Gross intestinal morphometry and allometry in primates

Although it is generally assumed that among mammals and within mammal groups, those species that rely on diets consisting of greater amounts of plant fiber have larger gastrointestinal tracts (GIT), statistical evidence for this simple claim is largely lacking. We compiled a dataset on the length of the small intestine, caecum, and colon in 42 strepsirrhine, platyrrhine, and catarrhine primate species, using specimens with known body mass (BM). We tested the scaling of intestine length with BM, and whether dietary proxies (percentage of leaves and a diet quality index) were significant covariates in these scaling relationships, using two sets of models: one that did not account for the phylogenetic structure of the data, and one that did. Intestine length mainly scaled geometrically at exponents that included 0.33 in the confidence interval; Strepsirrhini exhibited particularly long caeca, while those of Catarrhini were comparatively short. Diet proxies were only significant for the colon and the total large intestine (but not for the small intestine or the caecum), and only in conventional statistics (but not when accounting for phylogeny), indicating the pattern occurred across but not within clades. Compared to terrestrial Carnivora, primates have similar small intestine lengths, but longer large intestines. The data on intestine lengths presented here corroborate recent results on GIT complexity, suggesting that diet, as currently described, does not exhaustively explain GIT anatomy within primate clades.     

A Mathematical Framework for Combining Decisions of Multiple Experts toward Accurate and Remote Diagnosis of Malaria Using Tele-Microscopy

We propose a methodology for digitally fusing diagnostic decisions made by multiple medical experts in order to improve accuracy of diagnosis. Toward this goal, we report an experimental study involving nine experts, where each one was given more than 8,000 digital microscopic images of individual human red blood cells and asked to identify malaria infected cells. The results of this experiment reveal that even highly trained medical experts are not always self-consistent in their diagnostic decisions and that there exists a fair level of disagreement among experts, even for binary decisions (i.e., infected vs. uninfected). To tackle this general medical diagnosis problem, we propose a probabilistic algorithm to fuse the decisions made by trained medical experts to robustly achieve higher levels of accuracy when compared to individual experts making such decisions. By modelling the decisions of experts as a three component mixture model and solving for the underlying parameters using the Expectation Maximisation algorithm, we demonstrate the efficacy of our approach which significantly improves the overall diagnostic accuracy of malaria infected cells. Additionally, we present a mathematical framework for performing ‘slide-level’ diagnosis by using individual ‘cell-level’ diagnosis data, shedding more light on the statistical rules that should govern the routine practice in examination of e.g., thin blood smear samples. This framework could be generalized for various other tele-pathology needs, and can be used by trained experts within an efficient tele-medicine platform.     

Narratives of success among Irish and African Caribbean migrants

This paper compares the narratives of two men in midlife who migrated to the UK from Ireland and from the Caribbean as children, in the middle of the last century. We examine how success is narrated over the life course to show how migrants’ positioning of themselves differs from the ways in which they are positioned by outsiders, including in policy and public discourse. We conclude that while outsider narratives often polarise success and failure, insider understandings of success are dynamic and culturally and historically situated.     

Reduced Visual Cortex Gray Matter Volume and Thickness in Young Adults Who Witnessed Domestic Violence during Childhood

Exposure to interparental violence is associated with negative outcomes, such as depression, post-traumatic stress disorder and reduced cognitive abilities. However, little is known about the potential effects of witnessing domestic violence during childhood on gray matter volume (GMV) or cortical thickness. High-resolution 3.0 T volumetric scans (Siemens Trio Scanner) were obtained on 52 subjects (18–25 years) including 22 (6 males/16 females) with a history of visually witnessing episodes of domestic violence, and 30 (8 males/22 females) unexposed control subjects, with neither a current nor past DSM-IV Axis I or II disorder. Potential confounding effects of age, gender, level of parental verbal aggression, parental education, financial stress, full scale IQ, and total GMV, or average thickness were modeled using voxel based morphometry and FreeSurfer. Witnessing domestic violence subjects had a 6.1% GMV reduction in the right lingual gyrus (BA18) (P = 0.029, False Discovery Rate corrected peak level). Thickness in this region was also reduced, as was thickness in V2 bilaterally and left occipital pole. Theses regions were maximally sensitive to exposure to witnessing domestic violence between 11–13 years of age. Regional reductions in GMV and thickness were observed in both susceptible and resilient witnessing domestic violence subjects. Results in subjects witnessing domestic violence were similar to previously reported results in subjects with childhood sexual abuse, as the primary region affected was visual cortex. Brain regions that process and convey the adverse sensory input of the abuse may be specifically modified by this experience, particularly in subjects exposed to a single type of maltreatment. Exposure to multiple types of maltreatment is more commonly associated with morphological alterations in corticolimbic regions. These findings fit with preclinical studies showing that visual cortex is a highly plastic structure.