Agreeing on what? creating joint accounts of strategic change

This paper addresses a fundamental conundrum at the heart of meaning-making: how are multiple meanings accommodated within a joint account, given the plurivocal nature of organizations? While a new strategic initiative introduces new meanings that must coexist within multiple prevailing meanings; studies on meaning-making processes place different emphases on the accommodation of such multiplicity within a joint account. Based on the findings from a longitudinal case study conducted in a university setting, we develop a framework that demonstrates two patterns of meaning-making on the basis of distinct micro processes of expanding, combining and reframing that are involved in the accomplishment of a joint account. Our study offers counter-intuitive insights into the way vested interests enable or constrain the construction of a joint account of meaning. In doing so, we contribute to knowledge about resistance, ambiguity and the role of agreement, or lack of agreement in constructing joint accounts within a plurivocal context

Robotic ubiquitous cognitive ecology for smart homes

Robotic ecologies are networks of heterogeneous robotic devices pervasively embedded in everyday environments, where they cooperate to perform complex tasks. While their potential makes them increasingly popular, one fundamental problem is how to make them both autonomous and adaptive, so as to reduce the amount of preparation, pre-programming and human supervision that they require in real world applications. The project RUBICON develops learning solutions which yield cheaper, adaptive and efficient coordination of robotic ecologies. The approach we pursue builds upon a unique combination of methods from cognitive robotics, machine learning, planning and agent- based control, and wireless sensor networks. This paper illustrates the innovations advanced by RUBICON in each of these fronts before describing how the resulting techniques have been integrated and applied to a smart home scenario. The resulting system is able to provide useful services and pro-actively assist the users in their activities. RUBICON learns through an incremental and progressive approach driven by the feed- back received from its own activities and from the user, while also self-organizing the manner in which it uses available sensors, actuators and other functional components in the process. This paper summarises some of the lessons learned by adopting such an approach and outlines promising directions for future work

Quantification of atopy, lung function and airway hypersensitivity in adults

<p>Abstract</p> <p>Background</p> <p>Studies in children have shown that concentration of specific serum IgE (sIgE) and size of skin tests to inhalant allergens better predict wheezing and reduced lung function than the information on presence or absence of atopy. However, very few studies in adults have investigated the relationship of quantitative atopy with lung function and airway hyperresponsiveness (AHR).</p> <p>Objective</p> <p>To determine the association between lung function and AHR and quantitative atopy in a large sample of adults from the UK.</p> <p>Methods</p> <p>FEV₁ and FVC (% predicted) were measured using spirometry and airway responsiveness by methacholine challenge (5-breath dosimeter protocol) in 983 subjects (random sample of 800 parents of children enrolled in a population-based birth cohort enriched with 183 patients with physician-diagnosed asthma). Atopic status was assessed by skin prick tests (SPT) and measurement of sIgE (common inhalant allergens). We also measured indoor allergen exposure in subjects' homes.</p> <p>Results</p> <p>Spirometry was completed by 792 subjects and 626 underwent methacholine challenge, with 100 (16.0%) having AHR (dose-response slope>25). Using sIgE as a continuous variable in a multiple linear regression analysis, we found that increasing levels of sIgE to mite, cat and dog were significantly associated with lower FEV₁ (mite p = 0.001, cat p = 0.0001, dog p = 2.95 × 10^-8). Similar findings were observed when using the size of wheal on skin testing as a continuous variable, with significantly poorer lung function with increasing skin test size (mite p = 8.23 × 10^-8, cat p = 3.93 × 10^-10, dog p = 3.03 × 10^-15, grass p = 2.95 × 10^-9). The association between quantitative atopy with lung function and AHR remained unchanged when we repeated the analyses amongst subjects defined as sensitised using standard definitions (sIgE>0.35 kUa/l, SPT-3 mm>negative control).</p> <p>Conclusions</p> <p>In the studied population, lung function decreased and AHR increased with increasing sIgE levels or SPT wheal diameter to inhalant allergens, suggesting that atopy may not be a dichotomous outcome influencing lung function and AHR.</p

The Intensity of IUGR-Induced Transcriptome Deregulations Is Inversely Correlated with the Onset of Organ Function in a Rat Model

A low-protein diet applied during pregnancy in the rat results in intrauterine growth restricted (IUGR) fetuses. In humans, IUGR is associated with increased perinatal morbidity, higher incidence of neuro-developmental defects and increased risk of adult metabolic anomalies, such as diabetes and cardiovascular disease. Development and function of many organs are affected by environmental conditions such as those inducing fetal and early postnatal growth restriction. This phenomenon, termed “fetal programming” has been studied unconnectedly in some organs, but very few studies (if any) have investigated at the same time several organs, on a more comparative basis. However, it is quite probable that IUGR affects differentially most organ systems, with possible persistent changes in gene expression. In this study we address transcriptional alterations induced by IUGR in a multi-organ perspective, by systematic analysis of 20-days rat fetuses. We show that (1) expressional alterations are apparently stronger in organs functioning late in foetal or postnatal life than in organs that are functioning early (2) hierarchical classification of the deregulations put together kidney and placenta in one cluster, liver, lungs and heart in another; (3) the epigenetic machinery is set up especially in the placenta, while its alterations are rather mild in other organs; (4) the genes appear deregulated in chromosome clusters; (5) the altered expression cascades varies from organ to organ, with noticeably a very significant modification of the complement and coagulation cascades in the kidney; (6) we found a significant increase in TF binding site for HNF4 proteins specifically for liver genes that are down-regulated in IUGR, suggesting that this decrease is achieved through the action of HNF transcription factors, that are themselves transcriptionnally induced in the liver by IUGR (x 1.84 fold). Altogether, our study suggests that a combination of tissue-specific mechanisms contributes to bring about tissue-driven modifications of gene cascades. The question of these cascades being activated to adapt the organ to harsh environmental condition, or as an endpoint consequence is still raised

PlasmoDraft: a database of Plasmodium falciparum gene function predictions based on postgenomic data

<p>Abstract</p> <p>Background</p> <p>Of the 5 484 predicted proteins of <it>Plasmodium falciparum</it>, the main causative agent of malaria, about 60% do not have sufficient sequence similarity with proteins in other organisms to warrant provision of functional assignments. Non-homology methods are thus needed to obtain functional clues for these uncharacterized genes.</p> <p>Results</p> <p>We present PlasmoDraft <url>http://atgc.lirmm.fr/PlasmoDraft/</url>, a database of Gene Ontology (GO) annotation predictions for <it>P. falciparum </it>genes based on postgenomic data. Predictions of PlasmoDraft are achieved with a <it>Guilt By Association </it>method named Gonna. This involves (1) a predictor that proposes GO annotations for a gene based on the similarity of its profile (measured with transcriptome, proteome or interactome data) with genes already annotated by GeneDB; (2) a procedure that estimates the confidence of the predictions achieved with each data source; (3) a procedure that combines all data sources to provide a global summary and confidence estimate of the predictions. Gonna has been applied to all <it>P. falciparum </it>genes using most publicly available transcriptome, proteome and interactome data sources. Gonna provides predictions for numerous genes without any annotations. For example, 2 434 genes without any annotations in the Biological Process ontology are associated with specific GO terms (<it>e.g</it>. Rosetting, Antigenic variation), and among these, 841 have confidence values above 50%. In the Cellular Component and Molecular Function ontologies, 1 905 and 1 540 uncharacterized genes are associated with specific GO terms, respectively (740 and 329 with confidence value above 50%).</p> <p>Conclusion</p> <p>All predictions along with their confidence values have been compiled in PlasmoDraft, which thus provides an extensive database of GO annotation predictions that can be achieved with these data sources. The database can be accessed in different ways. A global view allows for a quick inspection of the GO terms that are predicted with high confidence, depending on the various data sources. A gene view and a GO term view allow for the search of potential GO terms attached to a given gene, and genes that potentially belong to a given GO term.</p

Gene encoder: a feature selection technique through unsupervised deep learning-based clustering for large gene expression data

© 2020, Springer-Verlag London Ltd., part of Springer Nature. Cancer is a severe condition of uncontrolled cell division that results in a tumor formation that spreads to other tissues of the body. Therefore, the development of new medication and treatment methods for this is in demand. Classification of microarray data plays a vital role in handling such situations. The relevant gene selection is an important step for the classification of microarray data. This work presents gene encoder, an unsupervised two-stage feature selection technique for the cancer samples’ classification. The first stage aggregates three filter methods, namely principal component analysis, correlation, and spectral-based feature selection techniques. Next, the genetic algorithm is used, which evaluates the chromosome utilizing the autoencoder-based clustering. The resultant feature subset is used for the classification task. Three classifiers, namely support vector machine, k-nearest neighbors, and random forest, are used in this work to avoid the dependency on any one classifier. Six benchmark gene expression datasets are used for the performance evaluation, and a comparison is made with four state-of-the-art related algorithms. Three sets of experiments are carried out to evaluate the proposed method. These experiments are for the evaluation of the selected features based on sample-based clustering, adjusting optimal parameters, and for selecting better performing classifier. The comparison is based on accuracy, recall, false positive rate, precision, F-measure, and entropy. The obtained results suggest better performance of the current proposal

The health disparities cancer collaborative: a case study of practice registry measurement in a quality improvement collaborative

<p>Abstract</p> <p>Background</p> <p>Practice registry measurement provides a foundation for quality improvement, but experiences in practice are not widely reported. One setting where practice registry measurement has been implemented is the Health Resources and Services Administration's Health Disparities Cancer Collaborative (HDCC).</p> <p>Methods</p> <p>Using practice registry data from 16 community health centers participating in the HDCC, we determined the completeness of data for screening, follow-up, and treatment measures. We determined the size of the change in cancer care processes that an aggregation of practices has adequate power to detect. We modeled different ways of presenting before/after changes in cancer screening, including count and proportion data at both the individual health center and aggregate collaborative level.</p> <p>Results</p> <p>All participating health centers reported data for cancer screening, but less than a third reported data regarding timely follow-up. For individual cancers, the aggregate HDCC had adequate power to detect a 2 to 3% change in cancer screening, but only had the power to detect a change of 40% or more in the initiation of treatment. Almost every health center (98%) improved cancer screening based upon count data, while fewer (77%) improved cancer screening based upon proportion data. The aggregate collaborative appeared to increase breast, cervical, and colorectal cancer screening rates by 12%, 15%, and 4%, respectively (p < 0.001 for all before/after comparisons). In subgroup analyses, significant changes were detectable among individual health centers less than one-half of the time because of small numbers of events.</p> <p>Conclusions</p> <p>The aggregate HDCC registries had both adequate reporting rates and power to detect significant changes in cancer screening, but not follow-up care. Different measures provided different answers about improvements in cancer screening; more definitive evaluation would require validation of the registries. Limits to the implementation and interpretation of practice registry measurement in the HDCC highlight challenges and opportunities for local and aggregate quality improvement activities.</p

Factors affecting the implementation of complex and evolving technologies: multiple case study of intensity-modulated radiation therapy (IMRT) in Ontario, Canada

<p>Abstract</p> <p>Background</p> <p>Research regarding the decision to adopt and implement technological innovations in radiation oncology is lacking. This is particularly problematic since these technologies are often complex and rapidly evolving, requiring ongoing revisiting of decisions regarding which technologies are the most appropriate to support. Variations in adoption and implementation decisions for new radiation technologies across cancer centres can impact patients' access to appropriate and innovative forms of radiation therapy. This study examines the key steps in the process of adopting and implementing intensity modulated radiation therapy (IMRT) in publicly funded cancer centres and identifies facilitating or impeding factors.</p> <p>Methods</p> <p>A multiple case study design, utilizing document analysis and key informant interviews was employed. Four cancer centres in Ontario, Canada were selected and interviews were conducted with radiation oncologists, medical physicists, radiation therapists, and senior administrative leaders.</p> <p>Results</p> <p>Eighteen key informants were interviewed. Overall, three centres made fair to excellent progress in the implementation of IMRT, while one centre achieved only limited implementation as of 2009. Key factors that influenced the extent of IMRT implementation were categorized as: 1) leadership, 2) training, expertise and standardization, 3) collaboration, 4) resources, and 5) resistance to change.</p> <p>Conclusion</p> <p>A framework for the adoption and implementation of complex and evolving technologies is presented. It identifies the key factors that should be addressed by decision-makers at specific stages of the adoption/implementation process.</p