36 research outputs found

    Revisión de los métodos computerizados para la reconstrucción de fragmentos arqueológicos de cerámica

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    [ES] Las cerámicas son los hallazgos más numerosos encontrados en las excavaciones arqueológicas; a menudo se usan para obtener información sobre la historia, la economía y el arte de un sitio. Los arqueólogos rara vez encuentran jarrones completos; en general, están dañados y en fragmentos, a menudo mezclados con otros grupos de cerámica.El análisis y la reconstrucción de fragmentos se realiza por un operador experto mediante el uso del método manual tradicional. Los artículos revisados proporcionaron evidencias de que el método tradicional no es reproducible, no es repetible, consume mucho tiempo y sus resultados generan grandes incertidumbres. Con el objetivo de superar los límites anteriores, en los últimos años, los investigadores han realizado esfuerzos para desarrollar métodos informáticos que permitan el análisis de fragmentos arqueológicos de cerámica, todo ello destinado a su reconstrucción. Para contribuir a este campo de estudio, en este artículo, se presenta un análisis exhaustivo de las publicaciones disponibles más importantes hasta finales de 2019. Este estudio, centrado únicamente en fragmentos de cerámica, se realiza mediante la recopilación de artículos en inglés de la base de datos Scopus, utilizando las siguientes palabras clave: "métodos informáticos en arqueología", "arqueología 3D", "reconstrucción 3D", "reconocimiento y reconstrucción automática de características", "restauración de reliquias en forma de cerámica ". La lista se completa con referencias adicionales que se encuentran a través de la lectura de documentos seleccionados. Los 53 trabajos seleccionados se dividen en tres períodos de tiempo. Según una revisión detallada de los estudios realizados, los elementos clave de cada método analizado se enumeran en función de las herramientas de adquisición de datos, las características extraídas, los procesos de clasificación y las técnicas de correspondencia. Finalmente, para superar las brechas reales, se proponen algunas recomendaciones para futuras investigaciones.[EN] Potteries are the most numerous finds found in archaeological excavations; they are often used to get information about the history, economy, and art of a site. Archaeologists rarely find complete vases but, generally, damaged and in fragments, often mixed with other pottery groups. By using the traditional manual method, the analysis and reconstruction of sherds are performed by a skilled operator. Reviewed papers provided evidence that the traditional method is not reproducible, not repeatable, time-consuming and its results have great uncertainties. To overcome the aforementioned limits, in the last years, researchers have made efforts to develop computer-based methods for archaeological ceramic sherds analysis, aimed at their reconstruction. To contribute to this field of study, in this paper, a comprehensive analysis of the most important available publications until the end of 2019 is presented. This study, focused on pottery fragments only, is performed by collecting papers in English by the Scopus database using the following keywords: “computer methods in archaeology", "3D archaeology", "3D reconstruction", "automatic feature recognition and reconstruction", "restoration of pottery shape relics”. The list is completed by additional references found through the reading of selected papers. The 53 selected papers are divided into three periods of time. According to a detailed review of the performed studies, the key elements of each analyzed method are listed based on data acquisition tools, features extracted, classification processes, and matching techniques. Finally, to overcome the actual gaps some recommendations for future researches are proposed.Highlights:The traditional manual method for reassembling sherds is very time-consuming and costly; it also requires a great deal effort from skilled archaeologists in repetitive and routine activities.Computer-based methods for archaeological ceramic sherds reconstruction can help archaeologists in the above-mentioned repetitive and routine activities.In this paper, the state-of-the-art computer-based methods for archaeological ceramic sherds reconstruction are reviewed, and some recommendations for future researches are proposed.Eslami, D.; Di Angelo, L.; Di Stefano, P.; Pane, C. (2020). Review of computer-based methods for archaeological ceramic sherds reconstruction. Virtual Archaeology Review. 11(23):34-49. https://doi.org/10.4995/var.2020.13134OJS34491123Andrews, S., & Laidlaw, D. H. (2002). Toward a framework for assembling broken pottery vessels. In Proceedings of the National Conference on Artificial Intelligence, (August 2003), (pp. 945-946).Banterle, F., Itkin, B., Dellepiane, M., Wolf, L., Callieri, M., Dershowitz, N., & Scopigno, R. (2017). VASESKETCH: Automatic 3D Representation of Pottery from Paper Catalog Drawings. In Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, 1(693548), (pp. 683-690). https://doi.org/10.1109/ICDAR.2017.117Belenguer, C. S., & Vidal, E. V. (2012). Archaeological fragment characterization and 3D reconstruction based on projective GPU depth maps. In Proceedings of the 2012 18th International Conference on Virtual Systems & Multimedia, VSMM 2012: Virtual Systems in the Information Society, (pp. 275-282). https://doi.org/10.1109/VSMM.2012.6365935Blender. (2018). An open-source 3D graphics and animation software. Retrieved from https://www.blender.orgBrown, B. J., Toler-Franklin, C., Nehab, D., Burns, M., Dobkin, D., Vlachopoulos, A., Weyrich, T. (2008). A system for high-volume acquisition and matching of fresco fragments: Reassembling Theran wall paintings. ACM Transactions on Graphics, 27(3). https://doi.org/10.1145/1360612.1360683Cao, Y., & Mumford, D. (2002). Geometric Structure Estimation of Axially Symmetric Pots from Small Fragments. In Proceedings of the signal processing, pattern recognition and applications, IASTED, Crete, Greece, June 25-28, 2002, (pp. 92-97).Cohen, F., Zhang, Z., & Jeppson, P. (2010). Virtual reconstruction of archaeological vessels using convex hulls of surface markings. 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition-Workshops, (pp. 55-61). http://dx.doi.org/10.1109/CVPRW.2010.5543528Cohen, F., Zhang, Z., & Liu, Z. (2016). Mending broken vessels a fusion between color markings and anchor points on surface breaks. Multimedia Tools and Applications, 75(7), 3709-3732. https://doi.org/10.1007/s11042-014-2190-0Cooper, D. B., Willis, A., Andrews, S., Baker, J., Cao, Y., Han, D., … others. (2001). Assembling virtual pots from 3D measurements of their fragments. In Proceedings of the 2001 Conference on Virtual Reality, Archeology, and Cultural Heritage, (pp. 241-254). https://doi.org/10.1145/584993.585032Di Angelo, L., Di Stefano, P., Morabito, A. E., & Pane, C. (2018). Measurement of constant radius geometric features in archaeological pottery. Measurement: Journal of the International Measurement Confederation, 124 (March), 138-146. https://doi.org/10.1016/j.measurement.2018.04.016Di Angelo, L., Di Stefano, P., & Pane, C. (2018). An automatic method for pottery fragments analysis. Measurement: Journal of the International Measurement Confederation, 128, 138-148. https://doi.org/10.1016/j.measurement.2018.06.008Di Angelo, Luca, Di Stefano, P., & Pane, C. (2017). Automatic dimensional characterization of pottery. Journal of Cultural Heritage, 26, 118-128. https://doi.org/10.1016/j.culher.2017.02.003Fragkos, S., Tzimtzimis, E., Tzetzis, D., Dodun, O., & Kyratsis, P. (2018). 3D laser scanning and digital restoration of an archaeological find. MATEC Web of Conferences, 178. https://doi.org/10.1051/matecconf/201817803013Funkhouser, T., Shin, H., Toler-Franklin, C., Castañeda, A. G., Brown, B., Dobkin, D., Weyrich, T. (2011). Learning how to match fresco fragments. Journal on Computing and Cultural Heritage, 4(2). https://doi.org/10.1145/2037820.2037824Halir, R., & Menard, C. (1996). Diameter estimation for archaeological pottery using active vision. In Proceedings of the 20th Workshop of the Austrian Association for Pattern Recognition (OAGM/AAPR) on Pattern Recognition 1996, (pp. 251-261).Halir, R., & Flusser, J. (1997). Estimation of profiles of sherds of archaeological pottery. In Proceedings of the of the Czech Pattern Recognition Workshop (CPRW'97), Czech Republic, February 1997, 1-5, (pp. 126-130).Halir, R. (1999). An Automatic Estimation Of The Axis Of Rotation Of Fragments Of Archaeological Pottery: A Multi-Step Model-Based Approach. In Proceedings of the 7th International Conference in Central Europe on Computer Graphics, Visualization and Interactive Digital Media (WSCG '99) https://semanticscholar.org/0248/ae5a8dca3d2c6bfff282ce481a5625d32362Hall, N. S., & Laflin, S. (1984). A computer aided design technique for pottery profiles. In Computer applications in Archaeology, (pp. 178-188). Computer Center, University of Birmingham Birmingham. Retrieved from https://www.bcin.ca/bcin/detail.app?id=40524Han, D., & Hahn, H. S. (2014). Axis estimation and grouping of rotationally symmetric object segments. Pattern Recognition, 47(1), 296-312. https://doi.org/10.1016/j.patcog.2013.06.022Hlavackova-Schindler, K., Kampel, M., & Sablatnig, R. (2001). Fitting of a Closed Planar Curve Representing a Profile of an Archaeological Fragment. In Proceedings VAST 2001 Virtual Reality, Archeology, and Cultural Heritage, (pp. 263-269). https://doi.org/10.1145/585031.585034Huang, Q. X., Flöry, S., Gelfand, N., Hofer, M., & Pottmann, H. (2006). Reassembling fractured objects by geometric matching. ACM SIGGRAPH 2006 Papers, SIGGRAPH '06, (May), (pp. 569-578). https://doi.org/10.1145/1179352.1141925Igwe, P. C., & Knopf, G. K. (2006). 3D object reconstruction using geometric computing. Geometric Modeling and Imaging New Trends, 9-14. https://doi.org/10.1109/GMAI.2006.1Kalasarinis, I., & Koutsoudis, A. (2019). Assisting pottery restoration procedures with digital technologies. International Journal of Computational Methods in Heritage Science, 3(1), 20-32. https://doi.org/10.4018/ijcmhs.2019010102Kampel, M., & Sablatnig, R. (2003). Profile-based Pottery Reconstruction. In IEEE Proceeding of Conference on Computer Vision and Pattern Recognition Workshops, Wisconsin, June, (pp. 1-6). https://doi.org/10.1109/CVPRW.2003.10007Kampel, M, & Mara, H. (2005). Robust 3D reconstruction of archaeological pottery based on concentric circular rills. In Proceedings of the Sixth International. Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS'05), Montreux, Switzerland, (pp. 14-20). Retrieved from https://semanticscholar.org/43df/9b3c6fef5aa54964bdc4825a86cc4e9f4531Kampel, M., & Sablatnig, R. (2003). An automated pottery archival and reconstruction system. Journal of Visualization and Computer Animation, 14(3), 111-120. https://doi.org/10.1002/vis.310Kampel, M., & Sablatnig, R. (2004). 3D Puzzling of Archeological Fragments. In Proceedings of 9th Computer Vision Winter Workshop, (February), (pp. 31-40). Retrieved from https://cvl.tuwien.ac.at/wp-content/uploads/2014/12/cvww041Karasik, A., & Smilansky, U. (2011). Computerized morphological classification of ceramics. Journal of Archaeological Science, 38(10), 2644-2657. https://doi.org/10.1016/j.jas.2011.05.023Kashihara, K. (2012). Three-dimensional reconstruction of artifacts based on a hybrid genetic algorithm. In IEEE International Conference on Systems, Man and Cybernetics, (pp. 900-905). https://doi.org/10.1109/ICSMC.2012.6377842Kashihara, K. (2017). An intelligent computer assistance system for artifact restoration based on genetic algorithms with plane image features. International Journal of Computational Intelligence and Applications, 16(3), 1-15. https://doi.org/10.1142/S1469026817500213Kleber, F., & Sablatnig, R. (2009). A survey of techniques for document and archaeology artifact reconstruction. In Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, (March 2014), (pp. 1061-1065). https://doi.org/10.1109/ICDAR.2009.154Kotoula, E. (2016). Semiautomatic fragments matching and virtual reconstruction: a case study on ceramics. International Journal of Conservation Science, 7(1), 71-86. Retrieved from http://eprints.lincoln.ac.uk/id/eprint/31035/Lucena, M., Martínez-Carrillo, A. L., Fuertes, J. M., Javier Carrascosa Malagón, F., & Ruiz Rodríguez, A. (2016). Decision support system for classifying archaeological pottery profiles based on mathematical morphology. Multimedia Tools and Applications, 75(7), 3677-3691. https://doi.org/10.1007/s11042-014-2063-6Maiza, C., & Gaildrat, V. (2005). Automatic classification of archaeological potsherds. In Proceedings of the 8th International Conference on Computer Graphics and Artificial Intelligence, Limoges, France, May 11-12, 2005, (pp. 135-147). https://semanticscholar.org/3c95/82c3e562b44e7d61dc0fd3487ea3dc977ff3Mara, H., Kampel, M., & Sablatnig, R. (2002). Preprocessing of 3D-Data for Classification of Archaeological Fragments in an Automated System. In Proceedings of the 26th Workshop of the Austrian Association for Pattern Recognition, Vision with Non-Traditional Sensors, (ÖAGM/AAPR), Graz, Austria, 10-11 September 2002, (pp. 257-264). https://doi.org/10.1.1.15.748Mara, H., & Sablatnig, R. (2006). The orientation of fragments of rotationally symmetrical 3D-shapes for archaeological documentation. In Proceedings - Third International Symposium on 3D Data Processing, Visualization, and Transmission, 3DPVT 2006, (June), (pp. 1064-1071). https://doi.org/10.1109/3DPVT.2006.105Melero, F. J., Torres, J. C., & Leon, A. (2003). On the interactive 3d reconstruction of Iberian vessels. In 4th International Symposium on Virtual Reality, Archaeology, and Intelligent Cultural Heritage, VAST, 3, (pp. 71-78). http://dx.doi.org/10.2312/VAST/VAST03/071-078Papaioannou, G., Karabassi, E. a., & Theoharis, T. (2000). Automatic Reconstruction of Archaeological Finds-A Graphics Approach. In International Conference on Computer Graphics and Artificial Intelligence, (March), (pp. 117-125). Retrieved from https://semanticscholar.org/6a3c/7ec8f544bbfb83174d868cd406eaaf40f438Papaioannou, G., Karabassi, E. A., & Theoharis, T. (2002). Reconstruction of three-dimensional objects through the matching of their parts. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(1), 114-124. https://doi.org/10.1109/34.982888Pulli, K. (1999). Multiview registration for large data sets. In Proceedings of Second International Conference on 3D Digital Imaging and Modeling, Ottawa, ON, Canada, 4-8 December 1999, (pp. 160-168). http://doi.org/10.1109/IM.1999.805346Rasheed, N. A., & Nordin, J. (2015a). A Survey of Computer Methods in Reconstruction of 3D Archaeological Pottery Objects. International Journal of Advanced Research, 3(3), 712-714. Retrieved from https://academia.edu.documents/45540231Rasheed, N. A., & Nordin, M. J. (2014). A polynomial function in the automatic reconstruction of fragmented objects. Journal of Computer Science, 10(11), 2339-2348. https://doi.org/10.3844/jcssp.2014.2339.2348Rasheed, N. A., & Nordin, M. J. (2015b). Archaeological fragments classification based on RGB color and texture features. Journal of Theoretical and Applied Information Technology, 76(3), 358-365. Retrieved from http://repository.uobabylon.edu.iq/papers/publication.aspx?pubid=6746Rasheed, N. A., & Nordin, M. J. (2018). Classification and reconstruction algorithms for the archaeological fragments. Journal of King Saud University-Computer and Information Sciences. https://doi.org/10.1016/j.jksuci.2018.09.019Rasheed, N. A., Nordin, M. J., Dakheel, A. H., Nados, W. L., & Maaroof, M. K. A. (2017). Classification archaeological fragments into groups. Research Journal of Applied Sciences, Engineering, and Technology, 14(9), 324-333. https://doi.org/10.19026/rjaset.14.5072Sablatnig, R., & Menard, C. (1997). 3D Reconstruction of Archaeological Pottery using Profile Primitives. In Proceedings of I International Workshop on Synthetic-Natural Hybrid Coding and Three-Dimensional Imaging, (pp. 93-96).Sablatnig, R., Menard, C., & Kropatseh, W. (1998). Classification of archaeological fragments using a description language. In Proceedings of European Signal Processing Conference, (Eusipco '98), (pp. 1097-1100), 1998.Sakpere, W. (2019). 3D Reconstruction of Archaeological Pottery from Its Point Cloud. In Proceedings of Iberian Conference on Pattern Recognition and Image Analysis, (pp. 125-136). https://doi.org/10.1007/978-3-030-31332-6_11Shin, H., Doumas, C., Funkhouser, T., Rusinkiewicz, S., Steiglitz, K.,Vlachopoulos, & Weyrich, T. (2010). Analyzing Fracture Patterns in Theran Wall Paintings. In Proceedings of the 11th International Symposium on Virtual Reality, Archaeology - VAST, (pp. 71-78). https://doi.org/10.2312/VAST/VAST10/071-078Son, K., Almeida, E. B., & Cooper, D. B. (2013). Axially symmetric 3D pots configuration system using the axis of symmetry and break curve. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, (pp. 257-264). https://doi.org/10.1109/CVPR.2013.40Stamatopoulos, M. I., & Anagnostopoulos, C.-N. (2016). 3D digital reassembling of archaeological ceramic pottery fragments based on their thickness profile. The Computing Research Repository (CoRR). Retrieved from https://arxiv.org/abs/1601.05824Toler-Franklin, C., Funkhouser, T., Rusinkiewicz, S., Brown, B., & Weyrich, T. (2010). Multi-Feature Matching of Fresco Fragments. ACM Transactions on Graphics, 29(6), 1-12. https://doi.org/10.1145/1882261.1866207Üçoluk, G., & Hakki Toroslu, I. (1999). Automatic reconstruction of broken 3-D surface objects. Computers and Graphics, 23(4), 573-582. https://doi.org/10.1016/S0097-8493(99)00075-8Vendrell-Vidal, E., & Sánchez-Belenguer, C. (2014). A Discrete Approach for Pairwise Matching of Archaeological Fragments. Journal on Computing and Cultural Heritage, 7(3), 1-19. https://doi.org/10.1145/2597178Willis, A., Orriols, X., & Cooper, D. B. (2003). Accurately Estimating Sherd 3D Surface Geometry with Application to Pot Reconstruction. In Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, (16-22 June 2003), Madison, Wisconsin, USA (pp. 1-7). https://doi.org/10.1109/CVPRW.2003.10014Willis, A. R., & Cooper, D. B. (2004). Bayesian assembly of 3D axially symmetric shapes from fragments. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1, (pp. 82-89). https://doi.org/10.1109/cvpr.2004.1315017Zhou, Mingquam, Geng, G., Wu, Z., Zheng, X., Shui, W., Lu, K., & Gao, Y. (2007). A system for re-assembly of fragment objects and computer-aided restoration of cultural relics. Virtual Retrospect 2007, 3, 21-27. Retrieved from http://hal.univ-savoie.fr/ENIB/hal-01765241v1Zhou, Mingquan, Geng, G., Wu, Z., & Shui, W. (2010). A Virtual Restoration System for Broken Pottery. In Proceedings of the CAA Conference 37th Computer applications and quantitative methods in archaeology, Williamsburg, VA, USA, 22-26 March 2009; (pp. 391-396). Retrieved from https://semanticscholar.org/87b5/aa5c7710806677abbedb4e43f6134e05304

    In chronic myeloid leukemia patients on second-line tyrosine kinase inhibitor therapy, deep sequencing of BCR-ABL1 at the time of warning may allow sensitive detection of emerging drug-resistant mutants

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    BACKGROUND: Imatinib-resistant chronic myeloid leukemia (CML) patients receiving second-line tyrosine kinase inhibitor (TKI) therapy with dasatinib or nilotinib have a higher risk of disease relapse and progression and not infrequently BCR-ABL1 kinase domain (KD) mutations are implicated in therapeutic failure. In this setting, earlier detection of emerging BCR-ABL1 KD mutations would offer greater chances of efficacy for subsequent salvage therapy and limit the biological consequences of full BCR-ABL1 kinase reactivation. Taking advantage of an already set up and validated next-generation deep amplicon sequencing (DS) assay, we aimed to assess whether DS may allow a larger window of detection of emerging BCR-ABL1 KD mutants predicting for an impending relapse. METHODS: a total of 125 longitudinal samples from 51 CML patients who had acquired dasatinib- or nilotinib-resistant mutations during second-line therapy were analyzed by DS from the time of failure and mutation detection by conventional sequencing backwards. BCR-ABL1/ABL1%(IS) transcript levels were used to define whether the patient had 'optimal response', 'warning' or 'failure' at the time of first mutation detection by DS. RESULTS: DS was able to backtrack dasatinib- or nilotinib-resistant mutations to the previous sample(s) in 23/51 (45 %) pts. Median mutation burden at the time of first detection by DS was 5.5 % (range, 1.5-17.5 %); median interval between detection by DS and detection by conventional sequencing was 3 months (range, 1-9 months). In 5 cases, the mutations were detectable at baseline. In the remaining cases, response level at the time mutations were first detected by DS could be defined as 'Warning' (according to the 2013 ELN definitions of response to 2nd-line therapy) in 13 cases, as 'Optimal response' in one case, as 'Failure' in 4 cases. No dasatinib- or nilotinib-resistant mutations were detected by DS in 15 randomly selected patients with 'warning' at various timepoints, that later turned into optimal responders with no treatment changes. CONCLUSIONS: DS enables a larger window of detection of emerging BCR-ABL1 KD mutations predicting for an impending relapse. A 'Warning' response may represent a rational trigger, besides 'Failure', for DS-based mutation screening in CML patients undergoing second-line TKI therapy

    Prevalence of Spinal Muscular Atrophy in the Era of Disease-Modifying Therapies: An Italian Nationwide Survey

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    Objective: Spinal muscular atrophy (SMA) is a neurodegenerative disorder caused by mutations in the SMN1 gene. The aim of this study was to assess the prevalence of SMA and treatment prescription in Italy. Methods: An online survey was distributed to 36 centers identified by the Italian government as referral centers for SMA. Data on the number of patients with SMA subdivided according to age, type, SMN2 copy number, and treatment were collected. Results: One thousand two hundred fifty-five patients with SMA are currently followed in the Italian centers with an estimated prevalence of 2.12/100,000. Of the 1,255, 284 were type I, 470 type II, 467 type III, and 15 type IV with estimated prevalence of 0.48, 0.79, 0.79 and 0.02/100,000, respectively. Three patients with SMA 0 and 16 presymptomatic patients were also included. Approximately 85% were receiving one of the available treatments. The percentage of treated patients decreased with decreasing severity (SMA I: 95.77%, SMA II: 85.11%, SMA III: 79.01%). Discussion: The results provide for the first time an estimate of the prevalence of SMA at the national level and the current distribution of patients treated with the available therapeutical options. These data provide a baseline to assess future changes in relation to the evolving therapeutical scenario

    Managing chronic myeloid leukemia for treatment-free remission: a proposal from the GIMEMA CML WP

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    Several papers authored by international experts have proposed recommendations on the management of BCR-ABL1+ chronic myeloid leukemia (CML). Following these recommendations, survival of CML patients has become very close to normal. The next, ambitious, step is to bring as many patients as possible into a condition of treatment-free remission (TFR). The Gruppo Italiano Malattie EMatologiche dell'Adulto (GIMEMA; Italian Group for Hematologic Diseases of the Adult) CML Working Party (WP) has developed a project aimed at selecting the treatment policies that may increase the probability of TFR, taking into account 4 variables: the need for TFR, the tyrosine kinase inhibitors (TKIs), the characteristics of leukemia, and the patient. A Delphi-like method was used to reach a consensus among the representatives of 50 centers of the CML WP. A consensus was reached on the assessment of disease risk (EUTOS Long Term Survival [ELTS] score), on the definition of the most appropriate age boundaries for the choice of first-line treatment, on the choice of the TKI for first-line treatment, and on the definition of the responses that do not require a change of the TKI (BCR-ABL1 6410% at 3 months, 641% at 6 months, 640.1% at 12 months, 640.01% at 24 months), and of the responses that require a change of the TKI, when the goal is TFR (BCR-ABL1 >10% at 3 and 6 months, >1% at 12 months, and >0.1% at 24 months). These suggestions may help optimize the treatment strategy for TFR

    Results of the Ontology Alignment Evaluation Initiative 2008

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    Ontology matching consists of finding correspondences between ontology entities. OAEI campaigns aim at comparing ontology matching systems on precisely defined test sets. Test sets can use ontologies of different nature (from expressive OWL ontologies to simple directories) and use different modalities, e.g., blind evaluation, open evaluation, consensus. OAEI-2008 builds over previous campaigns by having 4 tracks with 8 test sets followed by 13 participants. Following the trend of previous years, more participants reach the forefront. The official results of the campaign are those published on the OAEI web site

    3D Virtual Reconstruction of the Ancient Roman Incile of the Fucino Lake

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    The construction of the artificial emissary of Fucino Lake is one of the most ambitious engineering buildings of antiquity. It was the longest tunnel ever made until the 19th century and, due to the depth of the adduction inlet, it required a monumental and complex incile, which, for functionality, cannot be compared to other ancient emissaries. The Roman emissary and its "incile" (Latin name of the inlet structure) were almost completely destroyed in the 19th century, when Fucino Lake was finally dried. Today, only few auxiliary structures such as wells, tunnels, and winzes remain of this ancient work. As evidence of the ancient incile remains a description made by those who also destroyed it and some drawings made by travelers who, on various occasions, visited the site. This paper presents a virtual reconstruction of the Roman incile, obtained both through the philological study of the known documentation, interpreting iconographic sources that represent the last evidence of this structure, and through the survey on the territory. The main purpose is to understand its technical functionalities, the original structures, and its evolution during the time, taking into account the evolution of the Fucino Lake water levels, technological issues, and finally offering its visual reconstruction

    Adhesion of Enterococcus faecalis in the Nonculturable State to Plankton Is the Main Mechanism Responsible for Persistence of This Bacterium in both Lake and Seawater

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    The presence of enterococci in lake and seawater in an 18-month survey comparing molecular (PCR and quantitative PCR) and culture methods was evaluated, as well as the possibility that zooplankton could act as reservoirs for enterococci. Samples of both water and zooplankton were collected monthly from a Lake Garda site and an Adriatic Sea site. In lake water, the positive samples numbered 13 of 54 (24%) by culture and 32 of 54 (59%) when PCR was applied. In seawater, they numbered 0 of 51 by culture and 18 of 51 (35%) by PCR. Enterococci were found either totally bound to plankton or totally in water, depending on the presence or absence of plankton, respectively. These results clearly indicate that the PCR assay is a powerful tool for detecting fecal indicators and pathogens in the environment, thus providing a much more sensitive method than culture

    Androgen-secreting carcinoma of the adrenal cortex: a case study.

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    In tumors of the adrenal cortex an endocrine component, responsible for specific clinical symptoms, (Cushing’s syndrome, Conn’s syndrome, and hypersecretion of androgens), may be associated with the purely oncological component (adenomas and carcinomas). The authors describe the case of a 65-year-old woman with hirsutism, hypertension, and diabetes. To evaluate the patient a series of tests was required, including levels of adrenal hormones, (serum and urine cortisol, testosterone, androstenedione, dehydroepiandrosterone sulphate, and 17-OH progesterone), diagnostic imaging, (abdominal ultrasound, abdominal CT scan with contrast material, abdominal MRI without contrast material, and an 18F-FDG-PET total body scan). The hormonal profile revealed elevated levels of adrenal androgens, and an abnormal response to the dexamethasone suppression test, and the presence of urinary free cortisol confirmed the suspicion of an adrenal tumor. The CT scan and MRI identified a arge solid formation, 9 x 6 cm in size, in the right adrenal gland. It was in the axial plane, not clearly separated from segments I, VI, and VII of the liver, nfiltrating the inferior vena cava and the right renal vein, and with dishomogeneous enhancement after contrast material was administered. The total body 18F-FDG-PET scan confirmed that there was a dishomogeneous pattern of hyperactivity. The patient underwent en bloc resection of the right adrenal gland, as well as the right kidney and perirenal fat because the renal vessels had been infiltrated by the tumor. The histology exam confirmed the suspicion of adrenal carcinoma. Hirsutism, associated with increased levels of androgens, can be a sign of an androgen-secreting tumor. Careful evaluation of adrenal function is therefore essential and enables early diagnosis and treatment of tumors that are sometimes very aggressive
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