48 research outputs found

    DOR/Tp53inp2 and Tp53inp1 Constitute a Metazoan Gene Family Encoding Dual Regulators of Autophagy and Transcription

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    Human DOR/TP53INP2 displays a unique bifunctional role as a modulator of autophagy and gene transcription. However, the domains or regions of DOR that participate in those functions have not been identified. Here we have performed structure/function analyses of DOR guided by identification of conserved regions in the DOR gene family by phylogenetic reconstructions. We show that DOR is present in metazoan species. Invertebrates harbor only one gene, DOR/Tp53inp2, and in the common ancestor of vertebrates Tp53inp1 may have arisen by gene duplication. In keeping with these data, we show that human TP53INP1 regulates autophagy and that different DOR/TP53INP2 and TP53INP1 proteins display transcriptional activity. The use of molecular evolutionary information has been instrumental to determine the regions that participate in DOR functions. DOR and TP53INP1 proteins share two highly conserved regions (region 1, aa residues 28–42; region 2, 66–112 in human DOR). Mutation of conserved hydrophobic residues in region 1 of DOR (that are part of a nuclear export signal, NES) reduces transcriptional activity, and blocks nuclear exit and autophagic activity under autophagy-activated conditions. We also identify a functional and conserved LC3-interacting motif (LIR) in region 1 of DOR and TP53INP1 proteins. Mutation of conserved acidic residues in region 2 of DOR reduces transcriptional activity, impairs nuclear exit in response to autophagy activation, and disrupts autophagy. Taken together, our data reveal DOR and TP53INP1 as dual regulators of transcription and autophagy, and identify two conserved regions in the DOR family that concentrate multiple functions crucial for autophagy and transcription

    Considerations about quality in model-driven engineering

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    The final publication is available at Springer via http://dx.doi.org/10.1007/s11219-016-9350-6The virtue of quality is not itself a subject; it depends on a subject. In the software engineering field, quality means good software products that meet customer expectations, constraints, and requirements. Despite the numerous approaches, methods, descriptive models, and tools, that have been developed, a level of consensus has been reached by software practitioners. However, in the model-driven engineering (MDE) field, which has emerged from software engineering paradigms, quality continues to be a great challenge since the subject is not fully defined. The use of models alone is not enough to manage all of the quality issues at the modeling language level. In this work, we present the current state and some relevant considerations regarding quality in MDE, by identifying current categories in quality conception and by highlighting quality issues in real applications of the model-driven initiatives. We identified 16 categories in the definition of quality in MDE. From this identification, by applying an adaptive sampling approach, we discovered the five most influential authors for the works that propose definitions of quality. These include (in order): the OMG standards (e.g., MDA, UML, MOF, OCL, SysML), the ISO standards for software quality models (e.g., 9126 and 25,000), Krogstie, Lindland, and Moody. We also discovered families of works about quality, i.e., works that belong to the same author or topic. Seventy-three works were found with evidence of the mismatch between the academic/research field of quality evaluation of modeling languages and actual MDE practice in industry. We demonstrate that this field does not currently solve quality issues reported in industrial scenarios. The evidence of the mismatch was grouped in eight categories, four for academic/research evidence and four for industrial reports. These categories were detected based on the scope proposed in each one of the academic/research works and from the questions and issues raised by real practitioners. We then proposed a scenario to illustrate quality issues in a real information system project in which multiple modeling languages were used. For the evaluation of the quality of this MDE scenario, we chose one of the most cited and influential quality frameworks; it was detected from the information obtained in the identification of the categories about quality definition for MDE. We demonstrated that the selected framework falls short in addressing the quality issues. Finally, based on the findings, we derive eight challenges for quality evaluation in MDE projects that current quality initiatives do not address sufficiently.F.G, would like to thank COLCIENCIAS (Colombia) for funding this work through the Colciencias Grant call 512-2010. This work has been supported by the Gene-ralitat Valenciana Project IDEO (PROMETEOII/2014/039), the European Commission FP7 Project CaaS (611351), and ERDF structural funds.Giraldo-VelĂĄsquez, FD.; España Cubillo, S.; Pastor LĂłpez, O.; Giraldo, WJ. (2016). Considerations about quality in model-driven engineering. Software Quality Journal. 1-66. https://doi.org/10.1007/s11219-016-9350-6S166(1985). Iso information processing—documentation symbols and conventions for data, program and system flowcharts, program network charts and system resources charts. ISO 5807:1985(E) (pp. 1–25).(2011). Iso/iec/ieee systems and software engineering – architecture description. 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Model-driven engineering: a survey supported by the unified conceptual model. Computer Languages Systems and Structures, 43, 139–155.Da Silva Teixeira, D.G.M., Quirino, G.K., Gailly, F., De Almeida Falbo, R., Guizzardi, G., & Perini Barcellos, M. (2016). PoN-S: a Systematic Approach for Applying the Physics of Notation (PoN), (pp. 432–447). Cham: Springer International Publishing.Davies, I., Green, P., Rosemann, M., Indulska, M., & Gallo, S. (2006). How do practitioners use conceptual modeling in practice? Data and Knowledge Engineering, 58(3), 358 – 380. Including the special issue : {ER} 2004ER 2004.Davies, J., Milward, D., Wang, C.-W., & Welch, J. (2015). Formal model-driven engineering of critical information systems. Science of Computer Programming, 103(0), 88 – 113. Selected papers from the First International Workshop on Formal Techniques for Safety-Critical Systems (FTSCS 2012).De Oca, I.M.-M., Snoeck, M., Reijers, H.A., & RodrĂ­guez-Morffi, A. (2015). A systematic literature review of studies on business process modeling quality. Information and Software Technology, 58, 187–205.DenHaan, J. (2009). 8 reasons why model driven development is dangerous @ONLINE.DenHaan, J. (2010). Model driven engineering vs the commando pattern @ONLINE.DenHaan, J. (2011a). Why aren’t we all doing model driven development yet @ONLINE.DenHaan, J. (2011b). Why there is no future model driven development @ONLINE.Di Ruscio, D., Iovino, L., & Pierantonio, A. (2013). Managing the coupled evolution of metamodels and textual concrete syntax specifications. cited By (since 1996)0.Dijkman, R.M., Dumas, M., & Ouyang, C. (2008). Semantics and analysis of business process models in {BPMN}. Information and Software Technology, 50(12), 1281–1294.DomĂ­nguez-Mayo, F.J., Escalona, M.J., MejĂ­as, M., Ramos, I., & FernĂĄndez, L. (2011). A framework for the quality evaluation of mdwe methodologies and information technology infrastructures. International Journal of Human Capital and Information Technology Professionals, 2(4), 11–22.DomĂ­nguez-Mayo, F.J., Escalona, M.J., MejĂ­as, M., & Torres, A.H. (2010). A quality model in a quality evaluation framework for mdwe methodologies. pages 495–506. Affiliation: Departamento de Lenguajes y Sistemas InformĂ­ticos, University of Seville, Seville, Spain., Cited By (since 1996):1.Dubray, J.-J. (2011). Why did mde miss the boat?.Escalona, M.J., GutiĂ©rrez, J.J., PĂ©rez-PĂ©rez, M., Molina, A., DomĂ­nguez-Mayo, E., & DomĂ­nguez-Mayo, F.J. (2011). Measuring the Quality of Model-Driven Projects with NDT-Quality, (pp. 307–317). New York: Springer.Espinilla, M., DomĂ­nguez-Mayo, F.J., Escalona, M.J., MejĂ­as, M., Ross, M., & Staples, G. (2011). A Method Based on AHP to Define the Quality Model of QuEF (Vol. 123, pp. 685–694). Berlin, Heidelberg: Springer.Fabra, J., Castro, V.D., Álvarez, P., & Marcos, E. (2012). Automatic execution of business process models: exploiting the benefits of model-driven engineering approaches. Journal of Systems and Software, 85(3), 607–625. Novel approaches in the design and implementation of systems/software architecture.Falkenberg, E.D., Hesse, W., Lindgreen, P., Nilsson, B.E., Oei, J.L.H., Rolland, C., Stamper, R.K., Assche, F.J.M.V., Verrijn-Stuart, A.A., & Voss, K. (1996). Frisco: a framework of information system concepts. Technical report, The IFIP WG 8. 1 Task Group FRISCO.Fettke, P., Houy, C., Vella, A.-L., & Loos, P. (2012). Towards the Reconstruction and Evaluation of Conceptual Model Quality Discourses – Methodical Framework and Application in the Context of Model Understandability, volume 113 of Lecture Notes in Business Information Processing, chapter 28, pages 406–421, Springer, Berlin, Heidelberg.Finnie, S. (2015). Modeling community: Are we missing something?Fournier, C. (2008). Is uml [email protected], R., & Rumpe, B. (2007). Model-driven development of complex software: a research roadmap. In Future of Software Engineering, 2007, FOSE ’07 (pp. 37–54).Gallego, M., Giraldo, F.D., & Hitpass, B. (2015). Adapting the pbec-otss software selection approach for bpm suites: an application case. In 2015 34th International Conference of the Chilean Computer Science Society (SCCC) (pp. 1–10).GalvĂŁo, I., & Goknil, A. (2007). Survey of traceability approaches in model-driven engineering. cited By (since 1996)22.Giraldo, F., España, S., Giraldo, W., & Pastor, O. (2015). Modelling language quality evaluation in model-driven information systems engineering: a roadmap. In 2015 IEEE 9th International Conference on Research Challenges in Information Science (RCIS) (pp. 64–69).Giraldo, F., España, S., & Pastor, O. (2014). Analysing the concept of quality in model-driven engineering literature: a systematic review. In 2014 IEEE Eighth International Conference on Research Challenges in Information Science (RCIS) (pp. 1–12).Giraldo, F.D., España, S., & Pastor, O. (2016). Evidences of the mismatch between industry and academy on modelling language quality evaluation. arXiv: 1606.02025 .GonzĂĄlez, C., & Cabot, J. (2014). Formal verification of static software models in mde: a systematic review. Information and Software Technology, 56(8), 821–838. cited By (since 1996)0.GonzĂĄlez, C.A., BĂŒttner, F., ClarisĂł, R., & Cabot, J. (2012). Emftocsp: a tool for the lightweight verification of emf models. pages 44–50. Affiliation: cole des Mines de Nantes, INRIA, LINA, Nantes, France; Affiliation: Universitat Oberta de Catalunya, Barcelona, Spain. Cited By (since 1996):1.Gorschek, T., Tempero, E., & Angelis, L. (2014). On the use of software design models in software development practice: an empirical investigation. Journal of Systems and Software, 95(0), 176– 193.GoulĂŁo, M., Amaral, V., & Mernik, M. (2016). Quality in model-driven engineering: a tertiary study. Software Quality Journal, 1–33.Grobshtein, Y., & Dori, D. (2011). Generating sysml views from an opm model: design and evaluation. Systems Engineering, 14(3), 327–340.Haan, J.d. (2008). 8 reasons why model-driven approaches (will) fail.Harel, D., & Rumpe, B. (2000). Modeling languages: Syntax, semantics and all that stuff, part i: The basic stuff, Israel. Technical report Jerusalem Israel.Harel, D., & Rumpe, B. (2004). Meaningful modeling: what’s the semantics of semantics? Computer, 37(10), 64–72.Hebig, R., & Bendraou, R. (2014). On the need to study the impact of model driven engineering on software processes. In Proceedings of the 2014 International Conference on Software and System Process, ICSSP 2014 (pp. 164–168). New York: ACM.Heidari, F., & Loucopoulos, P. (2014). Quality evaluation framework (qef): modeling and evaluating quality of business processes. 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    Tixagevimab–cilgavimab for treatment of patients hospitalised with COVID-19: a randomised, double-blind, phase 3 trial

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    Background: Tixagevimab–cilgavimab is a neutralising monoclonal antibody combination hypothesised to improve outcomes for patients hospitalised with COVID-19. We aimed to compare tixagevimab–cilgavimab versus placebo, in patients receiving remdesivir and other standard care. Methods: In a randomised, double-blind, phase 3, placebo-controlled trial, adults with symptoms for up to 12 days and hospitalised for COVID-19 at 81 sites in the USA, Europe, Uganda, and Singapore were randomly assigned in a 1:1 ratio to receive intravenous tixagevimab 300 mg–cilgavimab 300 mg or placebo, in addition to remdesivir and other standard care. Patients were excluded if they had acute organ failure including receipt of invasive mechanical ventilation, extracorporeal membrane oxygenation, vasopressor therapy, mechanical circulatory support, or new renal replacement therapy. The study drug was prepared by an unmasked pharmacist; study participants, site study staff, investigators, and clinical providers were masked to study assignment. The primary outcome was time to sustained recovery up to day 90, defined as 14 consecutive days at home after hospital discharge, with co-primary analyses for the full cohort and for participants who were neutralising antibody-negative at baseline. Efficacy and safety analyses were done in the modified intention-to-treat population, defined as participants who received a complete or partial infusion of tixagevimab–cilgavimab or placebo. This study is registered with ClinicalTrials.gov, NCT04501978 and the participant follow-up is ongoing. Findings: From Feb 10 to Sept 30, 2021, 1455 patients were randomly assigned and 1417 in the primary modified intention-to-treat population were infused with tixagevimab–cilgavimab (n=710) or placebo (n=707). The estimated cumulative incidence of sustained recovery was 89% for tixagevimab–cilgavimab and 86% for placebo group participants at day 90 in the full cohort (recovery rate ratio [RRR] 1·08 [95% CI 0·97–1·20]; p=0·21). Results were similar in the seronegative subgroup (RRR 1·14 [0·97–1·34]; p=0·13). Mortality was lower in the tixagevimab–cilgavimab group (61 [9%]) versus placebo group (86 [12%]; hazard ratio [HR] 0·70 [95% CI 0·50–0·97]; p=0·032). The composite safety outcome occurred in 178 (25%) tixagevimab–cilgavimab and 212 (30%) placebo group participants (HR 0·83 [0·68–1·01]; p=0·059). Serious adverse events occurred in 34 (5%) participants in the tixagevimab–cilgavimab group and 38 (5%) in the placebo group. Interpretation: Among patients hospitalised with COVID-19 receiving remdesivir and other standard care, tixagevimab–cilgavimab did not improve the primary outcome of time to sustained recovery but was safe and mortality was lower. Funding: US National Institutes of Health (NIH) and Operation Warp Speed

    Social factors related to the clinical severity of influenza cases in Spain during the A(H1N1)2009 virus pandemic

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    Background During the 2009 influenza pandemic, a change in the type of patients most often affected by influenza was observed. The objective of this study was to assess the role of individual and social determinants in hospitalizations due to influenza A (H1N1) 2009 infection. Methods We studied hospitalized patients (cases) and outpatients (controls) with confirmed influenza A (H1N1) 2009 infection. A standardized questionnaire was used to collect data. Variables that might be related to the hospitalization of influenza cases were compared by estimation of the odds ratio (OR) and 95% confidence intervals (CI) and the variables entered into binomial logistic regression models. Results Hospitalization due to pandemic A (H1N1) 2009 influenza virus infections was associated with non-Caucasian ethnicity (OR: 2.18, 95% CI 1.17 − 4.08), overcrowding (OR: 2.84, 95% CI 1.20 − 6.72), comorbidity and the lack of previous preventive information (OR: 2.69, 95% CI: 1.50 − 4.83). Secondary or higher education was associated with a lower risk of hospitalization (OR 0.56, 95% CI: 0.36 − 0.87) Conclusions In addition to individual factors such as comorbidity, other factors such as educational level, ethnicity or overcrowding were associated with hospitalization due to A (H1N1) 2009 influenza virus infections

    Rare Moss-Built Microterraces in a High-Altitude, Acid Mine Drainage-Polluted Stream (Cordillera Negra, Peru)

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    The Rio Santiago in the Cordillera Negra of Peru is severely contaminated by acid mine drainage in its headwaters. In a strongly acid stream, at about 3800 m above sea level (masl), microterraces were found with terrace walls built up of dead moss, with encrustations and interstitial fine, creamy sediment. The stream water was turbid due to the presence of similar suspended sediment, which also occurred as a thin basal layer in inter-rim basins. The moss was identified as the rare bryophyte Anomobryum prostratum (MĂŒll. Hal.) Besch. Chemical and mineralogical analyses show that green, living parts of the moss are gradually coated by Al/Fe (hydr)oxides, inducing their senescence and death. The necromass is covered by creamy crusts through precipitation of schwertmannite-type material from the stream water and simultaneous ‘capture’ of fine sediment. The latter consists of a mixture of precipitate and fine detrital primary minerals. These processes are held responsible for the formation of the microterraces, which regarding their composition and environment seem to be unique. Remarkable is the high As content of the creamy crusts and sediment, attributed to strong sorption of As, whereas its solute concentration is relatively low. This calls for more attention to suspended fine sediment in the assessment of environmental risks of stream water use. Lastly, the results raise serious doubts about the use of aquatic bryophytes as bioindicator for chemical pollution in acid mine drainage-polluted streams. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11270-015-2390-x) contains supplementary material, which is available to authorized users
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