NLP-based Metadata Extraction for Legal Text Consolidation

The paper describes a system for the automatic consolidation of Italian legislative texts to be used as a support of an editorial consolidating activity and dealing with the following typology of textual amendments: repeal, substitution and integration. The focus of the paper is on the semantic analysis of the textual amendment provisions and the formalized representation of the amendments in terms of metadata. The proposed approach to consolidation is metadata- oriented and based on Natural Language Processing (NLP) techniques: we use XML-based standards for metadata annotation of legislative acts and a flexible NLP architecture for extracting metadata from parsed texts. An evaluation of achieved results is also provided

Assessment of DNA damages in lymphocytes of agricultural workers exposed to pesticides by comet assay in a cross-sectional study

Purpose: To assess the predictive power of the comet assay in the context of occupational exposure to pesticides. Materials and methods: The recruited subjects completed a structured questionnaire and gave a blood sample. Exposure to pesticides was measured by means of an algorithm based on Dosemeci’s work (Agricultural Health Study). Approximately 50 images were analyzed for each sample via fluores- cence microscopy. The extent of DNA damage was estimated by tail moment (TM) and is the product of tail DNA (%) and tail Length. Results: Crude significant risks (odds ratios, ORs) for values higher than the 75th percentile of TM were observed among the exposed subjects (score>1). The frequency of some confounding factors (sex, age and smoking) was significantly higher among the exposed workers. A significant dose–effect relationship was observed between TM and exposure score. Significant high-risk estimates (ORs), adjusted by the studied confounding factors, among exposure to pesticides and TM, % tail DNA and tail length were confirmed using unconditional logistic regression models. Conclusions: The adjusted associations (ORs) between the comet parameters and exposure to pesti- cides were significant. The sensitivity of the comet test was low (41%), the specificity (89%) and the predictive positive value (0.77) were found acceptable

Proceedings of LOAIT '07 : II Workshop on Legal Ontologies and Artificial Intelligence Techniques

Proceedings of the 2nd Workshop on Legal Ontologies and Artificial Intelligence Techniques June 4th, 2007, Stanford Universit

Banche dati d'interesse giuridico consultabili dal "nodo" IDG

3. edSIGLEITItal

Risk of lymphoma subtypes by occupational exposure in Southern Italy

Background: Occupational exposure is known to play a role in the aetiology of lymphomas. The aim of the present work was to explore the occupational risk of the major B-cell lymphoma subtypes using a case–control study design. Methods: From 2009 to 2014, we recruited 158 lymphoma cases and 76 controls in the provinces of Bari and Taranto (Apulia, Southern Italy). A retrospective assessment of occupational exposure based on complete work histories and the Carcinogen Exposure (CAREX) job-exposure matrix was performed. Results: After adjusting for major confounding factors, farmers showed an increased risk of diffuse large B-cell lymphoma (DLBCL) [odds ratio (OR) = 10.9 (2.3–51.6)] and multiple myeloma (MM) [OR = 16.5 (1.4–195.7)]; exposure to the fungicide Captafol was significantly associated with risk of non-Hodgkin lymphoma (NHL) [OR = 2.6 (1.1–8.2)], particularly with the risk of DLBCL [OR = 5.3 (1.6–17.3)]. Conclusions: Agricultural activity seems to be a risk factor for developing lymphoma subtypes, particularly DLBCL, in the provinces of Bari and Taranto (Apulia Region, Southern Italy). Exposure to the pesticides Captafol, Paraquat and Radon might be implicated. Trial registration: Protocol number UNIBA 2207WEJLZB_004 registered 22/09/2008. Keywords: Lymphomas, Occupational exposure, CAREX matrix, Pesticides, B-cell lymphoma subtypes, Case–control stud

Proceedings of LOAIT '07 : II Workshop on Legal Ontologies and Artificial Intelligence Techniques

Proceedings of the 2nd Workshop on Legal Ontologies and Artificial Intelligence Techniques June 4th, 2007, Stanford Universit