, NCAs display robust and generalizing goal-directed dynamics without centralized control, e.g., in controlling or regenerating composite robotic morphologies or even on cutting-edge reasoning tasks such as ARC-AGI-1. In addition, the same principles of iterative state-refinement is reminiscent to modern generative Artificial Intelligence (AI), such as probabilistic diffusion models. Their governing self-regulatory behavior is constraint to fully localized interactions, yet their collective behavior scales into coordinated system-level outcomes. We thus argue that NCAs constitute a unifying computationally lean paradigm that not only bridges fundamental insights from multiscale biology with modern generative AI, but have the potential to design truly bio-inspired collective intelligence capable of hierarchical reasoning and control.
神经细胞自动机(NCA)代表了一个强大的生物自组织建模框架,扩展了经典的基于规则的系统,使用可训练的、可微的(或可进化的)更新规则来捕获生物物质的自适应自我调节动态。通过嵌入人工神经网络(ann)作为局部决策中心和局部代理之间的交互规则,NCA可以模拟跨分子、细胞、组织和系统级别的过程,为进化、发育、再生、老化、形态发生和机器人控制提供多尺度能力架构视角。这些模型不仅再现了规范的、受生物学启发的目标模式,而且还推广到新的条件,展示了对扰动的鲁棒性,以及通过具体化进行开放式适应和推理的能力。鉴于它们在最近的发展中取得了巨大的成功,我们在这里回顾了目前主要与生物或生物工程应用相关的NCAs文献。此外,我们强调,在生物学之外,nca在没有集中控制的情况下表现出鲁棒性和泛化的目标导向动力学,例如,在控制或再生复合机器人形态或甚至在尖端推理任务(如ARC-AGI-1)中。此外,迭代状态优化的相同原理让人想起现代生成式人工智能(AI),如概率扩散模型。它们的治理自我调节行为是对完全局部交互的约束,但它们的集体行为可扩展为协调的系统级结果。因此,我们认为NCAs构成了一个统一的计算精益范式,它不仅将多尺度生物学的基本见解与现代生成人工智能联系起来,而且有可能设计出能够分层推理和控制的真正受生物启发的集体智能。
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引用次数: 0
From modelling PPST to modelling bodily self-consciousness: Comment on “Computational models of peripersonal space representation” by T. Bertoni, J.P. Noel & A. Serino 从模拟PPST到模拟身体自我意识:评T. Bertoni、J.P. Noel和A. Serino的“周围个人空间表征的计算模型”。
IF 14.3 1区 生物学 Q1 BIOLOGY Pub Date : 2026-03-01 Epub Date: 2025-12-21 DOI: 10.1016/j.plrev.2025.12.012
Renato Paredes , Peggy Seriès , Olaf Blanke
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引用次数: 0
The spatiotemporal structure of neural activities shapes cognitive functions: Comment on “brain dynamics shape cognition–spatiotemporal neuroscience” by Georg Northoff, Angelika Wolman, and Jianfeng Zhang 神经活动的时空结构塑造认知功能——评Georg Northoff、Angelika Wolman和张剑锋的“脑动力学塑造认知-时空神经科学”
IF 14.3 1区 生物学 Q1 BIOLOGY Pub Date : 2026-03-01 Epub Date: 2025-12-03 DOI: 10.1016/j.plrev.2025.12.002
Yuzhu Tang, Mengxiao Sun, Yifeng Wang, Xiujuan Jing
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引用次数: 0
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Physics of Life Reviews
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