Organismality grounds species collective responsibility

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Evidence-Based Policies? The Covid 19 Pandemic and the Prospects of Evidence Integration

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The Multi-Causal Basis of Developmental Potential Construction

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Epistemological prospects of evolutionary models of the growth of knowledge.

In the thesis I will argue that some models of evolutionary epistemology provide an extremely illuminating and original explanation of the workings of the scientific process. Evolutionary approaches to the growth of scientific knowledge have been criticised because of the putative existence of fundamental disanalogies between biological and scientific selective processes. I will show that these criticisms are largely misguided. I will distinguish two main kinds of evolutionary models. EEM models, which focus on the evolution of human cognitive mechanisms by natural selection (e.g. that developed by Ruse), do not provide a satisfactory basis on which to explain the nature of scientific selection processes, which are cultural rather than biological in origin. EET models, by contrast, focusing on the cultural and social origins of the selective systems operating in science, are better suited to this task. I will focus mainly on the EET models proposed by Donald Campbell and David Hull. Two general themes emerge from their analysis: the emphasis on the general validity of the variation-selection model of knowledge acquisition (i.e. trial-and-error), and the view that science is a socially adaptive and adapted system, governed by the action of peculiar selective mechanisms that partially lead to epistemic success. On the basis of the critical examination of these EET models I will argue for three main conclusions. First, EET approaches are correct in rejecting the methodological individualism so central to many alternative epistemologies. Second, EET models offer us genuinely normative epistemological insights, particularly where social epistemology is concerned. Third, EET provides a viable naturalistic alternative to social constructivism, by justifying epistemic standards as "evolutionary constructions" (i.e., products of selection processes)

Of humans and lichens

La versión estadística del concepto de naturaleza humana sigue siendo un concepto central en muchas ramas de las ciencias humanas. La clave del concepto es que existe un núcleo de fenotipos específicos que caracteriza a las especies biológicas, incluyendo la nuestra. Llamo a esta perspectiva esencialismo estadístico. Voy a sugerir que la tipicidad y la uniformidad fenotípica se consideran supuestos legítimos en muchas ciencias humanas, ya que el desarrollo biológico se interpreta como un proceso inherentemente conservador que utiliza sólo recursos endógenos, mientras que la evolución se interpreta como un proceso de normalización que destruye la variación fenotípica. Llamo a esta visión perspectiva homeostática. Voy a criticar la perspectiva homeostática presentando argumentos apoyados en consideraciones teóricas y empíricas. En particular, voy a destacar dos prejuicios anacrónicos que se encuentran en el corazón de la perspectiva homeostática: en primer lugar, su visión monomórfica de las especies, así como su visión monoorganísmica y monogenómica del organismo; en segundo lugar, su compromiso con una visión causal endógena del desarrollo. Finalmente voy a argumentar que el esencialismo estadístico es problemático porque respalda los mismos prejuicios monistas y endógenos que caracterizan la perspectiva homeostática. Parafraseando a Margulis y Sagan, los científicos pueden engañarse fácilmente al descuidar la investigación sobre la diversidad humana y la plasticidad del desarrollo.A statistical version of the concept of human nature remains a major foundational concept in many branches of the human sciences. The kernel of the concept is that there exists a core of species-specific phenotypes that characterises biological species, including ours. I call this view statistical essentialism. I will suggest that phenotypic typicality and uniformity are considered legitimate assumptions in many human sciences because biological development is interpreted as an inherently conservative process utilising only endogenous developmental resources, while evolution is interpreted as a normalizing process destroying phenotypic variation. I call this view homeostatic perspective. I will criticise the homeostatic perspective by presenting arguments supported by both theoretical considerations and empirical evidence. In particular, I will emphasise two anachronistic biases at the heart of the homeostatic perspective: first, its mono-morphic view of species as well as mono-organismic and mono-genomic view of the organism; secondly, its commitment to an endogenous view of developmental causation. I will finally argue that statistical essentialism is problematic because it endorses the same monistic and endogenous prejudices characterising the homeostatic perspective. Paraphrasing Margulis and Sagan, human scientists can easily fool themselves by neglecting research on human diversity and developmental plasticity

A relational-constructionist account of protein macrostructure and function

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Epigenesis and pre-formationism: radiography of an inconclusive antinomy

El desarrollo embriológico es un fenómeno que ha inspirado la especulación filosófica desde temprano en la historia del pensamiento. Desde los tiempos de Aristóteles dos modelos conceptuales antitéticos se han utilizado tradicionalmente para comprender la embriogénesis: o el embrión posee ya una forma o estructura, o ésta se forma de nuevo en cada generación. Nuestro objetivo en este artículo es mostrar que el contraste entre la posición preformacionista y epigenética persiste a pesar de los formidables avances teóricos y experimentales de la biología del desarrollo contemporánea. El preformacionismo y la epigénesis han perfeccionado constantemente sus posiciones en el curso de la historia con el fin de responder a los retos conceptuales de la época. Este continuo proceso de transformación ha dado lugar a una convergencia parcial entre las dos posiciones. Sin embargo, vamos a argumentar que, a pesar de los esfuerzos por conciliar ambas posturas, esta antinomia, que se erige como una de las más fundamentales de la biología, no será fácil de superar.The process of development of the embryo has inspired philosophical speculation since the advent of Western thought. Since the time of Aristotle two antithetical conceptual models have traditionally been used to understand embryogenesis: either form or structure is preformed in the embryo or it is newly formed with each generation. Our aim in this article is to show that the contrast between the pre-formationist and epigenetic positions persists despite the formidable theoretical and experimental advances of contemporary developmental biology. Pre-formationism and epigenesis have constantly refined their positions in the course of history in order to answer the conceptual challenges of each epoch. This process of continuous transformation has resulted in a partial convergence of the two positions. However, we shall argue that, despite the partial successes of this process of continuous convergence, one of the most fundamental antinomies in biology persists

Gauge-optimal approximate learning for small data classification problems

Small data learning problems are characterized by a significant discrepancy between the limited amount of response variable observations and the large feature space dimension. In this setting, the common learning tools struggle to identify the features important for the classification task from those that bear no relevant information, and cannot derive an appropriate learning rule which allows to discriminate between different classes. As a potential solution to this problem, here we exploit the idea of reducing and rotating the feature space in a lower-dimensional gauge and propose the Gauge-Optimal Approximate Learning (GOAL) algorithm, which provides an analytically tractable joint solution to the dimension reduction, feature segmentation and classification problems for small data learning problems. We prove that the optimal solution of the GOAL algorithm consists in piecewise-linear functions in the Euclidean space, and that it can be approximated through a monotonically convergent algorithm which presents -- under the assumption of a discrete segmentation of the feature space -- a closed-form solution for each optimization substep and an overall linear iteration cost scaling. The GOAL algorithm has been compared to other state-of-the-art machine learning (ML) tools on both synthetic data and challenging real-world applications from climate science and bioinformatics (i.e., prediction of the El Nino Southern Oscillation and inference of epigenetically-induced gene-activity networks from limited experimental data). The experimental results show that the proposed algorithm outperforms the reported best competitors for these problems both in learning performance and computational cost.Comment: 47 pages, 4 figure

Influence of plaque properties and constitutive modeling approach on the simulation of percutaneous angioplasty of chronic total occlusions

Clinical treatment of Chronic Total Occlusion (CTO) of an artery often involves percutaneous procedures, like sub-intimal balloon angioplasty, in which the controlled inflation of a balloon restores the lumen by compression ofatherosclerotic plaque. Realistic simulations of these challenging techniques could provide valuable information for clinician, but characterization of CTO in human studies is problematic. Reported data are highly variable and the few published models employed different approaches to fit (apparently) the same experimental tests. Moreover, atherosclerotic plaques are commonly assumed as elastic and incompressible, but in angioplasty procedures they may be subjected to large and not physiological overstretch. Permanent plaque damage after balloon inflation is expected, suggesting that some form of inelastic behavior should be considered. Thus, the goal of the present work is to investigate the influence of changing plaque properties and constitutive modeling assumptions, on the predicted outcomes of a simulation of CTO percutaneous angioplasty. To this aim, a finite element model of the compression of a total occlusion inside an artery was implemented. Different forms of hyperelastic constitutive laws proposed in literature were compared in presence of the complex stress state resulting from sub-intimal angioplasty. The degree of compressibility and the threshold for a permanent damage, introduced in the form of a plastic yield limit, were varied. Overall, results demonstrated that the choice of different data sets or constitutive modeling approaches for plaque has a primary influence. Some common assumptions for plaque modeling may lead to highly variable or even unrealistic predictions for the extreme case of total occlusion treatment. In this sense, more specific experimental investigations on the properties of plaque constituents as a function of heterogeneous CTO composition, are necessary in order to exploit the potential usefulness of the method as a patient-specific predictive tool