Biosystems最新文献_第5页

Turing instability on multiplex simplicial epidemic networks with cross-diffusion and behavioral delay 具有交叉扩散和行为延迟的多重简单流行病网络的图灵不稳定性。

IF 1.9 4区生物学 Q2 BIOLOGY

Biosystems

Pub Date : 2025-12-16 DOI: 10.1016/j.biosystems.2025.105679

Yue Liu, Jianwei Shen

Modern epidemics are characterized by the emergence of spatial hotspots and periodic outbreaks. This paper reveals that such complex spatiotemporal patterns are driven by a combination of many-body transmission pathways and delayed behavioral responses. We propose a reaction–diffusion epidemic model defined on a multiplex simplicial complex and introduce the behavioral response delay. Through linear stability analysis, we derive the conditions for Turing instability and delay-induced Hopf bifurcation. The analysis reveals that higher-order topological structures and cross-diffusion expand the instability domain and promote the formation of spatial patterns. The higher-order aggregation of susceptible individuals is a key factor in triggering Turing instability, while the higher-order structure of the infected layer primarily modulates its extent. Furthermore, the behavioral response delay acts as a bifurcation parameter, inducing temporal oscillations when it exceeds a critical threshold. Numerical simulations corroborate our theoretical findings, reproducing clustered and periodic oscillation phenomena analogous to those observed during the COVID-19 pandemic. Our results provide the policy implication that dispersing higher-order susceptible clusters and reducing response delays can mitigate spatial heterogeneity and recurrent outbreaks. This work deepens the understanding of epidemic dynamics by elucidating how network topology and human behavior jointly shape complex contagion patterns.

现代流行病的特点是出现空间热点和周期性爆发。这种复杂的时空模式是由多体传递途径和延迟行为反应共同驱动的。我们提出了一个定义在多重简单复合体上的反应-扩散流行病模型，并引入了行为反应延迟。通过线性稳定性分析，导出了图灵不稳定性和时滞诱导Hopf分岔的条件。分析表明，高阶拓扑结构和交叉扩散扩大了不稳定域，促进了空间格局的形成。易感个体的高阶聚集是触发图灵不稳定的关键因素，而感染层的高阶结构主要调节其程度。此外，行为反应延迟作为一个分岔参数，当它超过一个临界阈值时，会引起时间振荡。数值模拟证实了我们的理论发现，再现了类似于COVID-19大流行期间观察到的聚集性和周期性振荡现象。我们的研究结果提供了政策启示，即分散高阶易感集群和减少响应延迟可以减轻空间异质性和复发性爆发。这项工作通过阐明网络拓扑和人类行为如何共同塑造复杂的传染模式，加深了对流行病动力学的理解。

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引用次数: 0

A Unified Holographic Framework for neural computation and consciousness: From lipid membranes to the Schumann resonance 神经计算和意识的统一全息框架：从脂质膜到舒曼共振。

IF 1.9 4区生物学 Q2 BIOLOGY

Biosystems

Pub Date : 2025-12-15 DOI: 10.1016/j.biosystems.2025.105669

Marco Cavaglià, Jack A. Tuszynski

Understanding conscious experience requires looking beyond neuronal circuits alone. We propose that lipid membranes, vicinal water, and cerebrospinal fluid (CSF) form a coherent substrate capable of holographic encoding and coupling to endogenous/exogenous electromagnetic fields (EMF). In what follows: (i) we formulate four postulates (membrane as holographic plate; water as coherence medium; holographic read–write; environmental coupling), (ii) we present a dual-layer model (membrane–water–CSF ↔ EMF) and a one-panel graphical overview, (iii) we integrate the framework with existing theories, and (iv) we outline falsifiable experimental strategies and metrics.

理解意识经验需要超越神经回路。我们提出脂质膜、附近的水和脑脊液（CSF）形成一个连贯的底物，能够全息编码和耦合内源性/外源性电磁场（EMF）。在以下内容中：(i)我们制定了四个假设（膜作为全息板；水作为相干介质；全息读写；环境耦合），（ii）我们提出了一个双层模型（膜-水- csf↔EMF）和一个单面板图形概述，（iii）我们将框架与现有理论相结合，（iv）我们概述了可证伪的实验策略和指标。

引用次数: 0

Morphospace engineering: Morphological computation in scaffold design 形态空间工程：支架设计中的形态计算。

IF 1.9 4区生物学 Q2 BIOLOGY

Biosystems

Pub Date : 2025-12-12 DOI: 10.1016/j.biosystems.2025.105676

C. Galli , M.T. Colangelo , M. Meleti , S. Guizzardi

Scaffold geometry does more than support tissue—it encodes the rules by which matter organizes into function. Morphology operates as a generative constraint, transforming physical configuration into causal instruction. From molecular folding to cellular migration, form computes what matter can become. This work formalizes that principle across scales: using cellular automata as minimal models of morphogenesis and extending the same logic to scaffold design for tissue regeneration. Each scaffold can be described as a point in a high-dimensional morphospace whose axes—curvature, porosity, stiffness, fiber orientation—act as local update rules guiding cell behavior. Within this space, a viability kernel delineates the geometries that sustain growth and differentiation. By treating geometry as computation, bioengineering shifts from designing materials that contain life to shaping forms that generate it—a shape-first paradigm where the causal arrow runs from form to function.

支架的几何结构不仅仅是支撑组织，它还编码了物质组织成功能的规则。形态学作为一种生成约束，将物理结构转化为因果指令。从分子折叠到细胞迁移，形态决定了物质可以变成什么。这项工作跨尺度形式化了这一原则：使用细胞自动机作为形态发生的最小模型，并将相同的逻辑扩展到组织再生的支架设计中。每个支架可以被描述为高维形态空间中的一个点，其轴-曲率，孔隙率，刚度，纤维方向-作为指导细胞行为的局部更新规则。在这个空间内，生存能力内核描绘了维持增长和分化的几何形状。通过将几何视为计算，生物工程从设计包含生命的材料转变为塑造产生生命的形式——形状优先的范式，其中因果箭头从形式到功能。

引用次数: 0

EMI model: A scale free biophysical framework for human consciousness, cognition and behaviour EMI模型：人类意识、认知和行为的无标度生物物理框架

IF 1.9 4区生物学 Q2 BIOLOGY

Biosystems

Pub Date : 2025-12-09 DOI: 10.1016/j.biosystems.2025.105674

Tommaso Firaux , Jack A. Tuszynski , Marco Cavaglià

Understanding consciousness, cognition, and behaviour requires an integrated framework capable of bridging neurobiology, physics, and information theory. In this paper, we propose the Energy-Mass-Information (EMI) framework as a novel paradigm to conceptualize mental phenomena as emergent properties of dynamic, field-based interactions. Rooted in, and direct expression of the Unified Holographic Framework for Neural Coherence and Consciousness (UHF), EMI introduces a transdisciplinary approach that reconceptualizes the brain-mind system as a continuously evolving network of interactions among energetic oscillations, material substrates, and informational patterns. At the heart of the EMI model lies the notion that cognition arises through the formation and modulation of attractor states-stable yet flexible configurations in the brain's energy-information landscape-guided by resonance, plasticity, and self-organizing processes.

Consciousness is thus interpreted as a holographically organized phenomenon, embedded within the biophysical substrate of the brain-body system and dynamically shaped by both internal and external fields. Behaviour emerges as the macroscopic expression of shifts among informational attractors, driven by energetic gradients and encoded across multiple scales of neural and body organization. By integrating principles from quantum coherence, neural synchronization, and dynamic systems theory, EMI offers a unifying perspective that transcends reductionist models, linking subjective experience to measurable neurophysiological and field-level processes.

理解意识、认知和行为需要一个能够连接神经生物学、物理学和信息论的综合框架。在本文中，我们提出能量-质量-信息（EMI）框架作为一种新的范式，将心理现象概念化为动态的、基于场的相互作用的涌现特性。EMI根植于并直接表达了神经一致性和意识的统一全息框架（UHF），引入了一种跨学科的方法，将大脑-思维系统重新定义为能量振荡、物质基质和信息模式之间不断发展的相互作用网络。电磁干扰模型的核心概念是，认知是通过吸引子状态的形成和调节而产生的，吸引子状态是大脑能量信息景观中稳定而灵活的配置，由共振、可塑性和自组织过程引导。因此，意识被解释为一种全息组织现象，嵌入脑-体系统的生物物理基质中，并由内外场动态塑造。行为是信息吸引子之间变化的宏观表达，由能量梯度驱动，并在神经和身体组织的多个尺度上编码。通过整合量子相干、神经同步和动态系统理论的原理，EMI提供了一个超越还原论模型的统一视角，将主观体验与可测量的神经生理和现场水平的过程联系起来。

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引用次数: 0

Least ranked human individuals exhibit scale free behavioral responses in hierarchical social systems 排名最低的人类个体在等级社会系统中表现出无尺度的行为反应。

IF 1.9 4区生物学 Q2 BIOLOGY

Biosystems

Pub Date : 2025-12-08 DOI: 10.1016/j.biosystems.2025.105678

Chetan K. Yadav

Human behavior is the most complex system generated and represented by the cognitive brain. It is a function of highly adaptive dynamic cognitive states receiving sensory inputs and generating the behavioral responses. Social inputs belong to a class of sensory information affecting individual and collective human behavior for various purposes including a rewarded survival. Many models and theories have been proposed for understanding phenomenological dynamics of collective behavior, however most of them considered a group size effect possibly limiting cognitive scales of a given individual. Inter-element connectivity is an exclusive feature of the self-organized groups, getting optimized in the larger groups, and is a reason for better decision making in the smaller groups. We consider this as a preprocessing step in social information processing by an individual, narrowing down its own cognitive capabilities during a decision making process. Hence, in this perspective, We are considering an alternative form of social connectivity, the hierarchical social system, like in the corporate systems, allowing an individual to make decisions in light of singular instruction coming from its social partners at a higher rank. This model is proposed to unravel hidden cognitive scales in an individual's cognition as its confidence in social suggestions during decision making is expected to exhibit scale free dynamics emerging towards a critical point. Either side of this critical point can be a phase of random dynamics in absence of social information and a highly ordered phase of making limited decisions in light of aforesaid group size effect. We put forward a hypothesis that hierarchical social systems increase productivity and facilitate fruitful decision making allowing more scope to the individual cognition. Four behavioral experiments are proposed for testing this hypothesis in light of exciting scientific evidence discussed in the discussion section.

人类行为是由认知大脑产生和表现的最复杂的系统。它是一个高度自适应的动态认知状态的功能，它接受感官输入并产生行为反应。社会输入属于一类影响个人和集体人类行为的感官信息，用于各种目的，包括获得奖励的生存。人们提出了许多模型和理论来理解集体行为的现象学动力学，但大多数模型和理论都认为群体规模效应可能会限制特定个体的认知尺度。元素间连接是自组织组的独有特性，在较大的组中得到优化，并且是在较小的组中做出更好决策的原因。我们认为这是个体在社会信息处理中的预处理步骤，在决策过程中缩小了自己的认知能力。因此，从这个角度来看，我们正在考虑社会联系的另一种形式，即等级社会系统，就像公司系统一样，允许个人根据来自更高级别的社会伙伴的单一指令做出决定。该模型旨在揭示个体认知中隐藏的认知尺度，因为个体在决策过程中对社会建议的信心有望呈现出向临界点出现的尺度自由动态。这个临界点的任何一方都可以是缺乏社会信息的随机动态阶段，也可以是根据上述群体规模效应做出有限决策的高度有序阶段。我们提出了一个假设，等级社会制度提高了生产力，促进了富有成效的决策，允许更多的个人认知范围。根据讨论部分讨论的令人兴奋的科学证据，提出了四个行为实验来验证这一假设。

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引用次数: 0

Optimal information transmission in a non-Markovian auto-regulatory gene expression system 非马尔可夫自调节基因表达系统中的最优信息传递。

IF 1.9 4区生物学 Q2 BIOLOGY

Biosystems

Pub Date : 2025-12-08 DOI: 10.1016/j.biosystems.2025.105675

Zihao Wang , Meiling Chen , Zhenquan Zhang , Xiyan Yang , Tianshou Zhou , Changhong Shi , Jiajun Zhang

Gene expression is a multistep and inherently noisy process. Such multistep reactions introduces memory between molecular events, giving rise to non-Markovian dynamics. Simultaneously, noise in the gene regulatory network limits the fidelity with which input signals can be transmitted to gene expression outputs. These considerations raise a key unresolved question: how does molecular memory influence the maximum information transmission capacity of regulatory networks under varying physical conditions? To address this, we develop a theoretical framework for a non-Markovian auto-regulatory gene expression system with arbitrary feedback form. By introducing effective transition rates, we transform the original non-Markovian model into an equivalent Markovian formulation, enabling analytical treatment. We find that non-Markovianity confers a significantly stronger regulatory capacity than feedback alone. In monostable regimes, feedback strength shapes the pattern of optimal information transmission, giving rise to monotonic or non-monotonic dependencies on memory. In bistable regimes, increasing non-Markovianity leads to a consistent decrease in the upper bound of information transmission. Beyond these results, our approach establishes a generalizable strategy for analyzing information flow in complex gene regulatory systems involving memory, feedback, and noise.

基因表达是一个多步骤和固有噪声的过程。这种多步骤反应引入了分子事件之间的记忆，产生了非马尔可夫动力学。同时，基因调控网络中的噪声限制了输入信号传递到基因表达输出的保真度。这些考虑提出了一个关键的未解决的问题：在不同的物理条件下，分子记忆如何影响调节网络的最大信息传输能力？为了解决这个问题，我们开发了一个具有任意反馈形式的非马尔可夫自调节基因表达系统的理论框架。通过引入有效转移率，我们将原始的非马尔可夫模型转换为等效的马尔可夫公式，从而实现解析处理。我们发现非马尔可夫性比单独反馈具有更强的调节能力。在单稳定状态下，反馈强度塑造了最优信息传递的模式，导致对记忆的单调或非单调依赖。在双稳态状态下，非马尔可夫性的增加导致信息传输上界的持续下降。除了这些结果之外，我们的方法还建立了一种可推广的策略，用于分析涉及记忆、反馈和噪声的复杂基因调控系统中的信息流。

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引用次数: 0

Stochastic-Dissipative Least-Action framework for self-organizing biological systems, Part II: Empirical estimation, average action efficiency, and applications to ATP synthase. 自组织生物系统的随机耗散最小作用框架，第二部分：经验估计，平均作用效率，以及在ATP合酶中的应用。

IF 1.9 4区生物学 Q2 BIOLOGY

Biosystems

Pub Date : 2025-12-08 DOI: 10.1016/j.biosystems.2025.105667

Georgi Yordanov Georgiev

Quantifying how biological systems maintain organization far from thermodynamic equilibrium remains a fundamental challenge. Biochemical energy converters operate under stochastic fluctuations while maintaining tight mechanochemical coupling. The stochastic-dissipative variational structure developed in Part I predicts that such systems evolve toward a minimum average action per productive event. The precision of mechanochemical coupling is reflected directly in the near-invariance of the event-level action budget. In the limit of many repeated events, empirical cycle statistics converge closely to the theoretical ensemble expectations. For ATP synthase, the action associated with an elementary chemomechanical step can be obtained directly from aggregate energetic and kinetic observables, without reconstructing microscopic trajectories. Across a broad range of conditions, the product of energy transduced per step and its duration remains nearly invariant, revealing the iso-action reciprocity expected for tightly coupled chemomechanical machines. Using Nath's macro-level OXPHOS measurements, we find that the Average Action Efficiency (AAE) per elementary chemomechanical step is of order unity, corresponding to an average event action close to Planck's constant. This scale reflects the quantized, discrete chemical and rotational transitions that constrain the enzyme's operation and is naturally interpreted as a system-specific lower bound. This alignment with theory shows that AAE is experimentally accessible and that ATP synthase operates with the predicted invariance and near-maximal efficiency imposed by its architecture. Such optimization may represent a physical organizing tendency that complements random variation and natural selection by shaping the conditions under which evolutionary adaptation unfolds.

量化生物系统如何维持远离热力学平衡的组织仍然是一个根本性的挑战。生化能量转换器在随机波动下运行，同时保持紧密的机械化学耦合。在第一部分中提出的随机耗散变分结构预测，这样的系统将朝着每个生产事件的最小平均行动发展。机械化学耦合的精度直接反映在事件级动作预算的近不变性中。在许多重复事件的限制下，经验周期统计接近于理论集合期望。对于ATP合酶，与基本化学机械步骤相关的作用可以直接从聚集的能量和动力学观察中获得，而无需重建微观轨迹。在广泛的条件范围内，每一步转导的能量乘积及其持续时间几乎保持不变，揭示了紧密耦合化学机械机器所期望的等作用互易性。利用Nath的宏观OXPHOS测量，我们发现每个基本化学力学步骤的平均作用效率（AAE）是有序单位的，对应于接近普朗克常数的平均事件作用。这个尺度反映了量子化的、离散的化学和旋转转变，这些转变限制了酶的运作，自然地被解释为系统特定的下限。这与理论一致，表明AAE在实验上是可行的，并且ATP合酶的结构具有预测的不变性和接近最大的效率。这种优化可能代表了一种物理组织倾向，它通过塑造进化适应展开的条件来补充随机变异和自然选择。

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引用次数: 0

Obesity, body heat loss, and efficiency in movement 肥胖，身体热量损失和运动效率。

IF 1.9 4区生物学 Q2 BIOLOGY

Biosystems

Pub Date : 2025-12-08 DOI: 10.1016/j.biosystems.2025.105673

Adrian Bejan

This article makes an unexpected, counterintuitive theoretical step. Excessive inactive body mass (fat, carried load) has a negative impact on the efficiency of life movement to distances. Also negative is the impact of loss of body heat to the cold ambient. Surprisingly, the two negative impacts evolve naturally to a tradeoff such that the living body benefits from maximal efficiency in movement and access on the globe. The tradeoff reveals the amount of inactive mass (e.g., thickness of fat layer) most beneficial for movement. Tradeoffs between negative impacts govern the evolution (the morphing) of all moving design (animal, vehicle, river, etc.). For example, fat tends to be stored primarily at the interface between the warm inner body and the cold ambient. That's design in nature, configuration evolution. Furthermore, the perception of cold is physical and measurable in terms of physical outcomes: design for greater efficiency in movement on the globe, greater power, easier access, farther reach, economy and longer lifespan. Traditionally, perceptions are thought of as intangibles, opinions, beyond the predictive reach of physics. The physics underpinnings of perceptions, reaffirmed in this article, are essential to the future of robotics and AI, if such technologies are ever to compete with naked animal thought and action.

这篇文章做出了一个出乎意料的、违反直觉的理论步骤。过多的非活动体重（脂肪、负重）对远距离生活运动的效率有负面影响。身体热量流失到寒冷环境的影响也是负面的。令人惊讶的是，这两种负面影响自然演变为一种权衡，这样，活体就能从最大效率的运动和全球访问中受益。这种权衡揭示了最有利于运动的非活动质量（例如，脂肪层的厚度）的数量。负面影响之间的权衡支配着所有移动设计（动物、交通工具、河流等）的进化（变形）。例如，脂肪往往主要储存在温暖的身体内部和寒冷的环境之间的界面。这就是设计的本质，结构的进化。此外，对寒冷的感知是物理上的，并且在物理结果方面是可测量的：设计在全球范围内的运动效率更高，功率更大，更容易进入，更远的范围，经济和更长的寿命。传统上，感知被认为是一种无形的东西，是物理学无法预测的观点。如果机器人和人工智能技术要与赤裸裸的动物思想和行为竞争，那么本文重申的感知的物理基础对机器人和人工智能的未来至关重要。

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引用次数: 0

150 Years since the birth of Lev Berg: Nomogenesis is more relevant today than ever 列夫·伯格诞辰150周年：生理发育在今天比以往任何时候都更有意义。

IF 1.9 4区生物学 Q2 BIOLOGY

Biosystems

Pub Date : 2025-12-04 DOI: 10.1016/j.biosystems.2025.105670

A.V. Melkikh

This article is dedicated to the 150th anniversary of the evolutionist Lev Berg and explores his evolutionary ideas. Concepts such as convergence, parallelism, and mimicry are examined. A substantial body of modern research supports Berg's view of evolution as a directional process. In particular, Berg's conclusion that such complex living structures could not have arisen by chance is fully supported by modern calculations. Contemporary examples of parallelism research among animals (including domesticated ones) are considered. Contemporary examples of mimicry research are also considered. The extensive parallelism of species, organs, tissues, etc., also strongly supports Berg's theory. One of Berg's most important ideas was the improbability of random evolution in living systems. The lack of a solution to this problem is one of the main shortcomings of Darwinism. Modern genomic research allows us to further tighten the requirements for this probability, making it negligible.

这篇文章是为了纪念进化论者列夫·伯格诞辰150周年，并探讨他的进化思想。概念，如收敛，平行和模仿进行了检查。大量现代研究支持伯格的观点，即进化是一个有方向的过程。特别是，伯格关于这种复杂的生命结构不可能偶然出现的结论，完全得到了现代计算的支持。考虑了当代动物（包括驯化动物）之间平行研究的例子。还考虑了当代模仿研究的例子。物种、器官、组织等的广泛相似性也有力地支持了伯格的理论。伯格最重要的思想之一是生命系统中随机进化的不可能性。缺乏解决这个问题的方法是达尔文主义的主要缺点之一。现代基因组研究使我们能够进一步收紧对这种概率的要求，使其可以忽略不计。

引用次数: 0

The Natural history of the transition between RNA to DNA in the early stages of life 生命早期阶段RNA向DNA过渡的自然史

IF 1.9 4区生物学 Q2 BIOLOGY

Biosystems

Pub Date : 2025-12-04 DOI: 10.1016/j.biosystems.2025.105671

Sávio Torres de Farias , Marco José

In this work we examine different hypotheses for the fixation of DNA as the principal informational molecule. The emergence of protein RNA-dependent RNA polymerases heralded the beginning of a process that ultimately culminated in the transition from RNA to DNA as the primary informational molecule. To understand this pivotal transition, it is necessary to examine the evolutionary history of nucleic acid polymerases, with particular emphasis on RNA-dependent RNA polymerases, RNA-dependent DNA polymerases, and DNA-dependent DNA polymerases. Instead of resolving the debates over single versus multiple origins of DNA, we adhere to the need to conceptualize early evolution as a dynamic network, driven by horizontal transfer, molecular innovation, and symbiosis between cells and viruses.

在这项工作中，我们研究了DNA作为主要信息分子固定的不同假设。蛋白质RNA依赖的RNA聚合酶的出现预示着一个过程的开始，这个过程最终达到了从RNA到DNA作为主要信息分子的转变。为了理解这一关键转变，有必要研究核酸聚合酶的进化史，特别强调RNA依赖的RNA聚合酶、RNA依赖的DNA聚合酶和DNA依赖的DNA聚合酶。我们没有解决DNA单一起源与多重起源的争论，而是坚持将早期进化概念化为一个动态网络，由水平转移、分子创新和细胞与病毒之间的共生驱动。

引用次数: 0