The origins of oxidative phosphorylation, initially known as aerobic phosphorylation, grew out of three research areas of muscle metabolism, creatine phosphorylation, aerobic metabolism of lactic acid in muscle, and studies on the nature and role of adenosine triphosphate . Much of this work centred round the laboratory of Otto Meyerhof, and most of those contributing to the study of aerobic phosphorylation were influenced by that laboratory: particularly Lipmann and also Ochoa. The work of Engelhardt on ATP levels in blood also (...) appears to have been influenced by the studies of Meyerhof’s laboratory. However, with the work of Kalckar, influenced by Lipmann, biochemists began to realise the potential importance of the process. This was confirmed and extended by Belitzer and Ochoa and the theoretical contribution of Lipmann. Thus it is not easy to identify a single point that marked the initiation of studies in this field.The early work was based on the use of tissue homogenates and cells but ultimately this approach limited research possibilities. The development of techniques based on mitochondria opened up new possibilities and brought this first phase of the study of oxidative phorphorylation to a close. (shrink)

In recent years, the philosophical focus of the modeling literature has shifted from descriptions of general properties of models to an interest in different model functions. It has been argued that the diversity of models and their correspondingly different epistemic goals are important for developing intelligible scientific theories. However, more knowledge is needed on how a combination of different epistemic means can generate and stabilize new entities in science. This paper will draw on Rheinberger’s practice-oriented account of knowledge production. The (...) conceptual repertoire of Rheinberger’s historical epistemology offers important insights for an analysis of the modelling practice. I illustrate this with a case study on network modeling in systems biology where engineering approaches are applied to the study of biological systems. I shall argue that the use of multiple means of representations is an essential part of the dynamic of knowledge generation. It is because of – rather than in spite of – the diversity of constraints of different models that the interlocking use of different epistemic means creates a potential for knowledge production. (shrink)

Just when molecular biology is arguably delivering on some of its long‐promised medical applications—think mRNA vaccines, monoclonal antibody drugs, PCR testing, and gene therapies—the history of molecular biology has lost much of its shine. What not too long ago seemed like a burgeoning field of research with endless possibilities, is now often reduced to the “central dogma” that saw its apotheosis in the effort to sequence the human genome but has since unraveled. The essay will discuss several possible answers to (...) this apparent paradox. (shrink)

This essay considers how scholarly approaches to the development of molecular biology have too often narrowed the historical aperture to genes, overlooking the ways in which other objects and processes contributed to the molecularization of life. From structural and dynamic studies of biomolecules to cellular membranes and organelles to metabolism and nutrition, new work by historians, philosophers, and STS scholars of the life sciences has revitalized older issues, such as the relationship of life to matter, or of physicochemical inquiries to (...) biology. This scholarship points to a novel molecular vista that opens up a pluralist view of molecularizations in the twentieth century and considers their relevance to current science. (shrink)

Résumé Dans cet article, nous discuterons de l’intégration du numérique à la sémiotique et proposerons qu’une modélisation conceptuelle puisse offrir un pont de dialogue entre ces deux domaines classiquement cloisonnés. Plus précisément, nous avancerons l’hypothèse que tout projet de recherche qui en appellera à l’informatique soit une démarche scientifique que s’il construit une théorie qui contient, en plus des modèles classiques que sont les modèles formel, computationnel et physique, un modèle conceptuel. Ce lieu, où les chercheur-es conceptualisent les multiples dimensions (...) de leur objet de recherche, sera alors défini en tant que socle d’une relation solide entre la sémiotique et l’informatique. Nous verrons que les différentes définitions du modèle conceptuel convergent vers la thèse soutenant que la connaissance scientifique met en œuvre une instance de conceptualisation qui doit identifier les diverses dimensions du problème en plus de devoir s’exprimer de manière à ce qu’elle soit communicable entre les membres des communautés épistémiques. Nous verrons, enfin, qu’un projet de recherché sémiotique exige la construction d’un tel modèle afin de décrire, généraliser et sélectionner des problèmes et que ce même modèle, conceptuel, sera aussi nécessaire si le ou la sémioticien-ne utilise l’informatique dans le cadre de sa recherche.fr. (shrink)

We present two case studies from contemporary biology in which we observe conflicts between established and emerging approaches. The first case study discusses the relation between molecular biology and systems biology regarding the explanation of cellular processes, while the second deals with phylogenetic systematics and the challenge posed by recent network approaches to established ideas of evolutionary processes. We show that the emergence of new fields is in both cases driven by the development of high-throughput data generation technologies and the (...) transfer of modeling techniques from other fields. New and emerging views are characterized by different philosophies of nature, i.e. by different ontological and methodological assumptions and epistemic values and virtues. This results in a kind of conflict we call “epistemic competition” that manifests in two ways: On the one hand, opponents engage in mutual critique and defense of their fundamental assumptions. On the other hand, they compete for the acceptance and integration of the knowledge they provide by a broader scientific community. Despite an initial rhetoric of replacement, the views as well as the respective audiences come to be seen as more clearly distinct during the course of the debate. Hence, we observe—contrary to many other accounts of scientific change—that conflict results in the formation of new niches of research, leading to co-existence and perceived complementarity of approaches. Our model thus contributes to the understanding of the pluralization of the scientific landscape. (shrink)

This article examines to what extent a particular case of cross-disciplinary research in the 1930s was structured by mechanistic reasoning. For this purpose, it identifies the interfield theories that allowed biologists and chemists to use each other’s techniques and findings, and that provided the basis for the experiments performed to identify plant growth hormones and to learn more about their role in the mechanism of plant growth. In 1930, chemists and biologists in Utrecht and Pasadena began to cooperatively study plant (...) growth. I will argue that these researchers decided to join forces because they believed to rely on each other’s findings and methods to solve their research problems adequately. In the course of the cooperation, organic chemists arrived at isolating plant growth hormones by using a test method developed in plant physiology. This achievement, in turn, facilitated biologists’ investigation of the mechanism of plant growth. Researchers eventually believed to have the means to study the relation between a substance’s molecular structure and its physiological activity. The way they conceptualized the problem of identifying hormones and unraveling the mechanism of plant growth, as well as their actual research actions are compatible with the new mechanists’ account of mechanism research. The study illustrates that focusing on researchers’ mechanistic reasoning can contribute considerably to explaining the structure of cross-disciplinary research projects. (shrink)

Rationalities of Knowledge Production: On Transformations of Objects, Technologies and Information in Biomedicine and the Life Sciences. Since decades, scientific change has been interpreted in the light of of paradigm shifts and scientific revolutions. The Kuhnian interpretation of scientific change however is now more and more confronted with non‐disciplinary thinking in both, science and studies on science. This paper explores how research in biomedicine and the life sciences can be characterized by different rationalities, sometimes converging, sometimes contradictory, all present at (...) the same time with varying ways of influence, impact, and visibility. In general, the rationality of objects is generated by fitting new objects and findings into a new experimental context. The rationality of hypotheses is a move towards the construction of novel explanatory tools and models. This is often inseparable meshing with the third, the technological rationaliy, in which a technology‐driven, self‐supporting and sometimes self‐referential refinement of methods and technologies comes along with an extension into other fields. During the second and the third phase, the new and emerging fields tend to expand their explanatory reach not only across disciplinary boundaries but also into the social sphere, creating what has been characterized as “exceptionalism” (e.g. genetic exceptionalism or neuro‐exceptionalism). Finally, recent biomedicine and life‐sciences reach a level in which experimental work becomes more and more data‐driven because the technologically constructed experimental systems generate a plethora of findings (data) which at some point start to blur the original hypotheses. For the rationality of information the materiality of research practices becomes secondary and research objects are more and more getting out of sight. Finally, the credibility of science as a practice becomes more and more dependent on consensus about the applicability and relevance of its results. The rationality of interest (and accountability) has become more and more characteristic for a research process which is no longer primarily determined by the desire for knowledge but by the desire for relevance. This paper explores in which ways object‐driven and hypotheses‐driven experimental life‐sciences transformed into domains of experimental research evolving in a technologically constructed, data‐driven environment in which they are subjected to constant morphing due to the forces of different rationalities. (shrink)

Berichte zur Wissenschaftsgeschichte, Volume 45, Issue 3, Page 462-467, September 2022.