Search

This article examines the introduction of the medical mask in the late nineteenth century at the intersection of surgery, bacteriology and infection control. During this important episode in the longer history of the medical mask, respiratory protection became a tool of targeted germ control. In 1897, the surgeon Johannes Mikulicz at the University of Breslau (now Wroclaw, Poland), drawing on the bacteriological experiments of his colleague Carl Flügge, used a piece of gauze in front of his nose and mouth as a barrier against microorganisms moving from him to his patients. This article explores the social, cultural and medical contexts of this particular use of the mask, in connection with germ theory and surgeons’ struggle with wound infection. It explores the alignment of the new aseptic surgery with the emerging field of bacteriology in a local milieu that favoured interdisciplinary cooperation. The account also follows the uptake of the mask outside of surgery for other anti-infectious purposes and shows how the new type of anti-infectious mask spread simultaneously in operating rooms as well as in hospitals and sanatoria, and eventually in epidemic contexts.

This article investigates how a discourse about the role and value of public participation in science, technology, and innovation emerged and evolved in the research policies of the European Commission. At the beginning of the twenty-first century, two main discourses have been successively institutionalized: the first focused on participation in policy-making, while the second aimed at participation in the production of knowledge and innovation. This paper distinguishes three main institutional phases: (i) a phase dedicated to public participation in the governance of science and technology (2000–2010); (ii) a reframing period of science and technology policies by the Commission to integrate the growing emphasis on innovation (2010–2014); (iii) a period focusing on co-creation and citizen science as new ways to involve the public in science and technology (2014-today). Factors such as individual commitments of key policy actors, specific epistemic communities and institutional dynamics within the Commission played a crucial role in shaping the policies of participation. But broader factors are also essential to account for these changes. In this respect, the economic crisis of the late 2000s appears fundamental to understanding how the conception and promotion of public participation in the European science and technology policies have evolved over time. This paper thus offers new insights to the analysis of the political economy of public participation.

Over the past two decades, a number of digital platforms have been developed with the aim of engaging citizens in scientific research projects. The success of these platforms depends in no small part on their ability to attract and retain participants, turning diffuse crowds of users into active and productive communities. This article investigates how the collectives of online citizen science are formed and governed, and identifies two ideal-types of government, either based on self-interest or on universal norms of science. Based on an ethnography of three citizen science platforms and a series of interviews with their managers, we show how different technologies – rhetorical, of the self, social, and ontological – can be diversely combined to configure these collectives. We suggest that the shift from individual projects to platforms is a defining moment for online citizen science, during which the technologies that sustain the collectives are standardized and automatized in ways that make the crowd appear to be a natural community.

Rethinking histories of data requires not only better answers to existing questions, but also better questions. We suggest eight such questions here. What counts as data? How are objects related to data? What are digital data? What makes data measurable, and what does quantification do to data? What counts as an “information age” ? Why do we keep data, and how do we decide which data to lose or forget? Who owns data, and who uses them? Finally, how does “Big Data” transform the geography of science? Each question is a provocation to reconsider the meanings and uses of “data” not only in the past but in the present as well.

Research suggests that students tend to explain the origin of biological traits in terms of needs or purposes and/or as the direct product of genes, rather than as the outcome of evolutionary and developmental processes. We suggest that in order for students to be able to construct scientific explanations, it is important to clearly and explicitly distinguish between causes that make a difference to the production of effects and the processes through which these effects are produced in developing evolutionary and developmental explanations for the origin of biological traits. However, these distinctions are not usually made in textbooks and curricula, and it is unclear how biology teachers themselves explain the origins of biological traits. In this study, we present the conclusions from the analysis of the explanations that 19 preservice biology teachers gave for the origins of biological traits. The results indicate that they often referred to causes and processes in their evolutionary explanations, but that they did not always do this in their developmental explanations. We suggest that future biology teachers should understand the structure of explanations for the origins of traits to efficiently teach their students to construct such kinds of explanations.

The public acceptance of evolution is under constant scrutiny. Surveys and polls regularly measure whether the public accepts evolutionist or creationist views. The differences between groups, such as people from various countries, are then explained by variations in religious views. But what is often overlooked, is that the data also show that a large proportion of the population, about one-third, is unsure what to believe. This figure generally goes unnoticed. We argue that the emphasis on religious variables obscures another, perhaps more important, variable: the conceptual understanding of evolution. This factor may help explain why so many people are unsure about evolution and offers a greater potential to increase public understanding and acceptance of the theory, perhaps with the active involvement of science educators.

Advances in molecular genetics and genomics, and their applications in personalised medicine and other fields, are raising important socio-scientific issues. If the aim of science teaching is to educate scientifically literate citizens, the implications of current genetic and genomic technologies for our lives have to be addressed in science courses. Educational policies in all industrialized societies consider science literacy as a main goal of education. The science standards in several European Union member states (Eurydice Network 2011) and the United States (National Research Council 2012) have stated similar goals. Given the key role attributed to genes as determinants of human identity, health, and behavior, genetics is a scientific field about which science literacy is particularly important. With the wide media attention given to the identification of the genetic basis of human traits and the increasing availability of direct-to-consumer genetic tests it is important that non-experts understand what kinds of reliable genetic knowledge can be acquired and what their implications for society are. Thus, science educators and teachers need to be informed about the current status of genetics and genomics research, the technological state of the art, its biomedical applications, and the relevant ethical issues. The contribution of research scientists to the public understanding of science is important in this respect (Reydon et al. 2012).

The standard narrative in the history of the life sciences focuses on the rise of exper- imentalism since the late nineteenth century and the concomitant decline of natural history. Here, I propose to reexamine this story by concentrating on a specific set of material and cognitive practices centered on collections. I show that these have been central for the production of knowledge not only in natural history, from the Renais- sance to the present, but also in the experimental sciences. Reframing the history of the life sciences in this way makes historical continuities visible and raises new possibilities to contextualize recent developments in science, such as the prolifera- tion of databases and their growing use.

INTRODUCTIONThe image and caricature of the biologist roaming the field with a collecting box or poring over pinned up insect and butterfly cases endured well into the twentieth century. In contrast the molecular vision of life, and even more so molecular biology, the quintessential science of the late twentieth century, has most often been connected with experimenting and intervening on a handful of model organisms and systems. Underpinning this widespread opposition is the idea that biology as practised by naturalists was "merely" descriptive, systematic, and comparative. Naturalists would rely on collecting and comparing specimens, providing names and descriptions, and thereby document biological diversity. This way of approaching the natural world was supposedly superseded by the experimental approach in the late nineteenth century, with molecular biologists taking up that banner in the twentieth. Using ever more powerful instruments, imported from the physical and chemical sciences, and focusing their attention on a few well-chosen model systems, they studied processes and their underlying mechanisms. This view of the history has been promoted by latter-day biologists and by historians alike.1 Historians of molecular biology have insisted, for example, on the crucial role of the Rockefeller Foundation, since the 1930s, in promoting molecular approaches in the life sciences by providing funding for the acquisition of costly new physical and chemical instruments.2 The molecular vision of life was predicated upon sophisticated means of intervention which produced representations enabling further manipulations of life.3 Equal attention has been dedicated to the strategic choice of a few simple model organisms on which much of the early work in molecular biology was developed. We can think here of Max Delbruck' s introduction of phage for the study of genetics, and the extensive use of bacteria and viruses in studying genetic mechanisms in molecular terms, but also of moulds (Neurospora crassa), flies (Drosophila melanogaster), and later, worms (Caenorhabditis elegans), mice (Mus Musculus), and weeds (Arabidopsis thaliana), which all gained the enviable status (at least from the researcher's perspective) of model organism for the production of knowledge in molecular biology.4One of the historiographie side-effects of writing disciplinary histories, such as those of molecular biology mentioned previously, has been a tendency to emphasize cognitive, methodological, and sociological unity within the disciplines and differences among disciplines. By contrast, John Pickstone's call to focus on "ways of knowing" (or "working knowledges"), rather than disciplines, can help us make visible the heterogeneity of cognitive and material practices within disciplines and the similarities among disciplines. Indeed, according to Pickstone, even though ways of knowing have their own historicity and have, for example, enjoyed their greatest successes at different times, they do not replace each other, like Kuhnian paradigms, but add new layers in the makeup of science, technology and medicine.5 Pickstone's historiographie approach, unlike that of many others proponents of 'styles', is not taxonomic, but analytic; it reveals the different components which make up scientific practices. This perspective proves fruitful for a closer examination of the working practices of modern biologists. As we show in this paper, molecular biology did not take shape exclusively as an experimental science focused on 'exemplary' model organism and systems. Rather, much work in molecular biology can be described more accurately as comparative and relied far more than previously recognized on collections. This is true not only for late twentieth-century genomic scientists, who have been derided as "molecular birdwatchers",6 but also of early day molecular biologists, those most vehement in condemning natural history.7 In their studies of the most challenging problems of the new science, namely the structure and function of proteins and nucleic acids and the deciphering of the genetic code, they relied heavily on collections and comparisons of molecular data, the distinctive approach of the comparative biological sciences, usually associated with nineteenth-century natural history, anatomy, and embryology. …

Today, the production of knowledge in the experimental life sciences relies crucially on the use of biological data collections, such as DNA sequence databases. These collections, in both their creation and their current use, are embedded in the experimentalist tradition. At the same time, however, they exemplify the natural historical tradition, based on collecting and comparing natural facts. This essay focuses on the issues attending the establishment in 1982 of GenBank, the largest and most frequently accessed collection of experimental knowledge in the world. The debates leading to its creation—about the collection and distribution of data, the attribution of credit and authorship, and the proprietary nature of knowledge—illuminate the different moral economies at work in the life sciences in the late twentieth century. They offer perspective on the recent rise of public access publishing and data sharing in science. More broadly, this essay challenges the big picture according to which the rise of experimentalism led to the decline of natural history in the twentieth century. It argues that both traditions have been articulated into a new way of producing knowledge that has become a key practice in science at the beginning of the twenty-first century.

The rise of experimentation and the decline of natural history constitute the historiographic backbone to most narratives about the history of the life sciences in the twentieth century. As I argue here, however, natural history practices, such as the collection and comparison of data from numerous species, and experimental practices have actually converged throughout the century, giving rise to a new hybrid research culture which is essential to the contemporary life sciences. Looking at some examples of researchers who studied experimentally the relationships between organisms offers a unique window into how the norms, values, and practices of natural history entered the laboratory and, conversely, how the norms, values, and practices of experimentation transformed natural history. This paper concentrates on a largely overlooked episode in the history of the life sciences: the development of Alan A. Boyden's serological taxonomy. In the United States, from the late 1920s to the early 1960s, he was the most prominent advocate of this experimental approach in natural history. His quest for an objective method to understand the relationships among species, his creation of a serological museum where he could apply his comparative perspective, and his continued negotiations between natural historical and experimental traditions, illustrate the rise of a new hybrid research culture in the twentieth century. It also helps us solve a historiographic puzzle, namely how biological diversity become so central in the experimental life sciences, i.e., in a tradition which we generally understand as having focused on a few model organisms, and which relegated the study of biodiversity to naturalists and their museums.

Collecting, comparing, and computing molecular sequences are among the most prevalent practices in contemporary biological research. They represent a specific way of producing knowledge. This paper explores the historical development of these practices, focusing on the work of Margaret O. Dayhoff, Richard V. Eck, and Robert S. Ledley, who produced the first computer-based collection of protein sequences, published in book format in 1965 as the Atlas of Protein Sequence and Structure. While these practices are generally associated with the rise of molecular evolution in the 1960s, this paper shows that they grew out of research agendas from the previous decade, including the biochemical investigation of the relations between the structures and function of proteins and the theoretical attempt to decipher the genetic code. It also shows how computers became essential for the handling and analysis of sequence data. Finally, this paper reflects on the relationships between experimenting and collecting as two distinct ‘‘ways of knowing'' that were essential for the transformation of the life sciences in the twentieth century.

Neither science nor state has ever been transcendentally “neutral,” but they have sometimes been made neutral, together, as this paper shows in the context of cold war Europe. The paper explores how the Swiss government tried to “depoliticize” and “demilitarize” new international research institutions in the fields of high‐energy physics (CERN), space research (ESRO and ELDO), and molecular biology (EMBL) in order to make science neutral. Conversely, this paper investigates how participation in “neutralized” scientific institutions supported Switzerland’s neutrality policy and strengthened this essential element of its national identity. It thus addresses symmetrically the coproduction of neutral science and neutral state.

The European Molecular Biology Organization (EMBO) will celebrate its 40th birthday next year. This seems like a good opportunity to take a closer look at how EMBO came into being in 1964, and at the driving forces that established this first European organization to represent molecular biology. Investigating the origins of EMBO also allows us to explore the history of molecular biology in Europe and how it changed from a marginal specialty into a well‐established practice in most fields of experimental biomedicine. > When EMBO was informally created in Ravello, it was just a ‘club’ of life scientists who wanted to promote molecular biology research in Europe Like many other institutions, EMBO has its official history, and the canonical version was laid down in a sample copy of The EMBO Journal by John Tooze, former Executive Director of EMBO: “In December 1962, immediately following the Nobel Prize Investiture ceremony, John C. Kendrew together with James D. Watson visited the Centre Europeen de Recherche Nucleaire (CERN) in Geneva on their way home from Stockholm. Leo Szilard, the nuclear physicist‐turned‐molecular biologist, was also in Geneva at the time. Having decided that the Cuban missile crisis [October 1962] might lead to war he had left New York and had taken refuge in Switzerland. During the course of a conversation the three visitors had with Victor Weisskopf (CERN Director General), Leo Szilard proposed that Europe's molecular biologists should attempt to emulate their colleagues in particle physics and try to persuade their governments to establish an international laboratory for molecular or fundamental biology patterned on the CERN model. […] The upshot was a meeting held at Ravello, Italy on 16–17 September 1963. [A group of molecular biologists] discussed the possibility of international cooperation in fundamental biology. The group decided that a European organization was a more …

This article is a revision of the previous edition article by A. Cambrosio and P. Keating, volume 2, pp. 1222–1226, © 2001, Elsevier Ltd.

This special issue of Studies collects a set of original papers on the making of molecular biology in postwar Europe. It includes several contributions on countries which have not yet received much attention in the historiography of molecular biology, for example, Italy, Spain, Germany, or Switzerland, along with new perspectives on better known cases such as France and Britain. Yet not all papers deal with developments on the national level: some papers focus on single laboratories or follow specific research tools and practices; others adopt comparative approaches and international perspectives. While each study per se offers much rich material and analysis, together they document the breadth of new scholarship in the field and, through the common time frame and the European focus, introduce a comparative perspective which contributes significantly to our understanding of the early history of molecular biology and to the postwar transformation of the sciences more generally. The picture which emerges differs from conventional ‘big picture’ accounts in that it is based on in-depth local studies. That we focus on developments in Europe does not mean that we turn a blind eye to American developments. On the contrary, the scientific and political relations to the United States and how these played out in the different national contexts, as well as in the attempt to build a European laboratory, become one of the central themes. Other questions raised by the set of papers are: the impact of the different wartime legacies on national developments; the role and relative weight of postwar economic developments, national science policies, and local or national research tra

The intellectual origins of molecular biology are usually traced back to the 1930s. By contrast, molecular biology acquired a social reality only around 1960. To understand how it came to designate a community of researchers and a professional identity, I examine the creation of the first institutes of molecular biology, which took place around 1960, in four European countries: Germany, the United Kingdom, France, and Switzerland. This paper shows how the creation of these institutes was linked to the results of post-war economic reconstruction. Then, it compares how the promoters of these different institutional projects delimited the goals of their discipline, reflected on its history, and suggested how research should be organised. I show how they carefully positioned their new discipline within the emerging national science policy discourse of the 1950s, and aligned it with the current vision of scientific modernity. In particular, I discuss how they articulated the meaning of molecular biology with respect to five common themes: the role of physics in the atomic age, the relations between fundamental research and medical applications, the ‘Americanisation’ of scientific research, the value of science in the reconstruction of national identities, and the drive towards interdisciplinary research. This paper thus demonstrates that beyond the local and national accounts there is a European history of molecular biology.  2002 Elsevier Science Ltd. All rights reserved.

In 1949, Linus Pauling and his collaborators published a study in the journal Science entitled ‘‘Sickle Cell Anemia, a Molecular Disease.’’ In this now classic study, they showed that hemoglobin from patients suffering from sickle cell anemia has a different electrical charge than hemoglobin from healthy individuals. This result demonstrated for the first time that an abnormal protein could be causally linked to a disease, and that genes determined the structure of proteins. This report made headline news and had a powerful impact on both the biomedical community and the general public. Fifty years later, this study is discussed in almost every medical and biological textbook and has became a favorite example in editorials to illustrate the progress of biomedical research. This article explores the history of Pauling’s sickle cell anemia and its subsequent integration in different collective memories, up to the present day. It also discusses the function of the collective memories of Pauling’s discovery for contemporary biomedical research. 2002 Wiley-Liss, Inc.

Changes in the photosynthetic apparatus occurring during the synchronous cell cycle of the green alga Scenedesmus obliquus are compared to the adaptational response induced by light intensity variations. To investigate and compare these two phenomena, we analyze the polyphasic rise of the chlorophyll fluorescence yield exhibited by plants and cyanobacteria when exposed to high intensity actinic light. Four fluorescence parameters are calculated which are closely related to Photosystem II (PS II) structure and function: ABS/RC, the antenna size of PS II; ϕPO, the quantum yield for reduction of the primary PS II quinone acceptor; qPQ, related to the size of the plastoquinone pool; qEmax, the capacity for pH dependent non-photochemical quenching. The capacity for non-photochemical quenching changes in response to light intensity variations, but it is not affected by the developmental changes occurring during the cell cycle. In contras t, for ABS/RC, ϕPO and qPQ, we observe light induced as well as cell cycle dependent variations. We discuss the relations of the four fluorescence parameters to the molecular organization of the photosynthetic apparatus and its cell cycle and light dependent changes.

Chlorophyll a fluorescence induction is extensively used as a probe of photosynthesis, and thus, it has become necessary to quantitatively analyse it to extend its usefulness. We simulate the experimental data of fluorescence transients in strong light through numerical integration, both in dark- and light-adapted plants. In the mathematical model used here we have considered for the first time the redox reactions at both the acceptor and the donor sides of photosystem II, and the non-photochemical quenching by the oxidised plastoquinone molecules from the lipid matrix of the thylakoid membrane. The model is based on assumptions established in the literature and also the values of input parameters used in simulations. The simulated fluorescence induction curves show the characteristics O→J→I→P steps as in the experimental ones and, in specific conditions, the presence of a dip (D) between the I and P steps of the transient. Moreover, it has been shown here how typical patterns of fluorescence kinetics are influenced by the state of the sample by studying the basic effects of the influence of some parameters [i.e. the connectivity between different PS II units, initial Q B :Q B − ratio and the ratio of the starting states of the oxygen evolving complex (S 1 :S 2 ), number of plastoquinone molecules in the plastoquinone pool, initial redox state of the plastoquinone pool, and the rate of plastoquinol oxidation]. In this way the information can be drawn from the experimental curves relative to these parameters.

The chlorophyll a fluorescence transient measured under high light shows a typical O-J-I-P polyphasic rise. However, under certain stress situations such as heat or drought stress, a rapid phase with a maximum around 300 µs has been observed and called K (Guisse et al. (1995a) Arch Sci Geneve 48: 147–160). Here, we show that under various conditions, the appearance of the K-step and the following dip, as well as the lowered maximum fluorescence level (FM) attainable, can be explained by an imbalance between the electron flow leaving the RC to the acceptor side and the electron flow coming to the RC from the donor side. This leads to a stable oxidation of the secondary electron donor, the tyrosine Z (YZ), and possibly to the accumulation of P680+. In the case of heat stress, we confirm that this situation is caused by an inhibition of electron donation to YZ, which is due to a damaged oxygen evolving complex (OEC). Finally, we present a model which includes the OEC, YZ, P680, QA and QB which is in good agreement with the experimental data. The appearance of the K-step, under natural conditions, can now be used as a convenient stress indicator and specifically attributed to a damage on the electron donor side.

The American physical chemist Margaret Oakley Dayhoff was one of the major figures in the early history of bioinformatics. In 1965, she published the initial edition of the Atlas of Protein Sequence and Structure, the first comprehensive, computerised and publicly available collection of protein sequences. It became a model for many subsequent sequence databases, including GenBank. Dayhoff developed several methods to analyse protein sequences and infer their evolutionary relationships, as well as computer models to simulate the composition of planetary atmospheres. Key Concepts: Margaret O. Dayhoff was one of the founders in the field of bioinformatics. Margaret O. Dayhoff created the first public comprehensive, computerised and publicly available database of protein sequences, The Atlas of Protein Sequence and Structure (1965). The Atlas of Protein Sequence and Structure was the model for GenBank and many other molecular databases. The Atlas of Protein Sequence and Structure was a key tool for the development of molecular biology, molecular evolution and bioinformatics. The Atlas of Protein Sequence and Structure was tremendously successful among researchers, yet they were sometimes reluctant to contribute their data. Keywords: Bioinformatics; database; molecular biology; molecular evolution; biochemistry; computers; protein sequence

Even by the journal’s own standards, this was a wild claim. In July 2008, Wired magazine announced on its cover nothing less than ‘‘The End of Science’’. It explained that ‘‘The quest for knowledge used to begin with grand theories. Now it begins with massive amounts of data’’. Such claims about the emergence of a new ‘‘data-driven’’ science in response to a ‘‘data deluge’’ have now become common, from the pages of The Economist to those of Nature. Proponents of ‘‘data-driven’’ and ‘‘hypothesis-driven’’ science argue over the best methods to turn massive amounts of data into knowledge. Instead of jumping into the fray, I would like to historicize some of the questions and problems raised by data-driven science, taking as a point of departure the three rich papers by Isabelle Charmantier and Staffan Muller-Wille on Linnaeus’ information processing strategies, Sabina Leonelli and Rachel Ankeny on model organisms databases, and Peter Keating and Alberto Cambrosio on microarray data in clinical research. That a historical approach is warranted is made clear by the remark of the great book historian Robert Darnton that ‘‘every age was an age of information, each in its own way’’ (Darnton, 2000, p. 1). In particular, perceptions of an ‘‘information overload’’ (or a ‘‘data deluge’’) have emerged repeatedly from the Renaissance though the early modern and modern periods and each time specific technologies were invented to deal with the perceived overload (Ogilvie, 2003; Rosenberg, 2003). This commentary will explore the similarities and differences between past and present data-driven life sciences, from early modern natural history to current post-genomics. Renaissance naturalists were no less inundated with new information than our contemporaries. The expansion of travel, epitomized by the discovery of the New World, exposed European naturalists to new facts that did not fit into the systems of knowledge inherited from the Greeks and Romans. This prompted those interested in understanding the natural world to devise newmethods for managing this data, such as note-taking strategies, and new systems of classification (Blair, 2010; Ogilvie, 2006). Ironically, as Charmantier and Muller-Wille point out, these methods and systems, which were meant to tame the information overload, made it possible to accumulate even more data. But accumulation was usually only a mean to an end. These early naturalists established collections, which included specimens, drawings, and texts, so that they could compare these items systematically and draw from the comparisons conclusions about the natural world. In general, they were not testing specific hypotheses, but trying to bring order to the bewildering diversity of natural forms by examining large amounts of collected ‘‘data’’. This tradition continues to be central in natural history to the present day. As George Gaylord Simpson, the leading American paleontologist of the twentieth century,made clear in 1961, natural history, and taxonomy in particular, was the ‘‘science that is most explicitly and exclusively devoted to the ordering of complex data’’ (Simpson, 1961, p. 5). What is striking about Simpson’s definition is not only that he chose the ‘‘ordering of complex data’’ as the most essential element of natural history, but also how similar his definition is to current characterizations of the supposedly unprecedented data-driven sciences. This should come as no surprise since, for several centuries, the natural historical sciences have fundamentally been data-driven sciences. But was natural history driven by data alone? Most likely not, because natural history has never been free of ontological assumptions. For example most naturalists assume the existence of natural groups. As Charmantier and Muller-Wille show, Linnaeus who struggled with a data deluge of his own creation and devised numerous note-taking methods to deal with it, could only do so because he began with a hypothesis about the genus categories he used to organize his data. In other words, Linnaeus may have been driven by his data, but his approach was not exclusively datadriven. This conclusion, however, is insufficient to distinguish early modern approaches to data with contemporary ones. Indeed, as Keating and Cambrosio show in their paper, modern day biostatisticians analyzing cancer microarray data were equally driven by various hypotheses. For example, the determination of the sample size needed to produce statistically significant results required researchers to make an hypothesis about the number of classes that the data might reveal. In other words, they too were guided by

Fifty years ago this month, Linus Pauling published his seminal Science paper describing the difference in electrophoretic mobilities between normal hemoglobin and that from patients with sickle cell anemia. In so doing he founded the field of molecular medicine, as Strasser explains in a lively Perspective that looks at the discovery and its aftermath.