Talk of mechanisms is ubiquitous in the natural sciences. Interdisciplinary fields such as biochemistry and pharmacy frequently discuss mechanisms with the assistance of diagrams. Such diagrams usually depict entities as structures or boxes and activities or interactions as arrows. While some of these arrows may indicate causal or componential relations, others may represent temporal or operational orders. Importantly, what kind of relation an arrow represents may not only vary with context but also be underdetermined by empirical data. In this manuscript, (...) we investigate how an analysis of pharmacological mechanisms in terms of producing and underlying mechanisms—as discussed in the contemporary philosophy of science—may shed light on these issues. Specifically, we shall argue that while pharmacokinetic mechanisms usually describe causal chains of production, pharmacodynamics tends to focus on mechanisms of action underlying the in vivo effects of a drug. Considering the action of thyroid gland hormones in the human body as a case study, we further demonstrate that pharmacodynamic schemes tend to incorporate entities and interactions on multiple levels. Yet, traditional pharmacodynamic schemes are sketched “flat”, i.e., non-hierarchically. We suggest that transforming flat pharmacodynamic schemes into mechanistic multi-level representations may assist in disentangling the different kinds of mechanisms and relations depicted by arrows in flat schemes. The resulting Baumkuchen model provides a powerful and practical alternative to traditional flat schemes, as it explicates the relevant mechanisms and relations more clearly. On a more general note, our discussion demonstrates how pharmacology and related disciplines may benefit from applying concepts from the new mechanist philosophy to guide the interpretation of scientific diagrams. (shrink)

Aims: To examine the extent of social stigma toward diabetes among Singapore's multi-ethnic general population and determine whether this differs across socio-demographic sub-groups.Methods: Data for this study came from a nationwide cross-sectional study. A diabetes stigma questionnaire comprising Social Distance Scale and Negative Attitudes and Stereotyping Scale was administered to those respondents who had not been diagnosed with diabetes. Exploratory factor analysis was conducted to determine the dimensionality of the instruments and validated using confirmatory factor analysis. Multiple linear regression analysis (...) was conducted to examine associations between socio-demographic factors and measures of diabetes stigma.Results: In all, 2,895 participants were recruited from the general population giving a response rate of 66.2%. Factor analyses found that a one-factor model resulted in an acceptable fit for both stigma scales, which measured social distance and negative attitudes and stereotyping, respectively. Multiple linear regression analyses identified Indian ethnicity, higher personal income and having close friends or family members who had been diagnosed with diabetes to be significantly associated with lower social distance scores while those aged 50–64 years and those with secondary and vocational education were significantly associated with higher social distance scores. Those with a personal income of SG$2,000–3,999 and SGD $6,000 and above, and those with close friends or family members diagnosed with diabetes were significantly associated with lower negative attitudes and stereotyping scores. In contrast those aged 35 years and above, those with primary education and below, and those of Malay ethnicity were significantly associated with higher negative attitudes and stereotyping scores.Conclusions: The study found a relatively low level of stigma toward diabetes in the general population of Singapore, although some stigmatizing beliefs emerged. While greater knowledge of diabetes could reduce stigma, anti-stigma messaging should be incorporated into the “War on Diabetes” programme in Singapore. (shrink)

This anthology brings together for the first time leading essays and book chapters from theologians, philosophers, and scientists on their research relating to ethics, altruism, and love. Because the general consensus today is that scholarship in moral theory requires empirical research, the arguments of the leading scholars presented in this book will be particularly important to those examining issues in love, ethics, religion, and science. The first half of _The Altruism Reader_ offers key selections from religious texts, leading contemporary scholars, (...) and cutting-edge ethicists. Buddhism, Christianity, Hinduism, Islam, and Judaism are represented. Among the highly respected writers are Thomas Aquinas, the Dalai Lama, Thich Nhat Hanh, John Polkinghorne, Stephen Pope, Louis Fischer, Amira Shamma Abdin, Katharine Doob Sakenfeld, and Daniel Day Williams. Primary readings on love and altruism from the sciences are featured in the second half of the book. Here the focus is on anthropology, psychology, sociology, biology, and neurology, with material written by Daniel C. Batson, David Sloan Wilson, Robert Wright, Stephen G. Post, Robert Axelrod, Richard Dawkins, Holmes Rolston III, and other renowned scientists and philosophers. "Virtually all people act—and often talk—as if they have some inkling about love. We speak about loving food, falling in love, loving God, feeling loved, and loving a type of music. We say that love hurts, love waits, love stinks, and love means never having to say you're sorry.We use the word and its derivatives in a wide variety of ways.... My own definition of love is this: To love is to act intentionally, in sympathetic response to others, to promote well-being."—_Thomas Jay Oord_. (shrink)