Unifying the essential concepts of biological networks: biological insights and philosophical foundations by D. Kostić, C. Hilgetag and M. Tittgemeyer

 

 
Over the last decades, network-based approaches have become highly popular in diverse fields of biology, including neuroscience, ecology, molecular biology and genetics. While these approaches continue to grow very rapidly, some of their conceptual and methodological aspects still require a programmatic foundation. This challenge particularly concerns the question of whether a generalized account of explanatory, organizational and descriptive levels of networks can be applied universally across biological sciences. To this end, this highly interdisciplinary theme issue focuses on the definition, motivation and application of key concepts in biological network science, such as explanatory power of distinctively network explanations, network levels and network hierarchies.
This article is part of the theme issue ‘Unifying the essential concepts of biological networks: biological insights and philosophical foundations’.
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General Theory of Topological Explanations and Explanatory Asymmetry

 

 
In this paper, I present a general theory of topological explanations, and illustrate its fruitfulness by showing how it accounts for explanatory asymmetry. My argument is developed in three steps. In the first step, I show what it is for some topological property A to explain some physical or dynamical property B . Based on that, I derive three key criteria of successful topological explanations: a criterion concerning the facticity of topological explanations, i.e. what makes it true of a particular system; a criterion for describing counterfactual dependencies in two explanatory modes, i.e. the vertical and the horizontal and, finally, a third perspectival one that tells us when to use the vertical and when to use the horizontal mode. In the second step, I show how this general theory of topological explanations accounts for explanatory asymmetry in both the vertical and horizontal explanatory modes. Finally, in the third step, I argue that this theory is universally applicable across biological sciences, which helps in unifying essential concepts of biological networks. This article is part of the theme issue ‘Unifying the essential concepts of biological networks: biological insights and philosophical foundations’.
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Defining aging by Maël Lemoine

 

 
Aging is an elusive property of life, and many important questions about aging depend on its definition. This article proposes to draw a definition from the scientific literature on aging. First, a broad review reveals five features commonly used to define aging: structural damage, functional decline, depletion, typical phenotypic changes or their cause, and increasing probability of death. Anything that can be called ‘aging’ must present one of these features. Then, although many conditions are not consensual instances of aging, aging is consensually described as a process of loss characterized by a rate and resulting from the counteraction of protective mechanisms against mechanisms that limit lifespan. Beyond such an abstract definition, no one has yet succeeded in defining aging by a specific mechanism of aging because of an explanatory gap between such a mechanism and lifespan, a consensual explanandum of a theory of aging. By contrast, a sound theoretical definition can be obtained by revisiting the evolutionary theory of aging. Based on this theory, aging evolves thanks to the impossibility that natural selection eliminates late traits that are neutral mainly due to decreasing selective pressure. Yet, the results of physiological research suggest that this theory should be revised to also account for the small number of different aging pathways and for the existence of mechanisms counteracting these pathways, that must, on the contrary, have been selected. A synthetic, but temporary definition of aging can finally be proposed.
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Not by structures alone: Can the immune system recognize microbial functions? by G. Greslehner

 

 
A central question for immunology is: what does the immune system recognize and according to which principles does this kind of recognition work? Immunology has been dominated by the idea of recognizing molecular structures and triggering an appropriate immune response when facing non-self or danger. Recently, characterizations in terms of function have turned out to be more conserved and explanatory in microbiota research than taxonomic composition for understanding microbiota-host interactions. Starting from a conceptual analysis of the notions of structure and function, I raise the title question whether it is possible for the immune system to recognize microbial functions. I argue that this is indeed the case, making the claim that some function-associated molecular patterns are not indicative of the presence of certain taxa (‘‘who is there’’) but of biochemical activities and effects (‘‘what is going on’’). In addition, I discuss case studies which show that there are immunological sensors that can directly detect microbial activities, irrespective of their specific structural manifestation. At the same time, the discussed account puts the causal role notions of function on a more realist and objective basis.
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Mechanistic vs Statistical Extrapolation in Preclinical Research in Psychiatry: Challenging the Received View by M. Lemoine and al.

 

 
This chapter questions the received view that in medical research extrapolation from animal models mainly consists in establishing mechanisms of human pathological states in organisms, thanks to a step by step comparison of causal pathways. Mechanistic extrapolation takes the form: (1) cause C brings out effect E in animal through causal pathway M, (2) M is similar in animals and humans, (3) therefore C will likely bring out E in humans. As the example of psychiatric research shows, such mechanistic extrapolation may be replaced by statistical extrapolation, an inference of the form: (1) An animal model A has been successful in predicting the effects E of drugs D1…Dn of a certain class; (2) A will be successful again in predicting the effects of a new drug Dn+1 of the same class. Statistical extrapolation relies on the predictive validity of a given animal model, without any knowledge of the mechanisms involved, on the sole ground of past successes of the model in predicting the effects of a class of drugs on their human target.
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A dual decomposition strategy of both microbial and phenotypic components for a better understanding of causal claims by G. P. Greslehner & M. Lemoine

 

 
In our commentary on Lynch et al.’s target paper (Biol Philos, 2019. https://doi.org/10.1007/s10539-019-9702-2), we focus on decomposition as a research strategy. We argue that not only the presumptive microbial causes but also their supposed phenotypic effects need to be decomposed relative to each other. Such a dual decomposition strategy ought to improve the way in which causal claims in microbiome research can be made and understood.
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Right out of the box: How to situate metaphysics of science in relation to other metaphysical approaches, by A. Guay & T. Pradeu

 

 
Several advocates of the lively field of “metaphysics of science” have recently argued that a naturalistic metaphysics should be based solely on current science, and that it should replace more traditional, intuition-based, forms of metaphysics. The aim of the present paper is to assess that claim by examining the relations between metaphysics of science and general metaphysics. We show that the current metaphysical battlefield is richer and more complex than a simple dichotomy between “metaphysics of science” and “traditional metaphysics”, and that it should instead be understood as a three dimensional “box”, with one axis distinguishing “descriptive metaphysics” from “revisionary metaphysics”, a second axis distinguishing a priori from a posteriori metaphysics, and a third axis distinguishing “commonsense metaphysics”, “traditional metaphysics” and “metaphysics of science”. We use this three-dimensional figure to shed light on the project of current metaphysics of science, and to demonstrate that, in many instances, the target of that project is not defined with enough precision and clarity.
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Philosophy of Immunology by Thomas Pradeu

 

 
Immunology is central to contemporary biology and medicine, but it also provides novel philosophical insights. Its most significant contribution to philosophy concerns the understanding of biological individuality: what a biological individual is, what makes it unique, how its boundaries are established and what ensures its identity through time. Immunology also offers answers to some of the most interesting philosophical questions. What is the definition of life? How are bodily systems delineated? How do the mind and the body interact? In this Element, Thomas Pradeu considers the ways in which immunology can shed light on these and other important philosophical issues. This title is also available as Open Access on Cambridge Core.
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Philosophy of Biology: Characterizing causality in cancer by E. Rondeau, T. Pradeu and al.

 

 
Philosophers have explored the concept of causality for centuries. Here we argue that ideas about causality from philosophy can help scientists to better understand how cancerous tumors grow and spread in the body. After outlining six characteristics of causality that are relevant to cancer, we emphasize the importance of feedback loops and interactions between tumor-cell-intrinsic and tumor-cell-extrinsic factors for explaining the formation and dissemination of tumors.
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Frontiers in Physiology: Understanding Multicellularity – The Functional Organization of the Intercellular Space

Multicellularity exists in all domains of life, spanning from microbial biofilms to plans and metazoans. Clearly multicellularity offers many advantages (increase in size, division of labor, increased complexity), but also comes with a number of challenges (control and coordination of cells, availability of nutrients and signaling molecules,…).

A number of publications have looked at the solutions found by living organisms to counter the problems of multicellularity. Practically all of those studies have taken a cell-center point of view in their analysis. The authors of this article argue that seeing cells as the only actors in multicellularity has led to the omission of some fundamental features. In order to fully understand multicellular forms of life, the authors claim that the intercellular space has to be taken into account. By this they mean not only considering the space in which cells operate, and how they specify it, but also how the organization of space, in turn, has a direct influence on cell fate and behavior. Read more here.