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Heino MTJ, Proverbio D, Saurio K, Siegenfeld A, Hankonen N. From a false sense of safety to resilience under uncertainty. Front Psychol 2024; 15:1346542. [PMID: 38860037 PMCID: PMC11164187 DOI: 10.3389/fpsyg.2024.1346542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 04/24/2024] [Indexed: 06/12/2024] Open
Abstract
Understanding and acting upon risk is notably challenging, and navigating complexity with understandings developed for stable environments may inadvertently build a false sense of safety. Neglecting the potential for non-linear change or "black swan" events - highly impactful but uncommon occurrences - may lead to naive optimisation under assumed stability, exposing systems to extreme risks. For instance, loss aversion is seen as a cognitive bias in stable environments, but it can be an evolutionarily advantageous heuristic when complete destruction is possible. This paper advocates for better accounting of non-linear change in decision-making by leveraging insights from complex systems and psychological sciences, which help to identify blindspots in conventional decision-making and to develop risk mitigation plans that are interpreted contextually. In particular, we propose a framework using attractor landscapes to visualize and interpret complex system dynamics. In this context, attractors are states toward which systems naturally evolve, while tipping points - critical thresholds between attractors - can lead to profound, unexpected changes impacting a system's resilience and well-being. We present four generic attractor landscape types that provide a novel lens for viewing risks and opportunities, and serve as decision-making contexts. The main practical contribution is clarifying when to emphasize particular strategies - optimisation, risk mitigation, exploration, or stabilization - within this framework. Context-appropriate decision making should enhance system resilience and mitigate extreme risks.
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Affiliation(s)
- Matti T. J. Heino
- Faculty of Social Sciences, Unit of Social Research, Tampere University, Tampere, Finland
- Faculty of Social Sciences, Discipline of Social Psychology, University of Helsinki, Helsinki, Finland
| | - Daniele Proverbio
- Department of Industrial Engineering, University of Trento, Trento, Italy
| | - Kaisa Saurio
- Faculty of Social Sciences, Unit of Social Research, Tampere University, Tampere, Finland
| | | | - Nelli Hankonen
- Faculty of Social Sciences, Unit of Social Research, Tampere University, Tampere, Finland
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Pierik L, McDonald P, Anderson ARA, West J. Second-Order Effects of Chemotherapy Pharmacodynamics and Pharmacokinetics on Tumor Regression and Cachexia. Bull Math Biol 2024; 86:47. [PMID: 38546759 DOI: 10.1007/s11538-024-01278-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 02/29/2024] [Indexed: 04/30/2024]
Abstract
Drug dose response curves are ubiquitous in cancer biology, but these curves are often used to measure differential response in first-order effects: the effectiveness of increasing the cumulative dose delivered. In contrast, second-order effects (the variance of drug dose) are often ignored. Knowledge of second-order effects may improve the design of chemotherapy scheduling protocols, leading to improvements in tumor response without changing the total dose delivered. By considering treatment schedules with identical cumulative dose delivered, we characterize differential treatment outcomes resulting from high variance schedules (e.g. high dose, low dose) and low variance schedules (constant dose). We extend a previous framework used to quantify second-order effects, known as antifragility theory, to investigate the role of drug pharmacokinetics. Using a simple one-compartment model, we find that high variance schedules are effective for a wide range of cumulative dose values. Next, using a mouse-parameterized two-compartment model of 5-fluorouracil, we show that schedule viability depends on initial tumor volume. Finally, we illustrate the trade-off between tumor response and lean mass preservation. Mathematical modeling indicates that high variance dose schedules provide a potential path forward in mitigating the risk of chemotherapy-associated cachexia by preserving lean mass without sacrificing tumor response.
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Affiliation(s)
- Luke Pierik
- Center for Complex Biological Systems, University of California Irvine, Irvine, CA, USA
| | - Patricia McDonald
- Department of Cancer Physiology, Moffitt Cancer Center, Tampa, FL, USA
| | | | - Jeffrey West
- Integrated Mathematical Oncology, Moffitt Cancer Center, Tampa, FL, USA.
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Axenie C, López-Corona O, Makridis MA, Akbarzadeh M, Saveriano M, Stancu A, West J. Antifragility as a complex system's response to perturbations, volatility, and time. ARXIV 2023:arXiv:2312.13991v1. [PMID: 38196741 PMCID: PMC10775345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
Abstract
Antifragility characterizes the benefit of a dynamical system derived from the variability in environmental perturbations. Antifragility carries a precise definition that quantifies a system's output response to input variability. Systems may respond poorly to perturbations (fragile) or benefit from perturbations (antifragile). In this manuscript, we review a range of applications of antifragility theory in technical systems (e.g., traffic control, robotics) and natural systems (e.g., cancer therapy, antibiotics). While there is a broad overlap in methods used to quantify and apply antifragility across disciplines, there is a need for precisely defining the scales at which antifragility operates. Thus, we provide a brief general introduction to the properties of antifragility in applied systems and review relevant literature for both natural and technical systems' antifragility. We frame this review within three scales common to technical systems: intrinsic (input-output nonlinearity), inherited (extrinsic environmental signals), and interventional (feedback control), with associated counterparts in biological systems: ecological (homogeneous systems), evolutionary (heterogeneous systems), and interventional (control). We use the common noun in designing systems that exhibit antifragile behavior across scales and guide the reader along the spectrum of fragility-adaptiveness-resilience-robustness-antifragility, the principles behind it, and its practical implications.
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Affiliation(s)
- Cristian Axenie
- Department of Computer Science and Center for Artificial Intelligence, Nuremberg Institute of Technology Georg Simon Ohm, Nuremberg, Germany
| | - Oliver López-Corona
- Investigadores por México (IxM) at Instituto de Investigaciones en Matemáticas Aplicadas y Sistemas (IIMAS), Universidad Nacional Autónoma de México (UNAM), Ciudad Universitaria, CDMX, México
| | | | - Meisam Akbarzadeh
- Department of Transportation Engineering, Isfahan University of Technology, Isfahan, Iran
| | - Matteo Saveriano
- Department of Industrial Engineering, University of Trento, Trento, Italy
| | - Alexandru Stancu
- Department of Electrical and Electronic Engineering, The University of Manchester, Manchester, UK
| | - Jeffrey West
- Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA
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G-Santoyo I, Ramírez-Carrillo E, Sanchez JD, López-Corona O. Potential long consequences from internal and external ecology: loss of gut microbiota antifragility in children from an industrialized population compared with an indigenous rural lifestyle. J Dev Orig Health Dis 2023; 14:469-480. [PMID: 37222148 DOI: 10.1017/s2040174423000144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Human health is strongly mediated by the gut microbiota ecosystem, which, in turn, depends not only on its state but also on its dynamics and how it responds to perturbations. Healthy microbiota ecosystems tend to be in criticality and antifragile dynamics corresponding to a maximum complexity configuration, which may be assessed with information and network theory analysis. Under this complex system perspective, we used a new analysis of published data to show that a children's population with an industrialized urban lifestyle from Mexico City exhibits informational and network characteristics similar to parasitized children from a rural indigenous population in the remote mountainous region of Guerrero, México. We propose then, that in this critical age for gut microbiota maturation, the industrialized urban lifestyle could be thought of as an external perturbation to the gut microbiota ecosystem, and we show that it produces a similar loss in criticality/antifragility as the one observed by internal perturbation due to parasitosis by the helminth A. lumbricoides. Finally, several general complexity-based guidelines to prevent or restore gut ecosystem antifragility are discussed.
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Affiliation(s)
- Isaac G-Santoyo
- Neuroecology Lab, Department of Psychology, UNAM, México, 04510
- Unidad de Investigación en Psicobiología y Neurociencias, Department of Psychology, UNAM, México, 04510
| | | | | | - Oliver López-Corona
- Investigadores por México (IxM)-CONACyT, Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas (IIMAS), UNAM, México, 04510
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Hill Y, Den Hartigh RJR. Resilience in sports through the lens of dynamic network structures. FRONTIERS IN NETWORK PHYSIOLOGY 2023; 3:1190355. [PMID: 37275962 PMCID: PMC10235604 DOI: 10.3389/fnetp.2023.1190355] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 05/12/2023] [Indexed: 06/07/2023]
Affiliation(s)
- Yannick Hill
- Department of Human Movement Sciences, Faculty of Behavioral and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, Amsterdam, Netherlands
- Institute of Brain and Behaviour Amsterdam, Amsterdam, Netherlands
- Lyda Hill Institute for Human Resilience, Colorado Springs, CO, United States
| | - Ruud J. R. Den Hartigh
- Department of Psychology, Faculty of Behavioral and Social Sciences, University of Groningen, Groningen, Netherlands
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