Bioscientists generate far more data than their minds can handle, and this trend is likely to continue. With the aid of a small set of versatile tools for mathematical modeling and statistical assessment, bioscientists can explore their real-world systems without experiencing data overflow. This article outlines an approach for combining modern high-throughput, low-cost, but non-selective biospectroscopy measurements with soft, multivariate biochemometrics data modeling to overview complex systems, test hypotheses, and making new discoveries. From preliminary, broad hypotheses and goals, many relevant (...) samples are selected and measured with respect to many informative variables. The resulting tables represent a “cacophony” of data. From these, the most relevant and reliable “underlying harmonies and rhythms” are extracted and tested statistically, displayed for interpretation, and used for prediction. Outliers are detected automatically. Interesting subsets of samples can then be chosen for in-depth analyses in subsequent research cycles. This pragmatic, top-down approach takes advantage of developments in both “soft,” data-driven modeling and “hard,” knowledge-driven cultures. Data analytical examples show how information-rich biospectroscopy can be used for characterizing and quantifying known and unknown chemical constituents and physical phenomena in intact biosamples. This is based on a combination of deductive “hard” and inductive “soft” modeling. The examples represent NIR spectra of biochemical mixtures, FTIR spectra of a microbiological fermentation process, and FTIR analysis of fatty acids in milk for functional genomics. (shrink)

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. (shrink)

The term “synthetic biology” is a popular label of an emerging biotechnological field with strong claims to robustness, modularity, and controlled construction, finally enabling the creation of new organisms. Although the research community is heterogeneous, it advocates a common denominator that seems to define this field: the principles of rational engineering. However, it still remains unclear to what extent rational engineering—rather than “tinkering” or the usage of random based or non-rational processes—actually constitutes the basis for the techniques of synthetic (...) biology. In this article, we present the results of a quantitative bibliometric analysis of the realized extent of rational engineering in synthetic biology. In our analysis, we examine three issues: (1) We evaluate whether work at three levels of synthetic biology (parts, devices, and systems) is consistent with the principles of rational engineering. (2) We estimate the extent of rational engineering in synthetic biology laboratory practice by an evaluation of publications in synthetic biology. (3) We examine the methodological specialization in rational engineering of authors in synthetic biology. Our analysis demonstrates that rational engineering is prevalent in about half of the articles related to synthetic biology. Interestingly, in recent years the relative number of respective publications has decreased. Despite its prominent role among the claims of synthetic biology, rational engineering has not yet entirely replaced biotechnological methods based on “tinkering” and non-rational principles. (shrink)

Phylogenetics has inherent utility in evolutionary developmental biology (EDB) as it is an established methodology for estimating evolutionary relationships and for making comparisons between levels of biological organization. However, explicit phylogenetic methods generally have been limited to two levels of organization in EDB—the species and the gene. We demonstrate that phylogenetic methods can be applied broadly to other organizational levels, such as morphological structures or cell types, to identify evolutionary patterns. We present examples at and between different hierarchical levels (...) of organization to address questions central to EDB. We argue that this application of “hierarchical phylogenetics” can be a unifying analytical approach to the field of EDB. BioEssays 27:1158–1166, 2005. © 2005 Wiley Periodicals, Inc. (shrink)

This paper challenges the common assumption that some phenotypic traits are quantitative while others are qualitative. The distinction between these two kinds of traits is widely influential in biological and biomedical research as well as in scientific education and communication. This is probably due to both historical and epistemological reasons. However, the quantitative/qualitative distinction involves a variety of simplifications on the genetic causes of phenotypic variability and on the development of complex traits. Here, I examine three cases from (...) the life sciences that show inconsistencies in the distinction: Mendelian traits, Mendelian diseases, and polygenic mental disorders. I show that these traits can be framed both quantitatively and qualitatively depending, for instance, on the methods through which they are investigated and on specific epistemic purposes. This suggests that the received view of quantitative and qualitative traits has a limited heuristic power—limited to some local contexts or to the specific methodologies adopted. Throughout the paper, I provide directions for framing phenotypes beyond the quantitative/qualitative distinction. I conclude by pointing at the necessity of developing a principled characterisation of what phenotypic traits, in general, are. (shrink)

To study the interaction of forces that produce chest wall motion, we propose a model based on the lever system of Hillman and Finucane :951–961, 1987) and introduce some dynamic properties of the respiratory system. The passive elements are considered as elastic compartments linked to the open air via a resistive tube, an image of airways. The respiratory muscles force is applied to both compartments. Parameters of the model are identified in using experimental data of airflow signal measured by pneumotachography (...) and rib cage and abdomen signals measured by respiratory inductive plethysmography on eleven healthy volunteers in five conditions: at rest and with four level of added loads. A breath by breath analysis showed, whatever the individual and the condition are, that there are several breaths on which the airflow simulated by our model is well fitted to the airflow measured by pneumotachography as estimated by a determination coefficient R2 ≥ 0.70. This very simple model may well represent the behaviour of the chest wall and thus may be useful to interpret the relative motion of rib cage and abdomen during quiet breathing. (shrink)

The twentieth century witnessed a dramatic increase in the use of statistics by biologists, including systematists. The modern synthesis and new systematics stimulated this development, particularly after World War II. The rise of "the statistical frame of mind " resulted in a rethinking of the relationship between biological and mathematical points of view, the roles of objectivity and subjectivity in systematic research, the implications of new computing technologies, and the place of systematics among the biological disciplines.

How fast? How strong? How many? So what? Why do numbers matter in biology? Chromatin binding proteins are forever in motion, exchanging rapidly between bound and free pools. How do regulatory systems whose components are in constant flux ensure stability and flexibility? This review explores the application of quantitative and mathematical approaches to mechanisms of epigenetic regulation. We discuss methods for measuring kinetic parameters and protein quantities in living cells, and explore the insights that have been gained by (...) quantifying and modelling dynamics of chromatin binding proteins. (shrink)

The paper discusses how systems biology is working toward complex accounts that integrate explanation in terms of mechanisms and explanation by mathematical models—which some philosophers have viewed as rival models of explanation. Systems biology is an integrative approach, and it strongly relies on mathematical modeling. Philosophical accounts of mechanisms capture integrative in the sense of multilevel and multifield explanations, yet accounts of mechanistic explanation have failed to address how a mathematical model could contribute to such explanations. I discuss (...) how mathematical equations can be explanatorily relevant. Several cases from systems biology are discussed to illustrate the interplay between mechanistic research and mathematical modeling, and I point to questions about qualitative phenomena, where quantitative models are still indispensable to the explanation. Systems biology shows that a broader philosophical conception of mechanisms is needed, which takes into account functional-dynamical aspects, interaction in complex networks with feedback loops, system-wide functional properties such as distributed functionality and robustness, and a mechanism’s ability to respond to perturbations. I offer general conclusions for philosophical accounts of explanation. (shrink)

RNA binding proteins (RBPs) are key factors for the regulation of gene expression by binding to cis elements, i.e. short sequence motifs in RNAs. Recent studies demonstrate that cooperative binding of multiple RBPs is important for the sequence‐specific recognition of RNA and thereby enables the regulation of diverse biological activities by a limited set of RBPs. Cross‐linking immuno‐precipitation (CLIP) and other recently developed high‐throughput methods provide comprehensive, genome‐wide maps of protein‐RNA interactions in the cell. Structural biology gives detailed insights (...) into molecular mechanisms and principles of RNA recognition by RBPs, but has so far focused on single RNA binding proteins and often on single RNA binding domains. The combination of high‐throughput methods and detailed structural biology studies is expected to greatly advance our understanding of the code for protein‐RNA recognition in gene regulation, as we review in this article. (shrink)

To study the interaction of forces that produce chest wall motion, we propose a model based on the lever system of Hillman and Finucane (J Appl Physiol 63(3):951–961, 1987 ) and introduce some dynamic properties of the respiratory system. The passive elements (rib cage and abdomen) are considered as elastic compartments linked to the open air via a resistive tube, an image of airways. The respiratory muscles (active) force is applied to both compartments. Parameters of the model are identified in (...) using experimental data of airflow signal measured by pneumotachography and rib cage and abdomen signals measured by respiratory inductive plethysmography on eleven healthy volunteers in five conditions: at rest and with four level of added loads. A breath by breath analysis showed, whatever the individual and the condition are, that there are several breaths on which the airflow simulated by our model is well fitted to the airflow measured by pneumotachography as estimated by a determination coefficient R 2 ≥ 0.70. This very simple model may well represent the behaviour of the chest wall and thus may be useful to interpret the relative motion of rib cage and abdomen during quiet breathing. (shrink)

Pointillistic based super‐resolution techniques, such as photoactivated localization microscopy (PALM), involve multiple cycles of sequential activation, imaging, and precise localization of single fluorescent molecules. A super‐resolution image, having nanoscopic structural information, is then constructed by compiling all the image sequences. Because the final image resolution is determined by the localization precision of detected single molecules and their density, accurate image reconstruction requires imaging of biological structures labeled with fluorescent molecules at high density. In such image datasets, stochastic variations in photon (...) emission and intervening dark states lead to uncertainties in identification of single molecules. This, in turn, prevents the proper utilization of the wealth of information on molecular distribution and quantity. A recent strategy for overcoming this problem is pair‐correlation analysis applied to PALM. Using rigorous statistical algorithms to estimate the number of detected proteins, this approach allows the spatial organization of molecules to be quantitatively described. (shrink)

Quantitative comparison of human language and natural animal communication requires improved conceptualizations. We argue that an infrastructural approach to development and evolution incorporating an extended interpretation of the distinctions among illocution, perlocution, and meaning can help place the issues relevant to quantitative comparison in perspective. The approach can illuminate the controversy revolving around the notion of functional referentiality as applied to alarm calls, for example in the vervet monkey. We argue that referentiality offers a poor point of (...) class='Hi'>quantitative comparison across language and animal communication in the wild. Evidence shows that even the newborn human cry could be deemed to show functional referentiality according to the criteria typically invoked by advocates of referentiality in animal communication. Exploring the essence of the idea of illocution, we illustrate an important realm of commonality among animal communication systems and human language, a commonality that opens the door to more productive, quantifiable comparisons. Finally, we delineate two examples of infrastructural communicative capabilities that should be particularly amenable to direct quantitative comparison across humans and our closest relatives. (shrink)

The evolutionary implications of environmental change due to organismic action remain a controversial issue, after a decades—long debate on the subject. Much of this debate has been conducted in qualitative fashion, despite the availability of mathematical models for organism–environment interactions, and for gene frequencies when allele fitness can be related to exploitation of a particular environmental resource. In this article we focus on representative models dealing with niche construction, ecosystem engineering, the Gaia Hypothesis and community interactions of Lotka–Volterra type, and (...) show that their quantitative character helps bring into sharper focus the similarities and differences among their respective theoretical contexts. (shrink)

Whether the food movement is most likely to transform the food system through ‘alternative’ or ‘oppositional’ initiatives has been the focus of considerable scholarly debate. Alternative initiatives are widespread but risk reinforcing the conventional food system by supporting neoliberal discourse and governance mechanisms, including localism, consumer choice, entrepreneurialism and self-help. While oppositional initiatives such as political advocacy have the potential for system-wide change, the current neoliberal political and ideological context dominant in Canada poses difficulties for initiatives that explicitly oppose the (...) conventional food system. As such, some argue that the food movement requires convergence between alternative and oppositional initiatives. In this paper, we investigate convergence using survey results from 143 food movement organizations in four Canadian provinces. Results based on cluster analysis and descriptive statistics on organizational discourse, activities and visions of sustainable food systems demonstrate convergence around neoliberal discourse and governance mechanisms. Localism and consumer education characteristics are particularly prominent, with a majority of respondents describing their organizations as ‘local’, engaging in consumer education activities, and stating the importance of consumer education activities, indicating convergence around alternative, rather than oppositional, initiatives. While convergence around these discourse and strategies may limit the transformative potential of the food system when interpreted as neoliberalisation of the movement, such a reading does not demonstrate their full potential, as survey results also indicate trends of transformative visions of change and political engagement, particularly at the municipal level. This research demonstrates that the movement can work simultaneously within, and opposed to, the conventional food system, and provides understanding of both neoliberal leanings and the politics of the possible of the food movement. (shrink)

The field of psychology has emphasized quantitative laboratory research as a defining character of its role as a science, and has generally de-emphasized qualitative research and theorizing throughout its history. This article reviews some of the effects of this emphasis in two areas, intelligence testing, and learning and memory. On one side, quantitative measurement produced the widely used IQ test but shed little light on the construct of intelligence and its role in human cognition. On the other side, (...) reductive quantification and experimental constraints limited the investigation and understanding of human memory systems and complex learning throughout the first century of the field’s history. Recent research under fewer constraints has made greater progress in these areas. (shrink)

During the last two decades the role of quantitative genetics in evolutionary theory has expanded considerably. Quantitative genetic-based models addressing long term phenotypic evolution, evolution in multiple environments (phenotypic plasticity) and evolution of ontogenies (developmental trajectories) have been proposed. Yet, the mathematical foundations of quantitative genetics were laid with a very different set of problems in mind (mostly the prediction of short term responses to artificial selection), and at a time in which any details of the genetic (...) machinery were virtually unknown. In this paper we discuss what a model is in population biology, and what kind of model we need in order to address the complexities of phenotypic evolution. We review the assumptions of quantitative genetics and its most recent accomplishments, together with the limitations that such assumptions impose on the modelling of some aspects of phenotypic evolution. We also discuss three alternative appr oaches to the theoretical description of evolutionary trajectories (nonlinear dynamics, complexity theory and optimization theory), and their respective advantages and limitations. We conclude by calling for a new theoretical synthesis, including quantitative genetics and not necessarily limited to the other approaches here discussed. (shrink)

Cancer is a complex disease, necessitating research on many different levels; at the subcellular level to identify genes, proteins and signaling pathways associated with the disease; at the cellular level to identify, for example, cell-cell adhesion and communication mechanisms; at the tissue level to investigate disruption of homeostasis and interaction with the tissue of origin or settlement of metastasis; and finally at the systems level to explore its global impact, e.g. through the mechanism of cachexia. Mathematical models have been proposed (...) to identify key mechanisms that underlie dynamics and events at every scale of interest, and increasing effort is now being paid to multi-scale models that bridge the different scales. With more biological data becoming available and with increased interdisciplinary efforts, theoretical models are rendering suitable tools to predict the origin and course of the disease. The ultimate aims of cancer models, however, are to enlighten our concept of the carcinogenesis process and to assist in the designing of treatment protocols that can reduce mortality and improve patient quality of life. Conventional treatment of cancer is surgery combined with radiotherapy or chemotherapy for localized tumors or systemic treatment of advanced cancers, respectively. Although radiation is widely used as treatment, most scheduling is based on empirical knowledge and less on the predictions of sophisticated growth dynamical models of treatment response. Part of the failure to translate modeling research to the clinic may stem from language barriers, exacerbated by often esoteric model renderings with inaccessible parameterization. Here we discuss some ideas for combining tractable dynamical tumor growth models with radiation response models using biologically accessible parameters to provide a more intuitive and exploitable framework for understanding the complexity of radiotherapy treatment and failure. (shrink)

This article explores the overlap between systems biology and predictive neuroscience, placing them in their larger context, the contemporary trend of bioinformatic convergence across the sciences. These two domains overlap with respect to their interest in data accumulation and data integration; their reliance on computational statistical correlation; and their translational goals, that is, producing practical fruits and applications from the interscientific cross-pollination that contemporary data-integrative approaches make possible. The interventions that such translational conversations generate are medical and social in (...) nature, and are aimed at both prevention and treatment. It will be argued that such approaches, socially and medically applied, contain potential for conveying both agency-enhancing and agency-diminishing social messages. The article concludes with a call to balance the overwhelmingly quantitative focus characteristic of predictive neuroscience with more qualitative empirical methodologies. This would represent a double helical approach. (shrink)

Predictions about the health risks of low level radiation combine two sorts of measures. One estimates the amount and kinds of radiation released into the environment, and the other estimates the adverse health effects. A new field called health physics integrates and applies nuclear physics to cytology to supply both these estimates. It does so by first determining the kinds of effects different types of radiation produce in biological organisms, and second, by monitoring the extent of these effects produced by (...) given levels of exposure. This essay examines the interplay between evidential constraints and external, contextual interests and values in studying the biological hazards of radiation. By analyzing the debate over linear vs. quadratic dose response models, the essay focuses on problems of developing quantitative, rather than qualitative, estimates of the risks of increased cancer incidence in an exposed population. (shrink)

This research is an investigation of whether consciousness—one's ongoing experience—influences one's behavior and, if so, how. Analysis of the components, structure, properties, and temporal sequences of consciousness has established that, (1) contrary to one's intuitive understanding, consciousness does not have an active, executive role in determining behavior; (2) consciousness does have a biological function; and (3) consciousness is solely information in various forms. Consciousness is associated with a flexible response mechanism (FRM) for decision-making, planning, and generally responding in nonautomatic ways. (...) The FRM generates responses by manipulating information and, to function effectively, its data input must be restricted to task-relevant information. The properties of consciousness correspond to the various input requirements of the FRM; and when important information is missing from consciousness, functions of the FRM are adversely affected; both of which indicate that consciousness is the input data to the FRM. Qualitative and quantitative information (shape, size, location, etc.) are incorporated into the input data by a qualia array of colors, sounds, and so on, which makes the input conscious. This view of the biological function of consciousness provides an explanation why we have experiences; why we have emotional and other feelings, and why their loss is associated with poor decision-making; why blindsight patients do not spontaneously initiate responses to events in their blind field; why counter-habitual actions are only possible when the intended action is in mind; and the reason for inattentional blindness. (shrink)

The dichotomy between the qualitative and the quantitative has been a classic throughout the history of science. As will be seen, this dichotomy permeates all ontological levels of reality. In this work, phenomenological examples potentially related to semiosis are presented at the different levels established by Mario Bunge and Josep Ferrater Mora, contrasting the qualitative categorizations with the quantifiable physical reality. Likewise, the need to continue in the quantification of the biosemiotic and linguistic studies will be presented, while, in (...) contrast, the need to establish a qualitative framework in the little-addressed study of technosemiotics will be raised, of potential interest given the notable advances that are expected in communication systems for inert artifacts in the next years. In short, in the thesis defended here the qualitative precedes the quantitative in the defining path of science. (shrink)

Understanding biological systems in terms of scientific materialism has arguably reached a frontier, leaving fundamental questions about their complexity unanswered. In 1998, Friedrich Cramer proposed a general resonance theory as a way forward. His theory builds on the extension of the quantum physical duality of matter and wave to the macroscopic world. According to Cramer’ theory, agents constituting biological systems oscillate, akin to musical soundwaves, at specific eigenfrequencies. Biological system dynamics can be described as “Symphonies of Life” emerging from the (...) resonance (and dissonance) of eigenfrequencies within the interacting collective. His theory has potential for studying biological problems of increasing complexity in a fast‐changing Anthropocene from a new and transdisciplinary angle. Despite data becoming increasingly available for analyses, Cramer's theory remains ignored and therefore untested a quarter century after its publication. This paper discusses how the theory can move to quantitative assessments and application. Cramer's general resonance theory deserves revival. (shrink)

Evolutionary developmental biology (evo-devo) is considered a ‘mechanistic science,’ in that it causally explains morphological evolution in terms of changes in developmental mechanisms. Evo-devo is also an interdisciplinary and integrative approach, as its explanations use contributions from many fields and pertain to different levels of organismal organization. Philosophical accounts of mechanistic explanation are currently highly prominent, and have been particularly able to capture the integrative nature of multifield and multilevel explanations. However, I argue that evo-devo demonstrates the need for (...) a broadened philosophical conception of mechanisms and mechanistic explanation. Mechanistic explanation (in terms of the qualitative interactions of the structural parts of a whole) has been developed as an alternative to the traditional idea of explanation as derivation from laws or quantitative principles. Against the picture promoted by Carl Craver, that mathematical models describe but usually do not explain, my discussion of cases from the strand of evo-devo which is concerned with developmental processes points to qualitative phenomena where quantitative mathematical models are an indispensable part of the explanation. While philosophical accounts have focused on the actual organization and operation of mechanisms, properties of developmental mechanisms that are about how a mechanism reacts to modifications are of major evolutionary significance, including robustness, phenotypic plasticity, and modularity. A philosophical conception of mechanisms is needed that takes into account quantitative changes, transient entities and the generation of novel types of entities, feedback loops and complex interaction networks, emergent properties, and, in particular, functional-dynamical aspects of mechanisms, including functional (as opposed to structural) organization and distributed, system-wide phenomena. I conclude with general remarks on philosophical accounts of explanation. (shrink)

We here review primary methods used in quantifying and mapping 5‐hydroxymethylcytosine (5hmC), including global quantification, restriction enzyme‐based detection, and methods involving DNA‐enrichment strategies and the genome‐wide sequencing of 5hmC. As discovered in the mammalian genome in 2009, 5hmC, oxidized from 5‐methylcytosine (5mC) by ten‐eleven translocation (TET) dioxygenases, is increasingly being recognized as a biomarker in biological processes from development to pathogenesis, as its various detection methods have shown. We focus in particular on an ultrasensitive single‐molecule imaging technique that can detect (...) and quantify 5hmC from trace samples and thus offer information regarding the distance‐based relationship between 5hmC and 5mC when used in combination with fluorescence resonance energy transfer. (shrink)

Modeling mechanisms is central to the biological sciences – for purposes of explanation, prediction, extrapolation, and manipulation. A closer look at the philosophical literature reveals that mechanisms are predominantly modeled in a purely qualitative way. That is, mechanistic models are conceived of as representing how certain entities and activities are spatially and temporally organized so that they bring about the behavior of the mechanism in question. Although this adequately characterizes how mechanisms are represented in biology textbooks, contemporary biological research (...) practice shows the need for quantitative, probabilistic models of mechanisms, too. In this paper we argue that the formal framework of causal graph theory is well-suited to provide us with models of biological mechanisms that incorporate quantitative and probabilistic information. On the ba-sis of an example from contemporary biological practice, namely feedback regulation of fatty acid biosynthesis in Brassica napus, we show that causal graph theoretical models can account for feedback as well as for the multi-level character of mechanisms. However, we do not claim that causal graph theoretical representations of mechanisms are advantageous in all respects and should replace common qualitative models. Rather, we endorse the more balanced view that causal graph theoretical models of mechanisms are useful for some purposes, while being insufficient for others. (shrink)

The aim of this virtual special issue is to bring together philosophical and historical perspectives to address long-standing issues in the interpretation, utility, and impacts of quantitative genetics methods and findings. Methodological approaches and the underlying scientific understanding of genetics and heredity have transformed since the field's inception. These advances have brought with them new philosophical issues regarding the interpretation and understanding of quantitative genetic results. The contributions in this issue demonstrate that there is still work to be (...) done integrating old and new methodological and conceptual frameworks. In some cases, new results are interpreted using assumptions based on old concepts and methodologies that need to be explicitly recognised and updated. In other cases, new philosophical tools can be employed to synthesise historical quantitative genetics work with modern methodologies and findings. This introductory article surveys three general themes that have dominated philosophical discussion of quantitative genetics throughout history: (1) how methodologies have changed and transformed our knowledge and interpretations; (2) whether or not quantitative genetics can offer explanations relating to causation and prediction; and (3) the importance of defining the phenotypes under study. We situate the contributions in this virtual special issue within a historical framework addressing these three themes. (shrink)

This study evaluated the biological dimension of meditation and self-transcendent states. A convenience sample of 513 participants was drawn from attendees at a 4-day guided meditation workshop. Half were randomly assigned to an active placebo control intervention. All were assessed on a variety of measures, both psychological [anxiety, pain, posttraumatic stress disorder, positive emotions, and transcendent states], and physiological. Additional biological assessments including salivary immunoglobulin-A, cortisol, and Quantitative Electroencephalography were obtained from subset of the Experimental group. No significant difference (...) in psychological symptoms or positive emotions was observed between Experimental and placebo groups at baseline. At post-test, significant improvements were noted in the Experimental group, including a 49.5% median increase in SIgA, though cortisol remained unchanged. qEEG z-score analysis identified sustained stress reduction, including delta frequency band amplitude increases, high beta decreases, and faster acquisition of sustained alpha states. Psychological symptoms also improved on all measures. At 6-month follow-up, PTSD and somatic symptoms significantly improved from baseline, and post-test versus 6-month follow-up results indicated significant increases in happiness and spiritual and physical oneness, along with decreases in depressive symptoms. These findings suggest that autonomic self-regulation and transcendent states may be measured in both biological and psychological dimensions and are associated with pervasive health benefits. (shrink)

A causal approach to biological information is outlined. There are two aspects to this approach: information as determining a choice between alternative objects and information as determining the construction of a single object. The first aspect has been developed in earlier work to yield a quantitative measure of biological information that can be used to analyze biological networks. This article explores the prospects for a measure based on the second aspect and suggests some applications for such a measure. These (...) two aspects are not suggested to exhaust all the facets of biological information. (shrink)

Traction forces developed by most cell types play a significant role in the spatial organisation of biological tissues. However, due to the complexity of cell-extracellular matrix interactions, these forces are quantitatively difficult to estimate without explicitly considering cell properties and extracellular mechanical matrix responses. Recent experimental devices elaborated for measuring cell traction on extracellular matrix use cell deposits on a piece of gel placed between one fixed and one moving holder. We formulate here a mathematical model describing the dynamic behaviour (...) of the cell-gel medium in such devices. This model is based on a mechanical force balance quantification of the gel visco-elastic response to the traction forces exerted by the diffusing cells. Thus, we theoretically analyzed and simulated the displacement of the free moving boundary of the system under various conditions for cells and gel concentrations. This modelis then used as the theoretical basis of an experimental device where endothelial cells are seeded on a rectangular biogel of fibrin cast between two floating holders, one fixed and the other linked to a force sensor. From a comparison of displacement of the gel moving boundary simulated by the model and the experimental data recorded from the moving holder displacement, the magnitude of the traction forces exerted by the endothelial cell on the fibrin gel was estimated for different experimental situations. Different analytical expressions for the cell traction term are proposed and the corresponding force quantifications are compared to the traction force measurements reported for various kind of cells with the use of similar or different experimental devices. (shrink)

The current debate over extending inheritance and its evolutionary impact has focused on adding new categories of non-genetic factors to the classical transmission of DNA, and on trying to redefine inheritance. Transmitted factors have been mainly characterized by their directions of transmission and the way they store variations. In this paper, we leave aside the issue of defining inheritance. We rather try to build an evolutionary conceptual framework that allows for tracing most, if not all forms of transmission and makes (...) sense of their different tempos and modes. We discuss three key distinctions that should in particular be the targets of theoretical and empirical investigation, and try to assess the interplay among them and evolutionary dynamics. We distinguish two channels of transmission, two measurements of the temporal dynamics of transmission, respectively across and within generations, and two types of transmitted factors according to their evolutionary relevance. By implementing these three distinctions we can then map different forms of transmission over a continuous space describing the combination of their varying dynamical features. While our aim is not to provide yet another model of inheritance, putting together these distinctions and crossing them, we manage to offer an inclusive conceptual framework of transmission, grounded in empirical observation, and coherent with evolutionary theory. This interestingly opens possibilities for qualitative and quantitative analyses, and is a necessary step, we argue, in order to question the interplay between the dynamics of evolution and the dynamics of multiple forms of transmission. (shrink)

The progress of the molecular biosciences has been so enormous that a discipline studying how cellular functioning emerges out of the behaviors of their molecular constituents has become reality. Systems biology studies cells as spatiotemporal networks of interacting molecules using an integrative approach of theory , experimental biology , and quantitative network-wide analytical measurement . Its aim is to understand how molecules jointly bring about life. Systems biology is rapidly discovering principles governing the functioning of molecular (...) networks and methods to model and measure them. The application of the conceptual strength of systems sciences such as physics and engineering are opening up new ways of experimentally studying the design and functioning of molecular networks. Typically, in such studies models are used to highlight principles, design experiments, or to act in a predictive mode to specifically modify cellular behavior. In this trend article, theoretical approaches being applied in systems biology will be discussed. A number of books have recently appeared that deal with theoretical aspects of systems biology. In this article they are highlighted to facilitate the communication of systems biology to a broader audience. (shrink)

Arguments for an extended evolutionary synthesis often center on the concept of “reciprocal causation.” Proponents argue that reciprocal causation is superior to standard models of evolutionary causation for at least two reasons. First, it leads to better scientific models with more predictive power. Second, it more accurately represents the causal structure of the biological world. Simply put, proponents of an extended evolutionary synthesis argue that reciprocal causation is empirically and explanatorily apt relative to competing causal frameworks. In this paper, I (...) present quantitative survey data from faculty members in biology departments at universities across the United States to evaluate this claim. The survey data indicate that a majority of the participants do not agree (i.e., most either disagree or neither agree nor disagree) that the concept of reciprocal causation confers a larger advantage on research practices. However, a majority of the participants agree that the causal framework of the extended evolutionary synthesis more accurately represents the structure of the biological world. These results demonstrate that the explanatory merits of a conceptual framework and its practical utility can come apart in interesting and informative ways. (shrink)

Systems biology is sometimes presented as providing a superior approach to the problem of biological complexity. Its use of ‘unbiased’ methods and formal quantitative tools might lead to the impression that the human factor is effectively eliminated. However, a closer look reveals that this impression is misguided. Systems biologists cannot simply assemble molecular information and compute biological behavior. Instead, systems biology’s main contribution is to accelerate the discovery of mechanisms by applying models as heuristic tools. These models (...) rely on a variety of idealizing and simplifying assumptions in order to be efficient for this purpose. The strategies of systems biologists are similar to those of experimentalists in that they attempt to reduce the complexity of the discovery process. Analyzing and comparing these strategies, or ‘heuristics’, reveals the importance of the human factor in computational approaches and helps to situate systems biology within the epistemic landscape of the life sciences. (shrink)

Google Earth allows us to obtain a new vision of the planet we live on, with an ability to zoom in from space to ground level detail at any point on Earth. As it is only recently that we have been able to look toward the Earth from space, we review instead the history of imaging of the Jupiter moon Ganymede, another globe, first seen by Galileo. Observations of Ganymede are mined for lessons on the importance and impact of improving (...) imaging technology. Similarly, new insights may await us when we have proper tools for quantitatively looking at another unexplored globe, the embryo, in a sense for the first time. (shrink)

It is far from obvious that outside of highly specialized domains such as commercial agriculture, the methodology of biometrics—quantitative comparisons over groups of organisms—should be of any use in today’s bioinformatically informed biological sciences. The methods in our biometric textbooks, such as regressions and principal components analysis, make assumptions of homogeneity that are incompatible with current understandings of the origins of developmental or evolutionary data in historically contingent processes, processes that might have come out otherwise; the appropriate statistical methods (...) are those suited to random walks, not normal distributions. A valid methodology would further require that especially close attention be paid to the difference between aspects of processes that are plastic, those that encode their own histories or biographies, and the very small fraction of quantifications that can usefully and realistically be modeled as varying by colored noise around a central tendency that itself has some quantitative meaning. This point of view—that only a vanishingly small fraction of the quantitative information borne by any living organism is worth quantifying—is illustrated by some data on a human birth defect, namely, fetal alcohol syndrome. In a suggestive metaphor, the biometrician is like the pilgrim in Friedrich’s painting Der Wanderer über dem Nebelmeer, uncertain as to whether to measure the mountains or the clouds. The mountains stand for contingent history, the clouds for the subset of the data most closely matching controlled experiments suitable for quantitative biometric summary. Biometrics applies to the clouds, not the mountains. The success of statistical methods comes at the expense of all the theories that we simultaneously hold to be true about the biological materials to which they both pertain. Biometrics is thus complementary to all of the emerging reductionist sciences of biological structure. (shrink)