Transformation of local medicinal knowledge in the Andean Highlands: Case studies from Peru and Bolivia

In the Andean highlands, indigenous environmental knowledge is currently undergoing major changes as a result of various external and internal factors. As in other parts of the world, an overall process of erosion of local knowledge can be observed. In response to this trend, some initiatives that adopt a biocultural approach aim at actively strengthening local identities and revalorizing indigenous environmental knowledge and practices, assuming that such practices can contribute to more sustainable management of biodiversity. However, these initiatives usually lack a sound research basis, as few studies have focused on the dynamics of indigenous environmental knowledge in the Andes and on its links with biodiversity management. Against this background, the general objective of this research project was to contribute to the understanding of the dynamics of indigenous environmental knowledge in the Andean highlands of Peru and Bolivia by investigating how local medicinal knowledge is socially differentiated within rural communities, how it is transformed, and which external and internal factors influence these transformation processes. The project adopted an actor-oriented perspective and emphasized the concept of knowledge dialogue by analyzing the integration of traditional and formal medicinal systems within family therapeutic strategies. It also aimed at grasping some of the links between the dynamics of medicinal knowledge and the types of land use systems and biodiversity management. Research was conducted in two case study areas of the Andes, both Quechua-speaking and situated in comparable agro-ecological production belts - Pitumarca District, Department of Cusco (Southern Peruvian Highlands) and the Tunari National Park, Department of Cochabamba (Bolivian inner-Andean valleys). In each case study area, the land use systems and strategies of 18 families from two rural communities, their environmental knowledge related to medicine and to the local therapeutic flora, and an appreciation of the dynamics of this knowledge were assessed. Data were collected through a combination of disciplinary and participatory action-research methods. It was mostly analyzed using qualitative methods, though some quantitative ethnobotanical methods were also used. In both case studies, traditional medicine still constitutes the preferred option for the families interviewed, independently of their age, education level, economic status, religion, or migration status. Surprisingly and contrary to general assertions among local NGOs and researchers, results show that there is a revival of Andean medicine within the younger generation, who have greater knowledge of medicinal plants than the previous one, value this knowledge as an important element of their way of life and relationship with “Mother Earth” (Pachamama), and, at least in the Bolivian case, prefer to consult the traditional healer rather than go to the health post. Migration to the urban centres and the Amazon lowlands, commonly thought to be an important factor of local medicinal knowledge loss, only affects people’s knowledge in the case of families who migrate over half of the year or permanently. Migration does not influence the knowledge of medicinal plants or the therapeutic strategies of families who migrate temporarily for shorter periods of time. Finally, economic status influences neither the status of people’s medicinal knowledge, nor families’ therapeutic strategies, even though the financial factor is often mentioned by practitioners and local people as the main reason for not using the formal health system. The influence of the formal health system on traditional medicinal knowledge varies in each case study area. In the Bolivian case, where it was only introduced in the 1990s and access to it is still very limited, the main impact was to give local communities access to contraceptive methods and to vaccination. In the Peruvian case, the formal system had a much greater impact on families’ health practices, due to local and national policies that, for instance, practically prohibit some traditional practices such as home birth. But in both cases, biomedicine is not considered capable of responding to cultural illnesses such as “fear” (susto), “bad air” (malviento), or “anger” (colerina). As a consequence, Andean farmers integrate the traditional medicinal system and the formal one within their multiple therapeutic strategies, reflecting an inter-ontological dialogue between different conceptions of health and illness. These findings reflect a more general trend in the Andes, where indigenous communities are currently actively revalorizing their knowledge and taking up traditional practices, thus strengthening their indigenous collective identities in a process of cultural resistance.

A computer-aided diagnostic system to characterize CT focal liver lesions: design and optimization of a neural network classifier

In this paper, a computer-aided diagnostic (CAD) system for the classification of hepatic lesions from computed tomography (CT) images is presented. Regions of interest (ROIs) taken from nonenhanced CT images of normal liver, hepatic cysts, hemangiomas, and hepatocellular carcinomas have been used as input to the system. The proposed system consists of two modules: the feature extraction and the classification modules. The feature extraction module calculates the average gray level and 48 texture characteristics, which are derived from the spatial gray-level co-occurrence matrices, obtained from the ROIs. The classifier module consists of three sequentially placed feed-forward neural networks (NNs). The first NN classifies into normal or pathological liver regions. The pathological liver regions are characterized by the second NN as cyst or "other disease." The third NN classifies "other disease" into hemangioma or hepatocellular carcinoma. Three feature selection techniques have been applied to each individual NN: the sequential forward selection, the sequential floating forward selection, and a genetic algorithm for feature selection. The comparative study of the above dimensionality reduction methods shows that genetic algorithms result in lower dimension feature vectors and improved classification performance.

Investigation on the evolution of an indoor robotic localization system based on wireless networks

This work addresses the evolution of an artificial neural network (ANN) to assist in the problem of indoor robotic localization. We investigate the design and building of an autonomous localization system based on information gathered from wireless networks (WN). The article focuses on the evolved ANN, which provides the position of a robot in a space, as in a Cartesian coordinate system, corroborating with the evolutionary robotic research area and showing its practical viability. The proposed system was tested in several experiments, evaluating not only the impact of different evolutionary computation parameters but also the role of the transfer functions on the evolution of the ANN. Results show that slight variations in the parameters lead to significant differences on the evolution process and, therefore, in the accuracy of the robot position.

Mobile competence network for community health workers in rural Myanmar: a supportive information system that facilitates the improvement of health services.

The goal of this project is the development of international cooperation for fostering solutions to provide better access to basic healthcare services.

NETWORK TOPOLOGY IN HUMAN PROTEIN INTERACTION DATA PREDICTS FUNCTIONAL ASSOCIATION

High-throughput assays, such as yeast two-hybrid system, have generated a huge amount of protein-protein interaction (PPI) data in the past decade. This tremendously increases the need for developing reliable methods to systematically and automatically suggest protein functions and relationships between them. With the available PPI data, it is now possible to study the functions and relationships in the context of a large-scale network. To data, several network-based schemes have been provided to effectively annotate protein functions on a large scale. However, due to those inherent noises in high-throughput data generation, new methods and algorithms should be developed to increase the reliability of functional annotations. Previous work in a yeast PPI network (Samanta and Liang, 2003) has shown that the local connection topology, particularly for two proteins sharing an unusually large number of neighbors, can predict functional associations between proteins, and hence suggest their functions. One advantage of the work is that their algorithm is not sensitive to noises (false positives) in high-throughput PPI data. In this study, we improved their prediction scheme by developing a new algorithm and new methods which we applied on a human PPI network to make a genome-wide functional inference. We used the new algorithm to measure and reduce the influence of hub proteins on detecting functionally associated proteins. We used the annotations of the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) as independent and unbiased benchmarks to evaluate our algorithms and methods within the human PPI network. We showed that, compared with the previous work from Samanta and Liang, our algorithm and methods developed in this study improved the overall quality of functional inferences for human proteins. By applying the algorithms to the human PPI network, we obtained 4,233 significant functional associations among 1,754 proteins. Further comparisons of their KEGG and GO annotations allowed us to assign 466 KEGG pathway annotations to 274 proteins and 123 GO annotations to 114 proteins with estimated false discovery rates of <21% for KEGG and <30% for GO. We clustered 1,729 proteins by their functional associations and made pathway analysis to identify several subclusters that are highly enriched in certain signaling pathways. Particularly, we performed a detailed analysis on a subcluster enriched in the transforming growth factor β signaling pathway (P<10-50) which is important in cell proliferation and tumorigenesis. Analysis of another four subclusters also suggested potential new players in six signaling pathways worthy of further experimental investigations. Our study gives clear insight into the common neighbor-based prediction scheme and provides a reliable method for large-scale functional annotations in this post-genomic era.

Naive B-cell trafficking is shaped by local chemokine availability and LFA-1-independent stromal interactions.

It is not known how naive B cells compute divergent chemoattractant signals of the T-cell area and B-cell follicles during in vivo migration. Here, we used two-photon microscopy of peripheral lymph nodes (PLNs) to analyze the prototype G-protein-coupled receptors (GPCRs) CXCR4, CXCR5, and CCR7 during B-cell migration, as well as the integrin LFA-1 for stromal guidance. CXCR4 and CCR7 did not influence parenchymal B-cell motility and distribution, despite their role during B-cell arrest in venules. In contrast, CXCR5 played a nonredundant role in B-cell motility in follicles and in the T-cell area. B-cell migration in the T-cell area followed a random guided walk model, arguing against directed migration in vivo. LFA-1, but not α4 integrins, contributed to B-cell motility in PLNs. However, stromal network guidance was LFA-1 independent, uncoupling integrin-dependent migration from stromal attachment. Finally, we observed that despite a 20-fold reduction of chemokine expression in virus-challenged PLNs, CXCR5 remained essential for B-cell screening of antigen-presenting cells. Our data provide an overview of the contribution of prototype GPCRs and integrins during naive B-cell migration and shed light on the local chemokine availability that these cells compute.

Phytoplankton Scales of Variability in the California Current System: 1. Interannual and Cross-Shelf Variability

In the California Current System, strong mesoscale variability associated with eddies and meanders of the coastal jet play an important role in the biological productivity of the area. To assess the dominant timescales of variability, a wavelet analysis is applied to almost nine years (October 1997 to July 2006) of 1-km-resolution, 5-day-averaged, Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll a (chl a) concentration data. The dominant periods of chlorophyll variance, and how these change in time, are quantified as a function of distance offshore. The maximum variance in chlorophyll occurs with a period of similar to 100-200 days. A seasonal cycle in the timing of peak variance is revealed, with maxima in spring/summer close to shore (20 km) and in autumn/winter 200 km offshore. Interannual variability in the magnitude of chlorophyll variance shows maxima in 1999, 2001, 2002, and 2005. There is a very strong out-of-phase correspondence between the time series of chlorophyll variance and the Pacific Decadal Oscillation (PDO) index. We hypothesize that positive PDO conditions, which reflect weak winds and poor upwelling conditions, result in reduced mesoscale variability in the coastal region, and a subsequent decrease in chlorophyll variance. Although the chlorophyll variance responds to basin-scale forcing, chlorophyll biomass does not necessarily correspond to the phase of the PDO, suggesting that it is influenced more by local-scale processes. The mesoscale variability in the system may be as important as the chl a biomass in determining the potential productivity of higher trophic levels.

Avoidable hospitalizations in Switzerland: a small area analysis on regional variation, density of physicians, hospital supply and rurality.

BACKGROUND Avoidable hospitalizations (AH) are hospital admissions for diseases and conditions that could have been prevented by appropriate ambulatory care. We examine regional variation of AH in Switzerland and the factors that determine AH. METHODS We used hospital service areas, and data from 2008-2010 hospital discharges in Switzerland to examine regional variation in AH. Age and sex standardized AH were the outcome variable, and year of admission, primary care physician density, medical specialist density, rurality, hospital bed density and type of hospital reimbursement system were explanatory variables in our multilevel poisson regression. RESULTS Regional differences in AH were as high as 12-fold. Poisson regression showed significant increase of all AH over time. There was a significantly lower rate of all AH in areas with more primary care physicians. Rates increased in areas with more specialists. Rates of all AH also increased where the proportion of residences in rural communities increased. Regional hospital capacity and type of hospital reimbursement did not have significant associations. Inconsistent patterns of significant determinants were found for disease specific analyses. CONCLUSION The identification of regions with high and low AH rates is a starting point for future studies on unwarranted medical procedures, and may help to reduce their incidence. AH have complex multifactorial origins and this study demonstrates that rurality and physician density are relevant determinants. The results are helpful to improve the performance of the outpatient sector with emphasis on local context. Rural and urban differences in health care delivery remain a cause of concern in Switzerland.