One gene but different proteins and diseases: the complexity of dystonin and bullous pemphigoid antigen 1.

Since the immunochemical identification of the bullous pemphigoid antigen 230 (BP230) as one of the major target autoantigens of bullous pemphigoid (BP) in 1981, our understanding of this protein has significantly increased. Cloning of its gene, development and characterization of animal models with engineered gene mutations or spontaneous mouse mutations have revealed an unexpected complexity of the gene encoding BP230. The latter, now called dystonin (DST), is composed of at least 100 exons and gives rise to three major isoforms, an epithelial, a neuronal and a muscular isoform, named BPAG1e (corresponding to the original BP230), BPAG1a and BPAG1b, respectively. The various BPAG1 isoforms play a key role in fundamental processes, such as cell adhesion, cytoskeleton organization, and cell migration. Genetic defects of BPAG1 isoforms are the culprits of epidermolysis bullosa and complex, devastating neurological diseases. In this review, we summarize recent advances of our knowledge about several BPAG1 isoforms, their role in various biological processes and in human diseases.

Impact of Diabetic Status on Outcomes After Revascularization With Drug-Eluting Stents in Relation to Coronary Artery Disease Complexity: Patient-Level Pooled Analysis of 6081 Patients.

BACKGROUND Diabetes mellitus and angiographic coronary artery disease complexity are intertwined and unfavorably affect prognosis after percutaneous coronary interventions, but their relative impact on long-term outcomes after percutaneous coronary intervention with drug-eluting stents remains controversial. This study determined drug-eluting stents outcomes in relation to diabetic status and coronary artery disease complexity as assessed by the Synergy Between PCI With Taxus and Cardiac Surgery (SYNTAX) score. METHODS AND RESULTS In a patient-level pooled analysis from 4 all-comers trials, 6081 patients were stratified according to diabetic status and according to the median SYNTAX score ≤11 or >11. The primary end point was major adverse cardiac events, a composite of cardiac death, myocardial infarction, and clinically indicated target lesion revascularization within 2 years. Diabetes mellitus was present in 1310 patients (22%), and new-generation drug-eluting stents were used in 4554 patients (75%). Major adverse cardiac events occurred in 173 diabetics (14.5%) and 436 nondiabetic patients (9.9%; P<0.001). In adjusted Cox regression analyses, SYNTAX score and diabetes mellitus were both associated with the primary end point (P<0.001 and P=0.028, respectively; P for interaction, 0.07). In multivariable analyses, diabetic versus nondiabetic patients had higher risks of major adverse cardiac events (hazard ratio, 1.25; 95% confidence interval, 1.03-1.53; P=0.026) and target lesion revascularization (hazard ratio, 1.54; 95% confidence interval, 1.18-2.01; P=0.002) but similar risks of cardiac death (hazard ratio, 1.41; 95% confidence interval, 0.96-2.07; P=0.08) and myocardial infarction (hazard ratio, 0.89; 95% confidence interval, 0.64-1.22; P=0.45), without significant interaction with SYNTAX score ≤11 or >11 for any of the end points. CONCLUSIONS In this population treated with predominantly new-generation drug-eluting stents, diabetic patients were at increased risk for repeat target-lesion revascularization consistently across the spectrum of disease complexity. The SYNTAX score was an independent predictor of 2-year outcomes but did not modify the respective effect of diabetes mellitus. CLINICAL TRIAL REGISTRATION URL: http://www.clinicaltrials.gov. Unique identifiers: NCT00297661, NCT00389220, NCT00617084, and NCT01443104.

The Complexity of Non-Iterated Probabilistic Justification Logic

The logic PJ is a probabilistic logic defined by adding (noniterated) probability operators to the basic justification logic J. In this paper we establish upper and lower bounds for the complexity of the derivability problem in the logic PJ. The main result of the paper is that the complexity of the derivability problem in PJ remains the same as the complexity of the derivability problem in the underlying logic J, which is π[p/2] -complete. This implies that the probability operators do not increase the complexity of the logic, although they arguably enrich the expressiveness of the language.

Google Analytics & CONTENTdm: Harness Up Your Repository Metrics

A demonstration of the installation and use of Google Analytics with CONTENTdm in order to better gather metrics and insight into both general and specific online traffic across such digital repositories. Issues addressed will include collection-level traffic, digital object-level traffic, general site referrals to the repository, specific referrals to the repository, search engine referrals, user keywords, traffic occurring inside and/or outside an institution’s own network, reporting options.

Health information exchange: Using metrics to address quality of care and return on investment

Health Information Exchange (HIE) will play a key part in our nation’s effort to improve healthcare. The evidence of HIEs transformational role in healthcare delivery systems is quite limited. The lack of such evidence led us to explore what exists in the healthcare industry that may provide evidence of effectiveness and efficiency of HIEs. The objective of the study was to find out how many fully functional HIEs are using any measurements or metrics to gauge impact of HIE on quality improvement (QI) and on return on investment (ROI).^ A web-based survey was used to determine the number of operational HIEs using metrics for QI and ROI. Our study highlights the fact that only 50 percent of the HIEs who responded use or plan to use metrics. However, 95 percent of the respondents believed HIEs improve quality of care while only 56 percent believed HIE showed positive ROI. Although operational HIEs present numerous opportunities to demonstrate the business model for improving health care quality, evidence to document the impact of HIEs is lacking. ^

Energy, Complexity and Strategies of Evolution. En: Avá, nº 14

Cultural evolution has long been among the themes of anthropology but it has never ranked high. It is left mainly to archaeologists because they have to make sense of how society works and survives through time–a concern that has pretty much been abandoned by many cultural anthropologists. Anthropologists today seem little motivated to find out how society works, but rather to make the world a better place to live in for a particular population. The challenges of atmospheric change, nuclear proliferation, environmental degradation and resource exhaustion, the emergence of life threatening species–these challenges of contemporary evolution have awakened less interest in anthropology. The concern with cultural evolution seems to be of greater interest to non-anthropologists, such as in the work of Jarrod Diamond (2005), a biologist, and the genre that as emerged as Big History, with the works of David Christian (2005) and others. Among the few contemporary anthropologists who have sought the dynamics of cultural evolution, the work of Joseph Tainter (1996) stands out.

Environmental policy and knowledge. Copying with complexity through inclusive management

Scholars agree that governance of the public environment entails cooperation between science, policy and society. This requires the active role of public managers as catalysts of knowledge co-production, addressing participatory arenas in relation to knowledge integration and social learning. This paper deals with the question of whether public managers acknowledge and take on this task. A survey accessing Directors of Environmental Offices (EOs) of 64 municipalities was carried out in parallel for two regions - Tuscany (Italy) and Porto Alegre Metropolitan Region (Brazil). The survey data were analysed using the multiple correspondence method. Results showed that, regarding policy practices, EOs do not play the role of knowledge co-production catalysts, since when making environmental decisions they only use technical knowledge. We conclude that there is a gap between theory and practice, and identify some factors that may hinder local environmental managers in acting as catalyst of knowledge co-production, raising a further question for future research.

Decision evaluation in complex risk network systems (DecernsSDSS) demo and Black River case study

The selection of metrics for ecosystem restoration programs is critical for improving the quality of monitoring programs and characterizing project success. Moreover it is oftentimes very difficult to balance the importance of multiple ecological, social, and economical metrics. Metric selection process is a complex and must simultaneously take into account monitoring data, environmental models, socio-economic considerations, and stakeholder interests. We propose multicriteria decision analysis (MCDA) methods, broadly defined, for the selection of optimal sets of metrics to enhance evaluation of ecosystem restoration alternatives. Two MCDA methods, a multiattribute utility analysis (MAUT), and a probabilistic multicriteria acceptability analysis (ProMAA), are applied and compared for a hypothetical case study of a river restoration involving multiple stakeholders. Overall, the MCDA results in a systematic, unbiased, and transparent solution, informing restoration alternatives evaluation. The two methods provide comparable results in terms of selected metrics. However, because ProMAA can consider probability distributions for weights and utility values of metrics for each criteria, it is suggested as the best option if data uncertainty is high. Despite the increase in complexity in the metric selection process, MCDA improves upon the current ad-hoc decision practice based on the consultations with stakeholders and experts, and encourages transparent and quantitative aggregation of data and judgement, increasing the transparency of decision making in restoration projects. We believe that MCDA can enhance the overall sustainability of ecosystem by enhancing both ecological and societal needs.

On the Statistical Distribution of Object-Oriented System Properties

The statistical distributions of different software properties have been thoroughly studied in the past, including software size, complexity and the number of defects. In the case of object-oriented systems, these distributions have been found to obey a power law, a common statistical distribution also found in many other fields. However, we have found that for some statistical properties, the behavior does not entirely follow a power law, but a mixture between a lognormal and a power law distribution. Our study is based on the Qualitas Corpus, a large compendium of diverse Java-based software projects. We have measured the Chidamber and Kemerer metrics suite for every file of every Java project in the corpus. Our results show that the range of high values for the different metrics follows a power law distribution, whereas the rest of the range follows a lognormal distribution. This is a pattern typical of so-called double Pareto distributions, also found in empirical studies for other software properties.