Spencerism and the Causal Theory of Reference

Spencer’s heritage, while almost a forgotten chapter in the history of biology, lives on in psychology and the philosophy of mind. I particularly discuss externalist views of meaning, on which meaning crucially depends on a notion of reference, and ask whether reference should be thought of as cause or effect. Is the meaning of a word explained by what it refers to, or should we say that what we use a word to refer to is explained by what concept it expresses? I argue for the latter view, which I call ‘Darwinian’, and against the former, ‘Spencerian’ one, assuming conceptual structures in humans to be an instance of adaptive structures, and adaptive relations to an environment to be the effect rather than the cause of evolutionary novelties. I conclude with the deficiency – both empirically and methodologically – of a functionalist study of human concepts and the languages they are embedded in, as it would be undertaken in a paradigm that identifies meaning with reference or that gives reference an explanatory role to play for what concepts we have.     

Low Levels of Empathic Concern Predict Utilitarian Moral Judgment

Is it permissible to harm one to save many? Classic moral dilemmas are often defined by the conflict between a putatively rational response to maximize aggregate welfare (i.e., the utilitarian judgment) and an emotional aversion to harm (i.e., the non-utilitarian judgment). Here, we address two questions. First, what specific aspect of emotional responding is relevant for these judgments? Second, is this aspect of emotional responding selectively reduced in utilitarians or enhanced in non-utilitarians? The results reveal a key relationship between moral judgment and empathic concern in particular (i.e., feelings of warmth and compassion in response to someone in distress). Utilitarian participants showed significantly reduced empathic concern on an independent empathy measure. These findings therefore reveal diminished empathic concern in utilitarian moral judges.     

The ethics of functional genomics: same, same, but different?

Respect for human life--a notion of worth uniting all members of the human race--constitutes a sense of anthropocentrism that has long been the justification for the enrollment of animals in experimentation executed to develop therapies to alleviate human suffering. Currently, however, advances in functional genomics are causing a qualitative transformation of the rationale for medical research performed on animals. The notion of human distinctness is being fundamentally challenged when gene sequences similar to those found in humans are identified in different species. In this Opinion article, we would like to highlight an inherent tension brought about by the current developments in functional genomics: a tension between the scientific and the ethical status of gene sequences. Is it reasonable to argue that they are the same for all practical purposes but different in ethical status?     

What Capabilities for the Animal?

In this essay, I defend a bi-constructivist approach to ethology—a constructivist ethology assuming that each animal adopts constructivist strategies. I put it in opposition to what I call a realist-Cartesian approach, which is currently the dominant approach to ethology and comparative psychology. The starting point of the bi-constructivist approach can be formulated as a shift from the classical Aristotelian question “What is an animal?” to the Spinozean question, which is much less classical but which seems to me to be much stronger: “What are the capacities of the animal?”. Is it possible to conceptualize an ethology which insists on interpretation and therefore on invention, innovation and creativity, rather than on causality, the monotony of behavioural routines, and/or genetic or environmental determination? Such an ethology would be based not on the fiction of an absent observer but on fully recognizing the necessity of an observer, who is effectively present in order to get an observation. A pluralistic ethology does not dissociate itself from the marginal epistemologies of practitioners like animal trainers, hunters, stockbreeders etc., or, moreover, non-western experts. An ethology of this kind is not clamped within the boundaries of purely academic epistemology, obsessed by demarcation lines between the human and the animal. My work on the bi-constructivist approach represents a contribution towards the elaboration of an authentically biosemiotic ethology, one which is significantly different from the mechanical ethology of today.     

Comparing Families of Dynamic Causal Models

Mathematical models of scientific data can be formally compared using Bayesian model evidence. Previous applications in the biological sciences have mainly focussed on model selection in which one first selects the model with the highest evidence and then makes inferences based on the parameters of that model. This “best model” approach is very useful but can become brittle if there are a large number of models to compare, and if different subjects use different models. To overcome this shortcoming we propose the combination of two further approaches: (i) family level inference and (ii) Bayesian model averaging within families. Family level inference removes uncertainty about aspects of model structure other than the characteristic of interest. For example: What are the inputs to the system? Is processing serial or parallel? Is it linear or nonlinear? Is it mediated by a single, crucial connection? We apply Bayesian model averaging within families to provide inferences about parameters that are independent of further assumptions about model structure. We illustrate the methods using Dynamic Causal Models of brain imaging data.     

Applying Weight-of-Evidence in Retrospective Ecological Risk Assessment When Quantitative Data Are Limited

Retrospective ecological risk assessment attempts to identify likely causal agents to explain adverse effects that have occurred in ecological targets. It can never be decisive since it is post hoc and usually based on limited evidence that is rarely very quantitative. It can, nevertheless, be made more transparent, systematic, and logical, and less subjective. Based on human health epidemiological criteria we develop an approach that moves from systematic consideration of seven basic questions to assigning a likelihood of involvement of putative agents. The questions are: 1. Is there evidence that the target is or has been exposed to the agent? 2. Is there evidence for correlation between adverse effects in the target and exposure to the agent either in time or in space? 3. Do the measured or predicted environmental concentrations exceed quality criteria for water, sediment or body burden? 4. Have the results from controlled experiments in the field or laboratory led to the same effect? 5. Has removal of the agent led to amelioration of effects in the target? 6. Is there an effect in the target known to be specifically caused by exposure to the agent? 7. Does the proposed causal relationship make sense logically and scientifically? We identify 15 common scenarios of answers to the questions and illustrate the approach by reference to three real-world case studies (decline in benthos in a tropical marine bay, decline in fisheries in a temperate sea, decline in marine mollusc populations). The primary challenge in retrospective risk assessment is to make best use of the available evidence to develop rational management strategies and/or guide additional analyses to gain further evidence about likely agents as causes of observed harm.     

Discussion on the problems of general epidemiology

The key problems of general epidemiology: the subject, method, causality in the epidemic process, the main categories and laws, the systematization of infectious pathology and epidemiological terminology are under discussion. It is at this stage when students should form valid notions, well grounded on scientific facts and practical experience, concerning the epidemiology of noninfectious diseases with due regard to the existing differences in the interpretation of the causes of the epidemic process in noninfectious diseases and to the characteristic distribution of noninfectious diseases among the population under the influence of environmental factors without any participation of parasitic systems. The review of the notion apparatus of the theoretical epidemiology and putting it in order in accordance with general biological concepts are proposed in connection with the necessity of differentiation between the epidemic process proper (in cases of anthroponosis) and the epidemic manifestations of epizoonotic and epiphytotic processes (in cases of zoonoses and sapronoses).     

Vitamin D and overall mortality

Vitamin D is a steroid molecule, mainly produced in the skin that regulates the expression of a large number of genes. Several meta‐analyses of epidemiological studies support the evidence that low vitamin D serum level, which is highly prevalent worldwide, could be a ‘new’ risk factor for many chronic diseases including cancer, and for all‐cause mortality. A meta‐analysis in healthy subjects suggested that current doses of vitamin D supplements could be associated with decrease in total mortality rates. However, these associations are insufficient to establish causality between vitamin D and all‐cause mortality. Furthermore, long‐term health effects of high doses of vitamin D, that is, prolonged supplementation and association with different baseline vitamin D levels, remain to be investigated. Several trials are ongoing but population‐based, placebo‐controlled randomized trials with total mortality as the main endpoint should be planned to confirm a real beneficial effect of vitamin D for non‐skeletal diseases and to prove causality.     

The evolution of germs and the evolution of disease: some British debates, 1870-1900

The germ theory of disease famously brought a new notion of specificity into concepts of disease. At the same time, the work of Pasteur, Koch and their colleagues was developed during the same decades as Charles Darwin's theories of evolutionary biology challenged traditional notions of the essentialism of biological species. This essay examines some of the ways in which Darwin's work was invoked by British doctors seeking to explain clinical or epidemiological anomalies, in which infectious diseases did not appear to breed true.     

How does climate change cause extinction?

Anthropogenic climate change is predicted to be a major cause of species extinctions in the next 100 years. But what will actually cause these extinctions? For example, will it be limited physiological tolerance to high temperatures, changing biotic interactions or other factors? Here, we systematically review the proximate causes of climate-change related extinctions and their empirical support. We find 136 case studies of climatic impacts that are potentially relevant to this topic. However, only seven identified proximate causes of demonstrated local extinctions due to anthropogenic climate change. Among these seven studies, the proximate causes vary widely. Surprisingly, none show a straightforward relationship between local extinction and limited tolerances to high temperature. Instead, many studies implicate species interactions as an important proximate cause, especially decreases in food availability. We find very similar patterns in studies showing decreases in abundance associated with climate change, and in those studies showing impacts of climatic oscillations. Collectively, these results highlight our disturbingly limited knowledge of this crucial issue but also support the idea that changing species interactions are an important cause of documented population declines and extinctions related to climate change. Finally, we briefly outline general research strategies for identifying these proximate causes in future studies.     

Genomic instability en route to and from cancer stem cells

Cancer is caused by successive gene mutations that amount to confer malignant phenotype. Genomic instability (GIN) is considered a key endogenous mechanism for accumulation of mutations, and therefore, has been proposed as an engine of tumorigenesis. Recently, cancer stem cells, or tumor initiating cells, have been identified in a variety of human cancers. These cancer stem cells (CSCs) are believed to be responsible for the initiation of malignant growth and metastasis of some, and perhaps all cancer types. How are these two engines of tumorigenesis related to each other? Is GIN a driving force in the genesis of cancer stem cells? Is the genome in CSCs inherently unstable? Could GIN in CSC be the cause of the observed cancer cell heterogeneity? In this article, we will discuss some early clues indicating that these two driving forces of tumorigenesis appear to be intimately connected.     

The Forgotten Component of Plant Water Potential

Abstract: Experts in plant water relations are challenged to explain why the standard expression for the water potential of an intact, transpiring leaf omits one of the pressure components, namely the tissue pressure of the living leaf cells. Two questions are posed: A) Is there a reason for omitting this component? B) If not, what evidence exists that it may be ignored? When this component contributes significantly, the water potential cannot be interpreted in the accustomed way as measuring tension in the xylem sap.     

Immunosensing during colonization by Candida albicans: does it take a village to colonize the intestine?

Candida albicans, an opportunistic fungal pathogen and a component of the normal flora of the gastrointestinal tract, is a frequent colonizer of humans. Is C. albicans capable of sensing the immune status of its host, a process we term immunosensing, and, if so, how? C. albicans causes serious disease only in immunocompromised hosts and therefore the ability to immunosense would be advantageous to an organism. We propose a speculative model whereby, during colonization, C. albicans produces phenotypic variants that vary in relative concentration depending on host status. One variant is optimized for persistence as a commensal, whereas the other variant has higher capacity to initiate pathogenic interactions. When the ratio of the two variants changes, the pathogenic potential of the population changes. The critical element of this model is that the C. albicans colonizing population is not uniform but is composed of subpopulations of phenotypic variants that are advantageous under different host conditions.     

Direct observation and unambiguous inference

In science, it sometimes occurs that an event is directly observed, and on other occasions that it is not directly observed but one can make the unambiguous inference that it has occurred. Is there any difference concerning the analysis of data arising from these two situations? In this note we show that there is such a difference in one case arising frequently in genetics. The difference derives from the fact that the ability to make the unambiguous inference arises only from a restricted form of data.     

Why do parasitized hosts look different? Resolving the “chicken-egg” dilemma

Phenotypic differences between infected and non-infected hosts are often assumed to be the consequence of parasite infection. However, pre-existing differences in hosts’ phenotypes may promote differential susceptibility to infection. The phenotypic variability observed within the host population may therefore be a cause rather than a consequence of infection. In this study, we aimed at disentangling the causes and the consequences of parasite infection by calculating the value of a phenotypic trait (i.e., the growth rate) of the hosts both before and after infection occurred. That procedure was applied to two natural systems of host–parasite interactions. In the first system, the infection level of an ectoparasite (Tracheliastes polycolpus) decreases the growth rate of its fish host (the rostrum dace, Leuciscus leuciscus). Reciprocally, this same phenotypic trait before infection modulated the future level of host sensitivity to the direct pathogenic effect of the parasite, namely the level of fin degradation. In the second model, causes and consequences linked the growth rate of the fish host (the rainbow smelt, Osmerus mordax) and the level of endoparasite infection (Proteocephalus tetrastomus). Indeed, the host’s growth rate before infection determined the number of parasites later in life, and the parasite biovolume then decreased the host’s growth rate of heavily infected hosts. We demonstrated that reciprocal effects between host phenotypes and parasite infection can occur simultaneously in the wild, and that the observed variation in the host phenotype population was not necessarily a consequence of parasite infection. Disentangling the causality of host–parasite interactions should contribute substantially to evaluating the role of parasites in ecological and evolutionary processes. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Pairwise Measures of Causal Direction in the Epidemiology of Sleep Problems and Depression

Depressive mood is often preceded by sleep problems, suggesting that they increase the risk of depression. Sleep problems can also reflect prodromal symptom of depression, thus temporal precedence alone is insufficient to confirm causality. The authors applied recently introduced statistical causal-discovery algorithms that can estimate causality from cross-sectional samples in order to infer the direction of causality between the two sets of symptoms from a novel perspective. Two common-population samples were used; one from the Young Finns study (690 men and 997 women, average age 37.7 years, range 30–45), and another from the Wisconsin Longitudinal study (3101 men and 3539 women, average age 53.1 years, range 52–55). These included three depression questionnaires (two in Young Finns data) and two sleep problem questionnaires. Three different causality estimates were constructed for each data set, tested in a benchmark data with a (practically) known causality, and tested for assumption violations using simulated data. Causality algorithms performed well in the benchmark data and simulations, and a prediction was drawn for future empirical studies to confirm: for minor depression/dysphoria, sleep problems cause significantly more dysphoria than dysphoria causes sleep problems. The situation may change as depression becomes more severe, or more severe levels of symptoms are evaluated; also, artefacts due to severe depression being less well presented in the population data than minor depression may intervene the estimation for depression scales that emphasize severe symptoms. The findings are consistent with other emerging epidemiological and biological evidence.     

Review. The incentive sensitization theory of addiction: some current issues

We present a brief overview of the incentive sensitization theory of addiction. This posits that addiction is caused primarily by drug-induced sensitization in the brain mesocorticolimbic systems that attribute incentive salience to reward-associated stimuli. If rendered hypersensitive, these systems cause pathological incentive motivation (‘wanting’) for drugs. We address some current questions including: what is the role of learning in incentive sensitization and addiction? Does incentive sensitization occur in human addicts? Is the development of addiction-like behaviour in animals associated with sensitization? What is the best way to model addiction symptoms using animal models? And, finally, what are the roles of affective pleasure or withdrawal in addiction?     

The causal pie model: an epidemiological method applied to evolutionary biology and ecology

A general concept for thinking about causality facilitates swift comprehension of results, and the vocabulary that belongs to the concept is instrumental in cross‐disciplinary communication. The causal pie model has fulfilled this role in epidemiology and could be of similar value in evolutionary biology and ecology. In the causal pie model, outcomes result from sufficient causes. Each sufficient cause is made up of a “causal pie” of “component causes”. Several different causal pies may exist for the same outcome. If and only if all component causes of a sufficient cause are present, that is, a causal pie is complete, does the outcome occur. The effect of a component cause hence depends on the presence of the other component causes that constitute some causal pie. Because all component causes are equally and fully causative for the outcome, the sum of causes for some outcome exceeds 100%. The causal pie model provides a way of thinking that maps into a number of recurrent themes in evolutionary biology and ecology: It charts when component causes have an effect and are subject to natural selection, and how component causes affect selection on other component causes; which partitions of outcomes with respect to causes are feasible and useful; and how to view the composition of a(n apparently homogeneous) population. The diversity of specific results that is directly understood from the causal pie model is a test for both the validity and the applicability of the model. The causal pie model provides a common language in which results across disciplines can be communicated and serves as a template along which future causal analyses can be made.     

Optimizing Population Variability to Maximize Benefit

Variability is inherent in any population, regardless whether the population comprises humans, plants, biological cells, or manufactured parts. Is the variability beneficial, detrimental, or inconsequential? This question is of fundamental importance in manufacturing, agriculture, and bioengineering. This question has no simple categorical answer because research shows that variability in a population can have both beneficial and detrimental effects. Here we ask whether there is a certain level of variability that can maximize benefit to the population as a whole. We answer this question by using a model composed of a population of individuals who independently make binary decisions; individuals vary in making a yes or no decision, and the aggregated effect of these decisions on the population is quantified by a benefit function (e.g. accuracy of the measurement using binary rulers, aggregate income of a town of farmers). Here we show that an optimal variance exists for maximizing the population benefit function; this optimal variance quantifies what is often called the “right mix” of individuals in a population.     

Effect of different densities of the twospotted spider mite Tetranychus urticae on CO2 assimilation, transpiration, and stomatal behaviour in rose leaves

The effect of population density of Tetranychus urticae Koch on CO2 assimilation, transpiration and stomatal behaviour in rose leaves and on the diameter and length of stems and flower buds was investigated under greenhouse conditions. The investigation was performed in order to gain more insight into integrated control systems in rose crops grown under greenhouse conditions. Physiological processes, such as photosynthesis and transpiration, as well as stomatal behaviour and chlorophyll content, were studied as they form part of the plant's nutrition mechanism and therefore affect the quantity and quality of the flowers. Information related to the effect of spider mite population density on bloom quality, diameter and length of stems and flower buds was also collected. The data indicate that increased mite density coincides with a decrease in the net photosynthetic rate, transpiration and chlorophyll content. Higher mite densities on leaves cause stomata to remain open for longer periods, which allows a greater loss of water. Spider mite densities of 10 and 50 mites per leaf cause a reduction in flower stem length of 17 and 26%, respectively, as compared to plants with no mites present.