Archival Classification and Knowledge Organization: Theoretical Possibilities for the Archival Field

The main goal of this study is to outline a possible relation between archival classification and knowledge organization theory. In this sense, we seek to contribute to the conceptual classification in Archival Science, since there is a lack of systematization about archival classification; not just classification, but even the study of historical and conceptual aspects of the discipline. In the context of knowledge organization there is a considerable amount of research on how to build classification schemes and indexing systems that can help contribute to and expand archival classification theory. In order to comprehend this vast field of theories and methodologies we construct a parallel comparing the classification concepts in both areas and analyzing these concepts.

Infrastructure Support for Controlled Experimentation with Software Testing and Regression Testing Techniques

Where the creation, understanding, and assessment of software testing and regression testing techniques are concerned, controlled experimentation is an indispensable research methodology. Obtaining the infrastructure necessary to support such experimentation, however, is difficult and expensive. As a result, progress in experimentation with testing techniques has been slow, and empirical data on the costs and effectiveness of techniques remains relatively scarce. To help address this problem, we have been designing and constructing infrastructure to support controlled experimentation with testing and regression testing techniques. This paper reports on the challenges faced by researchers experimenting with testing techniques, including those that inform the design of our infrastructure. The paper then describes the infrastructure that we are creating in response to these challenges, and that we are now making available to other researchers, and discusses the impact that this infrastructure has and can be expected to have.

Sero-epidemiological evaluation of changes in Plasmodium falciparum and Plasmodium vivax transmission patterns over the rainy season in Cambodia

Background: In Cambodia, malaria transmission is low and most cases occur in forested areas. Seroepidemiological techniques can be used to identify both areas of ongoing transmission and high-risk groups to be targeted by control interventions. This study utilizes repeated cross-sectional data to assess the risk of being malaria sero-positive at two consecutive time points during the rainy season and investigates who is most likely to sero-convert over the transmission season. Methods: In 2005, two cross-sectional surveys, one in the middle and the other at the end of the malaria transmission season, were carried out in two ecologically distinct regions in Cambodia. Parasitological and serological data were collected in four districts. Antibodies to Plasmodium falciparum Glutamate Rich Protein (GLURP) and Plasmodium vivax Merozoite Surface Protein-119 (MSP-119) were detected using Enzyme Linked Immunosorbent Assay (ELISA). The force of infection was estimated using a simple catalytic model fitted using maximum likelihood methods. Risks for sero-converting during the rainy season were analysed using the Classification and Regression Tree (CART) method. Results: A total of 804 individuals participating in both surveys were analysed. The overall parasite prevalence was low (4.6% and 2.0% for P. falciparum and 7.9% and 6.0% for P. vivax in August and November respectively). P. falciparum force of infection was higher in the eastern region and increased between August and November, whilst P. vivax force of infection was higher in the western region and remained similar in both surveys. In the western region, malaria transmission changed very little across the season (for both species). CART analysis for P. falciparum in the east highlighted age, ethnicity, village of residence and forest work as important predictors for malaria exposure during the rainy season. Adults were more likely to increase their antibody responses to P. falciparum during the transmission season than children, whilst members of the Charay ethnic group demonstrated the largest increases. Discussion: In areas of low transmission intensity, such as in Cambodia, the analysis of longitudinal serological data enables a sensitive evaluation of transmission dynamics. Consecutive serological surveys allow an insight into spatio-temporal patterns of malaria transmission. The use of CART enabled multiple interactions to be accounted for simultaneously and permitted risk factors for exposure to be clearly identified.

"Evaluating the model of classification and valuation of disabilities used in Brazil and defining the elaboration and adoption of a unique model for all the country": Brazilian Interministerial Workgroup Task

The President of Brazil established an Interministerial Work Group in order to “evaluate the model of classification and valuation of disabilities used in Brazil and to define the elaboration and adoption of a unique model for all the country”. Eight Ministries and/or Secretaries participated in the discussion over a period of 10 months, concluding that a proposed model should be based on the United Nations Convention on the Rights of Person with Disabilities, the International Classification of Functioning, Disability and Health, and the ‘support theory’, and organizing a list of recommendations and necessary actions for a Classification, Evaluation and Certification Network with national coverage.

MicroRNA Expression Array Identifies Novel Diagnostic Markers for Conventional and Oncocytic Follicular Thyroid Carcinomas

Objective:The most difficult thyroid tumors to be diagnosed by cytology and histology are conventional follicular carcinomas (cFTCs) and oncocytic follicular carcinomas (oFTCs). Several microRNAs (miRNAs) have been previously found to be consistently deregulated in papillary thyroid carcinomas; however, very limited information is available for cFTC and oFTC. The aim of this study was to explore miRNA deregulation and find candidate miRNA markers for follicular carcinomas that can be used diagnostically.Design:Thirty-eight follicular thyroid carcinomas (21 cFTCs, 17 oFTCs) and 10 normal thyroid tissue samples were studied for expression of 381 miRNAs using human microarray assays. Expression of deregulated miRNAs was confirmed by individual RT-PCR assays in all samples. In addition, 11 follicular adenomas, two hyperplastic nodules (HNs), and 19 fine-needle aspiration samples were studied for expression of novel miRNA markers detected in this study.Results:The unsupervised hierarchical clustering analysis demonstrated individual clusters for cFTC and oFTC, indicating the difference in miRNA expression between these tumor types. Both cFTCs and oFTCs showed an up-regulation of miR-182/-183/-221/-222/-125a-3p and a down-regulation of miR-542-5p/-574-3p/-455/-199a. Novel miRNA (miR-885-5p) was found to be strongly up-regulated (>40-fold) in oFTCs but not in cFTCs, follicular adenomas, and HNs. The classification and regression tree algorithm applied to fine-needle aspiration samples demonstrated that three dysregulated miRNAs (miR-885-5p/-221/-574-3p) allowed distinguishing follicular thyroid carcinomas from benign HNs with high accuracy.Conclusions:In this study we demonstrate that different histopathological types of follicular thyroid carcinomas have distinct miRNA expression profiles. MiR-885-5p is highly up-regulated in oncocytic follicular carcinomas and may serve as a diagnostic marker for these tumors. A small set of deregulated miRNAs allows for an accurate discrimination between follicular carcinomas and hyperplastic nodules and can be used diagnostically in fine-needle aspiration biopsies.

Classification and selection of biomarkers in genomic data using LASSO

High-throughput gene expression technologies such as microarrays have been utilized in a variety of scientific applications. Most of the work has been on assessing univariate associations between gene expression with clinical outcome (variable selection) or on developing classification procedures with gene expression data (supervised learning). We consider a hybrid variable selection/classification approach that is based on linear combinations of the gene expression profiles that maximize an accuracy measure summarized using the receiver operating characteristic curve. Under a specific probability model, this leads to consideration of linear discriminant functions. We incorporate an automated variable selection approach using LASSO. An equivalence between LASSO estimation with support vector machines allows for model fitting using standard software. We apply the proposed method to simulated data as well as data from a recently published prostate cancer study.