Galleria mellonella as a host model to study Candida glabrata virulence and antifungal efficacy

This is the author accepted manuscript. The final version is available from Taylor & Francis via the DOI in this record.This work was supported in part by the Wellcome Trust Strategic Award for Medical Mycology and Fungal Immunology 097377/Z/11/

The TD50: a proposed general convention for the numerical description of the carcinogenic potency of chemicals in chronic-exposure animal experiments.

A generally accepted format for the numerical description of the carcinogenic potency of a particular chemical in a particular strain of animals is desirable so that statements from different sources about potency and attempts by different authors to correlate potency with particular laboratory measurements will be comparable. The choice of an appropriate standard format is to a certain extent arbitrary. In this paper we recommend that the TD50 (tumorigenic dose rate 50) be used. TD50 can be calculated for a single target site or combination of sites. The TD50, in analogy with the LD50, is defined as that chronic dose rate (in mg/kg body weight/day) which would halve the actuarially adjusted percentage of tumor-free animals at the end of a standard experiment time--the "standard lifespan" for the species. This paper consists of a brief discussion of the TD50, sufficient to make the general reader familiar with the properties of such an index, an appendix discussing methods for its estimation and certain conventions we have adopted for use in analyzing "nonstandard" experiments. A major problem in calculating any index of carcinogenic potency is that much published material gives only the final crude percentage of tumor-bearing animals at each dose, instead of percentages adjusted for the effects of intercurrent mortality or data from which these adjusted percentages can be derived. If the dose level administered to the animals is toxic, then premature death from nonneoplastic causes may prevent some dosed animals that would have developed tumors from actually doing so. This will particularly affect the high-dose group.(ABSTRACT TRUNCATED AT 250 WORDS

Modulating the neural bases of persuasion: why/how, gain/loss, and users/non-users

Designing persuasive content is challenging, in part because people can be poor predictors of their actions. Medial prefrontal cortex (MPFC) activation during message exposure reliably predicts downstream behavior, but past work has been largely atheoretical. We replicated past results on this relationship and tested two additional framing effects known to alter message receptivity. First, we examined gain- vs. loss-framed reasons for a health behavior (sunscreen use). Consistent with predictions from prospect theory, we observed greater MPFC activity to gain- vs. loss-framed messages, and this activity was associated with behavior. This relationship was stronger for those who were not previously sunscreen users. Second, building on theories of action planning, we compared neural activity during messages regarding how vs. why to enact the behavior. We observed rostral inferior parietal lobule and posterior inferior frontal gyrus activity during action planning (“how” messages), and this activity was associated with behavior; this is in contrast to the relationship between MPFC activity during the “why” (i.e., gain and loss) messages and behavior. These results reinforce that persuasion occurs in part via self-value integration—seeing value and incorporating persuasive messages into one\u27s self-concept—and extend this work to demonstrate how message framing and action planning may influence this process

Guaranteed clustering and biclustering via semidefinite programming

Identifying clusters of similar objects in data plays a significant role in a wide range of applications. As a model problem for clustering, we consider the densest k-disjoint-clique problem, whose goal is to identify the collection of k disjoint cliques of a given weighted complete graph maximizing the sum of the densities of the complete subgraphs induced by these cliques. In this paper, we establish conditions ensuring exact recovery of the densest k cliques of a given graph from the optimal solution of a particular semidefinite program. In particular, the semidefinite relaxation is exact for input graphs corresponding to data consisting of k large, distinct clusters and a smaller number of outliers. This approach also yields a semidefinite relaxation for the biclustering problem with similar recovery guarantees. Given a set of objects and a set of features exhibited by these objects, biclustering seeks to simultaneously group the objects and features according to their expression levels. This problem may be posed as partitioning the nodes of a weighted bipartite complete graph such that the sum of the densities of the resulting bipartite complete subgraphs is maximized. As in our analysis of the densest k-disjoint-clique problem, we show that the correct partition of the objects and features can be recovered from the optimal solution of a semidefinite program in the case that the given data consists of several disjoint sets of objects exhibiting similar features. Empirical evidence from numerical experiments supporting these theoretical guarantees is also provided