Biosystems最新文献

{"title":"“Assembly Theory” in life-origin models: A critical review","authors":"David Lynn Abel","doi":"10.1016/j.biosystems.2024.105378","DOIUrl":"10.1016/j.biosystems.2024.105378","url":null,"abstract":"<div><div>Any homeostatic protometabolism would have required orchestration of disparate biochemical pathways into integrated circuits. Extraordinarily specific molecular assemblies were also required at the right time and place. Assembly Theory conflated with its cousins—Complexity Theory, Chaos theory, Quantum Mechanics, Irreversible Nonequilibrium Thermodynamics and Molecular Evolution theory— collectively have great naturalistic appeal in hopes of their providing the needed exquisite steering and controls. They collectively offer the best hope of circumventing the need for active selection required to formally orchestrate bona fide formal organization (as opposed to the mere self-ordering of chaos theory) (Abel and Trevors, 2006b). This paper focuses specifically on AT's contribution to naturalistic life-origin models.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"247 ","pages":"Article 105378"},"PeriodicalIF":2.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142878459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cancer memory as a mechanism to establish malignancy","authors":"Thomas Lissek","doi":"10.1016/j.biosystems.2024.105381","DOIUrl":"10.1016/j.biosystems.2024.105381","url":null,"abstract":"<div><div>Cancers during oncogenic progression hold information in epigenetic memory which allows flexible encoding of malignant phenotypes and more rapid reaction to the environment when compared to purely mutation-based clonal evolution mechanisms. Cancer memory describes a proposed mechanism by which complex information such as metastasis phenotypes, therapy resistance and interaction patterns with the tumor environment might be encoded at multiple levels via mechanisms used in memory formation in the brain and immune system (e.g. single-cell epigenetic changes and distributed state modifications in cellular ensembles). Carcinogenesis might hence be the result of physiological multi-level learning mechanisms unleashed by defined heritable oncogenic changes which lead to tumor-specific loss of goal state integration into the whole organism. The formation of cancer memories would create and bind new levels of individuality within the host organism into the entity we call cancer. Translational implications of cancer memory are that cancers could be engaged at higher organizational levels (e.g. be “trained” for memory extinction) and that compounds that are known to interfere with memory processes could be investigated for their potential to block cancer memory formation or recall. It also suggests that diagnostic measures should extend beyond sequencing approaches to functional diagnosis of cancer physiology.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"247 ","pages":"Article 105381"},"PeriodicalIF":2.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142865877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to “Cosmos, mind, matter: Is mind in spacetime?” [Biosyst. (2024) 105262]","authors":"Stuart Kauffman ,&nbsp;Sudip Patra","doi":"10.1016/j.biosystems.2024.105333","DOIUrl":"10.1016/j.biosystems.2024.105333","url":null,"abstract":"","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"246 ","pages":"Article 105333"},"PeriodicalIF":2.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cosmos, mind, matter: Is mind in spacetime?","authors":"Stuart Kauffman ,&nbsp;Sudip Patra","doi":"10.1016/j.biosystems.2024.105332","DOIUrl":"10.1016/j.biosystems.2024.105332","url":null,"abstract":"<div><div>We attempt in this article to formulate a conceptual and testable framework weaving Cosmos, Mind and Matter into a whole. We build on three recent discoveries, each requiring more evidence: i. The particles of the Standard Model, SU(3) × SU(2) × U(1), are formally capable of collective autocatalysis. This leads us to ask what roles such autocatalysis may have played in Cosmogenesis, and in trying to answer, Why our Laws? Why our Constants? A capacity of the particles of SU(3) × SU(2) × U(1) for collective autocatalysis may be open to experimental test, stunning if confirmed. ii. Reasonable evidence now suggests that matter can expand spacetime. The first issue is to establish this claim at or beyond 5 sigma if that can be done. If true, this process may elucidate Dark Matter, Dark Energy and Inflation and require alteration of Einstein's Field Equations. Cosmology would be transformed. iii. Evidence at 6.49 Sigma suggests that mind can alter the outcome of the two-slit experiment. If widely and independently verified, the foundations of quantum mechanics must be altered. Mind plays a role in the universe. That role may include Cosmic Mind.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"246 ","pages":"Article 105332"},"PeriodicalIF":2.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142309003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding cancer from a biophysical, developmental and systems biology perspective using the landscapes-attractor model","authors":"Thomas W. Grunt","doi":"10.1016/j.biosystems.2024.105376","DOIUrl":"10.1016/j.biosystems.2024.105376","url":null,"abstract":"<div><div>Biophysical, developmental and systems-biology considerations enable deeper understanding why cancer is life threatening despite intensive research. Here we use two metaphors. Both conceive the cell genome and the encoded molecular system as an interacting gene regulatory network (GRN). According to Waddington's epigenetic (quasi-potential)-landscape, an instrumental tool in ontogenetics, individual interaction patterns ( = expression profiles) within this GRN represent possible cell states with different stabilities. Network interactions with low stability are represented on peaks. Unstable interactions strive towards regions with higher stability located at lower altitude in valleys termed attractors that correspond to stable cell phenotypes. Cancer cells are seen as GRNs adopting aberrant semi-stable attractor states (cancer attractor). In the second metaphor, Wright's phylogenetic fitness (adaptive) landscape, each genome ( = GRN) is assigned a specific position in the landscape according to its structure and reproductive fitness in the specific environment. High elevation signifies high fitness and low altitude low fitness. Selection ensures that mutant GRNs evolve and move from valleys to peaks. The genetic flexibility is highlighted in the fitness landscape, while non-genetic flexibility is captured in the quasi-potential landscape. These models resolve several inconsistencies that have puzzled cancer researchers, such as the fact that phenotypes generated by non-genetic mechanisms coexist in a single tumor with phenotypes caused by mutations and they mitigate conflicts between cancer theories that claim cancer is caused by mutation (somatic mutation theory) or by disruption of tissue architecture (tissue organization field theory). Nevertheless, spontaneous mutations play key roles in cancer. Remarkable, fundamental natural laws such as the second law of thermodynamics and quantum mechanics state that mutations are inevitable events. The good side of this is that without mutational variability in DNA, evolutionary development would not have occurred, but its bad side is that the occurrence of cancer is essentially inevitable. In summary, both landscapes together fully describe the behavior of cancer under normal and stressful conditions such as chemotherapy. Thus, the landscapes-attractor model fully describes cancer cell behavior and offers new perspectives for future treatment.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"247 ","pages":"Article 105376"},"PeriodicalIF":2.0,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142711773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A workflow for the hybrid modelling and simulation of multi-timescale biological systems","authors":"Mostafa Herajy ,&nbsp;Fei Liu ,&nbsp;Monika Heiner","doi":"10.1016/j.biosystems.2024.105365","DOIUrl":"10.1016/j.biosystems.2024.105365","url":null,"abstract":"<div><div>With the steady advance of in-silico biological experimentation, model construction and simulation becomes a ubiquitous tool to understand and predict the behaviour of many biological systems. However, biological processes may contain components from different types of reaction networks, resulting in models with different (e.g., slow and fast) timescales. Hybrid simulation is one approach which can be employed to efficiently execute multi-timescale models. In this paper, we present a methodology and workflow utilizing (coloured) hybrid Petri nets to construct smaller and more complicated hybrid models. The presented workflow integrates algorithms and ideas from hybrid simulation of biochemical reaction networks as well as Petri nets. We also construct multi-timescale hybrid models and then show how these models can be efficiently executed using three different advanced hybrid simulation algorithms.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"247 ","pages":"Article 105365"},"PeriodicalIF":2.0,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142695966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The existence of the two domains of life, Bacteria and Archaea, would in itself imply that LUCA and the ancestors of these domains were progenotes","authors":"Massimo Di Giulio","doi":"10.1016/j.biosystems.2024.105375","DOIUrl":"10.1016/j.biosystems.2024.105375","url":null,"abstract":"<div><div>The length of the deepest branches of the tree of life would tend to support the hypothesis that the distance of the branch that separates the sequences of archaea from those of bacteria, i.e. the interdomain one, is longer than the intradomain ones, i.e. those that separate the sequences of archaea and those of bacteria within them. Why should interdomain distance be larger than intradomain distances? The fact that the rate of amino acid substitutions was slowed as the domains of life appeared would seem to imply an evolutionary transition. The slowdown in the speed of evolution that occurred during the formation of the two domains of life would be the consequence of the progenote- &gt; cell evolutionary transition. Indeed, the evolutionary stage of the progenote being characterized by an accelerated tempo and mode of evolution might explain the considerable interdomain distance because the accumulation of many amino acid substitutions on this branch would indicate the progenote stage that is also characterized by a high rate of amino acid substitutions. Furthermore, the fact that intradomain distances are smaller than interdomain distances would corroborate the hypothesis of the achievement of cellularity at the appearance of the main phyletic lineages. Indeed, the cell stage, unlike the progenotic one, definitively establishes the relationship between the genotype and phenotype, lowering the rate of evolution. Therefore, the arguments presented lead to the conclusion that LUCA was a progenote.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"247 ","pages":"Article 105375"},"PeriodicalIF":2.0,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142693809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Benchmark for quantitative characterization of circadian clock cycles","authors":"Odile Burckard ,&nbsp;Michèle Teboul ,&nbsp;Franck Delaunay ,&nbsp;Madalena Chaves","doi":"10.1016/j.biosystems.2024.105363","DOIUrl":"10.1016/j.biosystems.2024.105363","url":null,"abstract":"<div><div>Understanding circadian clock mechanisms is fundamental in order to counteract the harmful effects of clock malfunctioning and associated diseases. Biochemical, genetic and systems biology approaches have provided invaluable information on the mechanisms of the circadian clock, from which many mathematical models have been developed to understand the dynamics and quantitative properties of the circadian oscillator. To better analyze and compare quantitatively all these circadian cycles, we propose a method based on a previously proposed circadian cycle segmentation into stages. We notably identify a sequence of eight stages that characterize the progress of the circadian cycle. Next, we apply our approach to an experimental dataset and to five different models, all built with ordinary differential equations. Our method permits to assess the agreement of mathematical model cycles with biological properties or to detect some inconsistencies. As another application of our method, we provide insights on how this segmentation into stages can help to analyze the effect of a clock gene loss of function on the dynamic of a genetic oscillator. The strength of our method is to provide a benchmark for characterization, comparison and improvement of new mathematical models of circadian oscillators in a wide variety of model systems.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"247 ","pages":"Article 105363"},"PeriodicalIF":2.0,"publicationDate":"2024-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142649571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sensing, feeling and sentience in unicellular organisms and living cells","authors":"F. Baluška ,&nbsp;W.B. Miller ,&nbsp;P. Slijepcevic ,&nbsp;A.S. Reber","doi":"10.1016/j.biosystems.2024.105374","DOIUrl":"10.1016/j.biosystems.2024.105374","url":null,"abstract":"<div><div>Cells represent the basic units of life, not only as structural building blocks, but also as cognitive agents endowed with subjective cellular feelings, sentience (consciousness), and cognitive infocomputatioal competence. Living cells act as ‘Kantian Wholes’: All of its parts exist for and by means of the whole system, allowing cells to use sentient agency for solving existential problems and evolve as living self-organizing units. Cell sentience is based on its excitable plasma membrane generating bioelectromagnetic fields that link to a whole-cell sensory architecture. This cellular sensory apparatus, termed its senome, represents the totality of cellular self-referential information obtained by cells via their sensory systems, including the subjective cellular inside and the cell’s self-referential appraisal of its external environment. The plasma membrane was ‘invented’ by the very first cells and has been uninterruptedly inherited by cells for billions of years through successive cell divisions.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"247 ","pages":"Article 105374"},"PeriodicalIF":2.0,"publicationDate":"2024-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142649686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Senescence, change, and competition: When the desire to pick one model harms our understanding","authors":"André C.R. Martins","doi":"10.1016/j.biosystems.2024.105364","DOIUrl":"10.1016/j.biosystems.2024.105364","url":null,"abstract":"<div><div>The question of why we age is a fundamental one. It is about who we are, and it also might have critical practical aspects as we try to find ways to age slower. Or to not age at all. Different reasons point at distinct strategies for the research of anti-aging drugs. While the main reason why biological systems work as they do is evolution, for quite a while, it was believed that aging required another explanation. Aging seems to harm individuals so much that even if it has group benefits, those benefits were unlikely to be enough. That has led many scientists to propose non-evolutionary explanations as to why we age. But those theories seem to fail at explaining all the data on how species age. Here, I will show that the insistence of finding the one idea that explains it all might be at the root of the difficulty of getting a full picture. By exploring an evolutionary model of aging where locality and temporal changes are fundamental aspects of the problem, I will show that environmental change causes the barrier for group advantages to become much weaker. That weakening might help small group advantages to add up to the point they could make an adaptive difference. To answer why we age, we might have to abandon asking which models are correct. The full answer might come from considering how much each hypothesis behind each existing model, evolutionary and non-evolutionary ones, contributes to the real world’s solution.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"247 ","pages":"Article 105364"},"PeriodicalIF":2.0,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142632119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}