Bridging the gap: Using reservoir ecology and human serosurveys to estimate Lassa virus spillover in West Africa

Forecasting the risk of pathogen spillover from reservoir populations of wild or domestic animals is essential for the effective deployment of interventions such as wildlife vaccination or culling. Due to the sporadic nature of spillover events and limited availability of data, developing and validating robust, spatially explicit, predictions is challenging. Recent efforts have begun to make progress in this direction by capitalizing on machine learning methodologies. An important weakness of existing approaches, however, is that they generally rely on combining human and reservoir infection data during the training process and thus conflate risk attributable to the prevalence of the pathogen in the reservoir population with the risk attributed to the realized rate of spillover into the human population. Because effective planning of interventions requires that these components of risk be disentangled, we developed a multi-layer machine learning framework that separates these processes. Our approach begins by training models to predict the geographic range of the primary reservoir and the subset of this range in which the pathogen occurs. The spillover risk predicted by the product of these reservoir specific models is then fit to data on realized patterns of historical spillover into the human population. The result is a geographically specific spillover risk forecast that can be easily decomposed and used to guide effective intervention. Applying our method to Lassa virus, a zoonotic pathogen that regularly spills over into the human population across West Africa, results in a model that explains a modest but statistically significant portion of geographic variation in historical patterns of spillover. When combined with a mechanistic mathematical model of infection dynamics, our spillover risk model predicts that 897,700 humans are infected by Lassa virus each year across West Africa, with Nigeria accounting for more than half of these human infections.     

Evaluation of SYPRO Ruby total protein stain for the normalization of two-dimensional Western blots

Due to post-translational modifications such as phosphorylation, proteins exist as distinct charge variants. Two-dimensional (2D) gel electrophoresis followed by immunoblotting enables the detection of these isoforms. For their accurate relative quantitation in different samples, a loading control is necessary to compensate for technical errors such as imprecise sample loading or transfer. The study reveals that the combinatory approach of SYPRO Ruby and chemiluminescence-based 2D Western blot analysis exhibits high linearity and excellent reproducibility and is applicable for limited sample amounts.     

Taxonomy and nomenclature of five hitherto inadequately-known genera of mealybugs (Homoptera: Coccoidea: Pseudococcidae)

Abstract The type-species of four genera of Pseudococcidae are studied. Fonscolombia Lichtenstein is redefined, the type-species, Fonscolombia graminis Lichtenstein is assigned to the Pseudococcidae, redescribed and a lectotype designated. Laboulbenia Lichtenstein is accepted as an objective synonym of Antonina Signoret. Tetrura Lichtenstein ( non : Lesson) is accepted as an objective synonym of Coccura Sulc. The adult female of the material of this species which Lichtenstein misidentified as Tetrura rubi (Schrank) is redescribed and illustrated. Brevennia Goux is redefined, and the type-species Ripersia (Brevennia) tetrapora Goux redescribed. The characteristics of Asphodelococcus Morrison are discussed, the type-species Ripersia asphodeli Bodenheimer redescribed and a neotype designated; A.meoconcitae Tranfaglia & Marotta is a new synonym of A. asphodeli .     

Mind Architecture and Brain Architecture

The use of the computer metaphor has led to the proposal of mind architecture (Pylyshyn 1984; Newell 1990) as a model of the organization of the mind. The dualist computational model, however, has, since the earliest days of psychological functionalism, required that the concepts mind architecture and brain architecture be remote from each other. The development of both connectionism and neurocomputational science, has sought to dispense with this dualism and provide general models of consciousness – a uniform cognitive architecture –, which is in general reductionist, but which retains the computer metaphor. This paper examines, in the first place, the concepts of mind architecture and brain architecture, in order to evaluate the syntheses which have recently been offered. It then moves on to show how modifications which have been made to classical functionalist mind architectures, with the aim of making them compatible with brain architectures, are unable to resolve some of the most serious problems of functionalism. Some suggestions are given as to why it is not possible to relate mind structures and brain structures by using neurocomputational approaches, and finally the question is raised of the validity of reductionism in a theory which sets out to unite mind and brain architectures.