Abstract Despite the near-ubiquity of plasmids in bacterial populations and the profound contribution of infectious gene transfer to the adaptation and evolution of bacteria, the mechanisms responsible for the maintenance of plasmids in bacterial populations are poorly understood. In this article, we address the question of how plasmids manage to persist over evolutionary time. Empirical studies suggest that plasmids are not infectiously transmitted at a rate high enough to be maintained as genetic parasites. In part i, we present a general mathematical proof that if this is the case, then plasmids will not be able to persist indefinitely solely by carrying genes that are beneficial or sometimes beneficial to their host bacteria. Instead, such genes should, in the long run, be incorporated into the bacterial chromosome. If the mobility of host-adaptive genes imposes a cost, that mobility will eventually be lost. In part ii, we illustrate a pair of mechanisms by which plasmids can be maintained indefinitely even when their rates of transmission are too low for them to be genetic parasites. First, plasmids may persist because they can transfer locally adapted genes to newly arriving strains bearing evolutionary innovations, and thereby preserve the local adaptations in the face of background selective sweeps. Second, plasmids may persist because of their ability to shuttle intermittently favored genes back and forth between various (noncompeting) bacterial strains, ecotypes, or even species.
In this article, we investigate the role of gender in collaboration patterns by analyzing gender-based homophily -- the tendency for researchers to co-author with individuals of the same gender. We develop and apply novel methodology to the corpus of JSTOR articles, a broad scholarly landscape, which we analyze at various levels of granularity. Most notably, for a precise analysis of gender homophily, we develop methodology which explicitly accounts for the fact that the data comprises heterogeneous intellectual communities and that not all authorships are exchangeable. In particular, we distinguish three phenomena which may affect the distribution of observed gender homophily in collaborations: a structural component that is due to demographics and non-gendered authorship norms of a scholarly community, a compositional component which is driven by varying gender representation across sub-disciplines and time, and a behavioral component which we define as the remainder of observed gender homophily after its structural and compositional components have been taken into account. Using minimal modeling assumptions, the methodology we develop allows us to test for behavioral homophily. We find that statistically significant behavioral homophily can be detected across the JSTOR corpus and show that this finding is robust to missing gender indicators in our data. In a secondary analysis, we show that the proportion of women representation in a field is positively associated with the probability of finding statistically significant behavioral homophily.
To comprehend the multipartite organization of large-scale biological and
social systems, we introduce a new information theoretic approach to reveal
community structure in weighted and directed networks. The method decomposes a
network into modules by optimally compressing a description of information
flows on the network. The result is a map that both simplifies and highlights
the regularities in the structure and their relationships. We illustrate the
method by making a map of scientific communication as captured in the citation
patterns of more than 6000 journals. We discover a multicentric organization
with fields that vary dramatically in size and degree of integration into the
network of science. Along the backbone of the network -- including physics,
chemistry, molecular biology, and medicine -- information flows
bidirectionally, but the map reveals a directional pattern of citation from the
applied fields to the basic sciences.
Control measures used to limit the spread of infectious disease often generate externalities. Vaccination for transmissible diseases can reduce the incidence of disease even among the unvaccinated, whereas antimicrobial chemotherapy can lead to the evolution of antimicrobial resistance and thereby limit its own effectiveness over time. We integrate the economic theory of public choice with mathematical models of infectious disease to provide a quantitative framework for making allocation decisions in the presence of these externalities. To illustrate, we present a series of examples: vaccination for tetanus, vaccination for measles, antibiotic treatment of otitis media, and antiviral treatment of pandemic influenza.
