新颖的图像分析方法揭示了对粘菌网络适应性微调的新见解。

IF 2.9 3区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Royal Society Open Science Pub Date : 2024-10-30 eCollection Date: 2024-10-01 DOI:10.1098/rsos.240950
Philipp Rosina, Martin Grube
{"title":"新颖的图像分析方法揭示了对粘菌网络适应性微调的新见解。","authors":"Philipp Rosina, Martin Grube","doi":"10.1098/rsos.240950","DOIUrl":null,"url":null,"abstract":"<p><p>This study introduces a novel methodology to explore the network dynamics of <i>Physarum polycephalum</i>, an organism celebrated for its remarkable adaptive capabilities. We used two innovative techniques to analyse its growth behaviour and network modifications under stress conditions, including starvation and differential epinephrine exposures. The first method provided a quantitative assessment of growth and exploration over time. The second method provided a detailed examination of vein diameter and contraction patterns, illuminating the physiological adjustments <i>P. polycephalum</i> undergoes in response to environmental challenges. By integrating these approaches, we were able to estimate the total network volume of the organism, with a focus on the normalized estimated volume, unveiling insightful aspects of its structural adaptations. While starvation reduced the volume, indicating a significant structural compromise, low and high epinephrine concentrations maintained a volume-to-area ratio comparable with the control. Determining the fractal dimension of the networks over time revealed a fine-tuning of the network complexity in response to environmental conditions, with significant reductions under stress indicating a constrained network adaptation strategy. These methods, novel in their application to <i>P. polycephalum</i>, provide a framework for future studies and a basis for exploring complex network behaviours with potential applications in bioengineering and adaptive network design.</p>","PeriodicalId":21525,"journal":{"name":"Royal Society Open Science","volume":"11 10","pages":"240950"},"PeriodicalIF":2.9000,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11528663/pdf/","citationCount":"0","resultStr":"{\"title\":\"Novel image-analytic approach reveals new insights in fine-tuning of slime mould network adaptation.\",\"authors\":\"Philipp Rosina, Martin Grube\",\"doi\":\"10.1098/rsos.240950\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This study introduces a novel methodology to explore the network dynamics of <i>Physarum polycephalum</i>, an organism celebrated for its remarkable adaptive capabilities. We used two innovative techniques to analyse its growth behaviour and network modifications under stress conditions, including starvation and differential epinephrine exposures. The first method provided a quantitative assessment of growth and exploration over time. The second method provided a detailed examination of vein diameter and contraction patterns, illuminating the physiological adjustments <i>P. polycephalum</i> undergoes in response to environmental challenges. By integrating these approaches, we were able to estimate the total network volume of the organism, with a focus on the normalized estimated volume, unveiling insightful aspects of its structural adaptations. While starvation reduced the volume, indicating a significant structural compromise, low and high epinephrine concentrations maintained a volume-to-area ratio comparable with the control. Determining the fractal dimension of the networks over time revealed a fine-tuning of the network complexity in response to environmental conditions, with significant reductions under stress indicating a constrained network adaptation strategy. These methods, novel in their application to <i>P. polycephalum</i>, provide a framework for future studies and a basis for exploring complex network behaviours with potential applications in bioengineering and adaptive network design.</p>\",\"PeriodicalId\":21525,\"journal\":{\"name\":\"Royal Society Open Science\",\"volume\":\"11 10\",\"pages\":\"240950\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2024-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11528663/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Royal Society Open Science\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1098/rsos.240950\",\"RegionNum\":3,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/10/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Royal Society Open Science","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1098/rsos.240950","RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/10/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

本研究介绍了一种新的方法来探索多头瘤 Physarum 的网络动力学,这种生物因其卓越的适应能力而闻名。我们使用了两种创新技术来分析它在饥饿和不同肾上腺素暴露等压力条件下的生长行为和网络变化。第一种方法提供了对生长和探索随时间变化的定量评估。第二种方法对静脉直径和收缩模式进行了详细研究,揭示了多头豹在应对环境挑战时所经历的生理调整。通过整合这些方法,我们能够估算出生物体的总网络体积,重点是归一化估算体积,从而揭示其结构适应性的深刻方面。饥饿使体积缩小,表明结构受到严重破坏,而低浓度和高浓度肾上腺素则使体积与面积之比保持在与对照组相当的水平。测定网络随时间变化的分形维度显示,网络的复杂性随环境条件的变化而微调,在压力下网络复杂性显著降低,这表明网络的适应策略受到限制。这些方法在应用于多头蛇尾草方面很新颖,为今后的研究提供了一个框架,为探索复杂的网络行为提供了基础,在生物工程和自适应网络设计方面具有潜在的应用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Novel image-analytic approach reveals new insights in fine-tuning of slime mould network adaptation.

This study introduces a novel methodology to explore the network dynamics of Physarum polycephalum, an organism celebrated for its remarkable adaptive capabilities. We used two innovative techniques to analyse its growth behaviour and network modifications under stress conditions, including starvation and differential epinephrine exposures. The first method provided a quantitative assessment of growth and exploration over time. The second method provided a detailed examination of vein diameter and contraction patterns, illuminating the physiological adjustments P. polycephalum undergoes in response to environmental challenges. By integrating these approaches, we were able to estimate the total network volume of the organism, with a focus on the normalized estimated volume, unveiling insightful aspects of its structural adaptations. While starvation reduced the volume, indicating a significant structural compromise, low and high epinephrine concentrations maintained a volume-to-area ratio comparable with the control. Determining the fractal dimension of the networks over time revealed a fine-tuning of the network complexity in response to environmental conditions, with significant reductions under stress indicating a constrained network adaptation strategy. These methods, novel in their application to P. polycephalum, provide a framework for future studies and a basis for exploring complex network behaviours with potential applications in bioengineering and adaptive network design.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Royal Society Open Science
Royal Society Open Science Multidisciplinary-Multidisciplinary
CiteScore
6.00
自引率
0.00%
发文量
508
审稿时长
14 weeks
期刊介绍: Royal Society Open Science is a new open journal publishing high-quality original research across the entire range of science on the basis of objective peer-review. The journal covers the entire range of science and mathematics and will allow the Society to publish all the high-quality work it receives without the usual restrictions on scope, length or impact.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信