280 research outputs found

    Prescription of benzodiazepines in a public general hospital in theprovince of Mendoza: problematic consumption?

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    Aún administradas regularmente a niveles terapéuticos, las BZD poseen un potencial de dependencia mayor que otros fármacos de acción ansiolítica y se ha reportado tolerancia farmacológica cuando la prescripción es por un tiempo mayor a cuatro semanas, así como la aparición del síndrome de abstinencia en el 30% de los pacientes después de un tratamiento de ocho semanas de duración

    Anomaly detection based on intelligent techniques over a bicomponent production plant used on wind generator blades manufacturing

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    [ES] Los avances tecnológicos en general, y en el ámbito de la industria en particular, conllevan el desarrollo y optimización de las actividades que en ella tienen lugar. Para alcanzar este objetivo, resulta de vital importancia detectar cualquier tipo de anomalía en su fase más incipiente, contribuyendo, entre otros, al ahorro energético y económico, y a una reducción del impacto ambiental. En un contexto en el que se fomenta la reducción de emisión de gases contaminantes, las energías alternativas, especialmente la energía eólica, juegan un papel crucial. En la fabricación de las palas de aerogenerador se recurre comúnmente a materiales de tipo bicomponente, obtenidos a través del mezclado de dos substancias primarias. En la presente investigación se evalúan distintas técnicas inteligentes de clasificación one-class para detectar anomalías en un sistema de mezclado para la obtención de materiales bicomponente empleados en la elaboración de palas de aerogenerador. Para lograr los modelos[EN] Technological advances, especially in the industrial field, have led to the development and optimization of the activities that takes place on it. To achieve this goal, an early detection of any kind of anomaly is very important. This can contribute to energy and economic savings and an environmental impact reduction. In a context where the reduction of pollution gasses emission is promoted, the use of alternative energies, specially the wind energy, plays a key role. The wind generator blades are usually manufactured from bicomponent material, obtained from the mixture of two dierent primary components. The present research assesses dierent one-class intelligent techniques to perform anomaly detection on a bicomponent mixing system used on the wind generator manufacturing. To perform the anomaly detection, the intelligent models were obtained from real dataset recorded during the right operation of a bicomponent mixing plant. The classifiers for each technique were validated using artJove, E.; Casteleiro-Roca, J.; Quintián, H.; Méndez-Pérez, JA.; Calvo-Rolle, JL. (2020). Detección de anomalías basada en técnicas inteligentes de una planta de obtención de material bicomponente empleado en la fabricación de palas de aerogenerador. Revista Iberoamericana de Automática e Informática industrial. 17(1):84-93. https://doi.org/10.4995/riai.2019.11055OJS8493171Bradley, A. P., 1997. The use of the area under the roc curve in the evaluation of machine learning algorithms. Pattern Recognition 30 (7), 1145 - 1159. https://doi.org/10.1016/S0031-3203(96)00142-2Casale, P., Pujol, O., Radeva, P., 2011. Approximate convex hulls family for one-class classification. In: Sansone, C., Kittler, J., Roli, F. (Eds.), Multiple Classifier Systems. Springer Berlin Heidelberg, Berlin, Heidelberg, pp. 106-115. https://doi.org/10.1007/978-3-642-21557-5_13Casale, P., Pujol, O., Radeva, P., 2014. Approximate polytope ensemble for oneclass classification. Pattern Recognition 47 (2), 854 - 864. https://doi.org/10.1016/j.patcog.2013.08.007Chandola, V., Banerjee, A., Kumar, V., 2009. Anomaly detection: A survey. ACM computing surveys (CSUR) 41 (3), 15. https://doi.org/10.1145/1541880.1541882Chen, Y., Zhou, X. S., Huang, T. S., 2001. One-class svm for learning in image retrieval. In: Image Processing, 2001. Proceedings. 2001 International Conference on. Vol. 1. IEEE, pp. 34-37.Chiang, L. H., Russell, E. L., Braatz, R. D., 2000. Fault detection and diagnosis in industrial systems. Springer Science & Business Media.de la Portilla, M. P., Piñeiro, A. L., Sánchez, J. A. S., Herrera, R. M., 2017. Modelado dinámico y control de un dispositivo sumergido provisto de actuadores hidrostáticos. Revista Iberoamericana de Automtica e Informática industrial 15 (1), 12-23. https://doi.org/10.4995/riai.2017.8824Fan, H.,Wong, C., Yuen, M.-F., April 2006. Prediction of material properties of epoxy materials using molecular dynamic simulation. In: Thermal, Mechanical and Multiphysics Simulation and Experiments in Micro-Electronics and Micro-Systems, 2006. EuroSime 2006. 7th International Conference on. pp. 1-4. https://doi.org/10.1109/ESIME.2006.1644033Fernández-Francos, D., Fontenla-Romero, O., Alonso-Betanzos, A., 2018. One-class convex hull-based algorithm for classification in distributed environments. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 1-11. https://doi.org/10.1109/TSMC.2017.2771341González, G., Angelo, C. D., Forchetti, D., Aligia, D., 2018. Diagnósico de fallas en el convertidor del rotor en generadores de inducción con rotor bobinado. Revista Iberoamericana de Automática e Informática industrial 15 (3), 297-308. https://doi.org/10.4995/riai.2017.9042Goodfellow, I., Bengio, Y., Courville, A., Bengio, Y., 2016. Deep learning. Vol. 1. MIT press Cambridge.Heller, K. A., Svore, K. M., Keromytis, A. 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A., Quintián, H., Corchado, E. (Eds.), International Joint Conference SOCO'18-CISIS'18- ICEUTE'18. Springer International Publishing, Cham, pp. 415-425. https://doi.org/10.1007/978-3-319-94120-2_40Krstajic, D., Buturovic, L. J., Leahy, D. E., Thomas, S., Mar 2014. Crossvalidation pitfalls when selecting and assessing regression and classification models. Journal of Cheminformatics 6 (1), 10. URL: https://doi.org/10.1186/1758-2946-6-10 https://doi.org/10.1186/1758-2946-6-10Li, K.-L., Huang, H.-K., Tian, S.-F., Xu, W., 2003. Improving one-class svm for anomaly detection. In: Machine Learning and Cybernetics, 2003 International Conference on. Vol. 5. IEEE, pp. 3077-3081.Miljkovic, D., 2011. Fault detection methods: A literature survey. In: MIPRO, 2011 proceedings of the 34th international convention. IEEE, pp. 750-755.Sakurada, M., Yairi, T., 2014. Anomaly detection using autoencoders with nonlinear dimensionality reduction. In: Proceedings of the MLSDA 2014 2nd Workshop on Machine Learning for Sensory Data Analysis. ACM, p. 4 https://doi.org/10.1145/2689746.2689747Schölkopf, B., Platt, J. C., Shawe-Taylor, J., Smola, A. J., Williamson, R. C., 2001. Estimating the support of a high-dimensional distribution. Neural computation 13 (7), 1443-1471. https://doi.org/10.1162/089976601750264965Schwartz, J., 1994. Air pollution and daily mortality: A review and meta analysis. Environmental Research 64 (1), 36 - 52. https://doi.org/10.1006/enrs.1994.1005Shalabi, L. A., Shaaban, Z., May 2006. Normalization as a preprocessing engine for data mining and the approach of preference matrix. In: 2006 International Conference on Dependability of Computer Systems. pp. 207-214. https://doi.org/10.1109/DEPCOS-RELCOMEX.2006.38Tax, D., Jan 2018. Ddtools, the data description toolbox for matlab. Version 2.1.3.Tax, D. M. J., 2001. One-class classification: concept-learning in the absence of counter-examples [ph. d. thesis]. Delft University of Technology.Vincent, P., Larochelle, H., Lajoie, I., Bengio, Y., Manzagol, P.-A., 2010. Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion. Journal of Machine Learning Research 11 (Dec), 3371-3408.Wei, X., Huang, G., Li, Y., Aug 2007. Mahalanobis ellipsoidal learning machine for one class classification. In: 2007 International Conference on Machine Learning and Cybernetics. Vol. 6. pp. 3528-3533. https://doi.org/10.1109/ICMLC.2007.4370758Westerhuis, J. A., Gurden, S. P., Smilde, A. K., 2000. Generalized contribution plots in multivariate statistical process monitoring. Chemometrics and intelligent laboratory systems 51 (1), 95-114. https://doi.org/10.1016/S0169-7439(00)00062-9Wu, J., Zhang, X., 2001. A pca classifier and its application in vehicle detection. In: IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No. 01CH37222). Vol. 1. 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    Selective chemical probe inhibitor of Stat3, identified through structure-based virtual screening, induces antitumor activity

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    S31-201 (NSC 74859) is a chemical probe inhibitor of Stat3 activity, which was identified from the National Cancer Institute chemical libraries by using structure-based virtual screening with a computer model of the Stat3 SH2 domain bound to its Stat3 phosphotyrosine peptide derived from the x-ray crystal structure of the Stat3 beta homodimer. S31-201 inhibits Stat3-Stat3 complex formation and Stat3 DNA-binding and transcriptional activities. Furthermore, S31-201 inhibits growth and induces apoptosis preferentially in tumor cells that contain persistently activated Stat3. Constitutively climerized and active Stat3C and Stat3 SH2 domain rescue tumor cells from S31-201-induced apoptosis. Finally, S31-201 inhibits the expression of the Stat3-regulated genes encoding cyclin D1, BcI-xL, and survivin and inhibits the growth of human breast tumors in vivo. These findings strongly suggest that the antitumor activity of S31-201 is mediated in part through inhibition of aberrant Stat3 activation and provide the proof-of-concept for the potential clinical use of Stat3 inhibitors such as S31-201 in tumors harboring aberrant Stat3

    Genome-wide profiling of non-smoking-related lung cancer cells reveals common RB1 rearrangements associated with histopathologic transformation in EGFR-mutant tumors.

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    The etiology and the molecular basis of lung adenocarcinomas (LuADs) in nonsmokers are currently unknown. Furthermore, the scarcity of available primary cultures continues to hamper our biological understanding of non-smoking-related lung adenocarcinomas (NSK-LuADs). We established patient-derived cancer cell (PDC) cultures from metastatic NSK-LuADs, including two pairs of matched EGFR-mutant PDCs before and after resistance to tyrosine kinase inhibitors (TKIs), and then performed whole-exome and RNA sequencing to delineate their genomic architecture. For validation, we analyzed independent cohorts of primary LuADs. In addition to known non-smoker-associated alterations (e.g. RET, ALK, EGFR, and ERBB2), we discovered novel fusions and recurrently mutated genes, including ATF7IP, a regulator of gene expression, that was inactivated in 5% of primary LuAD cases. We also found germline mutations at dominant familiar-cancer genes, highlighting the importance of genetic predisposition in the origin of a subset of NSK-LuADs. Furthermore, there was an over-representation of inactivating alterations at RB1, mostly through complex intragenic rearrangements, in treatment-naive EGFR-mutant LuADs. Three EGFR-mutant and one EGFR-wild-type tumors acquired resistance to EGFR-TKIs and chemotherapy, respectively, and histology on re-biopsies revealed the development of small-cell lung cancer/squamous cell carcinoma (SCLC/LuSCC) transformation. These features were consistent with RB1 inactivation and acquired EGFR-T790M mutation or FGFR3-TACC3 fusion in EGFR-mutant tumors. We found recurrent alterations in LuADs that deserve further exploration. Our work also demonstrates that a subset of NSK-LuADs arises within cancer-predisposition syndromes. The preferential occurrence of RB1 inactivation, via complex rearrangements, found in EGFR-mutant tumors appears to favor SCLC/LuSCC transformation under growth-inhibition pressures. Thus RB1 inactivation may predict the risk of LuAD transformation to a more aggressive type of lung cancer, and may need to be considered as a part of the clinical management of NSK-LuADs patients.This work was supported by the Fundacion Cientifica Asociacion Española Contra el Cancer-AECC (grant number GCB14142170MONT) to LMM, MS-C, and EF; the Spanish Ministry of Economy and Competitivity-MINECO (grant number SAF-2017-82186R to MS-C; Rio Hortega-CM17/00180 to MS; PROYBAR17005NADA to EN); the Health Institute Carlos III-ISCIII, Fondo Europeo de Desarrollo Regional-FEDER (grant Number PT13/0001/0044, PT17/0009/0019, PI16 01821); the Government of Navarra (grant number DIANA project); and the Ramon Areces Foundation (no grant number is applicable) to LMM and RP.S

    Ras Inhibition Induces Insulin Sensitivity and Glucose Uptake

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    BACKGROUND: Reduced glucose uptake due to insulin resistance is a pivotal mechanism in the pathogenesis of type 2 diabetes. It is also associated with increased inflammation. Ras inhibition downregulates inflammation in various experimental models. The aim of this study was to examine the effect of Ras inhibition on insulin sensitivity and glucose uptake, as well as its influence on type 2 diabetes development. METHODS AND FINDINGS: The effect of Ras inhibition on glucose uptake was examined both in vitro and in vivo. Ras was inhibited in cells transfected with a dominant-negative form of Ras or by 5-fluoro-farnesylthiosalicylic acid (F-FTS), a small-molecule Ras inhibitor. The involvement of IκB and NF-κB in Ras-inhibited glucose uptake was investigated by immunoblotting. High fat (HF)-induced diabetic mice were treated with F-FTS to test the effect of Ras inhibition on induction of hyperglycemia. Each of the Ras-inhibitory modes resulted in increased glucose uptake, whether in insulin-resistant C2C12 myotubes in vitro or in HF-induced diabetic mice in vivo. Ras inhibition also caused increased IκB expression accompanied by decreased expression of NF-κB . In fat-induced diabetic mice treated daily with F-FTS, both the incidence of hyperglycemia and the levels of serum insulin were significantly decreased. CONCLUSIONS: Inhibition of Ras apparently induces a state of heightened insulin sensitization both in vitro and in vivo. Ras inhibition should therefore be considered as an approach worth testing for the treatment of type 2 diabetes

    Dynamic metabolic patterns tracking neurodegeneration and gliosis following 26S proteasome dysfunction in mouse forebrain neurons

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    Metabolite profling is an important tool that may better capture the multiple features of neurodegeneration. With the considerable parallels between mouse and human metabolism, the use of metabolomics in mouse models with neurodegenerative pathology provides mechanistic insight and ready translation into aspects of human disease. Using 400MHz nuclear magnetic resonance spectroscopy we have carried out a temporal region-specifc investigation of the metabolome of neuron-specifc 26S proteasome knockout mice characterised by progressive neurodegeneration and Lewy-like inclusion formation in the forebrain. An early signifcant decrease in N-acetyl aspartate revealed evidence of neuronal dysfunction before cell death that may be associated with changes in brain neuroenergetics, underpinning the use of this metabolite to track neuronal health. Importantly, we show early and extensive activation of astrocytes and microglia in response to targeted neuronal dysfunction in this context, but only late changes in myo-inositol; the best established glial cell marker in magnetic resonance spectroscopy studies, supporting recent evidence that additional early neuroinfammatory markers are needed. Our results extend the limited understanding of metabolite changes associated with gliosis and provide evidence that changes in glutamate homeostasis and lactate may correlate with astrocyte activation and have biomarker potential for tracking neuroinfammation

    Nuclear Energy Advanced Modeling and Simulation (NEAMS) waste Integrated Performance and Safety Codes (IPSC) : gap analysis for high fidelity and performance assessment code development.

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    This report describes a gap analysis performed in the process of developing the Waste Integrated Performance and Safety Codes (IPSC) in support of the U.S. Department of Energy (DOE) Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) Campaign. The goal of the Waste IPSC is to develop an integrated suite of computational modeling and simulation capabilities to quantitatively assess the long-term performance of waste forms in the engineered and geologic environments of a radioactive waste storage or disposal system. The Waste IPSC will provide this simulation capability (1) for a range of disposal concepts, waste form types, engineered repository designs, and geologic settings, (2) for a range of time scales and distances, (3) with appropriate consideration of the inherent uncertainties, and (4) in accordance with rigorous verification, validation, and software quality requirements. The gap analyses documented in this report were are performed during an initial gap analysis to identify candidate codes and tools to support the development and integration of the Waste IPSC, and during follow-on activities that delved into more detailed assessments of the various codes that were acquired, studied, and tested. The current Waste IPSC strategy is to acquire and integrate the necessary Waste IPSC capabilities wherever feasible, and develop only those capabilities that cannot be acquired or suitably integrated, verified, or validated. The gap analysis indicates that significant capabilities may already exist in the existing THC codes although there is no single code able to fully account for all physical and chemical processes involved in a waste disposal system. Large gaps exist in modeling chemical processes and their couplings with other processes. The coupling of chemical processes with flow transport and mechanical deformation remains challenging. The data for extreme environments (e.g., for elevated temperature and high ionic strength media) that are needed for repository modeling are severely lacking. In addition, most of existing reactive transport codes were developed for non-radioactive contaminants, and they need to be adapted to account for radionuclide decay and in-growth. The accessibility to the source codes is generally limited. Because the problems of interest for the Waste IPSC are likely to result in relatively large computational models, a compact memory-usage footprint and a fast/robust solution procedure will be needed. A robust massively parallel processing (MPP) capability will also be required to provide reasonable turnaround times on the analyses that will be performed with the code. A performance assessment (PA) calculation for a waste disposal system generally requires a large number (hundreds to thousands) of model simulations to quantify the effect of model parameter uncertainties on the predicted repository performance. A set of codes for a PA calculation must be sufficiently robust and fast in terms of code execution. A PA system as a whole must be able to provide multiple alternative models for a specific set of physical/chemical processes, so that the users can choose various levels of modeling complexity based on their modeling needs. This requires PA codes, preferably, to be highly modularized. Most of the existing codes have difficulties meeting these requirements. Based on the gap analysis results, we have made the following recommendations for the code selection and code development for the NEAMS waste IPSC: (1) build fully coupled high-fidelity THCMBR codes using the existing SIERRA codes (e.g., ARIA and ADAGIO) and platform, (2) use DAKOTA to build an enhanced performance assessment system (EPAS), and build a modular code architecture and key code modules for performance assessments. The key chemical calculation modules will be built by expanding the existing CANTERA capabilities as well as by extracting useful components from other existing codes

    Two first-in-human studies of xentuzumab, a humanised insulin-like growth factor (IGF)-neutralising antibody, in patients with advanced solid tumours

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    BACKGROUND: Xentuzumab, an insulin-like growth factor (IGF)-1/IGF-2-neutralising antibody, binds IGF-1 and IGF-2, inhibiting their growth-promoting signalling. Two first-in-human trials assessed the maximum-tolerated/relevant biological dose (MTD/RBD), safety, pharmacokinetics, pharmacodynamics, and activity of xentuzumab in advanced/metastatic solid cancers. METHODS: These phase 1, open-label trials comprised dose-finding (part I; 3 + 3 design) and expansion cohorts (part II; selected tumours; RBD [weekly dosing]). Primary endpoints were MTD/RBD. RESULTS: Study 1280.1 involved 61 patients (part I: xentuzumab 10–1800 mg weekly, n = 48; part II: 1000 mg weekly, n = 13); study 1280.2, 64 patients (part I: 10–3600 mg three-weekly, n = 33; part II: 1000 mg weekly, n = 31). One dose-limiting toxicity occurred; the MTD was not reached for either schedule. Adverse events were generally grade 1/2, mostly gastrointestinal. Xentuzumab showed dose-proportional pharmacokinetics. Total plasma IGF-1 increased dose dependently, plateauing at ~1000 mg/week; at ≥450 mg/week, IGF bioactivity was almost undetectable. Two partial responses occurred (poorly differentiated nasopharyngeal carcinoma and peripheral primitive neuroectodermal tumour). Integration of biomarker and response data by Bayesian Logistic Regression Modeling (BLRM) confirmed the RBD. CONCLUSIONS: Xentuzumab was well tolerated; MTD was not reached. RBD was 1000 mg weekly, confirmed by BLRM. Xentuzumab showed preliminary anti-tumour activity

    Two first-in-human studies of xentuzumab, a humanised insulin-like growth factor (IGF)-neutralising antibody, in patients with advanced solid tumours

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    Background Xentuzumab, an insulin-like growth factor (IGF)-1/IGF-2-neutralising antibody, binds IGF-1 and IGF-2, inhibiting their growth-promoting signalling. Two first-in-human trials assessed the maximum-tolerated/relevant biological dose (MTD/RBD), safety, pharmacokinetics, pharmacodynamics, and activity of xentuzumab in advanced/metastatic solid cancers. Methods These phase 1, open-label trials comprised dose-finding (part I; 3 + 3 design) and expansion cohorts (part II; selected tumours; RBD [weekly dosing]). Primary endpoints were MTD/RBD. Results Study 1280.1 involved 61 patients (part I: xentuzumab 10–1800 mg weekly, n = 48; part II: 1000 mg weekly, n = 13); study 1280.2, 64 patients (part I: 10–3600 mg three-weekly, n = 33; part II: 1000 mg weekly, n = 31). One dose-limiting toxicity occurred; the MTD was not reached for either schedule. Adverse events were generally grade 1/2, mostly gastrointestinal. Xentuzumab showed dose-proportional pharmacokinetics. Total plasma IGF-1 increased dose dependently, plateauing at ~1000 mg/week; at ≥450 mg/week, IGF bioactivity was almost undetectable. Two partial responses occurred (poorly differentiated nasopharyngeal carcinoma and peripheral primitive neuroectodermal tumour). Integration of biomarker and response data by Bayesian Logistic Regression Modeling (BLRM) confirmed the RBD. Conclusions Xentuzumab was well tolerated; MTD was not reached. RBD was 1000 mg weekly, confirmed by BLRM. Xentuzumab showed preliminary anti-tumour activity. Clinical trial registration NCT01403974; NCT01317420
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