Collagen concentration and biomechanical properties of samples from the lower uterine cervix in relation to age and parity in non-pregnant women

<p>Abstract</p> <p>Background</p> <p>During normal pregnancy the cervix has a load bearing function. The cervical tissue consists mainly of an extracellular matrix (ECM) rich in collagen; important for the biomechanical properties. The aim of the present study was to evaluate how the biomechanical strength of samples from the distal cervix is associated with collagen content in relation to age and parity. This study demonstrates a method to investigate cervical tissue from women who still have their uterus in situ.</p> <p>Methods</p> <p>Cervical punch biopsies (2 × 15 mm) were obtained from 57 healthy women (median age: 39 years, range: 29-49 years). Biomechanical tensile testing was performed, and collagen concentration (as % of dry defatted weight (DDW)) and content (mg of collagen per mm of specimen length) was determined. Histomorphometry was used to determine the volume densities of extracellular matrix and smooth muscle cells. Smooth muscle cells were identified by immunohistochemistry. Finally, orientation of collagen fibers was estimated. Data are given as mean +/- SD.</p> <p>Results</p> <p>The mean collagen concentration (62.2 +/- 6.6%) increased with age (0.5% per year, r = 0.45, p = 0.003) and decreased with parity (1.7% per birth, r = -0.45, p = 0.033). Maximum load was positively correlated with collagen content (mg of collagen per mm of specimen length) (r = 0.76, p < 0.001). Normalized maximum stiffness was increased with age (r = 0.32, p = 0.017), whereas no correlation was found with regard to parity. In tissue samples with a length of approximately one cm, volume density of smooth muscle cells increased gradually from 8.9% in the distal part near the epithelium, to 15.5% in the proximal part (p < 0.001).</p> <p>Conclusions</p> <p>The present study shows that cervical collagen concentration increases with age and decreases with parity in non-pregnant women. In addition, collagen stiffness increased with age, whereas no change in collagen tensile strength with respect to age and parity was found. These results show that collagen contributes to cervical tissue tensile strength and age and parity should be considered confounding factors.</p

Mining Exceptional Social Behaviour

Essentially, our lives are made of social interactions. These can be recorded through personal gadgets as well as sensors adequately attached to people for research purposes. In particular, such sensors may record real time location of people. This location data can then be used to infer interactions, which may be translated into behavioural patterns. In this paper, we focus on the automatic discovery of exceptional social behaviour from spatio-temporal data. For that, we propose a method for Exceptional Behaviour Discovery (EBD). The proposed method combines Subgroup Discovery and Network Science techniques for finding social behaviour that deviates from the norm. In particular, it transforms movement and demographic data into attributed social interaction networks, and returns descriptive subgroups. We applied the proposed method on two real datasets containing location data from children playing in the school playground. Our results indicate that this is a valid approach which is able to obtain meaningful knowledge from the data.This work has been partially supported by the German Research Foundation (DFG) project “MODUS” (under grant AT 88/4-1). Furthermore, the research leading to these results has received funding (JG) from ESRC grant ES/N006577/1. This work was financed by the project Kids First, project number 68639

CoDEL - A Relationally Complete Language for Database Evolution

Software developers adapt to the fast-moving nature of software systems with agile development techniques. However, database developers lack the tools and concepts to keep pace. Data, already existing in a running product, needs to be evolved accordingly, usually by manually written SQL scripts. A promising approach in database research is to use a declarative database evolution language, which couples both schema and data evolution into intuitive operations. Existing database evolution languages focus on usability but did not aim for completeness. However, this is an inevitable prerequisite for reasonable database evolution to avoid complex and error-prone workarounds. We argue that relational completeness is the feasible expressiveness for a database evolution language. Building upon an existing language, we introduce CoDEL. We define its semantic using relational algebra, propose a syntax, and show its relational completeness

Spatial, temporal and spatio-temporal databases - Hot issues and directions for PhD

Spatial and temporal database systems, both in theory and in practice, have developed dramatically over the past two decades to the point where usable commercial systems, underpinned by a robust theoretical foundation, are now starting to appear. While much remains to be done, topics for research must be chosen carefully to avoid embarking on impractical or unprofitable areas. This is particularly true for doctoral research where the candidate must build a tangible contribution in a relatively short time. The panel session at the Eighth International Symposium on Spatial and Temporal Databases (SSTD 2003) held on Santorini Island, Greece [71 in July 2003 thus took as its focus the question What to focus on (and what to avoid) in Spatial and Temporal Databases : recommendations for doctoral research. This short paper, authored by the panel members, summarizes these discussions

Schema validation and evolution for graph databases

International audienc

Extraction of Spatio-Temporal Data for Social Networks

Abstract. It is often possible to better understand group change over time through examining social network data in a spatial and temporal context. Providing that context from a text analysis perspective requires identifying locations and associating them with people. This paper presents our GeoRef algorithm to automatically do this person-to-place mapping. It involves the identification of location, and uses syntactic proximity of words in the text to link location to person’s name. We describe an application using the algorithm based upon a small set of data from the Sudan Tribune divided into three periods in 2006 for the Darfur crisis. Contributions of this paper are (1) techniques to mine for location from text (2) techniques to mine for social network edges (associations between location and person), (3) use of the mined data to make spatio-temporal maps, and (4) use of the mined data to perform social network analysis