Mechanistic and topological explanations in medicine: the case of medical genetics and network medicine

A blueprint for a new commercial driving epidemiology: An emerging paradigm grounded in integrative exposome and network epistemologies

Excess health and safety risks of commercial drivers are largely determined by, embedded in, or operate as complex, dynamic, and randomly determined systems with interacting parts. Yet, prevailing epidemiology is entrenched in narrow, deterministic, and static exposure-response frameworks along with ensuing inadequate data and limiting methods, thereby perpetuating an incomplete understanding of commercial drivers' health and safety risks. This paper is grounded in our ongoing research that conceptualizes health and safety challenges of working people as multilayered "wholes" of interacting work and nonwork factors, exemplified by complex-systems epistemologies. Building upon and expanding these assumptions, herein we: (a) discuss how insights from integrative exposome and network-science-based frameworks can enhance our understanding of commercial drivers' chronic disease and injury burden; (b) introduce the "working life exposome of commercial driving" (WLE-CD)-an array of multifactorial and interdependent work and nonwork exposures and associated biological responses that concurrently or sequentially impact commercial drivers' health and safety during and beyond their work tenure; (c) conceptualize commercial drivers' health and safety risks as multilayered networks centered on the WLE-CD and network relational patterns and topological properties-that is, arrangement, connections, and relationships among network components-that largely govern risk dynamics; and (d) elucidate how integrative exposome and network-science-based innovations can contribute to a more comprehensive understanding of commercial drivers' chronic disease and injury risk dynamics. Development, validation, and proliferation of this emerging discourse can move commercial driving epidemiology to the frontier of science with implications for policy, action, other working populations, and population health at large.

Phenomenological physiotherapy: extending the concept of bodily intentionality

This study clarifies the need for a renewed account of the body in physiotherapy to fill sizable gaps between physiotherapeutical theory and practice. Physiotherapists are trained to approach bodily functioning from an objectivist perspective; however, their therapeutic interactions with patients are not limited to the provision of natural-scientific explanations. Physiotherapists' practice corresponds well to theorisation of the body as the bearer of original bodily intentionality, as outlined by Merleau-Ponty and elaborated upon by enactivists. We clarify how physiotherapeutical practice corroborates Merleau-Ponty's critical arguments against objectivist interpretations of the body; particularly, his analyses demonstrate that norms of optimal corporeal functioning are highly individual and variable in time and thus do not directly depend on generic physiological structures. In practice, objectively measurable physical deviations rarely correspond to specific subjective difficulties and, similarly, patients' reflective insights into their own motor deficiencies do not necessarily produce meaningful motor improvements. Physiotherapeutical procedures can be understood neither as mechanical manipulations of patients' machine-like bodies by experts nor as a process of such manipulation by way of instructing patients' explicit conscious awareness. Rather, physiotherapeutical practice and theory can benefit from the philosophical interpretation of motor disorders as modifications of bodily intentionality. Consequently, motor performances addressed in physiotherapy are interpreted as relational features of a living organism coupled with its environment, and motor disorders are approached as failures to optimally manage the motor requirements of a given situation owing to a relative loss of the capacity to structure one's relation with their environment through motor action. Building on this, we argue that the process of physiotherapy is most effective when understood as a bodily interaction to guide patients towards discovering better ways of grasping a situation as meaningful through bodily postures and movements.

Approaches in Post-Experimental Science. The Case of Precision Medicine

In the introduction to his Spalt und Fuge, Hans-Jörg Rheinberger points to the possibility that we are currently experiencing a new turning point regarding forms of experimentation, which is characterized by the growing importance of high-throughput methods and big data analytics. This essay will explore the thesis that data-intensive research indeed constitutes a form of post-experimental research by interrogating research practices in precision medicine. Section 1 will introduce this thesis and highlight salient features of precision medicine as an example of post-experimental research. Section 2 suggests approach as a category that is broader than experimental system, as discussed by Rheinberger, and can serve to analyze and compare diverse forms of research, including experimental and post-experimental practices. The essay concludes with a reflection on how categories developed for the historiography of recent science might require an update when the science or its context changes (section 3).

Integrating Philosophy of Understanding With the Cognitive Sciences

We provide two programmatic frameworks for integrating philosophical research on understanding with complementary work in computer science, psychology, and neuroscience. First, philosophical theories of understanding have consequences about how agents should reason if they are to understand that can then be evaluated empirically by their concordance with findings in scientific studies of reasoning. Second, these studies use a multitude of explanations, and a philosophical theory of understanding is well suited to integrating these explanations in illuminating ways.

Using network models in person-centered care in psychiatry: How perspectivism could help to draw boundaries

In this paper, we explore the conceptual problems that arise when using network analysis in person-centered care (PCC) in psychiatry. Personalized network models are potentially helpful tools for PCC, but we argue that using them in psychiatric practice raises boundary problems, i.e., problems in demarcating what should and should not be included in the model, which may limit their ability to provide clinically-relevant knowledge. Models can have explanatory and representational boundaries, among others. We argue that perspectival reasoning can make more explicit what questions personalized network models can address in PCC, given their boundaries.

Are topological explanations really free of mechanisms?

Topological explanations in biology have been largely assumed to be free of mechanisms. However, by examining two classic topological explanations in the philosophical literature, this article has identified mechanisms in the corrected and complete formulations of both explanations. This constitutes the major work of this article. The minor work of this article is to address a follow-up question: given that these two topological explanations contain mechanisms, would this significantly blur the widely assumed boundary between topological and mechanistic explanations? My answer to this question is negative and the argument I have developed is that although these two topological explanations contain mechanisms, these mechanisms are explanatorily irrelevant to the target properties, which is in stark contrast to the situation in mechanistic explanations.

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'.

Computational Inference of Gene Co-Expression Networks for the identification of Lung Carcinoma Biomarkers: An Ensemble Approach

Gene Networks (GN), have emerged as an useful tool in recent years for the analysis of different diseases in the field of biomedicine. In particular, GNs have been widely applied for the study and analysis of different types of cancer. In this context, Lung carcinoma is among the most common cancer types and its short life expectancy is partly due to late diagnosis. For this reason, lung cancer biomarkers that can be easily measured are highly demanded in biomedical research. In this work, we present an application of gene co-expression networks in the modelling of lung cancer gene regulatory networks, which ultimately served to the discovery of new biomarkers. For this, a robust GN inference was performed from microarray data concomitantly using three different co-expression measures. Results identified a major cluster of genes involved in SRP-dependent co-translational protein target to membrane, as well as a set of 28 genes that were exclusively found in networks generated from cancer samples. Amongst potential biomarkers, genes N C K A P 1 L and D M D are highlighted due to their implications in a considerable portion of lung and bronchus primary carcinomas. These findings demonstrate the potential of GN reconstruction in the rational prediction of biomarkers.