Viral thresholds and semiotic resonance: Rethinking the continuum between life and non-life

IF 2.1 4区 生物学 Q2 BIOLOGY
Biosystems Pub Date : 2026-01-01 Epub Date: 2025-11-28 DOI:10.1016/j.biosystems.2025.105664
Nicola Zengiaro
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引用次数: 0

Abstract

This article interrogates the ontological status of the virus, an entity that lacks cellular autonomy yet exhibits core evolutionary dynamics, to expose the limitations of classical definitions of life. The analysis moves beyond this classificatory impasse by integrating the paradigm of reticulate evolution, which repositions viruses as central agents in life's network history, with a materialist biosemiotics. This synthesis supports the paper's central thesis: that life is not an intrinsic property but an emergent condition defined by semiotic processes. To formalize this, we introduce the concept of semiotic resonance, a theoretical model defining life as the emergence of recursive interpretive coupling between material systems. This mechanism provides a physical and semiotic basis for biological organization, bridging the arbitrariness of codes with their material enactment. Ultimately, by reframing the virus as a paradigmatic case of resonance-dependent existence, this work proposes a shift in the study of life itself: away from classifying entities and toward an analysis of the relational thresholds where matter, meaning, and evolution converge.
病毒阈值与符号共振:重新思考生命与非生命之间的连续性。
本文探讨了病毒作为生命和非生命之间的阈限实体的本体论和认识论地位。基于生物符号学、理论生物学和生命起源研究的最新进展,本文认为,尽管缺乏细胞自主性,但病毒通过表现出环境依赖的代理和进化功能,挑战了经典的生命定义。通过整合符号学理论、物质生态符号学和系统生物学的跨学科方法,该研究分析了病毒准种动力学、宿主-寄生虫共同进化以及病毒复制的符号学含义。核心假说认为,生命不应该被定义为一种固定的属性,而应该被定义为一种基于符号相互作用的突现、过程和关系条件。本文建立了一个“共振符号学”的理论模型,以解释阈限实体在产生生物意义和转化中的积极作用。通过将病毒重新定义为理解生命流动边界的启发式数字,这项工作有助于在生物符号学范式中对生物个性化进行更具包容性和动态的概念化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biosystems
Biosystems 生物-生物学
CiteScore
3.70
自引率
18.80%
发文量
129
审稿时长
34 days
期刊介绍: BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.
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