Technologies of Connection

This is the written portion of this thesis

Therapy-based exercise from the perspective of adult patients: a qualitative systematic review conducted using an ethnographic approach

© The Author(s) 2019.Objectives: Many patients do not meet recommended levels of therapy-based exercise. This review aims to explore how adult patients view being prescribed therapy-based exercise, the information/education they are given and receive and if/how they independently practise and adhere. Design: A qualitative systematic review conducted using an ethnographic approach and in accordance with the PRISMA statement. Sources: PubMed, CINAHL, SCOPUS and EMBASE databases (01 January 2000–31 December 2018). Methods: Qualitative studies with a focus on engagement/adherence with therapy-based exercise were included. Data extraction and quality appraisal were undertaken by two reviewers. Results were discussed and data synthesized. Results: A total of 20,294 titles were screened, with data extracted from 39 full texts and data from 18 papers used to construct three themes. ‘The Guidance received’ suggests that the type of delivery desired to support and sustain engagement was context-dependent and individually situated. ‘The Therapist as teacher’ advocates that patients see independent therapy-based exercise as a shared activity and value caring, kind and professional qualities in their therapist. ‘The Person as learner’ proposes that when having to engage with and practise therapy-based exercise because of ill-health, patients often see themselves as new learners who experience fear and uncertainty about what to do. Patients may have unacknowledged ambivalences about learning that impact on engagement and persistence. Conclusion: The quality of the interaction between therapists and patients appears integral to patients engaging with, and sustaining practice of, rehabilitation programmes. Programmes need to be individualized, and health care professionals need to take patients’ previous experiences and ambivalences in motivation and empowerment into account.Peer reviewe

Functional glass slides for in vitro evaluation of interactions between bone cells and mineral-binding surfaces

Primary amine-functionalized glass slides obtained through a multi-step plasma treatment were conjugated with anionic amino acids that are frequently found as mineral binding elements in acidic extracellular matrix components of natural bone. The modified glass surfaces were characterized by X-ray photoelectron spectroscopy (XPS) and contact angle measurements. Human osteosarcoma TE85 cells were cultured on these functionalized slides and analyses on both protein and gene expression levels were performed to probe the ‘‘biocompatibility’’ of the surface ligands. Cell attachment and proliferation on anionic surfaces were either better than or comparable to those of cells cultured on tissue culture polystyrene (TCPS). The modified glass surfaces promoted the expression of osteocalcin, alkaline phosphatase activity and ECM proteins such as fibronectin and vitronectin under differentiation culture conditions. Transcript analysis using gene chip microarrays confirmed that culturing TE85 cells on anionic surfaces did not activate apoptotic pathways.Collectively, these results suggest that the potential mineral-binding anionic ligands examined here do not exert significant adverse effects on the expression of important osteogenic markers of TE85 cells. This work paves theway for the incorporation of these ligands into 3-dimensional artificial bone-like scaffolds

Critical gradient for internal erosion in earthen d ams : a comparative analysis of two predictive methodologies

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 79-81).Minimizing the uncertainty in predicting the critical gradient of a dam (i.e. the critical reservoir pool level) is important during the risk analysis of dams. Uncertainty leads to inexact relative risk in portfolio management; therefore it is essential to get as accurate a risk estimation as possible for each project in a portfolio. To understand the uncertainty inherent in the predictive methodologies, this thesis sets out to compare the two most commonly used predictive methodologies, Sellmeijer and Schmertmann, in the USACE portfolio in order to make a suggestion of when to use which. Both methodologies have been calibrated for a small range of ideal soil characteristics that may not reflect of existing conditions of the portfolio. This thesis concludes with the recommendation to broaden the range of applicability through additional experiments that include anisotropic conditions.by Catherine Donohue.M.Eng

Using Markov Models to Mine Temporal and Spatial Data

Référence du projet ANR BIODIVAGRIM : ANR 07 BDIV 02Markov models represent a powerful way to approach the problem of mining time and spatial signals whose variability is not yet fully understood. In this chapter, we will present a general methodology to mine different kinds of temporal and spatial signals having contrasting properties: continuous or discrete with few or many modalities. This methodology is based on a high order Markov modelling as implemented in a free software: carottAge (Gnu GPL)Les modèles de Markov sont des modèles puissants pour analyser des signaux temporels et spatiaux dont la variabilité n'est pas entièrement comprise. Dans ce chapitre, nous présentons notre méthodologie pour fouiller différentes sortes de signaux ayant des propriétés différentes: signaux continus ou discrets, simples ou composites. Cette méthodologie s'appuie sur des modèles de Markov cachés du second-ordre tels qu'implantés dans la boîte à outils CarottAge (licence Gnu-GPL)

A Case of Infectious Purpura Fulminans: An Unusual Organism and Method of Diagnosis

Infectious purpura fulminans is a rapidly progressive skin necrosis that carries a mortality rate of 30%. Here, we described a case of infectious purpura fulminans caused by Capnocytophaga diagnosed by a blood film

Data Mining Using Hidden Markov Models (HMM2) to Detect Heterogeneities into Bacteria Genomes

PosterThe Streptococcus genus contains both pathogenic bacteria and bacteria used in the food-processing industry. We are developing a statistical segmentation method to identify heterogeneous sequences such as sequences acquired from recent horizontal transfer or genes weakly or strongly expressed. The method is based on second order Hidden Markov Models (HMM2). After an automatic unsupervised training, this method allows to demarcating some particular areas into a genome. After checking the efficiency of such models on various controls and on chimeric sequences generated in silico, we choose a HMM2 (3-mer, 5 states) to analyse the complete genome sequence of S. Thermophilus CNRZ1066 (1.8 Mb). More the 80 atypical segments were extracted and are currently analysed further

Data Mining Using Hidden Markov Models (HMM2) to Detect Heterogeneities into Bacteria Genomes

International audienceThe Streptococcus genus contains both pathogenic bacteria and bacteria used in the food-processing industry. We are developing a statistical segmentation method to identify heterogeneous sequences such as sequences acquired from recent horizontal transfer or genes weakly or strongly expressed. The method is based on second order Hidden Markov Models (HMM2). After an automatic unsupervised training, this method allows to demarcating some particular areas into a genome. After checking the efficiency of such models on various controls and on chimeric sequences generated in silico, we choose a HMM2 (3-mer, 5 states) to analyse the complete genome sequence of S. Thermophilus CNRZ1066 (1.8 Mb). More the 80 atypical segments were extracted and are currently analysed further

A new data mining approach for the detection of bacterial promoters combining stochastic and combinatorial methods

International audienceWe present a new data mining method based on stochastic analysis (HMM for Hidden Markov Model) and combinatorial methods for discovering new transcriptional factors in bacterial genome sequences. Sigma factor binding sites (SFBSs) were described as patterns of box1 - spacer - box2 corresponding to the -35 and -10 DNA motifs of bacterial promoters. We used a high-order Hidden Markov Model in which the hidden process is a second-order Markov chain. Applied on the genome of the model bacterium Streptomyces coelicolor (2), the a posteriori state probabilities revealed local maxima or peaks whose distribution was enriched in the intergenic sequences (``iPeaks'' for intergenic peaks). Short DNA sequences underlying the iPeaks were extracted and clustered by a hierarchical classification algorithm based on the SmithWaterman local similarity. Some selected motif consensuses were used as box1 (-35 motif) in the search of a potential neighbouring box2 (-10 motif) using a word enumeration algorithm. This new SFBS mining methodology applied on Streptomyces coelicolor was successful to retrieve already known SFBSs and to suggest new potential transcriptional factor binding sites (TFBSs). The well defined SigR regulon (oxidative stress response) was also used as a test quorum to compare first and second-order HMM. Our approach also allowed the preliminary detection of known SFBSs in Bacillus subtilis