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The complexities of modern science are not adequately reflected in many bioethical discussions. This is especially problematic in highly contested cases where there is significant pressure to generate clinical applications fast, as in stem cell research. In those cases a more integrated approach to bioethics, which we call systems bioethics, can provide a useful framework to address ethical and policy issues. Much as systems biology brings together different experimental and methodological approaches in an integrative way, systems bioethics integrates aspects of the history and philosophy of science, social and political theory, and normative analysis with the science in question. In this paper we outline how a careful analysis of the science of stem cell research can help to refocus the discussions related to the clinical applications of stem cells. We show how inaccurate or inadequate scientific assumptions help to create a set of unrealistic expectations and badly inform ethical deliberations and policy development. Systems bioethics offers resources for moving beyond the current impasse. [ABSTRACT FROM AUTHOR]

Considerable evidence links the "Big Five" personality traits (neuroticism, extroversion, conscientiousness, agreeableness, and openness) with depression. However, potential mediating and moderating factors are less well understood. We utilized data from a cross-sectional survey of 3065 German-speaking adults from the D-A-CH region to estimate multivariable-adjusted odds ratios and 95% confidence intervalsbetween personality traits and lifetime prevalence of depression (overall and stratified by sex and age). We further explored proportions mediated by psychosocial factors optimism, empathy, perspective-taking, work-life balance, and interpersonal trust. High levels of neuroticism were associated with more than two-fold higher odds of depression, whereas higher levels of conscientiousness were associated with approximately 30% lower odds of depression. The association with neuroticism persisted in all investigated subgroups; apparently, stronger associations for females and participants aged ≥60 years did not correspond to statistically significant interactions. Overall and across all strata, the association of neuroticism with depression appeared to be mediated in part by the considered psychosocial factors; optimism explained the largest proportion of the association. Our results provide empirical evidence for the dynamic predisposition model. Further investigations of these relationships are warranted in longitudinal data with more precise outcome assessments.

Interpersonal trust declined worldwide during the COVID-19 pandemic; strategies are needed to restore it. We surveyed 3,065 quota-sampled German-speaking adults residing in the D-A-CH region. Using multinomial logistic regression models and backward elimination for variable selection, we calculated multivariable-adjusted odds ratios (OR) and 95% confidence intervals (95% CIs) to appraise correlates of interpersonal trust using the Interpersonal Trust Short Scale (KUSIV3). Participants with high levels of interpersonal trust (top KUSIV3 tertile (T3)) tended to be older, male, residents of Switzerland, university degree holders, and workers with higher income and work satisfaction (all Pdiff<0.01) compared to those in the lowest KUSIV3 tertile (T1). Optimism was most strongly associated with high interpersonal trust (ORT3vsT1 = 5.75, 95%CI = 4.33-7.64). Also significantly associated with high interpersonal trust were: Having voted in the last national election (for the opposition, OR = 1.39, 95%CI = 1.02-1.89 or the governing party, OR = 1.61, 95%CI = 1.23-2.11) versus non-voters; perspective taking (ORT3vsT1 = 1.46, 95%CI = 1.11-1.91); being more extraverted (ORT3vsT1 = 1.99, 95%CI = 1.53-2.59) and more agreeable (ORT3vsT1 = 1.95, 95% CI = 1.46-2.61); and scoring higher on complexity thinking (ORT3vsT1 = 1.32, 95%CI = 1.01-1.72). Participants scoring significantly lower for interpersonal trust did not regularly participate in religious meetings (OR = 0.61, 95%CI = 0.44-0.84, versus participation at least monthly); were more conscientious (ORT3vsT1 = 0.68, 95%CI = 0.51-0.91) or current smokers (OR = 0.68; 95%CI = 0.53-0.87, versus never smoking); had sleep problems >5 times a week (OR = 0.48; 95%CI = 0.36-0.66, versus none); and scored high on conspiracy belief (ORT3vsT1 = 0.53; 95%CI = 0.41-0.69). Results differed minimally by gender and country. These findings may be helpful in devising targeted strategies to strengthen interpersonal trust and social engagement in European societies, especially during times of crises., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Schernhammer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Emergence of new coronavirus variants and waning immunity may necessitate regular COVID-19 vaccine boosters, but empirical data on population willingness for regular vaccination are limited., Methods: In August 2021, we surveyed 3,067 quota-sampled German-speaking adults residing in the D-A-CH region (Germany, Austria, Switzerland). Using multivariable adjusted ordered logistic regression models we calculated odds ratios (OR) and 95% confidence intervals (95% CIs) to assess factors associated with willingness to vaccinate annually against COVID-19., Findings: Among 2,480 participants vaccinated or planning to get vaccinated, 82·4% indicated willingness to receive annual COVID-19 boosters. This willingness was higher in Austria (OR=1·47, 95% CI, 1·19-1·82; p < 0·001) and Germany (OR=1·98, 95% CI, 1·60-2·45; p  < 0·001) versus Switzerland and increased with age. Having voted in the last national election (OR opposition party voters =1·51, 95% CI=1·18-1·92; p  = 0·001 and OR governing party voters =1·57, 95% CI=1·28-1·93; p  < 0·001, versus non-voters) and not regularly participating in religious meetings (OR=1·37, 95% CI=1·08-1·73; p  = 0·009, versus participation at least monthly) were significantly associated with willingness to vaccinate, as was partial (OR=1·97, 95% CI=1·43-2·72; p  < 0·001) or total (OR=5·20, 95% CI=3·76-7·19; p  < 0·001) approval of COVID-19 mitigation measures (versus non-approval). By country, Austrians showed the strongest association of voting behavior and mitigation measure approval with willingness to vaccinate., Interpretation: Targeted promotion programs informed by political and religious engagement and mitigation measure approval are needed to increase willingness to receive regular COVID-19 boosters., Funding: Medical University of Vienna, Department of Epidemiology, Danube University Krems, Department for Knowledge and Communication Management; Austrian Society of Epidemiology., Competing Interests: JW received funding from the Austrian Society of Epidemiology. BMB reports that her institution (Brigham and Women's Hospital, Boston, MA, USA) received research grant funding from the US National Institutes of Health and from the American Institute for Cancer Research (AICR) to support research projects that she leads and that are unrelated to this manuscript (cancer etiology studies). She is also has been an unpaid member of the Scientific Advisory Panel of the Oliver Foundation (Key Biscayne, FL) since 2015 to help guide their work on pediatric cancer prevention. IS reports royalties from book publications and Honoraria (about 2-3 times per year) for invited lectures not exceeding on the average € 1000 per year. MB reports to have received funding from the German Federal Ministry of Science and Education, German Federal Ministry of Economic affairs, Saxonian Ministry of Science and the Arts, EU H-2020 and honoraria for reviews from European public funding organizations. MB also reports patents DE102021115850.8; DE102020134133.4; DE102020107138.8; DE102018105449.1; and he is Member of the Executive committee of the Saxonian Academy of Sciences, Secretary General for the technical sciences in the Saxonian Academy of Sciences, Head of DECHEMA expert group “Raw Materials”, as well as Director of Recycling unit at Fraunhofer Institute for Ceramic Technologies and Systems IKTS; Fraunhofer Technology Center for High-Performance Materials THM, Am St.-Niclas-Schacht 13, 09599 Freiberg, Germany. LZ reports small shares in a stock portfolio < 500 EUR. MDL reports funding from the NSF (USA), small amounts of royalties for several published books, and he is Advisory boards (KLI; Complexity Science Hub, Vienna, TU Graz; TISE). ESS reports funding from the National Institute of Health, FFG, FWF, H-2020, and received honoraria (about 2-3 times per year, each never >1000 Euro) for invited lectures. She is member on the Advisory board of trustees of the FWF (Austrian Science Fund), and the Scientific Advisory Board for the Annual Houska Award; honorary board member of the Austrian Cancer Help; scientific advisory board member for Cochrane Austria; advisory board member of the Austrian Scientific Community and member of Board of Trustees “Sparkling Science” Funding, Ministry of Health Austria; as well as ad hoc NIH study section member and Horizon Europe Scientific Review Panel member., (© 2022 The Author(s).)

Background: With the coronavirus disease 2019 (COVID-19) pandemic surging and new mutations evolving, trust in vaccines is essential., Methods: We explored correlates of vaccine hesitancy, considering political believes and psychosocial concepts, conducting a non-probability quota-sampled online survey with 1007 Austrians., Results: We identified several important correlates of vaccine hesitancy, ranging from demographics to complex factors such as voting behavior or trust in the government. Among those with hesitancy towards a COVID-19 vaccine, having voted for opposition parties (opp) or not voted (novote) were (95% Confidence Intervall (CI)opp, 1.44-2.95) to 2.25-times (95%CInovote, 1.53-3.30) that of having voted for governing parties. Only 46.2% trusted the Austrian government to provide safe vaccines, and 80.7% requested independent scientific evaluations regarding vaccine safety to increase willingness to vaccine., Conclusions: Contrary to expected, psychosocial dimensions were only weakly correlated with vaccine hesitancy. However, the strong correlation between distrust in the vaccine and distrust in authorities suggests a common cause of disengagement from public discourse., (© The Author(s) 2021. Published by Oxford University Press on behalf of Faculty of Public Health.)

The origins of innovation in science are typically understood using historical narratives that tend to be focused on small sets of influential authors, an approach that is rigorous but limited in scope. Here, we develop a framework for rigorously identifying innovation across an entire scientific field through automated analysis of a corpus of over 6000 documents that includes every paper published in the field of evolutionary medicine. This comprehensive approach allows us to explore statistical properties of innovation, asking where innovative ideas tend to originate within a field's pre-existing conceptual framework. First, we develop a measure of innovation based on novelty and persistence, quantifying the collective acceptance of novel language and ideas. Second, we study the field's conceptual landscape through a bibliographic coupling network. We find that innovations are disproportionately more likely in the periphery of the bibliographic coupling network, suggesting that the relative freedom allowed by remaining unconnected with well-established lines of research could be beneficial to creating novel and lasting change. In this way, the emergence of collective computation in scientific disciplines may have robustness-adaptability trade-offs that are similar to those found in other biosocial complex systems., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

To build better theories of cities, companies, and other social institutions such as universities, requires that we understand the tradeoffs and complementarities that exist between their core functions, and that we understand bounds to their growth. Scaling theory has been a powerful tool for addressing such questions in diverse physical, biological and urban systems, revealing systematic quantitative regularities between size and function. Here we apply scaling theory to the social sciences, taking a synoptic view of an entire class of institutions. The United States higher education system serves as an ideal case study, since it includes over 5,800 institutions with shared broad objectives, but ranges in strategy from vocational training to the production of novel research, contains public, nonprofit and for-profit models, and spans sizes from 10 to roughly 100,000 enrolled students. We show that, like organisms, ecosystems and cities, universities and colleges scale in a surprisingly systematic fashion following simple power-law behavior. Comparing seven commonly accepted sectors of higher education organizations, we find distinct regimes of scaling between a school's total enrollment and its expenditures, revenues, graduation rates and economic added value. Our results quantify how each sector leverages specific economies of scale to address distinct priorities. Taken together, the scaling of features within a sector along with the shifts in scaling across sectors implies that there are generic mechanisms and constraints shared by all sectors, which lead to tradeoffs between their different societal functions and roles. We highlight the strong complementarity between public and private research universities, and community and state colleges, that all display superlinear returns to scale. In contrast to the scaling of biological systems, our results highlight that much of the observed scaling behavior is modulated by the particular strategies of organizations rather than an immutable set of constraints., Competing Interests: The authors have declared that no competing interests exist.

COVID-19 has revealed that science needs to learn how to better deal with the irreducible uncertainty that comes with global systemic risks as well as with the social responsibility of science towards the public good. Further developing the epistemological principles of new theories and experimental practices, alternative investigative pathways and communication, and diverse voices can be an important contribution of history and philosophy of science and of science studies to ongoing transformations of the scientific enterprise.

We would like to extend on the article by Alley et al [...].

To what extent do simultaneous innovations occur and are independently from each other? In this paper we use a novel persistent keyword framework to systematically identify innovations in a large corpus containing academic papers in evolutionary medicine between 2007 and 2011. We examine whether innovative papers occurring simultaneously are independent from each other by evaluating the citation and co-authorship information gathered from the corpus metadata. We find that 19 out of 22 simultaneous innovative papers do, in fact, occur independently from each other. In particular, co-authors of simultaneous innovative papers are no more geographically concentrated than the co-authors of similar non-innovative papers in the field. Our result suggests producing innovative work draws from a collective knowledge pool, rather than from knowledge circulating in distinct localized collaboration networks. Therefore, new ideas can appear at multiple locations and with geographically dispersed co-authorship networks. Our findings support the perspective that simultaneous innovations are the outcome of collective behavior.

Although the first coronavirus disease 2019 (COVID-19) wave has peaked with the second wave underway, the world is still struggling to manage potential systemic risks and unpredictability of the pandemic. A particular challenge is the "superspreading" of the virus, which starts abruptly, is difficult to predict, and can quickly escalate into medical and socio-economic emergencies that contribute to long-lasting crises challenging our current ways of life. In these uncertain times, organizations and societies worldwide are faced with the need to develop appropriate strategies and intervention portfolios that require fast understanding of the complex interdependencies in our world and rapid, flexible action to contain the spread of the virus as quickly as possible, thus preventing further disastrous consequences of the pandemic. We integrate perspectives from systems sciences, epidemiology, biology, social networks, and organizational research in the context of the superspreading phenomenon to understand the complex system of COVID-19 pandemic and develop suggestions for interventions aimed at rapid responses.

The two most fundamental processes describing change in biology, development, and evolution, occur over drastically different timescales. Development involves temporal sequences of cell states controlled by hierarchies of regulatory structures. It occurs over the lifetime of a single individual and is associated with gene expression level change of a given genotype. Evolution, by contrast, entails genotypic change through mutation, the acquisition/loss of genes and changes in the network topology of interactions among genes. It involves the emergence of new, environmentally selected phenotypes over the lifetimes of many individuals. We start by reviewing the most limiting aspects of the theoretical modeling of gene regulatory networks (GRNs) which prevent the study of both timescales in a common, mathematical language. We then consider the simple framework of Boolean network models of GRNs and point out its inadequacy to include evolutionary processes. As opposed to one-to-one maps to specific attractors, we adopt a many-to-one map which makes each phenotype correspond to multiple attractors. This definition no longer requires a fixed size for the genotype and opens the possibility for modeling the phenotypic change of a genotype, which is itself changing over evolutionary timescales. At the same time, we show that this generalized framework does not interfere with established numerical techniques for the identification of the kernel of controlling nodes responsible for cell differentiation through external signals., (© 2020 Wiley Periodicals, Inc.)

Systems biology is a discipline that studies biological systems from a holistic and interdisciplinary perspective. It brings together biologists, mathematicians, computer scientists, physicists, and engineers, so it has both biology-oriented components and systems-oriented components. We applied several computational tools to analyze the bibliographic information of published articles in systems biology to answer the question: Did the research topics of systems biology become more biology-oriented or more systems-oriented from 1992 to 2013? We analyzed the metadata of 9923 articles on systems biology from the Web of Science database. We identified the most highly cited 330 references using computational tools and through close reading we divided them into nine categories of research types in systems biology. Interestingly, we found that articles in one category, namely, systems biology's applications in medical research, increased tremendously. This finding was corroborated by computational analysis of the abstracts, which also suggested that the percentages of topics on vaccines, diseases, drugs and cancers increased over time. In addition, we analyzed the institutional backgrounds of the corresponding authors of those 9923 articles and identified the most highly cited 330 authors over time. We found that before the mid-1990s, systems-oriented scientists had made the most referenced contributions. However, in recent years, researchers from biology-oriented institutions not only represented a huge percentage of the total number of researchers, but also had made the most referenced contributions. Notably, interdisciplinary institutions only produced a small percentage of researchers, but had made disproportionate contributions to this field., Competing Interests: The authors have declared that no competing interests exist.

Reconciling different underlying ontologies and explanatory contexts has been one of the main challenges and impediments for theory integration in biology. Here, we analyze the challenge of developing an inclusive and integrative theory of phenotypic evolution as an example for the broader challenge of developing a theory of theory integration within the life sciences and suggest a number of necessary formal steps toward the resolution of often incompatible (hidden) assumptions. Theory integration in biology requires a better formal understanding of the structure of biological theories The strategy for integrating theories crucially depends on the relationships of the underlying ontologies., (© 2018 Wiley Periodicals, Inc.)

Journal of the History of Biology provides a fifty-year long record for examining the evolution of the history of biology as a scholarly discipline. In this paper, we present a new dataset and preliminary quantitative analysis of the thematic content of JHB from the perspectives of geography, organisms, and thematic fields. The geographic diversity of authors whose work appears in JHB has increased steadily since 1968, but the geographic coverage of the content of JHB articles remains strongly lopsided toward the United States, United Kingdom, and western Europe and has diversified much less dramatically over time. The taxonomic diversity of organisms discussed in JHB increased steadily between 1968 and the late 1990s but declined in later years, mirroring broader patterns of diversification previously reported in the biomedical research literature. Finally, we used a combination of topic modeling and nonlinear dimensionality reduction techniques to develop a model of multi-article fields within JHB. We found evidence for directional changes in the representation of fields on multiple scales. The diversity of JHB with regard to the representation of thematic fields has increased overall, with most of that diversification occurring in recent years. Drawing on the dataset generated in the course of this analysis, as well as web services in the emerging digital history and philosophy of science ecosystem, we have developed an interactive web platform for exploring the content of JHB, and we provide a brief overview of the platform in this article. As a whole, the data and analyses presented here provide a starting-place for further critical reflection on the evolution of the history of biology over the past half-century.

Contrary to concerns of some critics, we present evidence that biomedical research is not dominated by a small handful of model organisms. An exhaustive analysis of research literature suggests that the diversity of experimental organisms in biomedical research has increased substantially since 1975. There has been a longstanding worry that organism-centric funding policies can lead to biases in experimental organism choice, and thus negatively impact the direction of research and the interpretation of results. Critics have argued that a focus on model organisms has unduly constrained the diversity of experimental organisms. The availability of large electronic databases of scientific literature, combined with interest in quantitative methods among philosophers of science, presents new opportunities for data-driven investigations into organism choice in biomedical research. The diversity of organisms used in NIH-funded research may be considerably lower than in the broader biomedical sciences, and may be subject to greater constraints on organism choice., (© 2017 WILEY Periodicals, Inc.)

Cell types are the basic building blocks of multicellular organisms and are extensively diversified in animals. Despite recent advances in characterizing cell types, classification schemes remain ambiguous. We propose an evolutionary definition of a cell type that allows cell types to be delineated and compared within and between species. Key to cell type identity are evolutionary changes in the 'core regulatory complex' (CoRC) of transcription factors, that make emergent sister cell types distinct, enable their independent evolution and regulate cell type-specific traits termed apomeres. We discuss the distinction between developmental and evolutionary lineages, and present a roadmap for future research.

Function is a central concept in biological theories and explanations. Yet discussions about function are often based on a narrow understanding of biological systems and processes, such as idealized molecular systems or simple evolutionary, i.e., selective, dynamics. Conflicting conceptions of function continue to be used in the scientific literature to support certain claims, for instance about the fraction of "functional DNA" in the human genome. Here we argue that all biologically meaningful interpretations of function are necessarily context dependent. This implies that they derive their meaning as well as their range of applicability only within a specific theoretical and measurement context. We use this framework to shed light on the current debate about functional DNA and argue that without considering explicitly the theoretical and measurement contexts all attempts to integrate biological theories are prone to fail.

This paper introduces a conceptual framework for the evolution of complex systems based on the integration of regulatory network and niche construction theories. It is designed to apply equally to cases of biological, social and cultural evolution. Within the conceptual framework we focus especially on the transformation of complex networks through the linked processes of externalization and internalization of causal factors between regulatory networks and their corresponding niches and argue that these are an important part of evolutionary explanations. This conceptual framework extends previous evolutionary models and focuses on several challenges, such as the path-dependent nature of evolutionary change, the dynamics of evolutionary innovation and the expansion of inheritance systems., (© 2015 The Authors. Journal of Experimental Zoology Part B: Molecular and Developmental Evolution published by Wiley Periodicals, Inc.)

Computational methods and perspectives can transform the history of science by enabling the pursuit of novel types of questions, dramatically expanding the scale of analysis (geographically and temporally), and offering novel forms of publication that greatly enhance access and transparency. This essay presents a brief summary of a computational research system for the history of science, discussing its implications for research, education, and publication practices and its connections to the open-access movement and similar transformations in the natural and social sciences that emphasize big data. It also argues that computational approaches help to reconnect the history of science to individual scientific disciplines.

The difference in phenotypes of queens and workers is a hallmark of the highly eusocial insects. The caste dimorphism is often described as a switch-controlled polyphenism, in which environmental conditions decide an individual's caste. Using theoretical modeling and empirical data from honeybees, we show that there is no discrete larval developmental switch. Instead, a combination of larval developmental plasticity and nurse worker feeding behavior make up a colony-level social and physiological system that regulates development and produces the caste dimorphism. Discrete queen and worker phenotypes are the result of discrete feeding regimes imposed by nurses, whereas a range of experimental feeding regimes produces a continuous range of phenotypes. Worker ovariole numbers are reduced through feeding-regime-mediated reduction in juvenile hormone titers, involving reduced sugar in the larval food. Based on the mechanisms identified in our analysis, we propose a scenario of the evolutionary history of honeybee development and feeding regimes.

The evolution and development of complex phenotypes in social insect colonies, such as queen-worker dimorphism or division of labor, can, in our opinion, only be fully understood within an expanded mechanistic framework of Developmental Evolution. Conversely, social insects offer a fertile research area in which fundamental questions of Developmental Evolution can be addressed empirically. We review the concept of gene regulatory networks (GRNs) that aims to fully describe the battery of interacting genomic modules that are differentially expressed during the development of individual organisms. We discuss how distinct types of network models have been used to study different levels of biological organization in social insects, from GRNs to social networks. We propose that these hierarchical networks spanning different organizational levels from genes to societies should be integrated and incorporated into full GRN models to elucidate the evolutionary and developmental mechanisms underlying social insect phenotypes. Finally, we discuss prospects and approaches to achieve such an integration., (© 2012 WILEY PERIODICALS, INC.)

Scientific theories seek to provide simple explanations for significant empirical regularities based on fundamental physical and mechanistic constraints. Biological theories have rarely reached a level of generality and predictive power comparable to physical theories. This discrepancy is explained through a combination of frozen accidents, environmental heterogeneity, and widespread non-linearities observed in adaptive processes. At the same time, model building has proven to be very successful when it comes to explaining and predicting the behavior of particular biological systems. In this respect biology resembles alternative model-rich frameworks, such as economics and engineering. In this paper we explore the prospects for general theories in biology, and suggest that these take inspiration not only from physics, but also from the information sciences. Future theoretical biology is likely to represent a hybrid of parsimonious reasoning and algorithmic or rule-based explanation. An open question is whether these new frameworks will remain transparent to human reason. In this context, we discuss the role of machine learning in the early stages of scientific discovery. We argue that evolutionary history is not only a source of uncertainty, but also provides the basis, through conserved traits, for very general explanations for biological regularities, and the prospect of unified theories of life., (Copyright © 2011. Published by Elsevier Ltd.)

This essay describes the approach and early results of the collaborative Embryo Project and its on-line encyclopedia (http://embryo.asu.edu). The project is based on a relational database that allows federated searches and inclusion of multiple types of objects targeted for multiple user groups. The emphasis is on the history and varied contexts of developmental biology, focusing on people, places, institutions, techniques, literature, images, and other aspects of study of embryos. This essay introduces the ways of working as well as the long-term goals of the project. We invite others to join the effort, both in this particular project and in joining together in digital collection, archiving, and knowledge generation at the borders of biology and history.

Theodor Boveri's major intellectual contribution was his focus on the causality of nuclear chromosomal determinants for embryological development. His initial experimental attempt to demonstrate that the character of the developing embryo is determined by nuclear rather than cytoplasmic factors was launched in 1889. The experimental design was to fertilize enucleate sea urchin eggs with sperm of another species that produces a distinguishably different embryonic morphology. Boveri's "hybrid merogone" experiment provided what he initially thought was empirical evidence for the nuclear control of development. However, for subtle reasons, the data were not interpretable and the experiment was repeated and contested. At the end of his life, Boveri was finally able to explain the technical difficulties that had beset the original experiment. However, by 1902 Boveri had carried out his famous polyspermy experiments, which provided decisive evidence for the role of nuclear chromosomal determinants in embryogenesis. Here we present the history of the hybrid merogone experiment as an important case of conceptual reasoning paired with (often difficult) experimental approaches. We then trace the further history of the merogone and normal species hybrid approaches that this experiment had set in train, and review their results from the standpoint of current insights. The history of Boveri's hybrid merogone experiment suggests important lessons about the interplay between what we call "models", the specific intellectual statements we conceive about how biology works, and the sometimes difficult task of generating experimental proof for these concepts.

Francois Jacob's article 'Evolution and Tinkering' published in Science in 1977 is still the locus classicus for the concept of tinkering in biology. It first introduced the notion of tinkering to a wide audience of scientists. Jacob drew on a variety of different sources ranging from molecular biology to evolutionary biology and cultural anthropology. The notion of tinkering, or more accurately, the concept of bricolage, are conceptual abstractions that allow for the theoretical analysis of a wide range of phenomena that are united by a shared underlying process--tinkering, or the opportunistic rearrangement and recombination of existing elements. This paper looks at Jacob's analysis as itself an example of conceptual tinkering. It traces the history of some of its elements and sketches how it has become part of an inclusive discourse of theoretical biology and evolutionary developmental biology that emerged over the last 30 years. I will argue that the theoretical power of Jacob's analysis lies in the fact that he captured a widespread phenomenon. His conceptual analysis is thus an example of an interdisciplinary synthesis that is based on a shared process rather than a shared object.

Alfred Kühn (1885-1968) was known as one of the most comprehensive zoologists of his time. His research program in developmental physiological genetics was one of the first successful attempts to integrate the experimental study of development and heredity. It led him to discover the first known reaction chain from gene to phenotype. Kühn also foresaw many elements of modern evolutionary developmental biology and as a student of Weismann and mentor to many developmental geneticists of the late 20th century directly connects Weismann with molecular developmental genetics., (Copyright 2004 Wiley-Liss, Inc.)

We present a mathematically precise formulation of total linkage disequilibrium between multiple loci as the deviation from probabilistic independence and provide explicit formulas for all higher-order terms of linkage disequilibrium, thereby combining J. Dausset et al.'s 1978 definition of linkage disequilibrium with H. Geiringer's 1944 approach. We recursively decompose higher-order linkage disequilibrium terms into lower-order ones. Our greatest simplification comes from defining linkage disequilibrium at a single locus as allele frequency at that locus. At each level, decomposition of linkage disequilibrium is mathematically equivalent to number theoretic compositions of positive integers; i.e., we have converted a genetic decomposition into a mathematical decomposition.

This paper reviews the scientific career of Rupert Riedl and his contributions to evolutionary biology. Rupert Riedl, a native of Vienna, Austria, began his career as a marine biologist who made important contributions to the systematics and anatomy of major invertebrate groups, as well as to marine ecology. When he assumed a professorship at the University of North Carolina in 1968, the predominant thinking in evolutionary biology focused on population genetics, to the virtual exclusion of most of the rest of biology. In this atmosphere Riedl developed his "systems theory" of evolution, which emphasizes the role of functional and developmental integration in limiting and enabling adaptive evolution by natural selection. The main objective of this theory is to account for the observed patterns of morphological evolution, such as the conservation of body plans. In contrast to other "alternative" theories of evolution, Riedl never denied the importance of natural selection as the driving force of evolution, but thought it necessary to contextualize natural selection with the organismal boundary conditions of adaptation. In Riedl's view development is the most important factor besides natural selection in shaping the pattern and processes of morphological evolution., (Copyright 2004 Wiley-Liss, Inc.)

Epistasis is defined as the influence of the genotype at one locus on the effect of a mutation at another locus. As such it plays a crucial role in a variety of evolutionary phenomena such as speciation, population bottle necks, and the evolution of genetic architecture (i.e., the evolution of dominance, canalization, and genetic correlations). In mathematical population genetics, however, epistasis is often represented as a mere noise term in an additive model of gene effects. In this paper it is argued that epistasis needs to be scaled in a way that is more directly related to the mechanisms of evolutionary change. A review of general measurement theory shows that the scaling of a quantitative concept has to reflect the empirical relationships among the objects. To apply these ideas to epistatic mutation effects, it is proposed to scale A x A epistatic effects as the change in the magnitude of the additive effect of a mutation at one locus due to a mutation at a second locus. It is shown that the absolute change in the additive effect at locus A due to a substitution at locus B is always identical to the absolute change in B due to the substitution at A. The absolute A x A epistatic effects of A on B and of B on A are identical, even if the relative effects can be different. The proposed scaling of A x A epistasis leads to particularly simple equations for the decomposition of genotypic variance. The Kacser Burns model of metabolic flux is analyzed for the presence of epistatic effects on flux. It is shown that the non-linearity of the Kacser Burns model is not sufficient to cause A x A epistasis among the genes coding for enzymes. It is concluded that non-linearity of the genotype-phenotype map is not sufficient to cause epistasis. Finally, it is shown that there exist correlations among the additive and epistatic effects among pairs of loci, caused by the inherent symmetries of Mendelian genetic systems. For instance, it is shown that a mutation that has a larger than average additive effect will tend to decrease the additive effect of a second mutation, i.e., it will tend to have a negative (canalizing) interaction with a subsequent gene substitution. This is confirmed in a preliminary analysis of QTL-data for adult body weight in mice.