Spatial pattern of landslides in Swiss Rhone valley

The present study analyses the spatial pattern of quaternary gravitational slope deformations (GSD) and historical/present-day instabilities (HPI) inventoried in the Swiss Rhone Valley. The main objective is to test if these events are clustered (spatial attraction) or randomly distributed (spatial independency). Moreover, analogies with the cluster behaviour of earthquakes inventoried in the same area were examined. The Ripley's K-function was applied to measure and test for randomness. This indicator allows describing the spatial pattern of a point process at increasing distance values. To account for the non-constant intensity of the geological phenomena, a modification of the K-function for inhomogeneous point processes was adopted. The specific goal is to explore the spatial attraction (i.e. cluster behaviour) among landslide events and between gravitational slope deformations and earthquakes. To discover if the two classes of instabilities (GSD and HPI) are spatially independently distributed, the cross K-function was computed. The results show that all the geological events under study are spatially clustered at a well-defined distance range. GSD and HPI show a similar pattern distribution with clusters in the range 0.75?9 km. The cross K-function reveals an attraction between the two classes of instabilities in the range 0?4 km confirming that HPI are more prone to occur within large-scale slope deformations. The K-function computed for GSD and earthquakes indicates that both present a cluster tendency in the range 0?10 km, suggesting that earthquakes could represent a potential predisposing factor which could influence the GSD distribution.

The mediterranean diet pattern and its main components are associated with lower plasma concentrations of tumor necrosis factor receptor 60 in patients at high risk for cardiovascular disease

Adherence to aMediterranean diet (MD) is associated with a reduced risk of coronary heart disease. However, themolecular mechanisms involved are not fully understood. The aim of this studywas to compare the effects of 2MD with those of a lowfat- diet (LFD) on circulating inflammatory biomarkers related to atherogenesis. A total of 516 participants included in the PreventionwithMediterraneanDiet Studywere randomized into 3 intervention groups [MD supplementedwith virgin olive oil (MD-VOO); MD supplemented with mixed nuts (MD-Nuts); and LFD]. At baseline and after 1 y, participants completed FFQ and adherence to MD questionnaires, and plasma concentrations of inflammatory markers including intercellular adhesion molecule-1(ICAM-1), IL-6, and 2 TNF receptors (TNFR60 and TNFR80) were measured by ELISA. At 1 y, the MD groups had lower plasma concentrations of IL-6, TNFR60, and TNFR80 (P , 0.05), whereas ICAM-1, TNFR60, and TNFR80 concentrations increased in the LFD group (P , 0.002). Due to between-group differences, participants in the 2 MD groups had lower plasma concentrations of ICAM-1, IL-6, TNFR60, and TNFR80 compared to those in the LFD group (P # 0.028). When participants were categorized in tertiles of 1-y changes in the consumption of selected foods, those in the highest tertile of virgin olive oil (VOO) and vegetable consumption had a lower plasma TNFR60 concentration compared with those in tertile 1 (P,0.02).Moreover, the only changes in consumption thatwere associated with 1-y changes in the geometricmean TNFR60 concentrations were those of VOO and vegetables (P = 0.01). This study suggests that a MD reduces TNFR concentrations in patients at high cardiovascular risk.

A Dependency Parsing Approach to Biomedical Text Mining

Biomedical research is currently facing a new type of challenge: an excess of information, both in terms of raw data from experiments and in the number of scientific publications describing their results. Mirroring the focus on data mining techniques to address the issues of structured data, there has recently been great interest in the development and application of text mining techniques to make more effective use of the knowledge contained in biomedical scientific publications, accessible only in the form of natural human language. This thesis describes research done in the broader scope of projects aiming to develop methods, tools and techniques for text mining tasks in general and for the biomedical domain in particular. The work described here involves more specifically the goal of extracting information from statements concerning relations of biomedical entities, such as protein-protein interactions. The approach taken is one using full parsing—syntactic analysis of the entire structure of sentences—and machine learning, aiming to develop reliable methods that can further be generalized to apply also to other domains. The five papers at the core of this thesis describe research on a number of distinct but related topics in text mining. In the first of these studies, we assessed the applicability of two popular general English parsers to biomedical text mining and, finding their performance limited, identified several specific challenges to accurate parsing of domain text. In a follow-up study focusing on parsing issues related to specialized domain terminology, we evaluated three lexical adaptation methods. We found that the accurate resolution of unknown words can considerably improve parsing performance and introduced a domain-adapted parser that reduced the error rate of theoriginal by 10% while also roughly halving parsing time. To establish the relative merits of parsers that differ in the applied formalisms and the representation given to their syntactic analyses, we have also developed evaluation methodology, considering different approaches to establishing comparable dependency-based evaluation results. We introduced a methodology for creating highly accurate conversions between different parse representations, demonstrating the feasibility of unification of idiverse syntactic schemes under a shared, application-oriented representation. In addition to allowing formalism-neutral evaluation, we argue that such unification can also increase the value of parsers for domain text mining. As a further step in this direction, we analysed the characteristics of publicly available biomedical corpora annotated for protein-protein interactions and created tools for converting them into a shared form, thus contributing also to the unification of text mining resources. The introduced unified corpora allowed us to perform a task-oriented comparative evaluation of biomedical text mining corpora. This evaluation established clear limits on the comparability of results for text mining methods evaluated on different resources, prompting further efforts toward standardization. To support this and other research, we have also designed and annotated BioInfer, the first domain corpus of its size combining annotation of syntax and biomedical entities with a detailed annotation of their relationships. The corpus represents a major design and development effort of the research group, with manual annotation that identifies over 6000 entities, 2500 relationships and 28,000 syntactic dependencies in 1100 sentences. In addition to combining these key annotations for a single set of sentences, BioInfer was also the first domain resource to introduce a representation of entity relations that is supported by ontologies and able to capture complex, structured relationships. Part I of this thesis presents a summary of this research in the broader context of a text mining system, and Part II contains reprints of the five included publications.

Pattern of injury with a graded excitotoxic insult and ensuing chronic medial septal damage in the rat brain

Brain damage caused by an acute injury depends on the initial severity of the injury and the time elapsed after the injury. To determine whether these two variables activate common mechanisms, we compared the response of the rat medial septum to insult with a graded series of concentrations of a-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) with the time-course effects of a low dose of AMPA. For this purpose we conducted a dose-response study at concentrations of AMPA between 0.27 and 10.8 nmol to measure atrophy of the septal area, losses of cholinergic and GABAergic neurons, astroglial and microglial reactions, and calcification. Cholinergic neurons, whose loss paralleled the degree of septal atrophy produced by AMPA, are more sensitive than GABAergic neurons to the injury produced by AMPA. At doses of AMPA above 2.7 nmol, calcification and the degree of microglial reaction increased only in the GABAergic region of the septal area, whereas atrophy and neuronal loss reached a plateau. We chose the 2.7-nmol dose of AMPA to determine how these parameters were modified between 4 days and 6 months after injection. We found that atrophy and neuronal loss increased progressively through the 6-month study period, whereas astrogliosis ceased to be observed after 1 month, and calcium precipitates were never detected. We conclude that septal damage does not increase with the intensity of an excitotoxic insult. Rather, it progresses continuously after the insult. Because these two situations involve different mechanisms, short-term paradigms are inappropriate for interpreting the pathogenic mechanisms responsible for long-term neurodegenerative processes.

Cell fusion reprogramming leads to a specific hepatic expression pattern during mouse bone marrow derived hepatocyte formation In Vivo

The fusion of bone marrow (BM) hematopoietic cells with hepatocytes to generate BM derived hepatocytes (BMDH) is a natural process, which is enhanced in damaged tissues. However, the reprogramming needed to generate BMDH and the identity of the resultant cells is essentially unknown. In a mouse model of chronic liver damage, here we identify a modification in the chromatin structure of the hematopoietic nucleus during BMDH formation, accompanied by the loss of the key hematopoietic transcription factor PU.1/Sfpi1 (SFFV proviral integration 1) and gain of the key hepatic transcriptional regulator HNF-1A homeobox A (HNF-1A/Hnf1a). Through genome-wide expression analysis of laser captured BMDH, a differential gene expression pattern was detected and the chromatin changes observed were confirmed at the level of chromatin regulator genes. Similarly, Tranforming Growth Factor-β1 (TGF-β1) and neurotransmitter (e.g. Prostaglandin E Receptor 4 [Ptger4]) pathway genes were over-expressed. In summary, in vivo BMDH generation is a process in which the hematopoietic cell nucleus changes its identity and acquires hepatic features. These BMDHs have their own cell identity characterized by an expression pattern different from hematopoietic cells or hepatocytes. The role of these BMDHs in the liver requires further investigation.

Post-partum persistence of abnormal circadian pattern of blood pressure after preeclampsia [109-POS]

OBJECTIVES: Blunted nocturnal dip of blood pressure (BP) and reversed circadian rhythm have been described in preeclampsia (PE). Non-dipper status and preeclampsia are both associated with an increased risk of cardiovascular disease later in life. Complete recovery of BP in PE is reported to occur over a variable period of time. Twenty-four hours-ambulatory blood pressure measurement (ABPM) in the post-partum follow-up after a PE has not been described. The aim of this study was to assess 24h-ambulatory blood pressure pattern after a PE and to determine the prevalence of non-dipper status, nocturnal hypertension, white coat hypertension and masked hypertension. METHODS: This is an observational, prospective study on women who suffered from a preeclampsia. A 24h-ABPM was done 6 weeks post-partum at the Hypertension Unit of the University Hospitals of Geneva, concomitantly with a clinical and biological evaluation. RESULTS: Forty-five women were included in a preliminary analysis. Mean age was 33±6years, 57.3% were Caucasian, mean BMI before pregnancy was 24±5kg/m(2). Office and ambulatory BP are shown in Table 1. Prevalence of nocturnal hypertension was high and half of the women had no nocturnal dipping. The diagnosis of hypertension based on office BP was discordant with the diagnosis based on ABPM in 25% of women. CONCLUSIONS: The prevalence of increased nighttime BP and abnormal BP pattern is high at 6weeks post-partum in preeclamptic women. Early assessment of BP with ABPM after preeclampsia allows an early identification of women with persistent circadian abnormalities who might be at increased risk. It also provides a more accurate assessment than office BP. DISCLOSURES: A. Ditisheim: None. B. Ponte: None. G. Wuerzner: None. M. Burnier: None. M. Boulvain: None. A. Pechère-Bertschi: None.

Pancreatic adenocarcinoma: the impact of preneoplastic lesion pattern on survival.

Pancreatic adenocarcinoma is associated with a very poor prognosis, characterized with a 5-year survival rate of only 5%. Surgery is the only curative treatment for selected patients. Nevertheless, recurrence is very frequent. Identifying prognostic factors is thus warranted. Like numerous other tumors, adenocarcinomas are preceded by preneoplastic lesions. The role and the impact of these lesions remain unclear. This study aimed to assess the impact of the preneoplastic lesion pattern and histo-morphological features, on survival after pancreatic resection. Thirty-five patients who underwent pancreatic resection for pancreatic adenocarcinoma were identified from a prospective database of a single center, between 2003 and 2008. We considered demographics, tumor characteristics and type of treatment. The major outcome was survival. Analyzes were separated into two groups, according to the preneoplastic lesions: Pancreatic intraepithelial neoplasia (PanIN)-related carcinomas and intracanalar papillary mucinous neoplasia (IPMN)-related carcinomas. The former were more frequent, accounting for 63% (22/35). Moreover, they displayed more aggressive features, with a higher tumor stage (p = 0.01) and higher rate of positive lymph nodes (p = 0.019). Lymphatic (p = 0.009) and perinervous (p = 0.019) invasions were also more frequent. Survival was negatively influenced by PanIN preneoplastic lesions (p = 0.015), T3-4 tumor stage (p = 0.038), positive lymph nodes (p = 0.044), lymphatic (p = 0.019) and vascular (p = 0.029) invasions. Pancreatic adenocarcinoma displays different behavior according to its preneoplastic lesion. Indeed, PanIN-related adenocarcinoma showed more aggressive features and lower survival rate. Preneoplastic lesions may represent predictive factors for survival. Their role and predictive value should be investigated more thoroughly.

Construction of an index of information from clinical practice in Radiology and Imaging Diagnosis based on text mining and thesaurus

Objective To construct a Portuguese language index of information on the practice of diagnostic radiology in order to improve the standardization of the medical language and terminology. Materials and Methods A total of 61,461 definitive reports were collected from the database of the Radiology Information System at Hospital das Clínicas – Faculdade de Medicina de Ribeirão Preto (RIS/HCFMRP) as follows: 30,000 chest x-ray reports; 27,000 mammography reports; and 4,461 thyroid ultrasonography reports. The text mining technique was applied for the selection of terms, and the ANSI/NISO Z39.19-2005 standard was utilized to construct the index based on a thesaurus structure. The system was created in *html. Results The text mining resulted in a set of 358,236 (n = 100%) words. Out of this total, 76,347 (n = 21%) terms were selected to form the index. Such terms refer to anatomical pathology description, imaging techniques, equipment, type of study and some other composite terms. The index system was developed with 78,538 *html web pages. Conclusion The utilization of text mining on a radiological reports database has allowed the construction of a lexical system in Portuguese language consistent with the clinical practice in Radiology.

Opinion Mining

In this thesis we study the field of opinion mining by giving a comprehensive review of the available research that has been done in this topic. Also using this available knowledge we present a case study of a multilevel opinion mining system for a student organization's sales management system. We describe the field of opinion mining by discussing its historical roots, its motivations and applications as well as the different scientific approaches that have been used to solve this challenging problem of mining opinions. To deal with this huge subfield of natural language processing, we first give an abstraction of the problem of opinion mining and describe the theoretical frameworks that are available for dealing with appraisal language. Then we discuss the relation between opinion mining and computational linguistics which is a crucial pre-processing step for the accuracy of the subsequent steps of opinion mining. The second part of our thesis deals with the semantics of opinions where we describe the different ways used to collect lists of opinion words as well as the methods and techniques available for extracting knowledge from opinions present in unstructured textual data. In the part about collecting lists of opinion words we describe manual, semi manual and automatic ways to do so and give a review of the available lists that are used as gold standards in opinion mining research. For the methods and techniques of opinion mining we divide the task into three levels that are the document, sentence and feature level. The techniques that are presented in the document and sentence level are divided into supervised and unsupervised approaches that are used to determine the subjectivity and polarity of texts and sentences at these levels of analysis. At the feature level we give a description of the techniques available for finding the opinion targets, the polarity of the opinions about these opinion targets and the opinion holders. Also at the feature level we discuss the various ways to summarize and visualize the results of this level of analysis. In the third part of our thesis we present a case study of a sales management system that uses free form text and that can benefit from an opinion mining system. Using the knowledge gathered in the review of this field we provide a theoretical multi level opinion mining system (MLOM) that can perform most of the tasks needed from an opinion mining system. Based on the previous research we give some hints that many of the laborious market research tasks that are done by the sales force, which uses this sales management system, can improve their insight about their partners and by that increase the quality of their sales services and their overall results.